Sample records for pattern search method
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NASA Technical Reports Server (NTRS)
Lewis, Robert Michael; Torczon, Virginia
1998-01-01
We give a pattern search adaptation of an augmented Lagrangian method due to Conn, Gould, and Toint. The algorithm proceeds by successive bound constrained minimization of an augmented Lagrangian. In the pattern search adaptation we solve this subproblem approximately using a bound constrained pattern search method. The stopping criterion proposed by Conn, Gould, and Toint for the solution of this subproblem requires explicit knowledge of derivatives. Such information is presumed absent in pattern search methods; however, we show how we can replace this with a stopping criterion based on the pattern size in a way that preserves the convergence properties of the original algorithm. In this way we proceed by successive, inexact, bound constrained minimization without knowing exactly how inexact the minimization is. So far as we know, this is the first provably convergent direct search method for general nonlinear programming.
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On the Local Convergence of Pattern Search
NASA Technical Reports Server (NTRS)
Dolan, Elizabeth D.; Lewis, Robert Michael; Torczon, Virginia; Bushnell, Dennis M. (Technical Monitor)
2000-01-01
We examine the local convergence properties of pattern search methods, complementing the previously established global convergence properties for this class of algorithms. We show that the step-length control parameter which appears in the definition of pattern search algorithms provides a reliable asymptotic measure of first-order stationarity. This gives an analytical justification for a traditional stopping criterion for pattern search methods. Using this measure of first-order stationarity, we analyze the behavior of pattern search in the neighborhood of an isolated local minimizer. We show that a recognizable subsequence converges r-linearly to the minimizer.
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Dynamic pattern matcher using incomplete data
NASA Technical Reports Server (NTRS)
Johnson, Gordon G. (Inventor); Wang, Lui (Inventor)
1993-01-01
This invention relates generally to pattern matching systems, and more particularly to a method for dynamically adapting the system to enhance the effectiveness of a pattern match. Apparatus and methods for calculating the similarity between patterns are known. There is considerable interest, however, in the storage and retrieval of data, particularly, when the search is called or initiated by incomplete information. For many search algorithms, a query initiating a data search requires exact information, and the data file is searched for an exact match. Inability to find an exact match thus results in a failure of the system or method.
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Searching for patterns in remote sensing image databases using neural networks
NASA Technical Reports Server (NTRS)
Paola, Justin D.; Schowengerdt, Robert A.
1995-01-01
We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.
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Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David
2001-01-01
Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681
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NASA Astrophysics Data System (ADS)
Rocha, Humberto; Dias, Joana M.; Ferreira, Brígida C.; Lopes, Maria C.
2013-05-01
Generally, the inverse planning of radiation therapy consists mainly of the fluence optimization. The beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) consists of selecting appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance better organ sparing and to improve tumor coverage. However, in clinical practice, most of the time, beam directions continue to be manually selected by the treatment planner without objective and rigorous criteria. The goal of this paper is to introduce a novel approach that uses beam’s-eye-view dose ray tracing metrics within a pattern search method framework in the optimization of the highly non-convex BAO problem. Pattern search methods are derivative-free optimization methods that require a few function evaluations to progress and converge and have the ability to better avoid local entrapment. The pattern search method framework is composed of a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and ensures the convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Beam’s-eye-view dose metrics assign a score to each radiation beam direction and can be used within the pattern search framework furnishing a priori knowledge of the problem so that directions with larger dosimetric scores are tested first. A set of clinical cases of head-and-neck tumors treated at the Portuguese Institute of Oncology of Coimbra is used to discuss the potential of this approach in the optimization of the BAO problem.
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Structator: fast index-based search for RNA sequence-structure patterns
2011-01-01
Background The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs. Results We present a novel method and readily applicable software for time efficient matching of RNA sequence-structure patterns in sequence databases. Our approach is based on affix arrays, a recently introduced index data structure, preprocessed from the target database. Affix arrays support bidirectional pattern search, which is required for efficiently handling the structural constraints of the pattern. Structural patterns like stem-loops can be matched inside out, such that the loop region is matched first and then the pairing bases on the boundaries are matched consecutively. This allows to exploit base pairing information for search space reduction and leads to an expected running time that is sublinear in the size of the sequence database. The incorporation of a new chaining approach in the search of RNA sequence-structure patterns enables the description of molecules folding into complex secondary structures with multiple ordered patterns. The chaining approach removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our method runs up to two orders of magnitude faster than previous methods. Conclusions The presented method's sublinear expected running time makes it well suited for RNA sequence-structure pattern matching in large sequence databases. RNA molecules containing several stem-loop substructures can be described by multiple sequence-structure patterns and their matches are efficiently handled by a novel chaining method. Beyond our algorithmic contributions, we provide with Structator a complete and robust open-source software solution for index-based search of RNA sequence-structure patterns. The Structator software is available at http://www.zbh.uni-hamburg.de/Structator. PMID:21619640
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Adaptive rood pattern search for fast block-matching motion estimation.
Nie, Yao; Ma, Kai-Kuang
2002-01-01
In this paper, we propose a novel and simple fast block-matching algorithm (BMA), called adaptive rood pattern search (ARPS), which consists of two sequential search stages: 1) initial search and 2) refined local search. For each macroblock (MB), the initial search is performed only once at the beginning in order to find a good starting point for the follow-up refined local search. By doing so, unnecessary intermediate search and the risk of being trapped into local minimum matching error points could be greatly reduced in long search case. For the initial search stage, an adaptive rood pattern (ARP) is proposed, and the ARP's size is dynamically determined for each MB, based on the available motion vectors (MVs) of the neighboring MBs. In the refined local search stage, a unit-size rood pattern (URP) is exploited repeatedly, and unrestrictedly, until the final MV is found. To further speed up the search, zero-motion prejudgment (ZMP) is incorporated in our method, which is particularly beneficial to those video sequences containing small motion contents. Extensive experiments conducted based on the MPEG-4 Verification Model (VM) encoding platform show that the search speed of our proposed ARPS-ZMP is about two to three times faster than that of the diamond search (DS), and our method even achieves higher peak signal-to-noise ratio (PSNR) particularly for those video sequences containing large and/or complex motion contents.
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Social Search: A Taxonomy of, and a User-Centred Approach to, Social Web Search
ERIC Educational Resources Information Center
McDonnell, Michael; Shiri, Ali
2011-01-01
Purpose: The purpose of this paper is to introduce the notion of social search as a new concept, drawing upon the patterns of web search behaviour. It aims to: define social search; present a taxonomy of social search; and propose a user-centred social search method. Design/methodology/approach: A mixed method approach was adopted to investigate…
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NASA Astrophysics Data System (ADS)
Singh, Manu Pratap; Radhey, Kishori; Kumar, Sandeep
2017-08-01
In the present paper, simultaneous classification of Orange and Apple has been carried out using both Grover's iterative algorithm (Grover 1996) and Ventura's model (Ventura and Martinez, Inf. Sci. 124, 273-296, 2000) taking different superposition of two- pattern start state containing Orange and Apple both, one- pattern start state containing Apple as search state and another one- pattern start state containing Orange as search state. It has been shown that the exclusion superposition is the most suitable two- pattern search state for simultaneous classification of pattern associated with Apples and Oranges and the superposition of phase-invariance are the best choice as the respective search state based on one -pattern start-states in both Grover's and Ventura's methods of classifications of patterns.
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A novel directional asymmetric sampling search algorithm for fast block-matching motion estimation
NASA Astrophysics Data System (ADS)
Li, Yue-e.; Wang, Qiang
2011-11-01
This paper proposes a novel directional asymmetric sampling search (DASS) algorithm for video compression. Making full use of the error information (block distortions) of the search patterns, eight different direction search patterns are designed for various situations. The strategy of local sampling search is employed for the search of big-motion vector. In order to further speed up the search, early termination strategy is adopted in procedure of DASS. Compared to conventional fast algorithms, the proposed method has the most satisfactory PSNR values for all test sequences.
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Quinn, Casey; Hercz, Daniel; Gillespie, James A
2013-01-01
Background Human immunodeficiency virus (HIV) is a serious health problem in the Russian Federation. However, the true scale of HIV in Russia has long been the subject of considerable debate. Using digital surveillance to monitor diseases has become increasingly popular in high income countries. But Internet users may not be representative of overall populations, and the characteristics of the Internet-using population cannot be directly ascertained from search pattern data. This exploratory infoveillance study examined if Internet search patterns can be used for disease surveillance in a large middle-income country with a dispersed population. Objective This study had two main objectives: (1) to validate Internet search patterns against national HIV prevalence data, and (2) to investigate the relationship between search patterns and the determinants of Internet access. Methods We first assessed whether online surveillance is a valid and reliable method for monitoring HIV in the Russian Federation. Yandex and Google both provided tools to study search patterns in the Russian Federation. We evaluated the relationship between both Yandex and Google aggregated search patterns and HIV prevalence in 2011 at national and regional tiers. Second, we analyzed the determinants of Internet access to determine the extent to which they explained regional variations in searches for the Russian terms for “HIV” and “AIDS”. We sought to extend understanding of the characteristics of Internet searching populations by data matching the determinants of Internet access (age, education, income, broadband access price, and urbanization ratios) and searches for the term “HIV” using principal component analysis (PCA). Results We found generally strong correlations between HIV prevalence and searches for the terms “HIV” and “AIDS”. National correlations for Yandex searches for “HIV” were very strongly correlated with HIV prevalence (Spearman rank-order coefficient [rs]=.881, P≤.001) and strongly correlated for “AIDS” (rs=.714, P≤.001). The strength of correlations varied across Russian regions. National correlations in Google for the term “HIV” (rs=.672, P=.004) and “AIDS” (rs=.584, P≤.001) were weaker than for Yandex. Second, we examined the relationship between the determinants of Internet access and search patterns for the term “HIV” across Russia using PCA. At the national level, we found Principal Component 1 loadings, including age (-0.56), HIV search (-0.533), and education (-0.479) contributed 32% of the variance. Principal Component 2 contributed 22% of national variance (income, -0.652 and broadband price, -0.460). Conclusions This study contributes to the methodological literature on search patterns in public health. Based on our preliminary research, we suggest that PCA may be used to evaluate the relationship between the determinants of Internet access and searches for health problems beyond high-income countries. We believe it is in middle-income countries that search methods can make the greatest contribution to public health. PMID:24220250
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Couvin, David; Zozio, Thierry; Rastogi, Nalin
2017-07-01
Spoligotyping is one of the most commonly used polymerase chain reaction (PCR)-based methods for identification and study of genetic diversity of Mycobacterium tuberculosis complex (MTBC). Despite its known limitations if used alone, the methodology is particularly useful when used in combination with other methods such as mycobacterial interspersed repetitive units - variable number of tandem DNA repeats (MIRU-VNTRs). At a worldwide scale, spoligotyping has allowed identification of information on 103,856 MTBC isolates (corresponding to 98049 clustered strains plus 5807 unique isolates from 169 countries of patient origin) contained within the SITVIT2 proprietary database of the Institut Pasteur de la Guadeloupe. The SpolSimilaritySearch web-tool described herein (available at: http://www.pasteur-guadeloupe.fr:8081/SpolSimilaritySearch) incorporates a similarity search algorithm allowing users to get a complete overview of similar spoligotype patterns (with information on presence or absence of 43 spacers) in the aforementioned worldwide database. This tool allows one to analyze spread and evolutionary patterns of MTBC by comparing similar spoligotype patterns, to distinguish between widespread, specific and/or confined patterns, as well as to pinpoint patterns with large deleted blocks, which play an intriguing role in the genetic epidemiology of M. tuberculosis. Finally, the SpolSimilaritySearch tool also provides with the country distribution patterns for each queried spoligotype. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns
2013-01-01
Background It is well known that the search for homologous RNAs is more effective if both sequence and structure information is incorporated into the search. However, current tools for searching with RNA sequence-structure patterns cannot fully handle mutations occurring on both these levels or are simply not fast enough for searching large sequence databases because of the high computational costs of the underlying sequence-structure alignment problem. Results We present new fast index-based and online algorithms for approximate matching of RNA sequence-structure patterns supporting a full set of edit operations on single bases and base pairs. Our methods efficiently compute semi-global alignments of structural RNA patterns and substrings of the target sequence whose costs satisfy a user-defined sequence-structure edit distance threshold. For this purpose, we introduce a new computing scheme to optimally reuse the entries of the required dynamic programming matrices for all substrings and combine it with a technique for avoiding the alignment computation of non-matching substrings. Our new index-based methods exploit suffix arrays preprocessed from the target database and achieve running times that are sublinear in the size of the searched sequences. To support the description of RNA molecules that fold into complex secondary structures with multiple ordered sequence-structure patterns, we use fast algorithms for the local or global chaining of approximate sequence-structure pattern matches. The chaining step removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our improved online algorithm is faster than the best previous method by up to factor 45. Our best new index-based algorithm achieves a speedup of factor 560. Conclusions The presented methods achieve considerable speedups compared to the best previous method. This, together with the expected sublinear running time of the presented index-based algorithms, allows for the first time approximate matching of RNA sequence-structure patterns in large sequence databases. Beyond the algorithmic contributions, we provide with RaligNAtor a robust and well documented open-source software package implementing the algorithms presented in this manuscript. The RaligNAtor software is available at http://www.zbh.uni-hamburg.de/ralignator. PMID:23865810
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Gillespie, James A; Quinn, Casey
2012-01-01
Background This is a methodological study investigating the online responses to a national debate over an important health and social problem in Russia. Russia is the largest Internet market in Europe, exceeding Germany in the absolute number of users. However, Russia is unusual in that the main search provider is not Google, but Yandex. Objective This study had two main objectives. First, to validate Yandex search patterns against those provided by Google, and second, to test this method's adequacy for investigating online interest in a 2010 national debate over Russian illicit drug policy. We hoped to learn what search patterns and specific search terms could reveal about the relative importance and geographic distribution of interest in this debate. Methods A national drug debate, centering on the anti-drug campaigner Egor Bychkov, was one of the main Russian domestic news events of 2010. Public interest in this episode was accompanied by increased Internet search. First, we measured the search patterns for 13 search terms related to the Bychkov episode and concurrent domestic events by extracting data from Google Insights for Search (GIFS) and Yandex WordStat (YaW). We conducted Spearman Rank Correlation of GIFS and YaW search data series. Second, we coded all 420 primary posts from Bychkov's personal blog between March 2010 and March 2012 to identify the main themes. Third, we compared GIFS and Yandex policies concerning the public release of search volume data. Finally, we established the relationship between salient drug issues and the Bychkov episode. Results We found a consistent pattern of strong to moderate positive correlations between Google and Yandex for the terms "Egor Bychkov" (r s = 0.88, P < .001), “Bychkov” (r s = .78, P < .001) and “Khimki”(r s = 0.92, P < .001). Peak search volumes for the Bychkov episode were comparable to other prominent domestic political events during 2010. Monthly search counts were 146,689 for “Bychkov” and 48,084 for “Egor Bychkov”, compared to 53,403 for “Khimki” in Yandex. We found Google potentially provides timely search results, whereas Yandex provides more accurate geographic localization. The correlation was moderate to strong between search terms representing the Bychkov episode and terms representing salient drug issues in Yandex–“illicit drug treatment” (r s = .90, P < .001), "illicit drugs" (r s = .76, P < .001), and "drug addiction" (r s = .74, P < .001). Google correlations were weaker or absent–"illicit drug treatment" (r s = .12, P = .58), “illicit drugs ” (r s = -0.29, P = .17), and "drug addiction" (r s = .68, P < .001). Conclusions This study contributes to the methodological literature on the analysis of search patterns for public health. This paper investigated the relationship between Google and Yandex, and contributed to the broader methods literature by highlighting both the potential and limitations of these two search providers. We believe that Yandex Wordstat is a potentially valuable, and underused data source for researchers working on Russian-related illicit drug policy and other public health problems. The Russian Federation, with its large, geographically dispersed, and politically engaged online population presents unique opportunities for studying the evolving influence of the Internet on politics and policy, using low cost methods resilient against potential increases in censorship. PMID:23238600
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Exhaustive search system and method using space-filling curves
Spires, Shannon V.
2003-10-21
A search system and method for one agent or for multiple agents using a space-filling curve provides a way to control one or more agents to cover an area of any space of any dimensionality using an exhaustive search pattern. An example of the space-filling curve is a Hilbert curve. The search area can be a physical geography, a cyberspace search area, or an area searchable by computing resources. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace.
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Phase demodulation from a single fringe pattern based on a correlation technique.
Robin, Eric; Valle, Valéry
2004-08-01
We present a method for determining the demodulated phase from a single fringe pattern. This method, based on a correlation technique, searches in a zone of interest for the degree of similarity between a real fringe pattern and a mathematical model. This method, named modulated phase correlation, is tested with different examples.
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Zheluk, Andrey; Gillespie, James A; Quinn, Casey
2012-12-13
This is a methodological study investigating the online responses to a national debate over an important health and social problem in Russia. Russia is the largest Internet market in Europe, exceeding Germany in the absolute number of users. However, Russia is unusual in that the main search provider is not Google, but Yandex. This study had two main objectives. First, to validate Yandex search patterns against those provided by Google, and second, to test this method's adequacy for investigating online interest in a 2010 national debate over Russian illicit drug policy. We hoped to learn what search patterns and specific search terms could reveal about the relative importance and geographic distribution of interest in this debate. A national drug debate, centering on the anti-drug campaigner Egor Bychkov, was one of the main Russian domestic news events of 2010. Public interest in this episode was accompanied by increased Internet search. First, we measured the search patterns for 13 search terms related to the Bychkov episode and concurrent domestic events by extracting data from Google Insights for Search (GIFS) and Yandex WordStat (YaW). We conducted Spearman Rank Correlation of GIFS and YaW search data series. Second, we coded all 420 primary posts from Bychkov's personal blog between March 2010 and March 2012 to identify the main themes. Third, we compared GIFS and Yandex policies concerning the public release of search volume data. Finally, we established the relationship between salient drug issues and the Bychkov episode. We found a consistent pattern of strong to moderate positive correlations between Google and Yandex for the terms "Egor Bychkov" (r(s) = 0.88, P < .001), "Bychkov" (r(s) = .78, P < .001) and "Khimki"(r(s) = 0.92, P < .001). Peak search volumes for the Bychkov episode were comparable to other prominent domestic political events during 2010. Monthly search counts were 146,689 for "Bychkov" and 48,084 for "Egor Bychkov", compared to 53,403 for "Khimki" in Yandex. We found Google potentially provides timely search results, whereas Yandex provides more accurate geographic localization. The correlation was moderate to strong between search terms representing the Bychkov episode and terms representing salient drug issues in Yandex-"illicit drug treatment" (r(s) = .90, P < .001), "illicit drugs" (r(s) = .76, P < .001), and "drug addiction" (r(s) = .74, P < .001). Google correlations were weaker or absent-"illicit drug treatment" (r(s) = .12, P = .58), "illicit drugs " (r(s) = -0.29, P = .17), and "drug addiction" (r(s) = .68, P < .001). This study contributes to the methodological literature on the analysis of search patterns for public health. This paper investigated the relationship between Google and Yandex, and contributed to the broader methods literature by highlighting both the potential and limitations of these two search providers. We believe that Yandex Wordstat is a potentially valuable, and underused data source for researchers working on Russian-related illicit drug policy and other public health problems. The Russian Federation, with its large, geographically dispersed, and politically engaged online population presents unique opportunities for studying the evolving influence of the Internet on politics and policy, using low cost methods resilient against potential increases in censorship.
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Computational mining for hypothetical patterns of amino acid side chains in protein data bank (PDB)
NASA Astrophysics Data System (ADS)
Ghani, Nur Syatila Ab; Firdaus-Raih, Mohd
2018-04-01
The three-dimensional structure of a protein can provide insights regarding its function. Functional relationship between proteins can be inferred from fold and sequence similarities. In certain cases, sequence or fold comparison fails to conclude homology between proteins with similar mechanism. Since the structure is more conserved than the sequence, a constellation of functional residues can be similarly arranged among proteins of similar mechanism. Local structural similarity searches are able to detect such constellation of amino acids among distinct proteins, which can be useful to annotate proteins of unknown function. Detection of such patterns of amino acids on a large scale can increase the repertoire of important 3D motifs since available known 3D motifs currently, could not compensate the ever-increasing numbers of uncharacterized proteins to be annotated. Here, a computational platform for an automated detection of 3D motifs is described. A fuzzy-pattern searching algorithm derived from IMagine an Amino Acid 3D Arrangement search EnGINE (IMAAAGINE) was implemented to develop an automated method for searching of hypothetical patterns of amino acid side chains in Protein Data Bank (PDB), without the need for prior knowledge on related sequence or structure of pattern of interest. We present an example of the searches, which is the detection of a hypothetical pattern derived from known structural motif of C2H2 structural pattern from zinc fingers. The conservation of particular patterns of amino acid side chains in unrelated proteins is highlighted. This approach can act as a complementary method for available structure- and sequence-based platforms and may contribute in improving functional association between proteins.
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Paterniti, Debora A; Wilson, Machelle; Bell, Robert A; Chan, Man Shan; Villareal, Chloe C; Nguyen, Hien Huy; Kravitz, Richard L
2015-01-01
Background Little is known about the processes people use to find health-related information on the Internet or the individual characteristics that shape selection of information-seeking approaches. Objective Our aim was to describe the processes by which users navigate the Internet for information about a hypothetical acute illness and to identify individual characteristics predictive of their information-seeking strategies. Methods Study participants were recruited from public settings and agencies. Interested individuals were screened for eligibility using an online questionnaire. Participants listened to one of two clinical scenarios—consistent with influenza or bacterial meningitis—and then conducted an Internet search. Screen-capture video software captured Internet search mouse clicks and keystrokes. Each step of the search was coded as hypothesis testing (etiology), evidence gathering (symptoms), or action/treatment seeking (behavior). The coded steps were used to form a step-by-step pattern of each participant’s information-seeking process. A total of 78 Internet health information seekers ranging from 21-35 years of age and who experienced barriers to accessing health care services participated. Results We identified 27 unique patterns of information seeking, which were grouped into four overarching classifications based on the number of steps taken during the search, whether a pattern consisted of developing a hypothesis and exploring symptoms before ending the search or searching an action/treatment, and whether a pattern ended with action/treatment seeking. Applying dual-processing theory, we categorized the four overarching pattern classifications as either System 1 (41%, 32/78), unconscious, rapid, automatic, and high capacity processing; or System 2 (59%, 46/78), conscious, slow, and deliberative processing. Using multivariate regression, we found that System 2 processing was associated with higher education and younger age. Conclusions We identified and classified two approaches to processing Internet health information. System 2 processing, a methodical approach, most resembles the strategies for information processing that have been found in other studies to be associated with higher-quality decisions. We conclude that the quality of Internet health-information seeking could be improved through consumer education on methodical Internet navigation strategies and the incorporation of decision aids into health information websites. PMID:26194787
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GEsture: an online hand-drawing tool for gene expression pattern search.
Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning
2018-01-01
Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.
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Environmental context explains Lévy and Brownian movement patterns of marine predators.
Humphries, Nicolas E; Queiroz, Nuno; Dyer, Jennifer R M; Pade, Nicolas G; Musyl, Michael K; Schaefer, Kurt M; Fuller, Daniel W; Brunnschweiler, Juerg M; Doyle, Thomas K; Houghton, Jonathan D R; Hays, Graeme C; Jones, Catherine S; Noble, Leslie R; Wearmouth, Victoria J; Southall, Emily J; Sims, David W
2010-06-24
An optimal search theory, the so-called Lévy-flight foraging hypothesis, predicts that predators should adopt search strategies known as Lévy flights where prey is sparse and distributed unpredictably, but that Brownian movement is sufficiently efficient for locating abundant prey. Empirical studies have generated controversy because the accuracy of statistical methods that have been used to identify Lévy behaviour has recently been questioned. Consequently, whether foragers exhibit Lévy flights in the wild remains unclear. Crucially, moreover, it has not been tested whether observed movement patterns across natural landscapes having different expected resource distributions conform to the theory's central predictions. Here we use maximum-likelihood methods to test for Lévy patterns in relation to environmental gradients in the largest animal movement data set assembled for this purpose. Strong support was found for Lévy search patterns across 14 species of open-ocean predatory fish (sharks, tuna, billfish and ocean sunfish), with some individuals switching between Lévy and Brownian movement as they traversed different habitat types. We tested the spatial occurrence of these two principal patterns and found Lévy behaviour to be associated with less productive waters (sparser prey) and Brownian movements to be associated with productive shelf or convergence-front habitats (abundant prey). These results are consistent with the Lévy-flight foraging hypothesis, supporting the contention that organism search strategies naturally evolved in such a way that they exploit optimal Lévy patterns.
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Generalized Pattern Search methods for a class of nonsmooth optimization problems with structure
NASA Astrophysics Data System (ADS)
Bogani, C.; Gasparo, M. G.; Papini, A.
2009-07-01
We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.
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The Lévy flight paradigm: random search patterns and mechanisms.
Reynolds, A M; Rhodes, C J
2009-04-01
Over recent years there has been an accumulation of evidence from a variety of experimental, theoretical, and field studies that many organisms use a movement strategy approximated by Lévy flights when they are searching for resources. Lévy flights are random movements that can maximize the efficiency of resource searches in uncertain environments. This is a highly significant finding because it suggests that Lévy flights provide a rigorous mathematical basis for separating out evolved, innate behaviors from environmental influences. We discuss recent developments in random-search theory, as well as the many different experimental and data collection initiatives that have investigated search strategies. Methods for trajectory construction and robust data analysis procedures are presented. The key to prediction and understanding does, however, lie in the elucidation of mechanisms underlying the observed patterns. We discuss candidate neurological, olfactory, and learning mechanisms for the emergence of Lévy flight patterns in some organisms, and note that convergence of behaviors along such different evolutionary pathways is not surprising given the energetic efficiencies that Lévy flight movement patterns confer.
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Ihme, Matthias; Marsden, Alison L; Pitsch, Heinz
2008-02-01
A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.
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Lau, Annie YS; Wynn, Rolf
2015-01-01
Background Online health information–seeking behaviors have been reported to be more common at the beginning of the workweek. This behavior pattern has been interpreted as a kind of “healthy new start” or “fresh start” due to regrets or attempts to compensate for unhealthy behavior or poor choices made during the weekend. However, the observations regarding the most common health information–seeking day were based only on the analyses of users’ behaviors with websites on health or on online health-related searches. We wanted to confirm if this pattern could be found in searches of Wikipedia on health-related topics and also if this search pattern was unique to health-related topics or if it could represent a more general pattern of online information searching—which could be of relevance even beyond the health sector. Objective The aim was to examine the degree to which the search pattern described previously was specific to health-related information seeking or whether similar patterns could be found in other types of information-seeking behavior. Methods We extracted the number of searches performed on Wikipedia in the Norwegian language for 911 days for the most common sexually transmitted diseases (chlamydia, gonorrhea, herpes, human immunodeficiency virus [HIV], and acquired immune deficiency syndrome [AIDS]), other health-related topics (influenza, diabetes, and menopause), and 2 nonhealth-related topics (footballer Lionel Messi and pop singer Justin Bieber). The search dates were classified according to the day of the week and ANOVA tests were used to compare the average number of hits per day of the week. Results The ANOVA tests showed that the sexually transmitted disease queries had their highest peaks on Tuesdays (P<.001) and the fewest searches on Saturdays. The other health topics also showed a weekly pattern, with the highest peaks early in the week and lower numbers on Saturdays (P<.001). Footballer Lionel Messi had the highest mean number of hits on Tuesdays and Wednesdays, whereas pop singer Justin Bieber had the most hits on Tuesdays. Both these tracked search queries also showed significantly lower numbers on Saturdays (P<.001). Conclusions Our study supports prior studies finding an increase in health information searching at the beginning of the workweek. However, we also found a similar pattern for 2 randomly chosen nonhealth-related terms, which may suggest that the search pattern is not unique to health-related searches. The results are potentially relevant beyond the field of health and our preliminary findings need to be further explored in future studies involving a broader range of nonhealth-related searches. PMID:26693859
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Path integration mediated systematic search: a Bayesian model.
Vickerstaff, Robert J; Merkle, Tobias
2012-08-21
The systematic search behaviour is a backup system that increases the chances of desert ants finding their nest entrance after foraging when the path integrator has failed to guide them home accurately enough. Here we present a mathematical model of the systematic search that is based on extensive behavioural studies in North African desert ants Cataglyphis fortis. First, a simple search heuristic utilising Bayesian inference and a probability density function is developed. This model, which optimises the short-term nest detection probability, is then compared to three simpler search heuristics and to recorded search patterns of Cataglyphis ants. To compare the different searches a method to quantify search efficiency is established as well as an estimate of the error rate in the ants' path integrator. We demonstrate that the Bayesian search heuristic is able to automatically adapt to increasing levels of positional uncertainty to produce broader search patterns, just as desert ants do, and that it outperforms the three other search heuristics tested. The searches produced by it are also arguably the most similar in appearance to the ant's searches. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Pattern Classifications Using Grover's and Ventura's Algorithms in a Two-qubits System
NASA Astrophysics Data System (ADS)
Singh, Manu Pratap; Radhey, Kishori; Rajput, B. S.
2018-03-01
Carrying out the classification of patterns in a two-qubit system by separately using Grover's and Ventura's algorithms on different possible superposition, it has been shown that the exclusion superposition and the phase-invariance superposition are the most suitable search states obtained from two-pattern start-states and one-pattern start-states, respectively, for the simultaneous classifications of patterns. The higher effectiveness of Grover's algorithm for large search states has been verified but the higher effectiveness of Ventura's algorithm for smaller data base has been contradicted in two-qubit systems and it has been demonstrated that the unknown patterns (not present in the concerned data-base) are classified more efficiently than the known ones (present in the data-base) in both the algorithms. It has also been demonstrated that different states of Singh-Rajput MES obtained from the corresponding self-single- pattern start states are the most suitable search states for the classification of patterns |00>,|01 >, |10> and |11> respectively on the second iteration of Grover's method or the first operation of Ventura's algorithm.
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Jiang, Ying; Gao, Ge; Fang, Gang; Gustafson, Eric L; Laverty, Maureen; Yin, Yanbin; Zhang, Yong; Luo, Jingchu; Greene, Jonathan R; Bayne, Marvin L; Hedrick, Joseph A; Murgolo, Nicholas J
2003-05-01
PepPat, a hybrid method that combines pattern matching with similarity scoring, is described. We also report PepPat's application in the identification of a novel tachykinin-like peptide. PepPat takes as input a query peptide and a user-specified regular expression pattern within the peptide. It first performs a database pattern match and then ranks candidates on the basis of their similarity to the query peptide. PepPat calculates similarity over the pattern spanning region, enhancing PepPat's sensitivity for short query peptides. PepPat can also search for a user-specified number of occurrences of a repeated pattern within the target sequence. We illustrate PepPat's application in short peptide ligand mining. As a validation example, we report the identification of a novel tachykinin-like peptide, C14TKL-1, and show it is an NK1 (neuokinin receptor 1) agonist whose message is widely expressed in human periphery. PepPat is offered online at: http://peppat.cbi.pku.edu.cn.
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Aab, A; Abreu, P; Aglietta, M; Ahn, E J; Samarai, I Al; Albuquerque, I F M; Allekotte, I; Allen, J; Allison, P; Almela, A; Castillo, J Alvarez; Alvarez-Muñiz, J; Batista, R Alves; Ambrosio, M; Aminaei, A; Anchordoqui, L; Andringa, S; Aramo, C; Aranda, V M; Arqueros, F; Asorey, H; Assis, P; Aublin, J; Ave, M; Avenier, M; Avila, G; Awal, N; Badescu, A M; Barber, K B; Bäuml, J; Baus, C; Beatty, J J; Becker, K H; Bellido, J A; Berat, C; Bertaina, M E; Bertou, X; Biermann, P L; Billoir, P; Blaess, S; Blanco, M; Bleve, C; Blümer, H; Boháčová, M; Boncioli, D; Bonifazi, C; Bonino, R; Borodai, N; Brack, J; Brancus, I; Bridgeman, A; Brogueira, P; Brown, W C; Buchholz, P; Bueno, A; Buitink, S; Buscemi, M; Caballero-Mora, K S; Caccianiga, B; Caccianiga, L; Candusso, M; Caramete, L; Caruso, R; Castellina, A; Cataldi, G; Cazon, L; Cester, R; Chavez, A G; Chiavassa, A; Chinellato, J A; Chudoba, J; Cilmo, M; Clay, R W; Cocciolo, G; Colalillo, R; Coleman, A; Collica, L; Coluccia, M R; Conceição, R; Contreras, F; Cooper, M J; Cordier, A; Coutu, S; Covault, C E; Cronin, J; Curutiu, A; Dallier, R; Daniel, B; Dasso, S; Daumiller, K; Dawson, B R; Almeida, R M de; Domenico, M De; Jong, S J de; Neto, J R T de Mello; Mitri, I De; Oliveira, J de; Souza, V de; Peral, L Del; Deligny, O; Dembinski, H; Dhital, N; Giulio, C Di; Matteo, A Di; Diaz, J C; Castro, M L Díaz; Diogo, F; Dobrigkeit, C; Docters, W; D'Olivo, J C; Dorofeev, A; Hasankiadeh, Q Dorosti; Dova, M T; Ebr, J; Engel, R; Erdmann, M; Erfani, M; Escobar, C O; Espadanal, J; Etchegoyen, A; Luis, P Facal San; Falcke, H; Fang, K; Farrar, G; Fauth, A C; Fazzini, N; Ferguson, A P; Fernandes, M; Fick, B; Figueira, J M; Filevich, A; Filipčič, A; Fox, B D; Fratu, O; Fröhlich, U; Fuchs, B; Fujii, T; Gaior, R; García, B; Roca, S T Garcia; Garcia-Gamez, D; Garcia-Pinto, D; Garilli, G; Bravo, A Gascon; Gate, F; Gemmeke, H; Ghia, P L; Giaccari, U; Giammarchi, M; Giller, M; Glaser, C; Glass, H; Berisso, M Gómez; Vitale, P F Gómez; Gonçalves, P; Gonzalez, J G; González, N; Gookin, B; Gordon, J; Gorgi, A; Gorham, P; Gouffon, P; Grebe, S; Griffith, N; Grillo, A F; Grubb, T D; Guarino, F; Guedes, G P; Hampel, M R; Hansen, P; Harari, D; Harrison, T A; Hartmann, S; Harton, J L; Haungs, A; Hebbeker, T; Heck, D; Heimann, P; Herve, A E; Hill, G C; Hojvat, C; Hollon, N; Holt, E; Homola, P; Hörandel, J R; Horvath, P; Hrabovský, M; Huber, D; Huege, T; Insolia, A; Isar, P G; Jandt, I; Jansen, S; Jarne, C; Josebachuili, M; Kääpä, A; Kambeitz, O; Kampert, K H; Kasper, P; Katkov, I; Kégl, B; Keilhauer, B; Keivani, A; Kemp, E; Kieckhafer, R M; Klages, H O; Kleifges, M; Kleinfeller, J; Krause, R; Krohm, N; Krömer, O; Kruppke-Hansen, D; Kuempel, D; Kunka, N; LaHurd, D; Latronico, L; Lauer, R; Lauscher, M; Lautridou, P; Coz, S Le; Leão, M S A B; Lebrun, D; Lebrun, P; Oliveira, M A Leigui de; Letessier-Selvon, A; Lhenry-Yvon, I; Link, K; López, R; Agüera, A Lopez; Louedec, K; Bahilo, J Lozano; Lu, L; Lucero, A; Ludwig, M; Malacari, M; Maldera, S; Mallamaci, M; Maller, J; Mandat, D; Mantsch, P; Mariazzi, A G; Marin, V; Mariş, I C; Marsella, G; Martello, D; Martin, L; Martinez, H; Bravo, O Martínez; Martraire, D; Meza, J J Masías; Mathes, H J; Mathys, S; Matthews, J; Matthews, J A J; Matthiae, G; Maurel, D; Maurizio, D; Mayotte, E; Mazur, P O; Medina, C; Medina-Tanco, G; Meissner, R; Melissas, M; Melo, D; Menshikov, A; Messina, S; Meyhandan, R; Mićanović, S; Micheletti, M I; Middendorf, L; Minaya, I A; Miramonti, L; Mitrica, B; Molina-Bueno, L; Mollerach, S; Monasor, M; Ragaigne, D Monnier; Montanet, F; Morello, C; Mostafá, M; Moura, C A; Muller, M A; Müller, G; Müller, S; Münchmeyer, M; Mussa, R; Navarra, G; Navas, S; Necesal, P; Nellen, L; Nelles, A; Neuser, J; Nguyen, P; Niechciol, M; Niemietz, L; Niggemann, T; Nitz, D; Nosek, D; Novotny, V; Nožka, L; Ochilo, L; Olinto, A; Oliveira, M; Pacheco, N; Selmi-Dei, D Pakk; Palatka, M; Pallotta, J; Palmieri, N; Papenbreer, P; Parente, G; Parra, A; Paul, T; Pech, M; Pȩkala, J; Pelayo, R; Pepe, I M; Perrone, L; Petermann, E; Peters, C; Petrera, S; Petrov, Y; Phuntsok, J; Piegaia, R; Pierog, T; Pieroni, P; Pimenta, M; Pirronello, V; Platino, M; Plum, M; Porcelli, A; Porowski, C; Prado, R R; Privitera, P; Prouza, M; Purrello, V; Quel, E J; Querchfeld, S; Quinn, S; Rautenberg, J; Ravel, O; Ravignani, D; Revenu, B; Ridky, J; Riggi, S; Risse, M; Ristori, P; Rizi, V; Carvalho, W Rodrigues de; Cabo, I Rodriguez; Fernandez, G Rodriguez; Rojo, J Rodriguez; Rodríguez-Frías, M D; Rogozin, D; Ros, G; Rosado, J; Rossler, T; Roth, M; Roulet, E; Rovero, A C; Saffi, S J; Saftoiu, A; Salamida, F; Salazar, H; Saleh, A; Greus, F Salesa; Salina, G; Sánchez, F; Sanchez-Lucas, P; Santo, C E; Santos, E; Santos, E M; Sarazin, F; Sarkar, B; Sarmento, R; Sato, R; Scharf, N; Scherini, V; Schieler, H; Schiffer, P; Schmidt, D; Schröder, F G; Scholten, O; Schoorlemmer, H; Schovánek, P; Schulz, A; Schulz, J; Schumacher, J; Sciutto, S J; Segreto, A; Settimo, M; Shadkam, A; Shellard, R C; Sidelnik, I; Sigl, G; Sima, O; Kowski, A Śmiał; Šmída, R; Snow, G R; Sommers, P; Sorokin, J; Squartini, R; Srivastava, Y N; Stanič, S; Stapleton, J; Stasielak, J; Stephan, M; Stutz, A; Suarez, F; Suomijärvi, T; Supanitsky, A D; Sutherland, M S; Swain, J; Szadkowski, Z; Szuba, M; Taborda, O A; Tapia, A; Tartare, M; Tepe, A; Theodoro, V M; Timmermans, C; Peixoto, C J Todero; Toma, G; Tomankova, L; Tomé, B; Tonachini, A; Elipe, G Torralba; Machado, D Torres; Travnicek, P; Trovato, E; Tueros, M; Ulrich, R; Unger, M; Urban, M; Galicia, J F Valdés; Valiño, I; Valore, L; Aar, G van; Bodegom, P van; Berg, A M van den; Velzen, S van; Vliet, A van; Varela, E; Vargas Cárdenas, B; Varner, G; Vázquez, J R; Vázquez, R A; Veberič, D; Verzi, V; Vicha, J; Videla, M; Villaseñor, L; Vlcek, B; Vorobiov, S; Wahlberg, H; Wainberg, O; Walz, D; Watson, A A; Weber, M; Weidenhaupt, K; Weindl, A; Werner, F; Widom, A; Wiencke, L; Wilczyńska, B; Wilczyński, H; Will, M; Williams, C; Winchen, T; Wittkowski, D; Wundheiler, B; Wykes, S; Yamamoto, T; Yapici, T; Yuan, G; Yushkov, A; Zamorano, B; Zas, E; Zavrtanik, D; Zavrtanik, M; Zaw, I; Zepeda, A; Zhou, J; Zhu, Y; Silva, M Zimbres; Ziolkowski, M; Zuccarello, F
Energy-dependent patterns in the arrival directions of cosmic rays are searched for using data of the Pierre Auger Observatory. We investigate local regions around the highest-energy cosmic rays with [Formula: see text] eV by analyzing cosmic rays with energies above [Formula: see text] eV arriving within an angular separation of approximately 15[Formula: see text]. We characterize the energy distributions inside these regions by two independent methods, one searching for angular dependence of energy-energy correlations and one searching for collimation of energy along the local system of principal axes of the energy distribution. No significant patterns are found with this analysis. The comparison of these measurements with astrophysical scenarios can therefore be used to obtain constraints on related model parameters such as strength of cosmic-ray deflection and density of point sources.
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Aab, Alexander
2015-06-20
Energy-dependent patterns in the arrival directions of cosmic rays are searched for using data of the Pierre Auger Observatory. We investigate local regions around the highest-energy cosmic rays with E ≥ 6×10 19 eV by analyzing cosmic rays with energies above E ≥ 5×10 18 eV arriving within an angular separation of approximately 15°. We characterize the energy distributions inside these regions by two independent methods, one searching for angular dependence of energy-energy correlations and one searching for collimation of energy along the local system of principal axes of the energy distribution. No significant patterns are found with this analysis.more » As a result, the comparison of these measurements with astrophysical scenarios can therefore be used to obtain constraints on related model parameters such as strength of cosmic-ray deflection and density of point sources.« less
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Perez, Susan L; Paterniti, Debora A; Wilson, Machelle; Bell, Robert A; Chan, Man Shan; Villareal, Chloe C; Nguyen, Hien Huy; Kravitz, Richard L
2015-07-20
Little is known about the processes people use to find health-related information on the Internet or the individual characteristics that shape selection of information-seeking approaches. Our aim was to describe the processes by which users navigate the Internet for information about a hypothetical acute illness and to identify individual characteristics predictive of their information-seeking strategies. Study participants were recruited from public settings and agencies. Interested individuals were screened for eligibility using an online questionnaire. Participants listened to one of two clinical scenarios—consistent with influenza or bacterial meningitis—and then conducted an Internet search. Screen-capture video software captured Internet search mouse clicks and keystrokes. Each step of the search was coded as hypothesis testing (etiology), evidence gathering (symptoms), or action/treatment seeking (behavior). The coded steps were used to form a step-by-step pattern of each participant's information-seeking process. A total of 78 Internet health information seekers ranging from 21-35 years of age and who experienced barriers to accessing health care services participated. We identified 27 unique patterns of information seeking, which were grouped into four overarching classifications based on the number of steps taken during the search, whether a pattern consisted of developing a hypothesis and exploring symptoms before ending the search or searching an action/treatment, and whether a pattern ended with action/treatment seeking. Applying dual-processing theory, we categorized the four overarching pattern classifications as either System 1 (41%, 32/78), unconscious, rapid, automatic, and high capacity processing; or System 2 (59%, 46/78), conscious, slow, and deliberative processing. Using multivariate regression, we found that System 2 processing was associated with higher education and younger age. We identified and classified two approaches to processing Internet health information. System 2 processing, a methodical approach, most resembles the strategies for information processing that have been found in other studies to be associated with higher-quality decisions. We conclude that the quality of Internet health-information seeking could be improved through consumer education on methodical Internet navigation strategies and the incorporation of decision aids into health information websites.
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Moriyama, Koichi; Fukui, Ken–ichi; Numao, Masayuki
2015-01-01
Background Non-medical professionals (consumers) are increasingly using the Internet to support their health information needs. However, the cognitive effort required to perform health information searches is affected by the consumer’s familiarity with health topics. Consumers may have different levels of familiarity with individual health topics. This variation in familiarity may cause misunderstandings because the information presented by search engines may not be understood correctly by the consumers. Objective As a first step toward the improvement of the health information search process, we aimed to examine the effects of health topic familiarity on health information search behaviors by identifying the common search activity patterns exhibited by groups of consumers with different levels of familiarity. Methods Each participant completed a health terminology familiarity questionnaire and health information search tasks. The responses to the familiarity questionnaire were used to grade the familiarity of participants with predefined health topics. The search task data were transcribed into a sequence of search activities using a coding scheme. A computational model was constructed from the sequence data using a Markov chain model to identify the common search patterns in each familiarity group. Results Forty participants were classified into L1 (not familiar), L2 (somewhat familiar), and L3 (familiar) groups based on their questionnaire responses. They had different levels of familiarity with four health topics. The video data obtained from all of the participants were transcribed into 4595 search activities (mean 28.7, SD 23.27 per session). The most frequent search activities and transitions in all the familiarity groups were related to evaluations of the relevancy of selected web pages in the retrieval results. However, the next most frequent transitions differed in each group and a chi-squared test confirmed this finding (P<.001). Next, according to the results of a perplexity evaluation, the health information search patterns were best represented as a 5-gram sequence pattern. The most common patterns in group L1 were frequent query modifications, with relatively low search efficiency, and accessing and evaluating selected results from a health website. Group L2 performed frequent query modifications, but with better search efficiency, and accessed and evaluated selected results from a health website. Finally, the members of group L3 successfully discovered relevant results from the first query submission, performed verification by accessing several health websites after they discovered relevant results, and directly accessed consumer health information websites. Conclusions Familiarity with health topics affects health information search behaviors. Our analysis of state transitions in search activities detected unique behaviors and common search activity patterns in each familiarity group during health information searches. PMID:25783222
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Internet search and krokodil in the Russian Federation: an infoveillance study.
Zheluk, Andrey; Quinn, Casey; Meylakhs, Peter
2014-09-18
Krokodil is an informal term for a cheap injectable illicit drug domestically prepared from codeine-containing medication (CCM). The method of krokodil preparation may produce desomorphine as well as toxic reactants that cause extensive tissue necrosis. The first confirmed report of krokodil use in Russia took place in 2004. In 2012, reports of krokodil-related injection injuries began to appear beyond Russia in Western Europe and the United States. This exploratory study had two main objectives: (1) to determine if Internet search patterns could detect regularities in behavioral responses to Russian CCM policy at the population level, and (2) to determine if complementary data sources could explain the regularities we observed. First, we obtained krokodil-related search pattern data for each Russia subregion (oblast) between 2011 and 2012. Second, we analyzed several complementary data sources included krokodil-related court cases, and related search terms on both Google and Yandex to evaluate the characteristics of terms accompanying krokodil-related search queries. In the 6 months preceding CCM sales restrictions, 21 of Russia's 83 oblasts had search rates higher than the national average (mean) of 16.67 searches per 100,000 population for terms associated with krokodil. In the 6 months following restrictions, mean national searches dropped to 9.65 per 100,000. Further, the number of oblasts recording a higher than average search rate dropped from 30 to 16. Second, we found krokodil-related court appearances were moderately positively correlated (Spearman correlation=.506, P≤.001) with behaviors consistent with an interest in the production and use of krokodil across Russia. Finally, Google Trends and Google and Yandex related terms suggested consistent public interest in the production and use of krokodil as well as for CCM as analgesic medication during the date range covered by this study. Illicit drug use data are generally regarded as difficult to obtain through traditional survey methods. Our analysis suggests it is plausible that Yandex search behavior served as a proxy for patterns of krokodil production and use during the date range we investigated. More generally, this study demonstrates the application of novel methods recently used by policy makers to both monitor illicit drug use and influence drug policy decision making.
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Giat, Eitan
2018-01-01
Background Profound vitamin B12 deficiency is a known cause of disease, but the role of low or intermediate levels of B12 in the development of neuropathy and other neuropsychiatric symptoms, as well as the relationship between eating meat and B12 levels, is unclear. Objective The objective of our study was to investigate the role of low or intermediate levels of B12 in the development of neuropathy and other neuropsychiatric symptoms. Methods We used food-related Internet search patterns from a sample of 8.5 million people based in the US as a proxy for B12 intake and correlated these searches with Internet searches related to possible effects of B12 deficiency. Results Food-related search patterns were highly correlated with known consumption and food-related searches (ρ=.69). Awareness of B12 deficiency was associated with a higher consumption of B12-rich foods and with queries for B12 supplements. Searches for terms related to neurological disorders were correlated with searches for B12-poor foods, in contrast with control terms. Popular medicines, those having fewer indications, and those which are predominantly used to treat pain, were more strongly correlated with the ability to predict neuropathic pain queries using the B12 contents of food. Conclusions Our findings show that Internet search patterns are a useful way of investigating health questions in large populations, and suggest that low B12 intake may be associated with a broader spectrum of neurological disorders than previously thought. PMID:29305340
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Drory Retwitzer, Matan; Polishchuk, Maya; Churkin, Elena; Kifer, Ilona; Yakhini, Zohar; Barash, Danny
2015-01-01
Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational RNA pattern matching as an enhancement to sequence similarity. State-of-the-art programs differ by the flexibility of patterns allowed as queries and by their simplicity of use. In particular—no existing method is available as a user-friendly web server. A general program that searches for RNA sequence-structure patterns is RNA Structator. However, it is not available as a web server and does not provide the option to allow flexible gap pattern representation with an upper bound of the gap length being specified at any position in the sequence. Here, we introduce RNAPattMatch, a web-based application that is user friendly and makes sequence/structure RNA queries accessible to practitioners of various background and proficiency. It also extends RNA Structator and allows a more flexible variable gaps representation, in addition to analysis of results using energy minimization methods. RNAPattMatch service is available at http://www.cs.bgu.ac.il/rnapattmatch. A standalone version of the search tool is also available to download at the site. PMID:25940619
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Internet Search and Krokodil in the Russian Federation: An Infoveillance Study
2014-01-01
Background Krokodil is an informal term for a cheap injectable illicit drug domestically prepared from codeine-containing medication (CCM). The method of krokodil preparation may produce desomorphine as well as toxic reactants that cause extensive tissue necrosis. The first confirmed report of krokodil use in Russia took place in 2004. In 2012, reports of krokodil-related injection injuries began to appear beyond Russia in Western Europe and the United States. Objective This exploratory study had two main objectives: (1) to determine if Internet search patterns could detect regularities in behavioral responses to Russian CCM policy at the population level, and (2) to determine if complementary data sources could explain the regularities we observed. Methods First, we obtained krokodil-related search pattern data for each Russia subregion (oblast) between 2011 and 2012. Second, we analyzed several complementary data sources included krokodil-related court cases, and related search terms on both Google and Yandex to evaluate the characteristics of terms accompanying krokodil-related search queries. Results In the 6 months preceding CCM sales restrictions, 21 of Russia's 83 oblasts had search rates higher than the national average (mean) of 16.67 searches per 100,000 population for terms associated with krokodil. In the 6 months following restrictions, mean national searches dropped to 9.65 per 100,000. Further, the number of oblasts recording a higher than average search rate dropped from 30 to 16. Second, we found krokodil-related court appearances were moderately positively correlated (Spearman correlation=.506, P≤.001) with behaviors consistent with an interest in the production and use of krokodil across Russia. Finally, Google Trends and Google and Yandex related terms suggested consistent public interest in the production and use of krokodil as well as for CCM as analgesic medication during the date range covered by this study. Conclusions Illicit drug use data are generally regarded as difficult to obtain through traditional survey methods. Our analysis suggests it is plausible that Yandex search behavior served as a proxy for patterns of krokodil production and use during the date range we investigated. More generally, this study demonstrates the application of novel methods recently used by policy makers to both monitor illicit drug use and influence drug policy decision making. PMID:25236385
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Target intersection probabilities for parallel-line and continuous-grid types of search
McCammon, R.B.
1977-01-01
The expressions for calculating the probability of intersection of hidden targets of different sizes and shapes for parallel-line and continuous-grid types of search can be formulated by vsing the concept of conditional probability. When the prior probability of the orientation of a widden target is represented by a uniform distribution, the calculated posterior probabilities are identical with the results obtained by the classic methods of probability. For hidden targets of different sizes and shapes, the following generalizations about the probability of intersection can be made: (1) to a first approximation, the probability of intersection of a hidden target is proportional to the ratio of the greatest dimension of the target (viewed in plane projection) to the minimum line spacing of the search pattern; (2) the shape of the hidden target does not greatly affect the probability of the intersection when the largest dimension of the target is small relative to the minimum spacing of the search pattern, (3) the probability of intersecting a target twice for a particular type of search can be used as a lower bound if there is an element of uncertainty of detection for a particular type of tool; (4) the geometry of the search pattern becomes more critical when the largest dimension of the target equals or exceeds the minimum spacing of the search pattern; (5) for elongate targets, the probability of intersection is greater for parallel-line search than for an equivalent continuous square-grid search when the largest dimension of the target is less than the minimum spacing of the search pattern, whereas the opposite is true when the largest dimension exceeds the minimum spacing; (6) the probability of intersection for nonorthogonal continuous-grid search patterns is not greatly different from the probability of intersection for the equivalent orthogonal continuous-grid pattern when the orientation of the target is unknown. The probability of intersection for an elliptically shaped target can be approximated by treating the ellipse as intermediate between a circle and a line. A search conducted along a continuous rectangular grid can be represented as intermediate between a search along parallel lines and along a continuous square grid. On this basis, an upper and lower bound for the probability of intersection of an elliptically shaped target for a continuous rectangular grid can be calculated. Charts have been constructed that permit the values for these probabilities to be obtained graphically. The use of conditional probability allows the explorationist greater flexibility in considering alternate search strategies for locating hidden targets. ?? 1977 Plenum Publishing Corp.
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Optimized stereo matching in binocular three-dimensional measurement system using structured light.
Liu, Kun; Zhou, Changhe; Wei, Shengbin; Wang, Shaoqing; Fan, Xin; Ma, Jianyong
2014-09-10
In this paper, we develop an optimized stereo-matching method used in an active binocular three-dimensional measurement system. A traditional dense stereo-matching algorithm is time consuming due to a long search range and the high complexity of a similarity evaluation. We project a binary fringe pattern in combination with a series of N binary band limited patterns. In order to prune the search range, we execute an initial matching before exhaustive matching and evaluate a similarity measure using logical comparison instead of a complicated floating-point operation. Finally, an accurate point cloud can be obtained by triangulation methods and subpixel interpolation. The experiment results verify the computational efficiency and matching accuracy of the method.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hart, W.E.
1999-02-10
Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less
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Discovering discovery patterns with Predication-based Semantic Indexing.
Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W; Davies, Peter; Rindflesch, Thomas C
2012-12-01
In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as "discovery patterns", such as "drug x INHIBITS substance y, substance y CAUSES disease z" that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. Copyright © 2012 Elsevier Inc. All rights reserved.
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Optimization of a Boiling Water Reactor Loading Pattern Using an Improved Genetic Algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kobayashi, Yoko; Aiyoshi, Eitaro
2003-08-15
A search method based on genetic algorithms (GA) using deterministic operators has been developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). The search method uses an Improved GA operator, that is, crossover, mutation, and selection. The handling of the encoding technique and constraint conditions is designed so that the GA reflects the peculiar characteristics of the BWR. In addition, some strategies such as elitism and self-reproduction are effectively used to improve the search speed. LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and three-dimensional-dependent constraints have alwaysmore » necessitated the use of three-dimensional core simulators for BWRs, so that an optimization method is required for computational efficiency. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant applying the Haling technique. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained.« less
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Evolutionary pattern search algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimentalmore » analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zarepisheh, M; Li, R; Xing, L
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) andmore » aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves quality of resultant treatment plans as compared with conventional VMAT or IMRT treatments.« less
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NASA Astrophysics Data System (ADS)
He, Lirong; Cui, Guangmang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting
2015-03-01
Coded exposure photography makes the motion de-blurring a well-posed problem. The integration pattern of light is modulated using the method of coded exposure by opening and closing the shutter within the exposure time, changing the traditional shutter frequency spectrum into a wider frequency band in order to preserve more image information in frequency domain. The searching method of optimal code is significant for coded exposure. In this paper, an improved criterion of the optimal code searching is proposed by analyzing relationship between code length and the number of ones in the code, considering the noise effect on code selection with the affine noise model. Then the optimal code is obtained utilizing the method of genetic searching algorithm based on the proposed selection criterion. Experimental results show that the time consuming of searching optimal code decreases with the presented method. The restoration image is obtained with better subjective experience and superior objective evaluation values.
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Discovering discovery patterns with predication-based Semantic Indexing
Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W.; Davies, Peter; Rindflesch, Thomas C.
2012-01-01
In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as “discovery patterns”, such as “drug x INHIBITS substance y, substance y CAUSES disease z” that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. PMID:22841748
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An improved CS-LSSVM algorithm-based fault pattern recognition of ship power equipments.
Yang, Yifei; Tan, Minjia; Dai, Yuewei
2017-01-01
A ship power equipments' fault monitoring signal usually provides few samples and the data's feature is non-linear in practical situation. This paper adopts the method of the least squares support vector machine (LSSVM) to deal with the problem of fault pattern identification in the case of small sample data. Meanwhile, in order to avoid involving a local extremum and poor convergence precision which are induced by optimizing the kernel function parameter and penalty factor of LSSVM, an improved Cuckoo Search (CS) algorithm is proposed for the purpose of parameter optimization. Based on the dynamic adaptive strategy, the newly proposed algorithm improves the recognition probability and the searching step length, which can effectively solve the problems of slow searching speed and low calculation accuracy of the CS algorithm. A benchmark example demonstrates that the CS-LSSVM algorithm can accurately and effectively identify the fault pattern types of ship power equipments.
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Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI
2006-07-01
This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for themore » refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)« less
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Breeding novel solutions in the brain: a model of Darwinian neurodynamics.
Szilágyi, András; Zachar, István; Fedor, Anna; de Vladar, Harold P; Szathmáry, Eörs
2016-01-01
Background : The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods : We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results : We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions : Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.
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NASA Astrophysics Data System (ADS)
Zaouche, Abdelouahib; Dayoub, Iyad; Rouvaen, Jean Michel; Tatkeu, Charles
2008-12-01
We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR) strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA) are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.
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ERIC Educational Resources Information Center
Maguire, S.; Mann, M. K.; Sibert, J.; Kemp, A.
2005-01-01
Aims: To investigate what patterns of bruising are diagnostic or suggestive of child abuse by means of a systematic review. Methods: All language literature search 1951-2004. Included: studies that defined patterns of bruising in non-abused or abused children <18 years. Excluded: personal practice, review articles, single case reports, inadequate…
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Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. This book provides a summary of principal techniques. Each chapter describes techniques that are drawn from many fields, including graph
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Hsu, Yi-Yu; Chen, Hung-Yu; Kao, Hung-Yu
2013-01-01
Background Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field. Previous studies, such as those using ontology-based and corpus-based approaches, measured semantic relatedness by using information from the structure of biomedical literature, but these methods are limited by the small size of training resources. To increase the size of training datasets, the outputs of search engines have been used extensively to analyze the lexical patterns of biomedical terms. Methodology/Principal Findings In this work, we propose the Mutually Reinforcing Lexical Pattern Ranking (ReLPR) algorithm for learning and exploring the lexical patterns of synonym pairs in biomedical text. ReLPR employs lexical patterns and their pattern containers to assess the semantic relatedness of biomedical terms. By combining sentence structures and the linking activities between containers and lexical patterns, our algorithm can explore the correlation between two biomedical terms. Conclusions/Significance The average correlation coefficient of the ReLPR algorithm was 0.82 for various datasets. The results of the ReLPR algorithm were significantly superior to those of previous methods. PMID:24348899
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NASA Astrophysics Data System (ADS)
Suharsono; Nurdian, S. W.; Palupi, I. R.
2016-11-01
Relocating hypocenter is a way to improve the velocity model of the subsurface. One of the method is Grid Search. To perform the distribution of the velocity in subsurface by tomography method, it is used the result of relocating hypocenter to be a reference for subsurface analysis in volcanic and major structural patterns, such as in Central Java. The main data of this study is the earthquake data recorded from 1952 to 2012 with the P wave number is 9162, the number of events is 2426 were recorded by 30 stations located in the vicinity of Central Java. Grid search method has some advantages they are: it can relocate the hypocenter more accurate because this method is dividing space lattice model into blocks, and each grid block can only be occupied by one point hypocenter. Tomography technique is done by travel time data that has had relocated with inversion pseudo bending method. Grid search relocated method show that the hypocenter's depth is shallower than before and the direction is to the south, the hypocenter distribution is modeled into the subduction zone between the continent of Eurasia with the Indo-Australian with an average angle of 14 °. The tomography results show the low velocity value is contained under volcanoes with value of -8% to -10%, then the pattern of the main fault structure in Central Java can be description by the results of tomography at high velocity that is from 8% to 10% with the direction is northwest and northeast-southwest.
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Misra, Dharitri; Chen, Siyuan; Thoma, George R
2009-01-01
One of the most expensive aspects of archiving digital documents is the manual acquisition of context-sensitive metadata useful for the subsequent discovery of, and access to, the archived items. For certain types of textual documents, such as journal articles, pamphlets, official government records, etc., where the metadata is contained within the body of the documents, a cost effective method is to identify and extract the metadata in an automated way, applying machine learning and string pattern search techniques.At the U. S. National Library of Medicine (NLM) we have developed an automated metadata extraction (AME) system that employs layout classification and recognition models with a metadata pattern search model for a text corpus with structured or semi-structured information. A combination of Support Vector Machine and Hidden Markov Model is used to create the layout recognition models from a training set of the corpus, following which a rule-based metadata search model is used to extract the embedded metadata by analyzing the string patterns within and surrounding each field in the recognized layouts.In this paper, we describe the design of our AME system, with focus on the metadata search model. We present the extraction results for a historic collection from the Food and Drug Administration, and outline how the system may be adapted for similar collections. Finally, we discuss some ongoing enhancements to our AME system.
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Fast ITTBC using pattern code on subband segmentation
NASA Astrophysics Data System (ADS)
Koh, Sung S.; Kim, Hanchil; Lee, Kooyoung; Kim, Hongbin; Jeong, Hun; Cho, Gangseok; Kim, Chunghwa
2000-06-01
Iterated Transformation Theory-Based Coding suffers from very high computational complexity in encoding phase. This is due to its exhaustive search. In this paper, our proposed image coding algorithm preprocess an original image to subband segmentation image by wavelet transform before image coding to reduce encoding complexity. A similar block is searched by using the 24 block pattern codes which are coded by the edge information in the image block on the domain pool of the subband segmentation. As a result, numerical data shows that the encoding time of the proposed coding method can be reduced to 98.82% of that of Joaquin's method, while the loss in quality relative to the Jacquin's is about 0.28 dB in PSNR, which is visually negligible.
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Graphical Representations of Electronic Search Patterns.
ERIC Educational Resources Information Center
Lin, Xia; And Others
1991-01-01
Discussion of search behavior in electronic environments focuses on the development of GRIP (Graphic Representor of Interaction Patterns), a graphing tool based on HyperCard that produces graphic representations of search patterns. Search state spaces are explained, and forms of data available from electronic searches are described. (34…
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Evaluating random search strategies in three mammals from distinct feeding guilds.
Auger-Méthé, Marie; Derocher, Andrew E; DeMars, Craig A; Plank, Michael J; Codling, Edward A; Lewis, Mark A
2016-09-01
Searching allows animals to find food, mates, shelter and other resources essential for survival and reproduction and is thus among the most important activities performed by animals. Theory predicts that animals will use random search strategies in highly variable and unpredictable environments. Two prominent models have been suggested for animals searching in sparse and heterogeneous environments: (i) the Lévy walk and (ii) the composite correlated random walk (CCRW) and its associated area-restricted search behaviour. Until recently, it was difficult to differentiate between the movement patterns of these two strategies. Using a new method that assesses whether movement patterns are consistent with these two strategies and two other common random search strategies, we investigated the movement behaviour of three species inhabiting sparse northern environments: woodland caribou (Rangifer tarandus caribou), barren-ground grizzly bear (Ursus arctos) and polar bear (Ursus maritimus). These three species vary widely in their diets and thus allow us to contrast the movement patterns of animals from different feeding guilds. Our results showed that although more traditional methods would have found evidence for the Lévy walk for some individuals, a comparison of the Lévy walk to CCRWs showed stronger support for the latter. While a CCRW was the best model for most individuals, there was a range of support for its absolute fit. A CCRW was sufficient to explain the movement of nearly half of herbivorous caribou and a quarter of omnivorous grizzly bears, but was insufficient to explain the movement of all carnivorous polar bears. Strong evidence for CCRW movement patterns suggests that many individuals may use a multiphasic movement strategy rather than one-behaviour strategies such as the Lévy walk. The fact that the best model was insufficient to describe the movement paths of many individuals suggests that some animals living in sparse environments may use strategies that are more complicated than those described by the standard random search models. Thus, our results indicate a need to develop movement models that incorporate factors such as the perceptual and cognitive capacities of animals. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.
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An experimental design method leading to chemical Turing patterns.
Horváth, Judit; Szalai, István; De Kepper, Patrick
2009-05-08
Chemical reaction-diffusion patterns often serve as prototypes for pattern formation in living systems, but only two isothermal single-phase reaction systems have produced sustained stationary reaction-diffusion patterns so far. We designed an experimental method to search for additional systems on the basis of three steps: (i) generate spatial bistability by operating autoactivated reactions in open spatial reactors; (ii) use an independent negative-feedback species to produce spatiotemporal oscillations; and (iii) induce a space-scale separation of the activatory and inhibitory processes with a low-mobility complexing agent. We successfully applied this method to a hydrogen-ion autoactivated reaction, the thiourea-iodate-sulfite (TuIS) reaction, and noticeably produced stationary hexagonal arrays of spots and parallel stripes of pH patterns attributed to a Turing bifurcation. This method could be extended to biochemical reactions.
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Xiao, Feng; Kong, Lingjiang; Chen, Jian
2017-06-01
A rapid-search algorithm to improve the beam-steering efficiency for a liquid crystal optical phased array was proposed and experimentally demonstrated in this paper. This proposed algorithm, in which the value of steering efficiency is taken as the objective function and the controlling voltage codes are considered as the optimization variables, consisted of a detection stage and a construction stage. It optimized the steering efficiency in the detection stage and adjusted its search direction adaptively in the construction stage to avoid getting caught in a wrong search space. Simulations had been conducted to compare the proposed algorithm with the widely used pattern-search algorithm using criteria of convergence rate and optimized efficiency. Beam-steering optimization experiments had been performed to verify the validity of the proposed method.
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Quantum Associative Neural Network with Nonlinear Search Algorithm
NASA Astrophysics Data System (ADS)
Zhou, Rigui; Wang, Huian; Wu, Qian; Shi, Yang
2012-03-01
Based on analysis on properties of quantum linear superposition, to overcome the complexity of existing quantum associative memory which was proposed by Ventura, a new storage method for multiply patterns is proposed in this paper by constructing the quantum array with the binary decision diagrams. Also, the adoption of the nonlinear search algorithm increases the pattern recalling speed of this model which has multiply patterns to O( {log2}^{2^{n -t}} ) = O( n - t ) time complexity, where n is the number of quantum bit and t is the quantum information of the t quantum bit. Results of case analysis show that the associative neural network model proposed in this paper based on quantum learning is much better and optimized than other researchers' counterparts both in terms of avoiding the additional qubits or extraordinary initial operators, storing pattern and improving the recalling speed.
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Reynolds, Andy M; Schultheiss, Patrick; Cheng, Ken
2014-01-07
We suggest that the Australian desert ant Melophorus bagoti approximates a Lévy search pattern by using an intrinsic bi-exponential walk and does so when a Lévy search pattern is advantageous. When attempting to locate its nest, M. bagoti adopt a stereotypical search pattern. These searches begin at the location where the ant expects to find the nest, and comprise loops that start and end at this location, and are directed in different azimuthal directions. Loop lengths are exponentially distributed when searches are in visually familiar surroundings and are well described by a mixture of two exponentials when searches are in unfamiliar landscapes. The latter approximates a power-law distribution, the hallmark of a Lévy search. With the aid of a simple analytically tractable theory, we show that an exponential loop-length distribution is advantageous when the distance to the nest can be estimated with some certainty and that a bi-exponential distribution is advantageous when there is considerable uncertainty regarding the nest location. The best bi-exponential search patterns are shown to be those that come closest to approximating advantageous Lévy looping searches. The bi-exponential search patterns of M. bagoti are found to approximate advantageous Lévy search patterns. Copyright © 2013. Published by Elsevier Ltd.
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Misra, Dharitri; Chen, Siyuan; Thoma, George R.
2010-01-01
One of the most expensive aspects of archiving digital documents is the manual acquisition of context-sensitive metadata useful for the subsequent discovery of, and access to, the archived items. For certain types of textual documents, such as journal articles, pamphlets, official government records, etc., where the metadata is contained within the body of the documents, a cost effective method is to identify and extract the metadata in an automated way, applying machine learning and string pattern search techniques. At the U. S. National Library of Medicine (NLM) we have developed an automated metadata extraction (AME) system that employs layout classification and recognition models with a metadata pattern search model for a text corpus with structured or semi-structured information. A combination of Support Vector Machine and Hidden Markov Model is used to create the layout recognition models from a training set of the corpus, following which a rule-based metadata search model is used to extract the embedded metadata by analyzing the string patterns within and surrounding each field in the recognized layouts. In this paper, we describe the design of our AME system, with focus on the metadata search model. We present the extraction results for a historic collection from the Food and Drug Administration, and outline how the system may be adapted for similar collections. Finally, we discuss some ongoing enhancements to our AME system. PMID:21179386
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Digital dream analysis: a revised method.
Bulkeley, Kelly
2014-10-01
This article demonstrates the use of a digital word search method designed to provide greater accuracy, objectivity, and speed in the study of dreams. A revised template of 40 word search categories, built into the website of the Sleep and Dream Database (SDDb), is applied to four "classic" sets of dreams: The male and female "Norm" dreams of Hall and Van de Castle (1966), the "Engine Man" dreams discussed by Hobson (1988), and the "Barb Sanders Baseline 250" dreams examined by Domhoff (2003). A word search analysis of these original dream reports shows that a digital approach can accurately identify many of the same distinctive patterns of content found by previous investigators using much more laborious and time-consuming methods. The results of this study emphasize the compatibility of word search technologies with traditional approaches to dream content analysis. Copyright © 2014 Elsevier Inc. All rights reserved.
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A Study on Pubmed Search Tag Usage Pattern: Association Rule Mining of a Full-day Pubmed Query Log
2013-01-01
Background The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. Methods A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. Results The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. Conclusions The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed’s Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE. PMID:23302604
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Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems
NASA Astrophysics Data System (ADS)
Vasant, P.; Barsoum, N.
2010-06-01
In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.
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Mixed-methods designs in mental health services research: a review.
Palinkas, Lawrence A; Horwitz, Sarah M; Chamberlain, Patricia; Hurlburt, Michael S; Landsverk, John
2011-03-01
Despite increased calls for use of mixed-methods designs in mental health services research, how and why such methods are being used and whether there are any consistent patterns that might indicate a consensus about how such methods can and should be used are unclear. Use of mixed methods was examined in 50 peer-reviewed journal articles found by searching PubMed Central and 60 National Institutes of Health (NIH)-funded projects found by searching the CRISP database over five years (2005-2009). Studies were coded for aims and the rationale, structure, function, and process for using mixed methods. A notable increase was observed in articles published and grants funded over the study period. However, most did not provide an explicit rationale for using mixed methods, and 74% gave priority to use of quantitative methods. Mixed methods were used to accomplish five distinct types of study aims (assess needs for services, examine existing services, develop new or adapt existing services, evaluate services in randomized controlled trials, and examine service implementation), with three categories of rationale, seven structural arrangements based on timing and weighting of methods, five functions of mixed methods, and three ways of linking quantitative and qualitative data. Each study aim was associated with a specific pattern of use of mixed methods, and four common patterns were identified. These studies offer guidance for continued progress in integrating qualitative and quantitative methods in mental health services research consistent with efforts by NIH and other funding agencies to promote their use.
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NASA Astrophysics Data System (ADS)
Reynolds, A. M.
2008-04-01
A random Lévy-looping model of searching is devised and optimal random Lévy-looping searching strategies are identified for the location of a single target whose position is uncertain. An inverse-square power law distribution of loop lengths is shown to be optimal when the distance between the centre of the search and the target is much shorter than the size of the longest possible loop in the searching pattern. Optimal random Lévy-looping searching patterns have recently been observed in the flight patterns of honeybees (Apis mellifera) when attempting to locate their hive and when searching after a known food source becomes depleted. It is suggested that the searching patterns of desert ants (Cataglyphis) are consistent with the adoption of an optimal Lévy-looping searching strategy.
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Tunnel-construction methods and foraging path of a fossorial herbivore, Geomys bursarius
Andersen, Douglas C.
1988-01-01
The fossorial rodent Geomys bursarius excavates tunnels to find and gain access to belowground plant parts. This is a study of how the foraging path of this animal, as denoted by feeding-tunnel systems constructed within experimental gardens, reflects both adaptive behavior and constraints associated with the fossorial lifestyle. The principal method of tunnel construction involves the end-to-end linking of short, linear segments whose directionalities are bimodal, but symmetrically distributed about 0°. The sequence of construction of left- and right-directed segments is random, and segments tend to be equal in length. The resulting tunnel advances, zigzag-fashion, along a single heading. This linearity, and the tendency for branches to be orthogonal to the originating tunnel, are consistent with the search path predicted for a "harvesting animal" (Pyke, 1978) from optimal-foraging theory. A suite of physical and physiological constraints on the burrowing process, however, may be responsible for this geometric pattern. That is, by excavating in the most energy-efficient manner, G. bursarius automatically creates the basic components to an optimal-search path. The general search pattern was not influenced by habitat quality (plant density). Branch origins are located more often than expected at plants, demonstrating area-restricted search, a tactic commonly noted in aboveground foragers. The potential trade-offs between construction methods that minimize energy cost and those that minimize vulnerability to predators are discussed.
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Statistical evaluation of synchronous spike patterns extracted by frequent item set mining
Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja
2013-01-01
We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487
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Multi-INT Complex Event Processing using Approximate, Incremental Graph Pattern Search
2012-06-01
graph pattern search and SPARQL queries . Total execution time for 10 executions each of 5 random pattern searches in synthetic data sets...01/11 1000 10000 100000 RDF triples Time (secs) 10 20 Graph pattern algorithm SPARQL queries Initial Performance Comparisons 09/18/11 2011 Thrust Area
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Beyond mind-reading: multi-voxel pattern analysis of fMRI data.
Norman, Kenneth A; Polyn, Sean M; Detre, Greg J; Haxby, James V
2006-09-01
A key challenge for cognitive neuroscience is determining how mental representations map onto patterns of neural activity. Recently, researchers have started to address this question by applying sophisticated pattern-classification algorithms to distributed (multi-voxel) patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. This multi-voxel pattern analysis (MVPA) approach has led to several impressive feats of mind reading. More importantly, MVPA methods constitute a useful new tool for advancing our understanding of neural information processing. We review how researchers are using MVPA methods to characterize neural coding and information processing in domains ranging from visual perception to memory search.
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Simultaneous beam sampling and aperture shape optimization for SPORT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zarepisheh, Masoud; Li, Ruijiang; Xing, Lei, E-mail: Lei@stanford.edu
Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decisionmore » variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. Conclusions: The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.« less
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Shack-Hartmann wavefront sensor with large dynamic range by adaptive spot search method.
Shinto, Hironobu; Saita, Yusuke; Nomura, Takanori
2016-07-10
A Shack-Hartmann wavefront sensor (SHWFS) that consists of a microlens array and an image sensor has been used to measure the wavefront aberrations of human eyes. However, a conventional SHWFS has finite dynamic range depending on the diameter of the each microlens. The dynamic range cannot be easily expanded without a decrease of the spatial resolution. In this study, an adaptive spot search method to expand the dynamic range of an SHWFS is proposed. In the proposed method, spots are searched with the help of their approximate displacements measured with low spatial resolution and large dynamic range. By the proposed method, a wavefront can be correctly measured even if the spot is beyond the detection area. The adaptive spot search method is realized by using the special microlens array that generates both spots and discriminable patterns. The proposed method enables expanding the dynamic range of an SHWFS with a single shot and short processing time. The performance of the proposed method is compared with that of a conventional SHWFS by optical experiments. Furthermore, the dynamic range of the proposed method is quantitatively evaluated by numerical simulations.
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Search Query Data to Monitor Interest in Behavior Change: Application for Public Health
Carr, Lucas J.; Dunsiger, Shira I.
2012-01-01
There is a need for effective interventions and policies that target the leading preventable causes of death in the U.S. (e.g., smoking, overweight/obesity, physical inactivity). Such efforts could be aided by the use of publicly available, real-time search query data that illustrate times and locations of high and low public interest in behaviors related to preventable causes of death. Objectives This study explored patterns of search query activity for the terms ‘weight’, ‘diet’, ‘fitness’, and ‘smoking’ using Google Insights for Search. Methods Search activity for ‘weight’, ‘diet’, ‘fitness’, and ‘smoking’ conducted within the United States via Google between January 4th, 2004 (first date data was available) and November 28th, 2011 (date of data download and analysis) were analyzed. Using a generalized linear model, we explored the effects of time (month) on mean relative search volume for all four terms. Results Models suggest a significant effect of month on mean search volume for all four terms. Search activity for all four terms was highest in January with observable declines throughout the remainder of the year. Conclusions These findings demonstrate discernable temporal patterns of search activity for four areas of behavior change. These findings could be used to inform the timing, location and messaging of interventions, campaigns and policies targeting these behaviors. PMID:23110198
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Dai, Shengfa; Wei, Qingguo
2017-01-01
Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.
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van der Gijp, A; Ravesloot, C J; Jarodzka, H; van der Schaaf, M F; van der Schaaf, I C; van Schaik, J P J; Ten Cate, Th J
2017-08-01
Eye tracking research has been conducted for decades to gain understanding of visual diagnosis such as in radiology. For educational purposes, it is important to identify visual search patterns that are related to high perceptual performance and to identify effective teaching strategies. This review of eye-tracking literature in the radiology domain aims to identify visual search patterns associated with high perceptual performance. Databases PubMed, EMBASE, ERIC, PsycINFO, Scopus and Web of Science were searched using 'visual perception' OR 'eye tracking' AND 'radiology' and synonyms. Two authors independently screened search results and included eye tracking studies concerning visual skills in radiology published between January 1, 1994 and July 31, 2015. Two authors independently assessed study quality with the Medical Education Research Study Quality Instrument, and extracted study data with respect to design, participant and task characteristics, and variables. A thematic analysis was conducted to extract and arrange study results, and a textual narrative synthesis was applied for data integration and interpretation. The search resulted in 22 relevant full-text articles. Thematic analysis resulted in six themes that informed the relation between visual search and level of expertise: (1) time on task, (2) eye movement characteristics of experts, (3) differences in visual attention, (4) visual search patterns, (5) search patterns in cross sectional stack imaging, and (6) teaching visual search strategies. Expert search was found to be characterized by a global-focal search pattern, which represents an initial global impression, followed by a detailed, focal search-to-find mode. Specific task-related search patterns, like drilling through CT scans and systematic search in chest X-rays, were found to be related to high expert levels. One study investigated teaching of visual search strategies, and did not find a significant effect on perceptual performance. Eye tracking literature in radiology indicates several search patterns are related to high levels of expertise, but teaching novices to search as an expert may not be effective. Experimental research is needed to find out which search strategies can improve image perception in learners.
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Efficient discovery of risk patterns in medical data.
Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul
2009-01-01
This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.
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Gabarron, Elia; Lau, Annie Y S; Wynn, Rolf
2015-12-22
Online health information-seeking behaviors have been reported to be more common at the beginning of the workweek. This behavior pattern has been interpreted as a kind of "healthy new start" or "fresh start" due to regrets or attempts to compensate for unhealthy behavior or poor choices made during the weekend. However, the observations regarding the most common health information-seeking day were based only on the analyses of users' behaviors with websites on health or on online health-related searches. We wanted to confirm if this pattern could be found in searches of Wikipedia on health-related topics and also if this search pattern was unique to health-related topics or if it could represent a more general pattern of online information searching--which could be of relevance even beyond the health sector. The aim was to examine the degree to which the search pattern described previously was specific to health-related information seeking or whether similar patterns could be found in other types of information-seeking behavior. We extracted the number of searches performed on Wikipedia in the Norwegian language for 911 days for the most common sexually transmitted diseases (chlamydia, gonorrhea, herpes, human immunodeficiency virus [HIV], and acquired immune deficiency syndrome [AIDS]), other health-related topics (influenza, diabetes, and menopause), and 2 nonhealth-related topics (footballer Lionel Messi and pop singer Justin Bieber). The search dates were classified according to the day of the week and ANOVA tests were used to compare the average number of hits per day of the week. The ANOVA tests showed that the sexually transmitted disease queries had their highest peaks on Tuesdays (P<.001) and the fewest searches on Saturdays. The other health topics also showed a weekly pattern, with the highest peaks early in the week and lower numbers on Saturdays (P<.001). Footballer Lionel Messi had the highest mean number of hits on Tuesdays and Wednesdays, whereas pop singer Justin Bieber had the most hits on Tuesdays. Both these tracked search queries also showed significantly lower numbers on Saturdays (P<.001). Our study supports prior studies finding an increase in health information searching at the beginning of the workweek. However, we also found a similar pattern for 2 randomly chosen nonhealth-related terms, which may suggest that the search pattern is not unique to health-related searches. The results are potentially relevant beyond the field of health and our preliminary findings need to be further explored in future studies involving a broader range of nonhealth-related searches.
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ERIC Educational Resources Information Center
Raymond, Jane E.; Fenske, Mark J.; Westoby, Nikki
2005-01-01
Visual search has been studied extensively, yet little is known about how its constituent processes affect subsequent emotional evaluation of searched-for and searched-through items. In 3 experiments, the authors asked observers to locate a colored pattern or tinted face in an array of other patterns or faces. Shortly thereafter, either the target…
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[Eye movement study in multiple object search process].
Xu, Zhaofang; Liu, Zhongqi; Wang, Xingwei; Zhang, Xin
2017-04-01
The aim of this study is to investigate the search time regulation of objectives and eye movement behavior characteristics in the multi-objective visual search. The experimental task was accomplished with computer programming and presented characters on a 24 inch computer display. The subjects were asked to search three targets among the characters. Three target characters in the same group were of high similarity degree while those in different groups of target characters and distraction characters were in different similarity degrees. We recorded the search time and eye movement data through the whole experiment. It could be seen from the eye movement data that the quantity of fixation points was large when the target characters and distraction characters were similar. There were three kinds of visual search patterns for the subjects including parallel search, serial search, and parallel-serial search. In addition, the last pattern had the best search performance among the three search patterns, that is, the subjects who used parallel-serial search pattern spent shorter time finding the target. The order that the targets presented were able to affect the search performance significantly; and the similarity degree between target characters and distraction characters could also affect the search performance.
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Simultaneous beam sampling and aperture shape optimization for SPORT.
Zarepisheh, Masoud; Li, Ruijiang; Ye, Yinyu; Xing, Lei
2015-02-01
Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.
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Patscanui: an intuitive web interface for searching patterns in DNA and protein data.
Blin, Kai; Wohlleben, Wolfgang; Weber, Tilmann
2018-05-02
Patterns in biological sequences frequently signify interesting features in the underlying molecule. Many tools exist to search for well-known patterns. Less support is available for exploratory analysis, where no well-defined patterns are known yet. PatScanUI (https://patscan.secondarymetabolites.org/) provides a highly interactive web interface to the powerful generic pattern search tool PatScan. The complex PatScan-patterns are created in a drag-and-drop aware interface allowing researchers to do rapid prototyping of the often complicated patterns useful to identifying features of interest.
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Protein structure database search and evolutionary classification.
Yang, Jinn-Moon; Tung, Chi-Hua
2006-01-01
As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].
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Rausch, Tobias; Thomas, Alun; Camp, Nicola J.; Cannon-Albright, Lisa A.; Facelli, Julio C.
2008-01-01
This paper describes a novel algorithm to analyze genetic linkage data using pattern recognition techniques and genetic algorithms (GA). The method allows a search for regions of the chromosome that may contain genetic variations that jointly predispose individuals for a particular disease. The method uses correlation analysis, filtering theory and genetic algorithms (GA) to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of markers, two versions of the method have been implemented. The first is an exhaustive analysis version that can be used to visualize, explore, and analyze small genetic data sets for two marker correlations; the second is a GA version, which uses a parallel implementation allowing searches of higher-order correlations in large data sets. Results on simulated data sets indicate that the method can be informative in the identification of major disease loci and gene-gene interactions in genome-wide linkage data and that further exploration of these techniques is justified. The results presented for both variants of the method show that it can help genetic epidemiologists to identify promising combinations of genetic factors that might predispose to complex disorders. In particular, the correlation analysis of IBD expression patterns might hint to possible gene-gene interactions and the filtering might be a fruitful approach to distinguish true correlation signals from noise. PMID:18547558
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Vander Lugt correlation of DNA sequence data
NASA Astrophysics Data System (ADS)
Christens-Barry, William A.; Hawk, James F.; Martin, James C.
1990-12-01
DNA, the molecule containing the genetic code of an organism, is a linear chain of subunits. It is the sequence of subunits, of which there are four kinds, that constitutes the unique blueprint of an individual. This sequence is the focus of a large number of analyses performed by an army of geneticists, biologists, and computer scientists. Most of these analyses entail searches for specific subsequences within the larger set of sequence data. Thus, most analyses are essentially pattern recognition or correlation tasks. Yet, there are special features to such analysis that influence the strategy and methods of an optical pattern recognition approach. While the serial processing employed in digital electronic computers remains the main engine of sequence analyses, there is no fundamental reason that more efficient parallel methods cannot be used. We describe an approach using optical pattern recognition (OPR) techniques based on matched spatial filtering. This allows parallel comparison of large blocks of sequence data. In this study we have simulated a Vander Lugt1 architecture implementing our approach. Searches for specific target sequence strings within a block of DNA sequence from the Co/El plasmid2 are performed.
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Semantic similarity measures in the biomedical domain by leveraging a web search engine.
Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching
2013-07-01
Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.
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Steinberg, Allyna; Griffin-Tomas, Marybec; Abu-Odeh, Desiree; Whitten, Alzen
The New York City (NYC) Department of Health and Mental Hygiene released the Teens in NYC mobile phone application (app) in 2013 as part of a program to promote sexual and reproductive health among adolescents aged 12-19 in NYC. The app featured a locator that allowed users to search for health service providers by sexual health services, contraceptive methods, and geographic locations. We analyzed data on searches from the Where to Go section of the app to understand the patterns of use of the app's search functionality. From January 7, 2013, through March 20, 2016, the app was downloaded more than 20 000 times, and more than 25 000 unique searches were conducted within the app. Results suggest that the app helped adolescents discover and access a wide range of sexual health services, including less commonly used contraceptives. Those designing similar apps should consider incorporating search functionality by sexual health service (including abortion), contraceptive method, and user location.
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Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment
2011-05-01
instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...REPORT Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Soil...cells). Thus, a method is required to downscale intermediate-resolution patterns to finer resolutions. Fortunately, fine-resolution variations in
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Cancer Information Seeking and Scanning: Sources and Patterns
ERIC Educational Resources Information Center
Barnes, Laura L. B.; Khojasteh, Jam J.; Wheeler, Denna
2017-01-01
Objective: This study aimed to identify predominant search patterns in a recent search for health information and a potential search for strongly needed cancer information, to identify the commonly scanned sources of information that may represent stable elements of the information fields characteristic of these patterns, and to evaluate whether…
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2017-01-01
Background Patient and consumer access to eHealth information is of crucial importance because of its role in patient-centered medicine and to improve knowledge about general aspects of health and medical topics. Objectives The objectives were to analyze and compare eHealth search patterns in a private (United States) and a public (United Kingdom) health care market. Methods A new taxonomy of eHealth websites is proposed to organize the largest eHealth websites. An online measurement framework is developed that provides a precise and detailed measurement system. Online panel data are used to accurately track and analyze detailed search behavior across 100 of the largest eHealth websites in the US and UK health care markets. Results The health, medical, and lifestyle categories account for approximately 90% of online activity, and e-pharmacies, social media, and professional categories account for the remaining 10% of online activity. Overall search penetration of eHealth websites is significantly higher in the private (United States) than the public market (United Kingdom). Almost twice the number of eHealth users in the private market have adopted online search in the health and lifestyle categories and also spend more time per website than those in the public market. The use of medical websites for specific conditions is almost identical in both markets. The allocation of search effort across categories is similar in both the markets. For all categories, the vast majority of eHealth users only access one website within each category. Those that conduct a search of two or more websites display very narrow search patterns. All users spend relatively little time on eHealth, that is, 3-7 minutes per website. Conclusions The proposed online measurement framework exploits online panel data to provide a powerful and objective method of analyzing and exploring eHealth behavior. The private health care system does appear to have an influence on eHealth search behavior in terms of search penetration and time spent per website in the health and lifestyle categories. Two explanations are offered: (1) the personal incentive of medical costs in the private market incentivizes users to conduct online search; and (2) health care information is more easily accessible through health care professionals in the United Kingdom compared with the United States. However, the use of medical websites is almost identical, suggesting that patients interested in a specific condition have a motivation to search and evaluate health information, irrespective of the health care market. The relatively low level of search in terms of the number of websites accessed and the average time per website raise important questions about the actual level of patient informedness in both the markets. Areas for future research are outlined. PMID:28408362
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Hanik, Bruce; Chaney, J. Don; Tennant, Bethany
2012-01-01
Background The current “Millennial Generation” of college students majoring in the health professions has unprecedented access to the Internet. Although some research has been initiated among medical professionals to investigate the cognitive basis for health information searches on the Internet, little is known about Internet search practices among health and medical professional students. Objective To systematically identify health professional college student perspectives of personal eHealth search practices. Methods Q methodology was used to examine subjective perspectives regarding personal eHealth search practices among allied health students majoring in a health education degree program. Thirteen (n = 13) undergraduate students were interviewed about their attitudes and experiences conducting eHealth searches. From the interviews, 36 statements were used in a structured ranking task to identify clusters and determine which specific perceptions of eHealth search practices discriminated students into different groups. Scores on an objective measure of eHealth literacy were used to help categorize participant perspectives. Results Q-technique factor analysis of the rankings identified 3 clusters of respondents with differing views on eHealth searches that generally coincided with participants’ objective eHealth literacy scores. The proficient resourceful students (pattern/structure coefficient range 0.56-0.80) described themselves as using multiple resources to obtain eHealth information, as opposed to simply relying on Internet search engines. The intermediate reluctant students (pattern/structure coefficient range 0.75-0.90) reported engaging only Internet search engines to locate eHealth information, citing undeveloped evaluation skills when considering sources of information located on the Internet. Both groups of advanced students reported not knowing how to use Boolean operators to conduct Internet health searches. The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information. Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task. Conclusions Subjective perspectives of eHealth search practices differed among students possessing different levels of eHealth literacy. These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet. PMID:22543437
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Seo, Dong-Woo; Sohn, Chang Hwan; Kim, Sung-Hoon; Ryoo, Seung Mok; Lee, Yoon-Seon; Lee, Jae Ho; Kim, Won Young; Lim, Kyoung Soo
2016-01-01
Background Digital surveillance using internet search queries can improve both the sensitivity and timeliness of the detection of a health event, such as an influenza outbreak. While it has recently been estimated that the mobile search volume surpasses the desktop search volume and mobile search patterns differ from desktop search patterns, the previous digital surveillance systems did not distinguish mobile and desktop search queries. The purpose of this study was to compare the performance of mobile and desktop search queries in terms of digital influenza surveillance. Methods and Results The study period was from September 6, 2010 through August 30, 2014, which consisted of four epidemiological years. Influenza-like illness (ILI) and virologic surveillance data from the Korea Centers for Disease Control and Prevention were used. A total of 210 combined queries from our previous survey work were used for this study. Mobile and desktop weekly search data were extracted from Naver, which is the largest search engine in Korea. Spearman’s correlation analysis was used to examine the correlation of the mobile and desktop data with ILI and virologic data in Korea. We also performed lag correlation analysis. We observed that the influenza surveillance performance of mobile search queries matched or exceeded that of desktop search queries over time. The mean correlation coefficients of mobile search queries and the number of queries with an r-value of ≥ 0.7 equaled or became greater than those of desktop searches over the four epidemiological years. A lag correlation analysis of up to two weeks showed similar trends. Conclusion Our study shows that mobile search queries for influenza surveillance have equaled or even become greater than desktop search queries over time. In the future development of influenza surveillance using search queries, the recognition of changing trend of mobile search data could be necessary. PMID:27391028
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Use of handheld sonar to locate a missing diver.
McGrane, Owen; Cronin, Aaron; Hile, David
2013-03-01
The purpose of this study was to investigate whether a handheld sonar device significantly reduces the mean time needed to locate a missing diver. This institutional review board approved, prospective, crossover study used a voluntary convenience sample of 10 scuba divers. Participants conducted both a standard and modified search to locate a simulated missing diver. The standard search utilized a conventional search pattern starting at the point where the missing diver (simulated) was last seen. The modified search used a sonar beacon to augment the search. For each search method, successful completion of the search was defined as locating the missing diver within 40 minutes. Twenty total dives were completed. Using a standard search pattern, the missing diver was found by only 1 diver (10%), taking 18 minutes and 45 seconds. In the sonar-assisted search group, the missing diver was found by all 10 participants (100%), taking an average of 2 minutes and 47 seconds (SD 1 minute, 20 seconds). Using the nonparametric related samples Wilcoxon signed rank test, actual times between the sonar group and the standard group were significant (P < .01). Using paired samples t tests, the sonar group's self-assessed confidence increased significantly after using the sonar (P < .001), whereas the standard group decreased in confidence (not statistically significant, P = .111). Handheld sonar significantly reduces the mean duration to locate a missing diver as well as increasing users' confidence in their ability to find a missing diver when compared with standard search techniques. Copyright © 2013 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.
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How bootstrap can help in forecasting time series with more than one seasonal pattern
NASA Astrophysics Data System (ADS)
Cordeiro, Clara; Neves, M. Manuela
2012-09-01
The search for the future is an appealing challenge in time series analysis. The diversity of forecasting methodologies is inevitable and is still in expansion. Exponential smoothing methods are the launch platform for modelling and forecasting in time series analysis. Recently this methodology has been combined with bootstrapping revealing a good performance. The algorithm (Boot. EXPOS) using exponential smoothing and bootstrap methodologies, has showed promising results for forecasting time series with one seasonal pattern. In case of more than one seasonal pattern, the double seasonal Holt-Winters methods and the exponential smoothing methods were developed. A new challenge was now to combine these seasonal methods with bootstrap and carry over a similar resampling scheme used in Boot. EXPOS procedure. The performance of such partnership will be illustrated for some well-know data sets existing in software.
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Noppert, Grace A; Kubale, John T; Wilson, Mark L
2017-01-01
Background Infectious disease epidemiologists have long recognised the importance of social variables as drivers of epidemics and disease risk, yet few apply analytic approaches from social epidemiology. We quantified and evaluated the extent to which recent infectious disease research is employing the perspectives and methods of social epidemiology by replicating the methodology used by Cohen et al in a 2007 study. Methods 2 search strategies were used to identify and review articles published from 1 January 2005 to 31 December 2013. First, we performed a keyword search of ‘social epidemiology’ in the title/abstract/text of published studies identified in PubMed, PsychInfo and ISI Web of Science, and classified each study as pertaining to infectious, non-infectious or other outcomes. A second PubMed search identified articles that were cross-referenced under non-infectious or infectious, and search terms relating to social variables. The abstracts of all articles were read, classified and examined to identify patterns over time. Results Findings suggest that infectious disease research publications that explicitly or implicitly incorporate social epidemiological approaches have stagnated in recent years. While the number of publications that were explicitly self-classified as ‘social epidemiology’ has risen, the proportion that investigated infectious disease outcomes has declined. Furthermore, infectious diseases accounted for the smallest proportion of articles that were cross-referenced with Medical Subject Headings (MeSH) terms related to social factors, and most of these involved sexually transmitted diseases. Conclusions The current landscape of infectious disease epidemiology could benefit from new approaches to understanding how the social and biophysical environment sustains transmission and exacerbates disparities. The framework of social epidemiology provides infectious disease researchers with such a perspective and research opportunity. PMID:27799618
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Booma, P M; Prabhakaran, S; Dhanalakshmi, R
2014-01-01
Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.
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Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.
2014-01-01
Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661
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2008-03-01
injector con- figurations for Scramjet applications.” International Journal of Heat and Mass Transfer 49: 3634–3644 (2006). 8. Anderson, C.D...Experimental Attainment of Optimal Conditions,” Journal of the Royal Statistical Society, B(13): 1–38, 1951. 19. Brewer, K.M. Exergy Methods for the Mission...second applies mvps to a new scramjet design in support of the Hypersonic International Flight Re- search Experimentation (hifire). The results
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ERIC Educational Resources Information Center
Bond, William Glenn
2012-01-01
In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid. The method presented first locates…
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A Graph Approach to Mining Biological Patterns in the Binding Interfaces.
Cheng, Wen; Yan, Changhui
2017-01-01
Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.
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Fingerprint pattern restoration by digital image processing techniques.
Wen, Che-Yen; Yu, Chiu-Chung
2003-09-01
Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.
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Stracuzzi, David John; Brost, Randolph C.; Phillips, Cynthia A.; ...
2015-09-26
Geospatial semantic graphs provide a robust foundation for representing and analyzing remote sensor data. In particular, they support a variety of pattern search operations that capture the spatial and temporal relationships among the objects and events in the data. However, in the presence of large data corpora, even a carefully constructed search query may return a large number of unintended matches. This work considers the problem of calculating a quality score for each match to the query, given that the underlying data are uncertain. As a result, we present a preliminary evaluation of three methods for determining both match qualitymore » scores and associated uncertainty bounds, illustrated in the context of an example based on overhead imagery data.« less
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PIPI: PTM-Invariant Peptide Identification Using Coding Method.
Yu, Fengchao; Li, Ning; Yu, Weichuan
2016-12-02
In computational proteomics, the identification of peptides with an unlimited number of post-translational modification (PTM) types is a challenging task. The computational cost associated with database search increases exponentially with respect to the number of modified amino acids and linearly with respect to the number of potential PTM types at each amino acid. The problem becomes intractable very quickly if we want to enumerate all possible PTM patterns. To address this issue, one group of methods named restricted tools (including Mascot, Comet, and MS-GF+) only allow a small number of PTM types in database search process. Alternatively, the other group of methods named unrestricted tools (including MS-Alignment, ProteinProspector, and MODa) avoids enumerating PTM patterns with an alignment-based approach to localizing and characterizing modified amino acids. However, because of the large search space and PTM localization issue, the sensitivity of these unrestricted tools is low. This paper proposes a novel method named PIPI to achieve PTM-invariant peptide identification. PIPI belongs to the category of unrestricted tools. It first codes peptide sequences into Boolean vectors and codes experimental spectra into real-valued vectors. For each coded spectrum, it then searches the coded sequence database to find the top scored peptide sequences as candidates. After that, PIPI uses dynamic programming to localize and characterize modified amino acids in each candidate. We used simulation experiments and real data experiments to evaluate the performance in comparison with restricted tools (i.e., Mascot, Comet, and MS-GF+) and unrestricted tools (i.e., Mascot with error tolerant search, MS-Alignment, ProteinProspector, and MODa). Comparison with restricted tools shows that PIPI has a close sensitivity and running speed. Comparison with unrestricted tools shows that PIPI has the highest sensitivity except for Mascot with error tolerant search and ProteinProspector. These two tools simplify the task by only considering up to one modified amino acid in each peptide, which results in a higher sensitivity but has difficulty in dealing with multiple modified amino acids. The simulation experiments also show that PIPI has the lowest false discovery proportion, the highest PTM characterization accuracy, and the shortest running time among the unrestricted tools.
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Emery, Sherry L; Vera, Lisa; Huang, Jidong; Szczypka, Glen
2014-01-01
Background Awareness and use of electronic cigarettes has rapidly grown in the USA recently, in step with increased product marketing. Using responses to a population survey of US adults, we analysed demographic patterns of exposure to, searching for and sharing of e-cigarette-related information across media platforms. Methods An online survey of 17 522 US adults was conducted in 2013. The nationally representative sample was drawn from GfK Group's KnowledgePanel plus off-panel recruitment. Fixed effects logit models were applied to analyse relationships between exposure to, searching for and sharing of e-cigarette-related information and demographic characteristics, e-cigarette and tobacco use, and media behaviours. Results High levels of awareness about e-cigarettes were indicated (86% aware; 47% heard through media channels). Exposure to e-cigarette-related information was associated with tobacco use, age, gender, more education, social media use and time spent online. Although relatively small proportions of the sample had searched for (∼5%) or shared (∼2%) e-cigarette information, our analyses indicated demographic patterns to those behaviours. Gender, high income and using social media were associated with searching for e-cigarette information; lesbian, gay and bisexual and less education were associated with sharing. Current tobacco use, age, being Hispanic and time spent online were associated with both searching and sharing. Conclusions US adults are widely exposed to e-cigarette marketing through the media; such marketing may differentially target specific demographic groups. Further research should longitudinally examine how exposure to, searching for and sharing of e-cigarette information relate to subsequent use of e-cigarettes and/or combustible tobacco. PMID:24935893
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A flexible motif search technique based on generalized profiles.
Bucher, P; Karplus, K; Moeri, N; Hofmann, K
1996-03-01
A flexible motif search technique is presented which has two major components: (1) a generalized profile syntax serving as a motif definition language; and (2) a motif search method specifically adapted to the problem of finding multiple instances of a motif in the same sequence. The new profile structure, which is the core of the generalized profile syntax, combines the functions of a variety of motif descriptors implemented in other methods, including regular expression-like patterns, weight matrices, previously used profiles, and certain types of hidden Markov models (HMMs). The relationship between generalized profiles and other biomolecular motif descriptors is analyzed in detail, with special attention to HMMs. Generalized profiles are shown to be equivalent to a particular class of HMMs, and conversion procedures in both directions are given. The conversion procedures provide an interpretation for local alignment in the framework of stochastic models, allowing for clear, simple significance tests. A mathematical statement of the motif search problem defines the new method exactly without linking it to a specific algorithmic solution. Part of the definition includes a new definition of disjointness of alignments.
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NASA Astrophysics Data System (ADS)
Zhang, Wenshuai; Zeng, Xiaoyan; Zhang, Li; Peng, Haiyan; Jiao, Yongjun; Zeng, Jun; Treutlein, Herbert R.
2013-06-01
In this work, we have developed a new approach to predict the epitopes of antigens that are recognized by a specific antibody. Our method is based on the "multiple copy simultaneous search" (MCSS) approach which identifies optimal locations of small chemical functional groups on the surfaces of the antibody, and identifying sequence patterns of peptides that can bind to the surface of the antibody. The identified sequence patterns are then used to search the amino-acid sequence of the antigen protein. The approach was validated by reproducing the binding epitope of HIV gp120 envelop glycoprotein for the human neutralizing antibody as revealed in the available crystal structure. Our method was then applied to predict the epitopes of two glycoproteins of a newly discovered bunyavirus recognized by an antibody named MAb 4-5. These predicted epitopes can be verified by experimental methods. We also discuss the involvement of different amino acids in the antigen-antibody recognition based on the distributions of MCSS minima of different functional groups.
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A Robust and Efficient Method for Steady State Patterns in Reaction-Diffusion Systems
Lo, Wing-Cheong; Chen, Long; Wang, Ming; Nie, Qing
2012-01-01
An inhomogeneous steady state pattern of nonlinear reaction-diffusion equations with no-flux boundary conditions is usually computed by solving the corresponding time-dependent reaction-diffusion equations using temporal schemes. Nonlinear solvers (e.g., Newton’s method) take less CPU time in direct computation for the steady state; however, their convergence is sensitive to the initial guess, often leading to divergence or convergence to spatially homogeneous solution. Systematically numerical exploration of spatial patterns of reaction-diffusion equations under different parameter regimes requires that the numerical method be efficient and robust to initial condition or initial guess, with better likelihood of convergence to an inhomogeneous pattern. Here, a new approach that combines the advantages of temporal schemes in robustness and Newton’s method in fast convergence in solving steady states of reaction-diffusion equations is proposed. In particular, an adaptive implicit Euler with inexact solver (AIIE) method is found to be much more efficient than temporal schemes and more robust in convergence than typical nonlinear solvers (e.g., Newton’s method) in finding the inhomogeneous pattern. Application of this new approach to two reaction-diffusion equations in one, two, and three spatial dimensions, along with direct comparisons to several other existing methods, demonstrates that AIIE is a more desirable method for searching inhomogeneous spatial patterns of reaction-diffusion equations in a large parameter space. PMID:22773849
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NASA Astrophysics Data System (ADS)
Cheng, Ruida; Jackson, Jennifer N.; McCreedy, Evan S.; Gandler, William; Eijkenboom, J. J. F. A.; van Middelkoop, M.; McAuliffe, Matthew J.; Sheehan, Frances T.
2016-03-01
The paper presents an automatic segmentation methodology for the patellar bone, based on 3D gradient recalled echo and gradient recalled echo with fat suppression magnetic resonance images. Constricted search space outlines are incorporated into recursive ray-tracing to segment the outer cortical bone. A statistical analysis based on the dependence of information in adjacent slices is used to limit the search in each image to between an outer and inner search region. A section based recursive ray-tracing mechanism is used to skip inner noise regions and detect the edge boundary. The proposed method achieves higher segmentation accuracy (0.23mm) than the current state-of-the-art methods with the average dice similarity coefficient of 96.0% (SD 1.3%) agreement between the auto-segmentation and ground truth surfaces.
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Real view radiology-impact on search patterns and confidence in radiology education.
Bailey, Jared H; Roth, Trenton D; Kohli, Mark D; Heitkamp, Darel E
2014-07-01
Search patterns are important for radiologists because they enable systematic case review. Because radiology residents are exposed to so many imaging modalities and anatomic regions, and they rotate on-and-off service so frequently, they may have difficulty establishing effective search patterns. We developed Real View Radiology (RVR), an educational system founded on guided magnetic resonance imaging (MRI) case review and evaluated its impact on search patterns and interpretative confidence of junior radiology residents. RVR guides learners through unknown examinations by sequentially prompting learners to certain aspects of a case via a comprehensive question set and then providing immediate feedback. Junior residents first completed a brief evaluation regarding their level of confidence when interpreting certain joint MRI cases and frequency of search pattern use. They spent four half-days interpreting cases using RVR. Once finished, they repeated the evaluations. The junior resident results were compared to third-year residents who had not used RVR. The data were analyzed for change in confidence, use of search patterns, and number of cases completed. Twelve first-year and thirteen second-year residents (trained cohort) were enrolled in the study. During their 4-week musculoskeletal rotations, they completed on average 29.3 MRI knee (standard deviation [SD], 1.6) and 17.4 shoulder (SD, 1.2) cases using RVR. Overall search pattern scores of the trained cohort increased significantly both from pretraining to posttraining (knee P < .01, shoulder P < .01) and compared to the untrained third-year residents (knee (P < .01, and shoulder P < .01). The trained cohort confidence scores also increased significantly from pre to post for all joints (knee P < .01, shoulder P < .01, pelvis P < .01, and ankle P < .01). Radiology residents can increase their MRI case interpretation confidence and improve the consistency of search pattern use by training with a question-based sequential reveal educational program. RVR could be used to supplement training and assist with search pattern creation in areas in which residents often do not acquire adequate clinical exposure. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.
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Search prefilters to assist in library searching of infrared spectra of automotive clear coats.
Lavine, Barry K; Fasasi, Ayuba; Mirjankar, Nikhil; White, Collin; Sandercock, Mark
2015-01-01
Clear coat searches of the infrared (IR) spectral library of the paint data query (PDQ) forensic database often generate an unusable number of hits that span multiple manufacturers, assembly plants, and years. To improve the accuracy of the hit list, pattern recognition methods have been used to develop search prefilters (i.e., principal component models) that differentiate between similar but non-identical IR spectra of clear coats on the basis of manufacturer (e.g., General Motors, Ford, Chrysler) or assembly plant. A two step procedure to develop these search prefilters was employed. First, the discrete wavelet transform was used to decompose each IR spectrum into wavelet coefficients to enhance subtle but significant features in the spectral data. Second, a genetic algorithm for IR spectral pattern recognition was employed to identify wavelet coefficients characteristic of the manufacturer or assembly plant of the vehicle. Even in challenging trials where the paint samples evaluated were all from the same manufacturer (General Motors) within a limited production year range (2000-2006), the respective assembly plant of the vehicle was correctly identified. Search prefilters to identify assembly plants were successfully validated using 10 blind samples provided by the Royal Canadian Mounted Police (RCMP) as part of a study to populate PDQ to current production years, whereas the search prefilter to discriminate among automobile manufacturers was successfully validated using IR spectra obtained directly from the PDQ database. Copyright © 2014 Elsevier B.V. All rights reserved.
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ERIC Educational Resources Information Center
Bourbeau-Walker, Micheline
1984-01-01
It is proposed that while the sciences have progressed steadily, language teaching methods have swung like a pendulum between two broad approaches: formal and functional. The history of this pattern is outlined, current practices are discussed, and the possibility of escaping from this polarizing cycle is examined. (MSE)
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2016-01-01
Background Infodemiology can offer practical and feasible health research applications through the practice of studying information available on the Web. Google Trends provides publicly accessible information regarding search behaviors in a population, which may be studied and used for health campaign evaluation and disease monitoring. Additional studies examining the use and effectiveness of Google Trends for these purposes remain warranted. Objective The objective of our study was to explore the use of infodemiology in the context of health campaign evaluation and chronic disease monitoring. It was hypothesized that following a launch of a campaign, there would be an increase in information seeking behavior on the Web. Second, increasing and decreasing disease patterns in a population would be associated with search activity patterns. This study examined 4 different diseases: human immunodeficiency virus (HIV) infection, stroke, colorectal cancer, and marijuana use. Methods Using Google Trends, relative search volume data were collected throughout the period of February 2004 to January 2015. Campaign information and disease statistics were obtained from governmental publications. Search activity trends were graphed and assessed with disease trends and the campaign interval. Pearson product correlation statistics and joinpoint methodology analyses were used to determine significance. Results Disease patterns and online activity across all 4 diseases were significantly correlated: HIV infection (r=.36, P<.001), stroke (r=.40, P<.001), colorectal cancer (r= −.41, P<.001), and substance use (r=.64, P<.001). Visual inspection and the joinpoint analysis showed significant correlations for the campaigns on colorectal cancer and marijuana use in stimulating search activity. No significant correlations were observed for the campaigns on stroke and HIV regarding search activity. Conclusions The use of infoveillance shows promise as an alternative and inexpensive solution to disease surveillance and health campaign evaluation. Further research is needed to understand Google Trends as a valid and reliable tool for health research. PMID:27733330
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Complex dynamics of our economic life on different scales: insights from search engine query data.
Preis, Tobias; Reith, Daniel; Stanley, H Eugene
2010-12-28
Search engine query data deliver insight into the behaviour of individuals who are the smallest possible scale of our economic life. Individuals are submitting several hundred million search engine queries around the world each day. We study weekly search volume data for various search terms from 2004 to 2010 that are offered by the search engine Google for scientific use, providing information about our economic life on an aggregated collective level. We ask the question whether there is a link between search volume data and financial market fluctuations on a weekly time scale. Both collective 'swarm intelligence' of Internet users and the group of financial market participants can be regarded as a complex system of many interacting subunits that react quickly to external changes. We find clear evidence that weekly transaction volumes of S&P 500 companies are correlated with weekly search volume of corresponding company names. Furthermore, we apply a recently introduced method for quantifying complex correlations in time series with which we find a clear tendency that search volume time series and transaction volume time series show recurring patterns.
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NASA Astrophysics Data System (ADS)
Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.
2004-11-01
Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.
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Huang, Chung-Chi; Lu, Zhiyong
2016-01-01
Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as ‘CHEMICAL-1 compared to CHEMICAL-2.’ With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical–disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order covering diverse bio-entity relations. To assess the potential utility of our automated top-ranked patterns of a given relation in semantic search, we performed a pilot study on frequently sought semantic relations in PubMed and observed improved literature retrieval effectiveness based on post-hoc human relevance evaluation. Further investigation in larger tests and in real-world scenarios is warranted. PMID:27016698
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Numerical linear algebra in data mining
NASA Astrophysics Data System (ADS)
Eldén, Lars
Ideas and algorithms from numerical linear algebra are important in several areas of data mining. We give an overview of linear algebra methods in text mining (information retrieval), pattern recognition (classification of handwritten digits), and PageRank computations for web search engines. The emphasis is on rank reduction as a method of extracting information from a data matrix, low-rank approximation of matrices using the singular value decomposition and clustering, and on eigenvalue methods for network analysis.
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The foxconn suicides and their media prominence: is the werther effect applicable in china?
2011-01-01
Background Media reporting of suicide and its relationship with actual suicide has rarely been investigated in Mainland China. The "Foxconn suicides" is a description referring to a string of suicides/attempts during 2010, all of which were related to a giant electrical manufacturing company, Foxconn. This study aimed to examine the clustering and copycat effects of the Foxconn suicides, and to investigate temporal patterns in how they were reported by the media in Mainland China, Hong Kong (HK), and Taiwan (TW). Methods Relevant articles were collected from representative newspapers published in three big cities in Mainland China (Beijing (BJ), Shenzhen (SZ), and Guangzhou (GZ)), HK, and TW, together with searching intensity data on the topic conducted using the Baidu search engine in Mainland China. The temporal clustering effects of the Foxconn suicides and their media prominence were assessed using the Kolmogorov-Smirnov test. The media reports of the Foxconn suicides' temporal patterns were explored using a nonparametric curve estimation method (that is, the local linear method). The potential mutual interactions between the Foxconn suicides and their media prominence were also examined, using logistic and Poisson regression methods. Results The results support a temporal clustering effect for the Foxconn suicides. The BJ-based newspapers' reporting and the occurrence of a Foxconn suicide/attempt are each found to be associated with an elevated chance of a further Foxconn suicide 3 days later. The occurrence of a Foxconn suicide also immediately influenced the intensity of both Baidu searching and newspaper reporting. Regional diversity in suicide reporting tempo-patterns within Mainland China, and similarities between HK and TW, are also demonstrated. Conclusions The Foxconn suicides were temporally clustered. Their occurrences were influenced by the reporting of BJ-based newspapers, and contagion within the company itself. Further suicide research and prevention work in China should consider its special media environment. PMID:22044598
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Age differences in visual search for compound patterns: long- versus short-range grouping.
Burack, J A; Enns, J T; Iarocci, G; Randolph, B
2000-11-01
Visual search for compound patterns was examined in observers aged 6, 8, 10, and 22 years. The main question was whether age-related improvement in search rate (response time slope over number of items) was different for patterns defined by short- versus long-range spatial relations. Perceptual access to each type of relation was varied by using elements of same contrast (easy to access) or mixed contrast (hard to access). The results showed large improvements with age in search rate for long-range targets; search rate for short-range targets was fairly constant across age. This pattern held regardless of whether perceptual access to a target was easy or hard, supporting the hypothesis that different processes are involved in perceptual grouping at these two levels. The results also point to important links between ontogenic and microgenic change in perception (H. Werner, 1948, 1957).
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Image Halftoning Using Optimized Dot Diffusion
1998-01-01
ppvnath@sys.caltech.edu ABSTRACT The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion ...digital halftoning : ordered dither [1], error diffusion [2], neural-net based methods [8], and more recently direct binary search (DBS) [7]. Ordered...from periodic patterns. On the other hand error diffused halftones do not suffer from periodicity and offer blue noise characteristic [3] which is
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Astrometric Search Method for Individually Resolvable Gravitational Wave Sources with Gaia
NASA Astrophysics Data System (ADS)
Moore, Christopher J.; Mihaylov, Deyan P.; Lasenby, Anthony; Gilmore, Gerard
2017-12-01
Gravitational waves (GWs) cause the apparent position of distant stars to oscillate with a characteristic pattern on the sky. Astrometric measurements (e.g., those made by Gaia) provide a new way to search for GWs. The main difficulty facing such a search is the large size of the data set; Gaia observes more than one billion stars. In this Letter the problem of searching for GWs from individually resolvable supermassive black hole binaries using astrometry is addressed for the first time; it is demonstrated how the data set can be compressed by a factor of more than 1 06, with a loss of sensitivity of less than 1%. This technique was successfully used to recover artificially injected GW signals from mock Gaia data and to assess the GW sensitivity of Gaia. Throughout the Letter the complementarity of Gaia and pulsar timing searches for GWs is highlighted.
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Predicting hospital visits from geo-tagged Internet search logs.
Agarwal, Vibhu; Han, Lichy; Madan, Isaac; Saluja, Shaurya; Shidham, Aaditya; Shah, Nigam H
2016-01-01
The steady rise in healthcare costs has deprived over 45 million Americans of healthcare services (1, 2) and has encouraged healthcare providers to look for opportunities to improve their operational efficiency. Prior studies have shown that evidence of healthcare seeking intent in Internet searches correlates well with healthcare resource utilization. Given the ubiquitous nature of mobile Internet search, we hypothesized that analyzing geo-tagged mobile search logs could enable us to machine-learn predictors of future patient visits. Using a de-identified dataset of geo-tagged mobile Internet search logs, we mined text and location patterns that are predictors of healthcare resource utilization and built statistical models that predict the probability of a user's future visit to a medical facility. Our efforts will enable the development of innovative methods for modeling and optimizing the use of healthcare resources-a crucial prerequisite for securing healthcare access for everyone in the days to come.
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Evaluation of Simulated Clinical Breast Exam Motion Patterns Using Marker-Less Video Tracking
Azari, David P.; Pugh, Carla M.; Laufer, Shlomi; Kwan, Calvin; Chen, Chia-Hsiung; Yen, Thomas Y.; Hu, Yu Hen; Radwin, Robert G.
2016-01-01
Objective This study investigates using marker-less video tracking to evaluate hands-on clinical skills during simulated clinical breast examinations (CBEs). Background There are currently no standardized and widely accepted CBE screening techniques. Methods Experienced physicians attending a national conference conducted simulated CBEs presenting different pathologies with distinct tumorous lesions. Single hand exam motion was recorded and analyzed using marker-less video tracking. Four kinematic measures were developed to describe temporal (time pressing and time searching) and spatial (area covered and distance explored) patterns. Results Mean differences between time pressing, area covered, and distance explored varied across the simulated lesions. Exams were objectively categorized as either sporadic, localized, thorough, or efficient for both temporal and spatial categories based on spatiotemporal characteristics. The majority of trials were temporally or spatially thorough (78% and 91%), exhibiting proportionally greater time pressing and time searching (temporally thorough) and greater area probed with greater distance explored (spatially thorough). More efficient exams exhibited proportionally more time pressing with less time searching (temporally efficient) and greater area probed with less distance explored (spatially efficient). Just two (5.9 %) of the trials exhibited both high temporal and spatial efficiency. Conclusions Marker-less video tracking was used to discriminate different examination techniques and measure when an exam changes from general searching to specific probing. The majority of participants exhibited more thorough than efficient patterns. Application Marker-less video kinematic tracking may be useful for quantifying clinical skills for training and assessment. PMID:26546381
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NASA Astrophysics Data System (ADS)
Huebner, Claudia S.
2016-10-01
As a consequence of fluctuations in the index of refraction of the air, atmospheric turbulence causes scintillation, spatial and temporal blurring as well as global and local image motion creating geometric distortions. To mitigate these effects many different methods have been proposed. Global as well as local motion compensation in some form or other constitutes an integral part of many software-based approaches. For the estimation of motion vectors between consecutive frames simple methods like block matching are preferable to more complex algorithms like optical flow, at least when challenged with near real-time requirements. However, the processing power of commercially available computers continues to increase rapidly and the more powerful optical flow methods have the potential to outperform standard block matching methods. Therefore, in this paper three standard optical flow algorithms, namely Horn-Schunck (HS), Lucas-Kanade (LK) and Farnebäck (FB), are tested for their suitability to be employed for local motion compensation as part of a turbulence mitigation system. Their qualitative performance is evaluated and compared with that of three standard block matching methods, namely Exhaustive Search (ES), Adaptive Rood Pattern Search (ARPS) and Correlation based Search (CS).
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Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns
Chérel, Guillaume; Cottineau, Clémentine; Reuillon, Romain
2015-01-01
Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic. PMID:26368917
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Importance Sampling of Word Patterns in DNA and Protein Sequences
Chan, Hock Peng; Chen, Louis H.Y.
2010-01-01
Abstract Monte Carlo methods can provide accurate p-value estimates of word counting test statistics and are easy to implement. They are especially attractive when an asymptotic theory is absent or when either the search sequence or the word pattern is too short for the application of asymptotic formulae. Naive direct Monte Carlo is undesirable for the estimation of small probabilities because the associated rare events of interest are seldom generated. We propose instead efficient importance sampling algorithms that use controlled insertion of the desired word patterns on randomly generated sequences. The implementation is illustrated on word patterns of biological interest: palindromes and inverted repeats, patterns arising from position-specific weight matrices (PSWMs), and co-occurrences of pairs of motifs. PMID:21128856
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In Search of Theory and Method in American Indian Studies
ERIC Educational Resources Information Center
Champagne, Duane
2007-01-01
American Indian studies should have a theoretical and methodological focus sufficient to organize an academic discipline. A primary focus of American Indian studies as a discipline is to conceptualize, research, and explain patterns of American Indian individual and collective community choices and strategies when confronted with relations with…
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Forecasting of hourly load by pattern recognition in a small area power system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dehdashti-Shahrokh, A.
1982-01-01
An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less
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Searching for substructures in fragment spaces.
Ehrlich, Hans-Christian; Volkamer, Andrea; Rarey, Matthias
2012-12-21
A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are composed of molecular fragments and their connection rules, made the representation of large combinatorial data sets feasible. At the same time, search algorithms face the problem of structural features spanning over multiple fragments. Due to the combinatorial nature of FSs, an enumeration of all products is impossible. In order to overcome these time and storage issues, we present a method that is able to find substructures in FSs without explicit product enumeration. This is accomplished by splitting substructures into subsubstructures and mapping them onto fragments with respect to fragment connectivity rules. The method has been evaluated on three different drug discovery scenarios considering the exploration of a molecule class, the elaboration of decoration patterns for a molecular core, and the exhaustive query for peptides in FSs. FSs can be searched in seconds, and found products contain novel compounds not present in the PubChem database which may serve as hints for new lead structures.
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Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data.
Zhang, Chao; Zheng, Yu; Ma, Xiuli; Han, Jiawei
2015-08-01
Recent years have witnessed the wide proliferation of geo-sensory applications wherein a bundle of sensors are deployed at different locations to cooperatively monitor the target condition. Given massive geo-sensory data, we study the problem of mining spatial co-evolving patterns (SCPs), i.e ., groups of sensors that are spatially correlated and co-evolve frequently in their readings. SCP mining is of great importance to various real-world applications, yet it is challenging because (1) the truly interesting evolutions are often flooded by numerous trivial fluctuations in the geo-sensory time series; and (2) the pattern search space is extremely large due to the spatiotemporal combinatorial nature of SCP. In this paper, we propose a two-stage method called Assembler. In the first stage, Assembler filters trivial fluctuations using wavelet transform and detects frequent evolutions for individual sensors via a segment-and-group approach. In the second stage, Assembler generates SCPs by assembling the frequent evolutions of individual sensors. Leveraging the spatial constraint, it conceptually organizes all the SCPs into a novel structure called the SCP search tree, which facilitates the effective pruning of the search space to generate SCPs efficiently. Our experiments on both real and synthetic data sets show that Assembler is effective, efficient, and scalable.
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2014-01-01
Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277
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Pattern recognition with parallel associative memory
NASA Technical Reports Server (NTRS)
Toth, Charles K.; Schenk, Toni
1990-01-01
An examination is conducted of the feasibility of searching targets in aerial photographs by means of a parallel associative memory (PAM) that is based on the nearest-neighbor algorithm; the Hamming distance is used as a measure of closeness, in order to discriminate patterns. Attention has been given to targets typically used for ground-control points. The method developed sorts out approximate target positions where precise localizations are needed, in the course of the data-acquisition process. The majority of control points in different images were correctly identified.
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Perez, Susan L; Kravitz, Richard L; Bell, Robert A; Chan, Man Shan; Paterniti, Debora A
2016-08-09
The Internet is valuable for those with limited access to health care services because of its low cost and wealth of information. Our objectives were to investigate how the Internet is used to obtain health-related information and how individuals with differing socioeconomic resources navigate it when presented with a health decision. Study participants were recruited from public settings and social service agencies. Participants listened to one of two clinical scenarios - consistent with influenza or bacterial meningitis - and then conducted an Internet search. Screen-capture video software captured the Internet search. Participant Internet search strategies were analyzed and coded for pre- and post-Internet search guess at diagnosis and information seeking patterns. Individuals who did not have a college degree and were recruited from locations offering social services were categorized as "lower socioeconomic status" (SES); the remainder was categorized as "higher SES." Participants were 78 Internet health information seekers, ranging from 21-35 years of age, who experienced barriers to accessing health care services. Lower-SES individuals were more likely to use an intuitive, rather than deliberative, approach to Internet health information seeking. Lower- and higher-SES participants did not differ in the tendency to make diagnostic guesses based on Internet searches. Lower-SES participants were more likely than their higher-SES counterparts to narrow the scope of their search. Our findings suggest that individuals with different levels of socioeconomic status vary in the heuristics and search patterns they rely upon to direct their searches. The influence and use of credible information in the process of making a decision is associated with education and prior experiences with healthcare services. Those with limited resources may be disadvantaged when turning to the Internet to make a health decision.
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Signatures of active and passive optimized Lévy searching in jellyfish.
Reynolds, Andy M
2014-10-06
Some of the strongest empirical support for Lévy search theory has come from telemetry data for the dive patterns of marine predators (sharks, bony fishes, sea turtles and penguins). The dive patterns of the unusually large jellyfish Rhizostoma octopus do, however, sit outside of current Lévy search theory which predicts that a single search strategy is optimal. When searching the water column, the movement patterns of these jellyfish change over time. Movement bouts can be approximated by a variety of Lévy and Brownian (exponential) walks. The adaptive value of this variation is not known. On some occasions movement pattern data are consistent with the jellyfish prospecting away from a preferred depth, not finding an improvement in conditions elsewhere and so returning to their original depth. This 'bounce' behaviour also sits outside of current Lévy walk search theory. Here, it is shown that the jellyfish movement patterns are consistent with their using optimized 'fast simulated annealing'--a novel kind of Lévy walk search pattern--to locate the maximum prey concentration in the water column and/or to locate the strongest of many olfactory trails emanating from more distant prey. Fast simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a large search space. This new finding shows that the notion of active optimized Lévy walk searching is not limited to the search for randomly and sparsely distributed resources, as previously thought, but can be extended to embrace other scenarios, including that of the jellyfish R. octopus. In the presence of convective currents, it could become energetically favourable to search the water column by riding the convective currents. Here, it is shown that these passive movements can be represented accurately by Lévy walks of the type occasionally seen in R. octopus. This result vividly illustrates that Lévy walks are not necessarily the result of selection pressures for advantageous searching behaviour but can instead arise freely and naturally from simple processes. It also shows that the family of Lévy walkers is vastly larger than previously thought and includes spores, pollens, seeds and minute wingless arthropods that on warm days disperse passively within the atmospheric boundary layer. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
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Huang, Yin-Fu; Wang, Chia-Ming; Liou, Sing-Wu
2013-01-01
A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete.
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Wang, Chia-Ming; Liou, Sing-Wu
2013-01-01
A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete. PMID:23737711
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Seasonal variation in Internet searches for vitamin D.
Moon, Rebecca J; Curtis, Elizabeth M; Davies, Justin H; Cooper, Cyrus; Harvey, Nicholas C
2017-12-01
Internet search rates for "vitamin D" were explored using Google Trends. Search rates increased from 2004 until 2010 and thereafter displayed a seasonal pattern peaking in late winter. This knowledge could help guide the timing of public health interventions aimed at managing vitamin D deficiency. The Internet is an important source of health information. Analysis of Internet search activity rates can provide information on disease epidemiology, health related behaviors and public interest. We explored Internet search rates for vitamin D to determine whether this reflects the increasing scientific interest in this topic. Google Trends is a publically available tool that provides data on Internet searches using Google. Search activity for the term "vitamin D" from 1st January 2004 until 31st October 2016 was obtained. Comparison was made to other bone and nutrition related terms. Worldwide, searches for "vitamin D" increased from 2004 until 2010 and thereafter a statistically significant (p < 0.001) seasonal pattern with a peak in February and nadir in August was observed. This seasonal pattern was evident for searches originating from both the USA (peak in February) and Australia (peak in August); p < 0.001 for both. Searches for the terms "osteoporosis", "rickets", "back pain" or "folic acid" did not display the increase observed for vitamin D or evidence of seasonal variation. Public interest in vitamin D, as assessed by Internet search activity, did increase from 2004 to 2010, likely reflecting the growing scientific interest, but now displays a seasonal pattern with peak interest during late winter. This information could be used to guide public health approaches to managing vitamin D deficiency.
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Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data
Hutchison, Alan L.; Maienschein-Cline, Mark; Chiang, Andrew H.; Tabei, S. M. Ali; Gudjonson, Herman; Bahroos, Neil; Allada, Ravi; Dinner, Aaron R.
2015-01-01
Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms. PMID:25793520
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Cortés-Marcial, Malinalli; Briones-Salas, Miguel
2014-12-01
The use of camera traps and mammal track search are complementary methods to monitoring species of which is not well documented their natural history, as in the case of medium and large mammals. To ensure its conservation and good management, it is necessary to generate information about the structure of the community and their populations. The objective of the present study was to estimate the diversity, relative abundance and activity patterns of medium and large mammals in a tropical deciduous forest located in the Isthmus of Tehuantepec, Oaxaca, Mexico. Samplings were conducted in three month intervals, from September 2011 to May 2013. We used photographic-sampling and track search, two complementary sampling methods. For photographic-sampling, 12 camera traps were placed covering an area of 60 km2, while for the tracks search a monthly tour of four line-transect surveys of three kilometers length each was undertaken. We obtained a total of 344 pictures with 5292 trap-days total sampling effort; in addition, 187 track records in a total of 144 km. With both methods we registered 21 species of mammals, in 13 families and seven orders, and five species resulted in new records to the area. The diversity index of Shannon-Wiener obtained with the method of tracks was H' = 2.41, while the most abundant species were Urocyon cinereoargen- teus (IAR = 0.23) and Pecari tajacu (IAR = 0.20). By the method of trap the most abundant species were P. tajacu (IAR = 2.62) and Nasua narica (IAR = 1.28). In terms of patterns of activity P. tajacu, N. narica and Odocoileus virginianus were primarily diurnal species; Canis latrans and Leopardus pardalis did not show preference for any schedule in particular, and Didelphis virginiana and Dasypus novemcinctus preferred to have nocturnal activity. This information can be of help to the creation of programs of management and conservation of mam- mals of medium and large in the Isthmus of Tehuantepec, Oaxaca, México.
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An improved method for determining the distribution of swift fox in Kansas
Roy, Christiane C.; Sovada, Marsha A.; Sargeant, Glen A.; Roy, Christiane C.
1999-01-01
During 1997 and 1998 we tested a new method for determining the distribution of swift foxes (Vulpes velox) in Kansas. From a sampling frame of 30 counties in western Kansas, we selected a systematic sample of alternate townships in a checkerboard pattern. During September and October 1997 and August 1998, experienced observers delineated suitable swift fox habitat within each sample township and searched it for evidence of occupancy (tracks, dens, and the animals themselves) by swift fox and other furbearers. Each township was searched for a minimum of 30 minutes, with searches continuing until swift foxes were either detected or for 120 minutes. Of the 288 townships selected in 1997, 271 (94.1%) were searched effectively with swift fox detected in 40.5% of the townships. Adverse weather conditions prevented surveys in two northwestern counties of our sample frame. In 1998, 245 township were searched effectively. Swift fox were detected in 27 counties searched to date. We did not detect swift fox in Seward, Meade and Ford counties, where the species is thought to be uncommon or absent. Tracks were difficult to discern in areas with hard or sandy soils and were sometimes obliterated by adverse weather, vehicle traffic, and agricultural activities. To determine how frequently we failed to detect swift foxes that were present, we plan to repeat searches in 1999 in townships where swift foxes were not detected previously. Nevertheless, preliminary results suggest our method to be a practical means for conducting landscape-scale presence/absence surveys of swift fox. Restricting searches to habitat judged best for swift foxes and most favorable for track detection helped control costs and achieve high detection rates.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
- PNNL, Harold Trease
2012-10-10
ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.
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Patterns of Information-Seeking for Cancer on the Internet: An Analysis of Real World Data
Ofran, Yishai; Paltiel, Ora; Pelleg, Dan; Rowe, Jacob M.; Yom-Tov, Elad
2012-01-01
Although traditionally the primary information sources for cancer patients have been the treating medical team, patients and their relatives increasingly turn to the Internet, though this source may be misleading and confusing. We assess Internet searching patterns to understand the information needs of cancer patients and their acquaintances, as well as to discern their underlying psychological states. We screened 232,681 anonymous users who initiated cancer-specific queries on the Yahoo Web search engine over three months, and selected for study users with high levels of interest in this topic. Searches were partitioned by expected survival for the disease being searched. We compared the search patterns of anonymous users and their contacts. Users seeking information on aggressive malignancies exhibited shorter search periods, focusing on disease- and treatment-related information. Users seeking knowledge regarding more indolent tumors searched for longer periods, alternated between different subjects, and demonstrated a high interest in topics such as support groups. Acquaintances searched for longer periods than the proband user when seeking information on aggressive (compared to indolent) cancers. Information needs can be modeled as transitioning between five discrete states, each with a unique signature representing the type of information of interest to the user. Thus, early phases of information-seeking for cancer follow a specific dynamic pattern. Areas of interest are disease dependent and vary between probands and their contacts. These patterns can be used by physicians and medical Web site authors to tailor information to the needs of patients and family members. PMID:23029317
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Furuya-Kanamori, Luis; McKenzie, Samantha J.; Yakob, Laith; Clark, Justin; Paterson, David L.; Riley, Thomas V.; Clements, Archie C.
2015-01-01
Background Studies have demonstrated seasonal variability in rates of Clostridium difficile infection (CDI). Synthesising all available information on seasonality is a necessary step in identifying large-scale epidemiological patterns and elucidating underlying causes. Methods Three medical and life sciences publication databases were searched from inception to October 2014 for longitudinal epidemiological studies written in English, Spanish or Portuguese that reported the incidence of CDI. The monthly frequency of CDI were extracted, standardized and weighted according to the number of follow-up months. Cross correlation coefficients (XCORR) were calculated to examine the correlation and lag between the year-month frequencies of reported CDI across hemispheres and continents. Results The search identified 13, 5 and 2 studies from North America, Europe, and Oceania, respectively that met the inclusion criteria. CDI had a similar seasonal pattern in the Northern and Southern Hemisphere characterized by a peak in spring and lower frequencies of CDI in summer/autumn with a lag of 8 months (XCORR = 0.60) between hemispheres. There was no difference between the seasonal patterns across European and North American countries. Conclusion CDI demonstrates a distinct seasonal pattern that is consistent across North America, Europe and Oceania. Further studies are required to identify the driving factors of the observed seasonality. PMID:25775463
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Sanches Machado d’Almeida, Karina; Ronchi Spillere, Stefanny; Zuchinali, Priccila; Corrêa Souza, Gabriela
2018-01-01
Background: Heart failure (HF) is a complex syndrome and is recognized as the ultimate pathway of cardiovascular disease (CVD). Studies using nutritional strategies based on dietary patterns have proved to be effective for the prevention and treatment of CVD. Although there are studies that support the protective effect of these diets, their effects on the prevention of HF are not clear yet. Methods: We searched the Medline, Embase, and Cochrane databases for studies that examined dietary patterns, such as dietary approaches to stop hypertension (DASH diet), paleolithic, vegetarian, low-carb and low-fat diets and prevention of HF. No limitations were used during the search in the databases. Results: A total of 1119 studies were identified, 14 met the inclusion criteria. Studies regarding the Mediterranean, DASH, vegetarian, and Paleolithic diets were found. The Mediterranean and DASH diets showed a protective effect on the incidence of HF and/or worsening of cardiac function parameters, with a significant difference in relation to patients who did not adhere to these dietary patterns. Conclusions: It is observed that the adoption of Mediterranean or DASH-type dietary patterns may contribute to the prevention of HF, but these results need to be analyzed with caution due to the low quality of evidence. PMID:29320401
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Combining the Bourne-Shell, sed and awk in the UNIX Environment for Language Analysis.
ERIC Educational Resources Information Center
Schmitt, Lothar M.; Christianson, Kiel T.
This document describes how to construct tools for language analysis in research and teaching using the Bourne-shell, sed, and awk, three search tools, in the UNIX operating system. Applications include: searches for words, phrases, grammatical patterns, and phonemic patterns in text; statistical analysis of text in regard to such searches,…
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Job Search Patterns of College Graduates: The Role of Social Capital
ERIC Educational Resources Information Center
Coonfield, Emily S.
2012-01-01
This dissertation addresses job search patterns of college graduates and the implications of social capital by race and class. The purpose of this study is to explore (1) how the job search transpires for recent college graduates, (2) how potential social networks in a higher educational context, like KU, may make a difference for students with…
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Field Differences in the Use and Perceived Usefulness of Scholarly Mailing Lists
ERIC Educational Resources Information Center
Talja, Sanna; Savolainen, Reijo; Maula, Hanni
2004-01-01
Based on a qualitative comparative study across four domains, this paper explores how the use and perceived usefulness of scholarly mailing lists is related to primary search methods, collaboration patterns, loci of critical information, physical proximity of like-minded colleagues, field size, the desirability of sharing information in public or…
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A Review of Gastrointestinal Outbreaks in Schools: Effective Infection Control Interventions
ERIC Educational Resources Information Center
Lee, Marilyn B.; Greig, Judy D.
2010-01-01
Background: The purpose of this study was to review documented outbreaks of gastrointestinal illness in schools, published in the last 10 years, to identify etiology, mode of transmission, the number of children affected, morbidity and mortality patterns, and interventions for control and prevention. Methods: Searches of electronic databases,…
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Sims, David W; Humphries, Nicolas E; Bradford, Russell W; Bruce, Barry D
2012-03-01
1. Search processes play an important role in physical, chemical and biological systems. In animal foraging, the search strategy predators should use to search optimally for prey is an enduring question. Some models demonstrate that when prey is sparsely distributed, an optimal search pattern is a specialised random walk known as a Lévy flight, whereas when prey is abundant, simple Brownian motion is sufficiently efficient. These predictions form part of what has been termed the Lévy flight foraging hypothesis (LFF) which states that as Lévy flights optimise random searches, movements approximated by optimal Lévy flights may have naturally evolved in organisms to enhance encounters with targets (e.g. prey) when knowledge of their locations is incomplete. 2. Whether free-ranging predators exhibit the movement patterns predicted in the LFF hypothesis in response to known prey types and distributions, however, has not been determined. We tested this using vertical and horizontal movement data from electronic tagging of an apex predator, the great white shark Carcharodon carcharias, across widely differing habitats reflecting different prey types. 3. Individual white sharks exhibited movement patterns that predicted well the prey types expected under the LFF hypothesis. Shark movements were best approximated by Brownian motion when hunting near abundant, predictable sources of prey (e.g. seal colonies, fish aggregations), whereas movements approximating truncated Lévy flights were present when searching for sparsely distributed or potentially difficult-to-detect prey in oceanic or shelf environments, respectively. 4. That movement patterns approximated by truncated Lévy flights and Brownian behaviour were present in the predicted prey fields indicates search strategies adopted by white sharks appear to be the most efficient ones for encountering prey in the habitats where such patterns are observed. This suggests that C. carcharias appears capable of exhibiting search patterns that are approximated as optimal in response to encountered changes in prey type and abundance, and across diverse marine habitats, from the surf zone to the deep ocean. 5. Our results provide some support for the LFF hypothesis. However, it is possible that the observed Lévy patterns of white sharks may not arise from an adaptive behaviour but could be an emergent property arising from simple, straight-line movements between complex (e.g. fractal) distributions of prey. Experimental studies are needed in vertebrates to test for the presence of Lévy behaviour patterns in the absence of complex prey distributions. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.
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[Study on the food consumption pattern of elderly people in four "cuisine" areas of China].
Zhao, Wenhua; You, Yue; Zhang, Xin; Wang, Junling
2002-02-01
In order to investigate the situation of food intake, diet habit and dietary pattern in people living in different "cuisine" areas of China, and to search for the relations between diet and health status, a total of 538 subjects (269 couples) aged between 50-60 years in four rural areas were surveyed by a food frequency questionnaire method. Selected items of food consumption pattern and food intake of the subjects were analyzed. The results showed significant differences on food intake among the people in the four cuisine areas. This study provided references for the future study on the relationship between diet and health.
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He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei
2014-01-01
Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.
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Optimization technique for problems with an inequality constraint
NASA Technical Reports Server (NTRS)
Russell, K. J.
1972-01-01
General technique uses a modified version of an existing technique termed the pattern search technique. New procedure called the parallel move strategy permits pattern search technique to be used with problems involving a constraint.
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The Foxconn suicides and their media prominence: is the Werther Effect applicable in China?
Cheng, Qijin; Chen, Feng; Yip, Paul S F
2011-11-02
Media reporting of suicide and its relationship with actual suicide has rarely been investigated in Mainland China. The "Foxconn suicides" is a description referring to a string of suicides/attempts during 2010, all of which were related to a giant electrical manufacturing company, Foxconn. This study aimed to examine the clustering and copycat effects of the Foxconn suicides, and to investigate temporal patterns in how they were reported by the media in Mainland China, Hong Kong (HK), and Taiwan (TW). Relevant articles were collected from representative newspapers published in three big cities in Mainland China (Beijing (BJ), Shenzhen (SZ), and Guangzhou (GZ)), HK, and TW, together with searching intensity data on the topic conducted using the Baidu search engine in Mainland China. The temporal clustering effects of the Foxconn suicides and their media prominence were assessed using the Kolmogorov-Smirnov test. The media reports of the Foxconn suicides' temporal patterns were explored using a nonparametric curve estimation method (that is, the local linear method). The potential mutual interactions between the Foxconn suicides and their media prominence were also examined, using logistic and Poisson regression methods. The results support a temporal clustering effect for the Foxconn suicides. The BJ-based newspapers' reporting and the occurrence of a Foxconn suicide/attempt are each found to be associated with an elevated chance of a further Foxconn suicide 3 days later. The occurrence of a Foxconn suicide also immediately influenced the intensity of both Baidu searching and newspaper reporting. Regional diversity in suicide reporting tempo-patterns within Mainland China, and similarities between HK and TW, are also demonstrated. The Foxconn suicides were temporally clustered. Their occurrences were influenced by the reporting of BJ-based newspapers, and contagion within the company itself. Further suicide research and prevention work in China should consider its special media environment.
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Dorsal scapular nerve neuropathy: a narrative review of the literature
Muir, Brad
2017-01-01
Objective The purpose of this paper is to elucidate this little known cause of upper back pain through a narrative review of the literature and to discuss the possible role of the dorsal scapular nerve (DSN) in the etiopathology of other similar diagnoses in this area including cervicogenic dorsalgia (CD), notalgia paresthetica (NP), SICK scapula and a posterolateral arm pain pattern. Background Dorsal scapular nerve (DSN) neuropathy has been a rarely thought of differential diagnosis for mid scapular, upper to mid back and costovertebral pain. These are common conditions presenting to chiropractic, physiotherapy, massage therapy and medical offices. Methods The methods used to gather articles for this paper included: searching electronic databases; and hand searching relevant references from journal articles and textbook chapters. Results One hundred-fourteen articles were retrieved. After removing duplicates, there were 57 articles of which 29 were retrieved. There were 26 articles and textbook chapters retrieved by hand searching equaling 55 articles retrieved of which 47 relevant articles were used in this report. Discussion The anatomy, pathway and function of the dorsal scapular nerve can be varied and exceptionally rarely may include a sensory component. The signs and symptoms, therefore, may include pain, atrophy, scapular winging, and dysesthesia. The mechanism of injury to the DSN is also quite varied ranging from postural to overuse in overhead work and sport. Other conditions in this area, including CD, NP, SICK scapula and a posterolateral arm pain pattern bear a striking resemblance to DSN neuropathy. Conclusion DSN neuropathy should be included in the list of common differential diagnoses of upper and mid-thoracic pain, stiffness, dysesthesia and dysfunction. The study also brings forward interesting connections between DSN neuropathy, CD, NP, SICK scapula and a posterolateral arm pain pattern. PMID:28928496
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2014-01-01
Background Health consumers have moved away from a reliance on medical practitioner advice to more independent decision processes and so their information search processes have subsequently widened. This study examined how persons with back pain searched for alternative treatment types and service providers. That is, what information do they seek and how; what sources do they use and why; and by what means do they search for it? Methods 12 persons with back pain were interviewed. The method used was convergent interviewing. This involved a series of semi-structured questions to obtain open-ended answers. The interviewer analysed the responses and refined the questions after each interview, to converge on the dominant factors influencing decisions about treatment patterns. Results Persons with back pain mainly search their memories and use word of mouth (their doctor and friends) for information about potential treatments and service providers. Their search is generally limited due to personal, provider-related and information-supply reasons. However, they did want in-depth information about the alternative treatments and providers in an attempt to establish apriori their efficacy in treating their specific back problems. They searched different sources depending on the type of information they required. Conclusions The findings differ from previous studies about the types of information health consumers require when searching for information about alternative or mainstream healthcare services. The results have identified for the first time that limited information availability was only one of three categories of reasons identified about why persons with back pain do not search for more information particularly from external non-personal sources. PMID:24725300
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Image Halftoning and Inverse Halftoning for Optimized Dot Diffusion
1998-01-01
systems.caltech.edu, ppvnath@sys.caltech.edu ABSTRACT The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error ... halftoning : ordered dither [3], error diffusion [4], neural-net based methods [2], and more recently direct binary search (DBS) [10]. Ordered dithering is a...patterns. On the other hand error diffused halftones do not suffer from periodicity and offer blue noise characteristic [11] which is found to be
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Pattern formation and geometry of the manifold
NASA Astrophysics Data System (ADS)
Haji, Amir Hossein; Mahzoon, Mojtaba; Javadpour, Sirus
2011-03-01
The objective of the present work is to investigate how pattern formation in the Cahn-Hilliard system can be influenced by geometry of the manifold. This is in contrast to control methods in which the physical field is modified and the pattern formation of the original system changes in response to control inputs. The idea begins with the cylindrical manifold symmetry leading to circumferential rolls while the torus manifold can be used to produce and control helical rolls. The next step is to search for a weaker restriction on the geometry of the manifold in order to reduce its dimension. In particular a short amplitude sinusoidal modulation on a flat surface is studied. At the final step a sequential pattern formation is presented.
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Huang, Chung-Chi; Lu, Zhiyong
2016-01-01
Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order covering diverse bio-entity relations. To assess the potential utility of our automated top-ranked patterns of a given relation in semantic search, we performed a pilot study on frequently sought semantic relations in PubMed and observed improved literature retrieval effectiveness based on post-hoc human relevance evaluation. Further investigation in larger tests and in real-world scenarios is warranted. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
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Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...
2014-10-23
Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres
Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less
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NASA Astrophysics Data System (ADS)
Lutich, Andrey
2017-07-01
This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.
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Temporal stability of visual search-driven biometrics
NASA Astrophysics Data System (ADS)
Yoon, Hong-Jun; Carmichael, Tandy R.; Tourassi, Georgia
2015-03-01
Previously, we have shown the potential of using an individual's visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circles shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant's "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, temporally stable personalized fingerprint of perceptual organization.
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Preliminary Results on Uncertainty Quantification for Pattern Analytics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stracuzzi, David John; Brost, Randolph; Chen, Maximillian Gene
2015-09-01
This report summarizes preliminary research into uncertainty quantification for pattern ana- lytics within the context of the Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) project. The primary focus of PANTHER was to make large quantities of remote sensing data searchable by analysts. The work described in this re- port adds nuance to both the initial data preparation steps and the search process. Search queries are transformed from does the specified pattern exist in the data? to how certain is the system that the returned results match the query? We show example results for both data processing and search,more » and discuss a number of possible improvements for each.« less
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SlideSort: all pairs similarity search for short reads
Shimizu, Kana; Tsuda, Koji
2011-01-01
Motivation: Recent progress in DNA sequencing technologies calls for fast and accurate algorithms that can evaluate sequence similarity for a huge amount of short reads. Searching similar pairs from a string pool is a fundamental process of de novo genome assembly, genome-wide alignment and other important analyses. Results: In this study, we designed and implemented an exact algorithm SlideSort that finds all similar pairs from a string pool in terms of edit distance. Using an efficient pattern growth algorithm, SlideSort discovers chains of common k-mers to narrow down the search. Compared to existing methods based on single k-mers, our method is more effective in reducing the number of edit distance calculations. In comparison to backtracking methods such as BWA, our method is much faster in finding remote matches, scaling easily to tens of millions of sequences. Our software has an additional function of single link clustering, which is useful in summarizing short reads for further processing. Availability: Executable binary files and C++ libraries are available at http://www.cbrc.jp/~shimizu/slidesort/ for Linux and Windows. Contact: slidesort@m.aist.go.jp; shimizu-kana@aist.go.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21148542
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A View through a Bamboo Screen: From Moire Patterns to Black Holes.
ERIC Educational Resources Information Center
Oda, Minoru
1992-01-01
Describes the genesis, the early experiments, and the limitations of X-ray astronomy. Discusses original methods for searching and locating the first interstellar X-ray source, modern attempts to identify a massive black hole as part of a binary system X-ray source, and the effort to generate X-ray images of solar flares. (JJK)
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Word aligned bitmap compression method, data structure, and apparatus
Wu, Kesheng; Shoshani, Arie; Otoo, Ekow
2004-12-14
The Word-Aligned Hybrid (WAH) bitmap compression method and data structure is a relatively efficient method for searching and performing logical, counting, and pattern location operations upon large datasets. The technique is comprised of a data structure and methods that are optimized for computational efficiency by using the WAH compression method, which typically takes advantage of the target computing system's native word length. WAH is particularly apropos to infrequently varying databases, including those found in the on-line analytical processing (OLAP) industry, due to the increased computational efficiency of the WAH compressed bitmap index. Some commercial database products already include some version of a bitmap index, which could possibly be replaced by the WAH bitmap compression techniques for potentially increased operation speed, as well as increased efficiencies in constructing compressed bitmaps. Combined together, this technique may be particularly useful for real-time business intelligence. Additional WAH applications may include scientific modeling, such as climate and combustion simulations, to minimize search time for analysis and subsequent data visualization.
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Predicting the performance of fingerprint similarity searching.
Vogt, Martin; Bajorath, Jürgen
2011-01-01
Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.
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NASA Astrophysics Data System (ADS)
Weng, Tongfeng; Zhang, Jie; Small, Michael; Harandizadeh, Bahareh; Hui, Pan
2018-03-01
We propose a unified framework to evaluate and quantify the search time of multiple random searchers traversing independently and concurrently on complex networks. We find that the intriguing behaviors of multiple random searchers are governed by two basic principles—the logarithmic growth pattern and the harmonic law. Specifically, the logarithmic growth pattern characterizes how the search time increases with the number of targets, while the harmonic law explores how the search time of multiple random searchers varies relative to that needed by individual searchers. Numerical and theoretical results demonstrate these two universal principles established across a broad range of random search processes, including generic random walks, maximal entropy random walks, intermittent strategies, and persistent random walks. Our results reveal two fundamental principles governing the search time of multiple random searchers, which are expected to facilitate investigation of diverse dynamical processes like synchronization and spreading.
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Bouda, Martin; Caplan, Joshua S.; Saiers, James E.
2016-01-01
Fractal dimension (FD), estimated by box-counting, is a metric used to characterize plant anatomical complexity or space-filling characteristic for a variety of purposes. The vast majority of published studies fail to evaluate the assumption of statistical self-similarity, which underpins the validity of the procedure. The box-counting procedure is also subject to error arising from arbitrary grid placement, known as quantization error (QE), which is strictly positive and varies as a function of scale, making it problematic for the procedure's slope estimation step. Previous studies either ignore QE or employ inefficient brute-force grid translations to reduce it. The goals of this study were to characterize the effect of QE due to translation and rotation on FD estimates, to provide an efficient method of reducing QE, and to evaluate the assumption of statistical self-similarity of coarse root datasets typical of those used in recent trait studies. Coarse root systems of 36 shrubs were digitized in 3D and subjected to box-counts. A pattern search algorithm was used to minimize QE by optimizing grid placement and its efficiency was compared to the brute force method. The degree of statistical self-similarity was evaluated using linear regression residuals and local slope estimates. QE, due to both grid position and orientation, was a significant source of error in FD estimates, but pattern search provided an efficient means of minimizing it. Pattern search had higher initial computational cost but converged on lower error values more efficiently than the commonly employed brute force method. Our representations of coarse root system digitizations did not exhibit details over a sufficient range of scales to be considered statistically self-similar and informatively approximated as fractals, suggesting a lack of sufficient ramification of the coarse root systems for reiteration to be thought of as a dominant force in their development. FD estimates did not characterize the scaling of our digitizations well: the scaling exponent was a function of scale. Our findings serve as a caution against applying FD under the assumption of statistical self-similarity without rigorously evaluating it first. PMID:26925073
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NASA Astrophysics Data System (ADS)
Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas
2010-03-01
Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.
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Signatures of active and passive optimized Lévy searching in jellyfish
Reynolds, Andy M.
2014-01-01
Some of the strongest empirical support for Lévy search theory has come from telemetry data for the dive patterns of marine predators (sharks, bony fishes, sea turtles and penguins). The dive patterns of the unusually large jellyfish Rhizostoma octopus do, however, sit outside of current Lévy search theory which predicts that a single search strategy is optimal. When searching the water column, the movement patterns of these jellyfish change over time. Movement bouts can be approximated by a variety of Lévy and Brownian (exponential) walks. The adaptive value of this variation is not known. On some occasions movement pattern data are consistent with the jellyfish prospecting away from a preferred depth, not finding an improvement in conditions elsewhere and so returning to their original depth. This ‘bounce’ behaviour also sits outside of current Lévy walk search theory. Here, it is shown that the jellyfish movement patterns are consistent with their using optimized ‘fast simulated annealing’—a novel kind of Lévy walk search pattern—to locate the maximum prey concentration in the water column and/or to locate the strongest of many olfactory trails emanating from more distant prey. Fast simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a large search space. This new finding shows that the notion of active optimized Lévy walk searching is not limited to the search for randomly and sparsely distributed resources, as previously thought, but can be extended to embrace other scenarios, including that of the jellyfish R. octopus. In the presence of convective currents, it could become energetically favourable to search the water column by riding the convective currents. Here, it is shown that these passive movements can be represented accurately by Lévy walks of the type occasionally seen in R. octopus. This result vividly illustrates that Lévy walks are not necessarily the result of selection pressures for advantageous searching behaviour but can instead arise freely and naturally from simple processes. It also shows that the family of Lévy walkers is vastly larger than previously thought and includes spores, pollens, seeds and minute wingless arthropods that on warm days disperse passively within the atmospheric boundary layer. PMID:25100323
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A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching.
Romero, José R; Carballido, Jessica A; Garbus, Ingrid; Echenique, Viviana C; Ponzoni, Ignacio
2016-01-01
The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow the discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. In this study, a de novo strategy for detecting patterns that represent nested motifs was designed based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories, motifs within other motifs, motifs flanked by other motifs, and motifs of large size. The methodology used in this study, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa , revealed that it is possible to identify putative nested TEs by detecting these three types of patterns. The results were validated through BLAST alignments, which revealed the efficacy and usefulness of the new method, which is called Mamushka.
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Hahn, Lars; Leimeister, Chris-André; Ounit, Rachid; Lonardi, Stefano; Morgenstern, Burkhard
2016-10-01
Many algorithms for sequence analysis rely on word matching or word statistics. Often, these approaches can be improved if binary patterns representing match and don't-care positions are used as a filter, such that only those positions of words are considered that correspond to the match positions of the patterns. The performance of these approaches, however, depends on the underlying patterns. Herein, we show that the overlap complexity of a pattern set that was introduced by Ilie and Ilie is closely related to the variance of the number of matches between two evolutionarily related sequences with respect to this pattern set. We propose a modified hill-climbing algorithm to optimize pattern sets for database searching, read mapping and alignment-free sequence comparison of nucleic-acid sequences; our implementation of this algorithm is called rasbhari. Depending on the application at hand, rasbhari can either minimize the overlap complexity of pattern sets, maximize their sensitivity in database searching or minimize the variance of the number of pattern-based matches in alignment-free sequence comparison. We show that, for database searching, rasbhari generates pattern sets with slightly higher sensitivity than existing approaches. In our Spaced Words approach to alignment-free sequence comparison, pattern sets calculated with rasbhari led to more accurate estimates of phylogenetic distances than the randomly generated pattern sets that we previously used. Finally, we used rasbhari to generate patterns for short read classification with CLARK-S. Here too, the sensitivity of the results could be improved, compared to the default patterns of the program. We integrated rasbhari into Spaced Words; the source code of rasbhari is freely available at http://rasbhari.gobics.de/.
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Aggregate age-at-marriage patterns from individual mate-search heuristics.
Todd, Peter M; Billari, Francesco C; Simão, Jorge
2005-08-01
The distribution of age at first marriage shows well-known strong regularities across many countries and recent historical periods. We accounted for these patterns by developing agent-based models that simulate the aggregate behavior of individuals who are searching for marriage partners. Past models assumed fully rational agents with complete knowledge of the marriage market; our simulated agents used psychologically plausible simple heuristic mate search rules that adjust aspiration levels on the basis of a sequence of encounters with potential partners. Substantial individual variation must be included in the models to account for the demographically observed age-at-marriage patterns.
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Structural Pattern Recognition Techniques for Data Retrieval in Massive Fusion Databases
NASA Astrophysics Data System (ADS)
Vega, J.; Murari, A.; Rattá, G. A.; Castro, P.; Pereira, A.; Portas, A.
2008-03-01
Diagnostics of present day reactor class fusion experiments, like the Joint European Torus (JET), generate thousands of signals (time series and video images) in each discharge. There is a direct correspondence between the physical phenomena taking place in the plasma and the set of structural shapes (patterns) that they form in the signals: bumps, unexpected amplitude changes, abrupt peaks, periodic components, high intensity zones or specific edge contours. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behavior, i.e. discharges with "similar" patterns. Pattern recognition techniques are efficient tools to search for similar structural forms within the database in a fast an intelligent way. To this end, classification systems must be developed to be used as indexation methods to directly fetch the more similar patterns.
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Local weather is associated with rates of online searches for musculoskeletal pain symptoms.
Telfer, Scott; Obradovich, Nick
2017-01-01
Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.
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Scene Analysis: Non-Linear Spatial Filtering for Automatic Target Detection.
1982-12-01
In this thesis, a method for two-dimensional pattern recognition was developed and tested. The method included a global search scheme for candidate...test global switch TYPEO Creating negative video file only.W 11=0 12=256 13=512 14=768 GO 70 2 1 TYPE" Creating negative and horizontally flipped video...purpose was to develop a base of image processing software for the AFIT Digital Signal Processing Laboratory NOVA- ECLIPSE minicomputer system, for
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Best chirplet chain: Near-optimal detection of gravitational wave chirps
NASA Astrophysics Data System (ADS)
Chassande-Mottin, Éric; Pai, Archana
2006-02-01
The list of putative sources of gravitational waves possibly detected by the ongoing worldwide network of large scale interferometers has been continuously growing in the last years. For some of them, the detection is made difficult by the lack of a complete information about the expected signal. We concentrate on the case where the expected gravitational wave (GW) is a quasiperiodic frequency modulated signal i.e., a chirp. In this article, we address the question of detecting an a priori unknown GW chirp. We introduce a general chirp model and claim that it includes all physically realistic GW chirps. We produce a finite grid of template waveforms which samples the resulting set of possible chirps. If we follow the classical approach (used for the detection of inspiralling binary chirps, for instance), we would build a bank of quadrature matched filters comparing the data to each of the templates of this grid. The detection would then be achieved by thresholding the output, the maximum giving the individual which best fits the data. In the present case, this exhaustive search is not tractable because of the very large number of templates in the grid. We show that the exhaustive search can be reformulated (using approximations) as a pattern search in the time-frequency plane. This motivates an approximate but feasible alternative solution which is clearly linked to the optimal one. The time-frequency representation and pattern search algorithm are fully determined by the reformulation. This contrasts with the other time-frequency based methods presented in the literature for the same problem, where these choices are justified by “ad hoc” arguments. In particular, the time-frequency representation has to be unitary. Finally, we assess the performance, robustness and computational cost of the proposed method with several benchmarks using simulated data.
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Context-aware pattern discovery for moving object trajectories
NASA Astrophysics Data System (ADS)
Sharif, Mohammad; Asghar Alesheikh, Ali; Kaffash Charandabi, Neda
2018-05-01
Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.
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Multi-Dimensional Pattern Discovery of Trajectories Using Contextual Information
NASA Astrophysics Data System (ADS)
Sharif, M.; Alesheikh, A. A.
2017-10-01
Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.
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2017-01-01
Background In many Western countries, after a motor vehicle collision, those involved seek health care for the assessment of injuries and for insurance documentation purposes. In contrast, in many less wealthy countries, there may be limited access to care and no insurance or compensation system. Objective The purpose of this infodemiology study was to investigate the global pattern of evolving Internet usage in countries with and without insurance and the corresponding compensation systems for whiplash injury. Methods We used the Internet search engine analytics via Google Trends to study the health information-seeking behavior concerning whiplash injury at national population levels in Europe. Results We found that the search for “whiplash” is strikingly and consistently often associated with the search for “compensation” in countries or cultures with a tort system. Frequent or traumatic painful injuries; diseases or disorders such as arthritis, headache, radius, and hip fracture; depressive disorders; and fibromyalgia were not associated similarly with searches on “compensation.” Conclusions In this study, we present evidence from the evolving viewpoint of naturalistic Internet search engine analytics that the expectations for receiving compensation may influence Internet search behavior in relation to whiplash injury. PMID:28347974
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Research on parallel algorithm for sequential pattern mining
NASA Astrophysics Data System (ADS)
Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao
2008-03-01
Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.
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Dynamic search and working memory in social recall.
Hills, Thomas T; Pachur, Thorsten
2012-01-01
What are the mechanisms underlying search in social memory (e.g., remembering the people one knows)? Do the search mechanisms involve dynamic local-to-global transitions similar to semantic search, and are these transitions governed by the general control of attention, associated with working memory span? To find out, we asked participants to recall individuals from their personal social networks and measured each participant's working memory capacity. Additionally, participants provided social-category and contact-frequency information about the recalled individuals as well as information about the social proximity among the recalled individuals. On the basis of these data, we tested various computational models of memory search regarding their ability to account for the patterns in which participants recalled from social memory. Although recall patterns showed clustering based on social categories, models assuming dynamic transitions between representations cued by social proximity and frequency information predicted participants' recall patterns best-no additional explanatory power was gained from social-category information. Moreover, individual differences in the time between transitions were positively correlated with differences in working memory capacity. These results highlight the role of social proximity in structuring social memory and elucidate the role of working memory for maintaining search criteria during search within that structure.
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NASA Astrophysics Data System (ADS)
Lihoreau, Mathieu; Ings, Thomas C.; Chittka, Lars; Reynolds, Andy M.
2016-07-01
Simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a search space. It is frequently implemented in computers working on complex optimization problems but until now has not been directly observed in nature as a searching strategy adopted by foraging animals. We analysed high-speed video recordings of the three-dimensional searching flights of bumblebees (Bombus terrestris) made in the presence of large or small artificial flowers within a 0.5 m3 enclosed arena. Analyses of the three-dimensional flight patterns in both conditions reveal signatures of simulated annealing searches. After leaving a flower, bees tend to scan back-and forth past that flower before making prospecting flights (loops), whose length increases over time. The search pattern becomes gradually more expansive and culminates when another rewarding flower is found. Bees then scan back and forth in the vicinity of the newly discovered flower and the process repeats. This looping search pattern, in which flight step lengths are typically power-law distributed, provides a relatively simple yet highly efficient strategy for pollinators such as bees to find best quality resources in complex environments made of multiple ephemeral feeding sites with nutritionally variable rewards.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, Andrew; Haass, Michael; Rintoul, Mark Daniel
GazeAppraise advances the state of the art of gaze pattern analysis using methods that simultaneously analyze spatial and temporal characteristics of gaze patterns. GazeAppraise enables novel research in visual perception and cognition; for example, using shape features as distinguishing elements to assess individual differences in visual search strategy. Given a set of point-to-point gaze sequences, hereafter referred to as scanpaths, the method constructs multiple descriptive features for each scanpath. Once the scanpath features have been calculated, they are used to form a multidimensional vector representing each scanpath and cluster analysis is performed on the set of vectors from all scanpaths.more » An additional benefit of this method is the identification of causal or correlated characteristics of the stimuli, subjects, and visual task through statistical analysis of descriptive metadata distributions within and across clusters.« less
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Visual search for facial expressions of emotions: a comparison of dynamic and static faces.
Horstmann, Gernot; Ansorge, Ulrich
2009-02-01
A number of past studies have used the visual search paradigm to examine whether certain aspects of emotional faces are processed preattentively and can thus be used to guide attention. All these studies presented static depictions of facial prototypes. Emotional expressions conveyed by the movement patterns of the face have never been examined for their preattentive effect. The present study presented for the first time dynamic facial expressions in a visual search paradigm. Experiment 1 revealed efficient search for a dynamic angry face among dynamic friendly faces, but inefficient search in a control condition with static faces. Experiments 2 to 4 suggested that this pattern of results is due to a stronger movement signal in the angry than in the friendly face: No (strong) advantage of dynamic over static faces is revealed when the degree of movement is controlled. These results show that dynamic information can be efficiently utilized in visual search for facial expressions. However, these results do not generally support the hypothesis that emotion-specific movement patterns are always preattentively discriminated. (c) 2009 APA, all rights reserved
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Transterm—extended search facilities and improved integration with other databases
Jacobs, Grant H.; Stockwell, Peter A.; Tate, Warren P.; Brown, Chris M.
2006-01-01
Transterm has now been publicly available for >10 years. Major changes have been made since its last description in this database issue in 2002. The current database provides data for key regions of mRNA sequences, a curated database of mRNA motifs and tools to allow users to investigate their own motifs or mRNA sequences. The key mRNA regions database is derived computationally from Genbank. It contains 3′ and 5′ flanking regions, the initiation and termination signal context and coding sequence for annotated CDS features from Genbank and RefSeq. The database is non-redundant, enabling summary files and statistics to be prepared for each species. Advances include providing extended search facilities, the database may now be searched by BLAST in addition to regular expressions (patterns) allowing users to search for motifs such as known miRNA sequences, and the inclusion of RefSeq data. The database contains >40 motifs or structural patterns important for translational control. In this release, patterns from UTRsite and Rfam are also incorporated with cross-referencing. Users may search their sequence data with Transterm or user-defined patterns. The system is accessible at . PMID:16381889
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Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud
Munisamy, Shyamala Devi; Chokkalingam, Arun
2015-01-01
Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization. PMID:26380364
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Munisamy, Shyamala Devi; Chokkalingam, Arun
2015-01-01
Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.
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Kangaroo – A pattern-matching program for biological sequences
2002-01-01
Background Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells. Results Kangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/. Conclusion A low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats. PMID:12150718
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Evidence of Levy walk foraging patterns in human hunter-gatherers.
Raichlen, David A; Wood, Brian M; Gordon, Adam D; Mabulla, Audax Z P; Marlowe, Frank W; Pontzer, Herman
2014-01-14
When searching for food, many organisms adopt a superdiffusive, scale-free movement pattern called a Lévy walk, which is considered optimal when foraging for heterogeneously located resources with little prior knowledge of distribution patterns [Viswanathan GM, da Luz MGE, Raposo EP, Stanley HE (2011) The Physics of Foraging: An Introduction to Random Searches and Biological Encounters]. Although memory of food locations and higher cognition may limit the benefits of random walk strategies, no studies to date have fully explored search patterns in human foraging. Here, we show that human hunter-gatherers, the Hadza of northern Tanzania, perform Lévy walks in nearly one-half of all foraging bouts. Lévy walks occur when searching for a wide variety of foods from animal prey to underground tubers, suggesting that, even in the most cognitively complex forager on Earth, such patterns are essential to understanding elementary foraging mechanisms. This movement pattern may be fundamental to how humans experience and interact with the world across a wide range of ecological contexts, and it may be adaptive to food distribution patterns on the landscape, which previous studies suggested for organisms with more limited cognition. Additionally, Lévy walks may have become common early in our genus when hunting and gathering arose as a major foraging strategy, playing an important role in the evolution of human mobility.
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Schneider, Janina Anne; Holland, Christopher Patrick
2017-04-13
Patient and consumer access to eHealth information is of crucial importance because of its role in patient-centered medicine and to improve knowledge about general aspects of health and medical topics. The objectives were to analyze and compare eHealth search patterns in a private (United States) and a public (United Kingdom) health care market. A new taxonomy of eHealth websites is proposed to organize the largest eHealth websites. An online measurement framework is developed that provides a precise and detailed measurement system. Online panel data are used to accurately track and analyze detailed search behavior across 100 of the largest eHealth websites in the US and UK health care markets. The health, medical, and lifestyle categories account for approximately 90% of online activity, and e-pharmacies, social media, and professional categories account for the remaining 10% of online activity. Overall search penetration of eHealth websites is significantly higher in the private (United States) than the public market (United Kingdom). Almost twice the number of eHealth users in the private market have adopted online search in the health and lifestyle categories and also spend more time per website than those in the public market. The use of medical websites for specific conditions is almost identical in both markets. The allocation of search effort across categories is similar in both the markets. For all categories, the vast majority of eHealth users only access one website within each category. Those that conduct a search of two or more websites display very narrow search patterns. All users spend relatively little time on eHealth, that is, 3-7 minutes per website. The proposed online measurement framework exploits online panel data to provide a powerful and objective method of analyzing and exploring eHealth behavior. The private health care system does appear to have an influence on eHealth search behavior in terms of search penetration and time spent per website in the health and lifestyle categories. Two explanations are offered: (1) the personal incentive of medical costs in the private market incentivizes users to conduct online search; and (2) health care information is more easily accessible through health care professionals in the United Kingdom compared with the United States. However, the use of medical websites is almost identical, suggesting that patients interested in a specific condition have a motivation to search and evaluate health information, irrespective of the health care market. The relatively low level of search in terms of the number of websites accessed and the average time per website raise important questions about the actual level of patient informedness in both the markets. Areas for future research are outlined. ©Janina Anne Schneider, Christopher Patrick Holland. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.04.2017.
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Pattern recall skills of talented soccer players: Two new methods applied.
van Maarseveen, Mariëtte J J; Oudejans, Raôul R D; Savelsbergh, Geert J P
2015-06-01
In this study we analyzed the pattern recall skills of talented soccer players by means of two innovative methods of analysis and gaze behavior data. Twenty-two young female soccer players watched video clips of 3 vs. 3 small-sided games and, after occlusion, had to reproduce the positions of the players. Recall performance was measured by calculating the spatial error of the recalled player positions at the moment of occlusion and at consecutive 33ms increments. We analyzed player positions relative to each other, by assessing geometric pattern features in terms of angles between players, and we transformed the data into real-world coordinates to exclude the effects of the 2D perspective in the video clips. The results showed that the participants anticipated the movements of the patterns. In real-world coordinates, the more experienced players anticipated the pattern further in advance than the less experienced players and demonstrated a higher search rate, a shorter fixation duration and a higher fixation order. The differences in recall accuracy between the defensive and offensive elements were not consistent across the methods of analysis and, therefore, we propose that perspective effects of the video clip should be taken into account in further research. Copyright © 2015 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Anderegg, William R. L.; Goldsmith, Gregory R.
2014-05-01
Despite overwhelming scientific consensus concerning anthropogenic climate change, many in the non-expert public perceive climate change as debated and contentious. There is concern that two recent high-profile media events—the hacking of the University of East Anglia emails and the Himalayan glacier melt rate presented in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change—may have altered public opinion of climate change. While survey data is valuable for tracking public perception and opinion over time, including in response to climate-related media events, emerging methods that facilitate rapid assessment of spatial and temporal patterns in public interest and opinion could be exceptionally valuable for understanding and responding to these events’ effects. We use a novel, freely-available dataset of worldwide web search term volumes to assess temporal patterns of interest in climate change over the past ten years, with a particular focus on looking at indicators of climate change skepticism around the high-profile media events. We find that both around the world and in the US, the public searches for the issue as ‘global warming,’ rather than ‘climate change,’ and that search volumes have been declining since a 2007 peak. We observe high, but transient spikes of search terms indicating skepticism around the two media events, but find no evidence of effects lasting more than a few months. Our results indicate that while such media events are visible in the short-term, they have little effect on salience of skeptical climate search terms on longer time-scales.
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RankExplorer: Visualization of Ranking Changes in Large Time Series Data.
Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin
2012-12-01
For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.
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ERIC Educational Resources Information Center
Mangan, Jean; Pugh, Geoff; Gray, John
2005-01-01
The article explores changes in the examination performance of a random sample of 500 English secondary schools between 1992 and 2001. Using econometric methods, it concludes that: there is an overall deterministic trend in school performance but it is not stable, making prediction accuracy poor; the aggregate trend does not explain improvement…
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A Study of Periodical Literature Searching at an Urban Research Library: Problems and Patterns.
ERIC Educational Resources Information Center
Carey, Kevin
Patron use of periodical indexes at an urban academic research library was studied over a 7-week period in the summer of 1982. A total of 98 patrons were interviewed on a random basis as they used various periodical and newspaper indexes. The questionnaire was designed to gather information on citation elements, the methods patrons use to locate…
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Navarro, Gonzalo; Raffinot, Mathieu
2003-01-01
The problem of fast exact and approximate searching for a pattern that contains classes of characters and bounded size gaps (CBG) in a text has a wide range of applications, among which a very important one is protein pattern matching (for instance, one PROSITE protein site is associated with the CBG [RK] - x(2,3) - [DE] - x(2,3) - Y, where the brackets match any of the letters inside, and x(2,3) a gap of length between 2 and 3). Currently, the only way to search for a CBG in a text is to convert it into a full regular expression (RE). However, a RE is more sophisticated than a CBG, and searching for it with a RE pattern matching algorithm complicates the search and makes it slow. This is the reason why we design in this article two new practical CBG matching algorithms that are much simpler and faster than all the RE search techniques. The first one looks exactly once at each text character. The second one does not need to consider all the text characters, and hence it is usually faster than the first one, but in bad cases may have to read the same text character more than once. We then propose a criterion based on the form of the CBG to choose a priori the fastest between both. We also show how to search permitting a few mistakes in the occurrences. We performed many practical experiments using the PROSITE database, and all of them show that our algorithms are the fastest in virtually all cases.
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A literature review of empirical research on learning analytics in medical education
Saqr, Mohammed
2018-01-01
The number of publications in the field of medical education is still markedly low, despite recognition of the value of the discipline in the medical education literature, and exponential growth of publications in other fields. This necessitates raising awareness of the research methods and potential benefits of learning analytics (LA). The aim of this paper was to offer a methodological systemic review of empirical LA research in the field of medical education and a general overview of the common methods used in the field in general. Search was done in Medline database using the term “LA.” Inclusion criteria included empirical original research articles investigating LA using qualitative, quantitative, or mixed methodologies. Articles were also required to be written in English, published in a scholarly peer-reviewed journal and have a dedicated section for methods and results. A Medline search resulted in only six articles fulfilling the inclusion criteria for this review. Most of the studies collected data about learners from learning management systems or online learning resources. Analysis used mostly quantitative methods including descriptive statistics, correlation tests, and regression models in two studies. Patterns of online behavior and usage of the digital resources as well as predicting achievement was the outcome most studies investigated. Research about LA in the field of medical education is still in infancy, with more questions than answers. The early studies are encouraging and showed that patterns of online learning can be easily revealed as well as predicting students’ performance. PMID:29599699
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A literature review of empirical research on learning analytics in medical education.
Saqr, Mohammed
2018-01-01
The number of publications in the field of medical education is still markedly low, despite recognition of the value of the discipline in the medical education literature, and exponential growth of publications in other fields. This necessitates raising awareness of the research methods and potential benefits of learning analytics (LA). The aim of this paper was to offer a methodological systemic review of empirical LA research in the field of medical education and a general overview of the common methods used in the field in general. Search was done in Medline database using the term "LA." Inclusion criteria included empirical original research articles investigating LA using qualitative, quantitative, or mixed methodologies. Articles were also required to be written in English, published in a scholarly peer-reviewed journal and have a dedicated section for methods and results. A Medline search resulted in only six articles fulfilling the inclusion criteria for this review. Most of the studies collected data about learners from learning management systems or online learning resources. Analysis used mostly quantitative methods including descriptive statistics, correlation tests, and regression models in two studies. Patterns of online behavior and usage of the digital resources as well as predicting achievement was the outcome most studies investigated. Research about LA in the field of medical education is still in infancy, with more questions than answers. The early studies are encouraging and showed that patterns of online learning can be easily revealed as well as predicting students' performance.
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Classification of Animal Movement Behavior through Residence in Space and Time.
Torres, Leigh G; Orben, Rachael A; Tolkova, Irina; Thompson, David R
2017-01-01
Identification and classification of behavior states in animal movement data can be complex, temporally biased, time-intensive, scale-dependent, and unstandardized across studies and taxa. Large movement datasets are increasingly common and there is a need for efficient methods of data exploration that adjust to the individual variability of each track. We present the Residence in Space and Time (RST) method to classify behavior patterns in movement data based on the concept that behavior states can be partitioned by the amount of space and time occupied in an area of constant scale. Using normalized values of Residence Time and Residence Distance within a constant search radius, RST is able to differentiate behavior patterns that are time-intensive (e.g., rest), time & distance-intensive (e.g., area restricted search), and transit (short time and distance). We use grey-headed albatross (Thalassarche chrysostoma) GPS tracks to demonstrate RST's ability to classify behavior patterns and adjust to the inherent scale and individuality of each track. Next, we evaluate RST's ability to discriminate between behavior states relative to other classical movement metrics. We then temporally sub-sample albatross track data to illustrate RST's response to less resolved data. Finally, we evaluate RST's performance using datasets from four taxa with diverse ecology, functional scales, ecosystems, and data-types. We conclude that RST is a robust, rapid, and flexible method for detailed exploratory analysis and meta-analyses of behavioral states in animal movement data based on its ability to integrate distance and time measurements into one descriptive metric of behavior groupings. Given the increasing amount of animal movement data collected, it is timely and useful to implement a consistent metric of behavior classification to enable efficient and comparative analyses. Overall, the application of RST to objectively explore and compare behavior patterns in movement data can enhance our fine- and broad- scale understanding of animal movement ecology.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoon, Hong-Jun; Carmichael, Tandy; Tourassi, Georgia
Previously, we have shown the potential of using an individual s visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circlesmore » shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant s "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, fairly stable personalized fingerprint of perceptual organization.« less
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Self-evaluation on Motion Adaptation for Service Robots
NASA Astrophysics Data System (ADS)
Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru
We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.
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Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S.; Sinha, Saurabh
2011-01-01
Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, ‘enhancers’), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for ‘motif-blind’ CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to ‘supervise’ the search. We propose a new statistical method, based on ‘Interpolated Markov Models’, for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. PMID:21821659
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Saleh, Ahlam A.; Ratajeski, Melissa A.; Bertolet, Marnie
2015-01-01
Objective To identify estimates of time taken to search grey literature in support of health sciences systematic reviews and to identify searcher or systematic review characteristics that may impact resource selection or time spent searching. Methods A survey was electronically distributed to searchers embarking on a new systematic review. Characteristics of the searcher and systematic review were collected along with time spent searching and what resources were searched. Time and resources were tabulated and resources were categorized as grey or non-grey. Data was analyzed using Kruskal-Wallis tests. Results Out of 81 original respondents, 21% followed through with completion of the surveys in their entirety. The median time spent searching all resources was 471 minutes, and of those a median of 85 minutes were spent searching grey literature. The median number of resources used in a systematic review search was four and the median number of grey literature sources searched was two. The amount of time spent searching was influenced by whether the systematic review was grant funded. Additionally, the number of resources searched was impacted by institution type and whether systematic review training was received. Conclusions This study characterized the amount of time for conducting systematic review searches including searching the grey literature, in addition to the number and types of resources used. This may aid searchers in planning their time, along with providing benchmark information for future studies. This paper contributes by quantifying current grey literature search patterns and associating them with searcher and review characteristics. Further discussion and research into the search approach for grey literature in support of systematic reviews is encouraged. PMID:25914722
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Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data.
Ingram, David G; Matthews, Camilla K; Plante, David T
2015-03-01
The primary aim of the current study was to test the hypothesis that there is a seasonal component to snoring and obstructive sleep apnea (OSA) through the use of Google search engine query data. Internet search engine query data were retrieved from Google Trends from January 2006 to December 2012. Monthly normalized search volume was obtained over that 7-year period in the USA and Australia for the following search terms: "snoring" and "sleep apnea". Seasonal effects were investigated by fitting cosinor regression models. In addition, the search terms "snoring children" and "sleep apnea children" were evaluated to examine seasonal effects in pediatric populations. Statistically significant seasonal effects were found using cosinor analysis in both USA and Australia for "snoring" (p < 0.00001 for both countries). Similarly, seasonal patterns were observed for "sleep apnea" in the USA (p = 0.001); however, cosinor analysis was not significant for this search term in Australia (p = 0.13). Seasonal patterns for "snoring children" and "sleep apnea children" were observed in the USA (p = 0.002 and p < 0.00001, respectively), with insufficient search volume to examine these search terms in Australia. All searches peaked in the winter or early spring in both countries, with the magnitude of seasonal effect ranging from 5 to 50 %. Our findings indicate that there are significant seasonal trends for both snoring and sleep apnea internet search engine queries, with a peak in the winter and early spring. Further research is indicated to determine the mechanisms underlying these findings, whether they have clinical impact, and if they are associated with other comorbid medical conditions that have similar patterns of seasonal exacerbation.
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A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.
Mosa, Abu Saleh Mohammad; Yoo, Illhoi
2013-01-09
The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed's Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE.
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Contextual cueing impairment in patients with age-related macular degeneration.
Geringswald, Franziska; Herbik, Anne; Hoffmann, Michael B; Pollmann, Stefan
2013-09-12
Visual attention can be guided by past experience of regularities in our visual environment. In the contextual cueing paradigm, incidental learning of repeated distractor configurations speeds up search times compared to random search arrays. Concomitantly, fewer fixations and more direct scan paths indicate more efficient visual exploration in repeated search arrays. In previous work, we found that simulating a central scotoma in healthy observers eliminated this search facilitation. Here, we investigated contextual cueing in patients with age-related macular degeneration (AMD) who suffer from impaired foveal vision. AMD patients performed visual search using only their more severely impaired eye (n = 13) as well as under binocular viewing (n = 16). Normal-sighted controls developed a significant contextual cueing effect. In comparison, patients showed only a small nonsignificant advantage for repeated displays when searching with their worse eye. When searching binocularly, they profited from contextual cues, but still less than controls. Number of fixations and scan pattern ratios showed a comparable pattern as search times. Moreover, contextual cueing was significantly correlated with acuity in monocular search. Thus, foveal vision loss may lead to impaired guidance of attention by contextual memory cues.
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Determination of geographic variance in stroke prevalence using Internet search engine analytics.
Walcott, Brian P; Nahed, Brian V; Kahle, Kristopher T; Redjal, Navid; Coumans, Jean-Valery
2011-06-01
Previous methods to determine stroke prevalence, such as nationwide surveys, are labor-intensive endeavors. Recent advances in search engine query analytics have led to a new metric for disease surveillance to evaluate symptomatic phenomenon, such as influenza. The authors hypothesized that the use of search engine query data can determine the prevalence of stroke. The Google Insights for Search database was accessed to analyze anonymized search engine query data. The authors' search strategy utilized common search queries used when attempting either to identify the signs and symptoms of a stroke or to perform stroke education. The search logic was as follows: (stroke signs + stroke symptoms + mini stroke--heat) from January 1, 2005, to December 31, 2010. The relative number of searches performed (the interest level) for this search logic was established for all 50 states and the District of Columbia. A Pearson product-moment correlation coefficient was calculated from the statespecific stroke prevalence data previously reported. Web search engine interest level was available for all 50 states and the District of Columbia over the time period for January 1, 2005-December 31, 2010. The interest level was highest in Alabama and Tennessee (100 and 96, respectively) and lowest in California and Virginia (58 and 53, respectively). The Pearson correlation coefficient (r) was calculated to be 0.47 (p = 0.0005, 2-tailed). Search engine query data analysis allows for the determination of relative stroke prevalence. Further investigation will reveal the reliability of this metric to determine temporal pattern analysis and prevalence in this and other symptomatic diseases.
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Optimization of Operations Resources via Discrete Event Simulation Modeling
NASA Technical Reports Server (NTRS)
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
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An initial log analysis of usage patterns on a research networking system.
Boland, Mary Regina; Trembowelski, Sylvia; Bakken, Suzanne; Weng, Chunhua
2012-08-01
Usage data for research networking systems (RNSs) are valuable but generally unavailable for understanding scientific professionals' information needs and online collaborator seeking behaviors. This study contributes a method for evaluating RNSs and initial usage knowledge of one RNS obtained from using this method. We designed a log for an institutional RNS, defined categories of users and tasks, and analyzed correlations between usage patterns and user and query types. Our results show that scientific professionals spend more time performing deep Web searching on RNSs than generic Google users and we also show that retrieving scientist profiles is faster on an RNS than on Google (3.5 seconds vs. 34.2 seconds) whereas organization-specific browsing on a RNS takes longer than on Google (117.0 seconds vs. 34.2 seconds). Usage patterns vary by user role, e.g., faculty performed more informational queries than administrators, which implies role-specific user support is needed for RNSs. © 2012 Wiley Periodicals, Inc.
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An Initial Log Analysis of Usage Patterns on a Research Networking System
Boland, Mary Regina; Trembowelski, Sylvia; Bakken, Suzanne; Weng, Chunhua
2012-01-01
Abstract Usage data for research networking systems (RNSs) are valuable but generally unavailable for understanding scientific professionals’ information needs and online collaborator seeking behaviors. This study contributes a method for evaluating RNSs and initial usage knowledge of one RNS obtained from using this method. We designed a log for an institutional RNS, defined categories of users and tasks, and analyzed correlations between usage patterns and user and query types. Our results show that scientific professionals spend more time performing deep Web searching on RNSs than generic Google users and we also show that retrieving scientist profiles is faster on an RNS than on Google (3.5 seconds vs. 34.2 seconds) whereas organization‐specific browsing on a RNS takes longer than on Google (117.0 seconds vs. 34.2 seconds). Usage patterns vary by user role, e.g., faculty performed more informational queries than administrators, which implies role‐specific user support is needed for RNSs. Clin Trans Sci 2012; Volume 5: 340–347 PMID:22883612
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Computational mass spectrometry for small molecules
2013-01-01
The identification of small molecules from mass spectrometry (MS) data remains a major challenge in the interpretation of MS data. This review covers the computational aspects of identifying small molecules, from the identification of a compound searching a reference spectral library, to the structural elucidation of unknowns. In detail, we describe the basic principles and pitfalls of searching mass spectral reference libraries. Determining the molecular formula of the compound can serve as a basis for subsequent structural elucidation; consequently, we cover different methods for molecular formula identification, focussing on isotope pattern analysis. We then discuss automated methods to deal with mass spectra of compounds that are not present in spectral libraries, and provide an insight into de novo analysis of fragmentation spectra using fragmentation trees. In addition, this review shortly covers the reconstruction of metabolic networks using MS data. Finally, we list available software for different steps of the analysis pipeline. PMID:23453222
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Synonym set extraction from the biomedical literature by lexical pattern discovery.
McCrae, John; Collier, Nigel
2008-03-24
Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction based on patterns was first suggested by Hearst 1, but it is still not clear how to automatically construct such patterns for different semantic relations and domains. In particular it is not certain which patterns are useful for capturing synonymy. The assumption of extant resources such as parsers is also a limiting factor for many languages, so it is desirable to find patterns that do not use syntactical analysis. Finally to give a more consistent and applicable result it is desirable to use these patterns to form synonym sets in a sound way. We present a method that automatically generates regular expression patterns by expanding seed patterns in a heuristic search and then develops a feature vector based on the occurrence of term pairs in each developed pattern. This allows for a binary classifications of term pairs as synonymous or non-synonymous. We then model this result as a probability graph to find synonym sets, which is equivalent to the well-studied problem of finding an optimal set cover. We achieved 73.2% precision and 29.7% recall by our method, out-performing hand-made resources such as MeSH and Wikipedia. We conclude that automatic methods can play a practical role in developing new thesauri or expanding on existing ones, and this can be done with only a small amount of training data and no need for resources such as parsers. We also concluded that the accuracy can be improved by grouping into synonym sets.
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Interest in tanning beds and sunscreen in German-speaking countries.
Kirchberger, Michael C; Kirchberger, Laura F; Eigentler, Thomas K; Reinhard, Raphael; Berking, Carola; Schuler, Gerold; Heinzerling, Lucie; Heppt, Markus V
2017-12-01
The growing incidence of nearly all types of skin cancer can be attributed to increased exposure to natural or artificial ultraviolet (UV) radiation. However, there is a scarcity of statistical data on risk behavior or sunscreen use, which would be important for any prevention efforts. Using the search engine Google ® , we analyzed search patterns for the terms Solarium (tanning bed), Sonnencreme (sunscreen), and Sonnenschutz (sun protection) in Germany, Austria, and Switzerland between 2004 and 2016, and compared it to search patterns worldwide. For this purpose, "normalized search volumes" (NSVs) were calculated for the various search queries. The corresponding polynomial functions were then compared with each other over the course of time. Since 2001, there has been a marked worldwide decrease in the search queries for tanning bed, whereas those for sunscreen have steadily increased. In German-speaking countries, on the other hand, there have - for years - consistently been more search queries for tanning bed than for sunscreen. There is an annual periodicity of the queries, with the highest NSVs for tanning bed between March and May and those for sunscreen in the summer months around June. In Germany, the city-states of Hamburg and Berlin have particularly high NSVs for tanning bed. Compared to the rest of the world, German-speaking countries show a strikingly unfavorable search pattern. There is still great need for education and prevention with respect to sunscreen use and avoidance of artificial UV exposure. © 2017 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.
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Hierarchical random walks in trace fossils and the origin of optimal search behavior
Sims, David W.; Reynolds, Andrew M.; Humphries, Nicolas E.; Southall, Emily J.; Wearmouth, Victoria J.; Metcalfe, Brett; Twitchett, Richard J.
2014-01-01
Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa. PMID:25024221
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Semantic Approaches Applied to Scientific Ocean Drilling Data
NASA Astrophysics Data System (ADS)
Fils, D.; Jenkins, C. J.; Arko, R. A.
2012-12-01
The application of Linked Open Data methods to 40 years of data from scientific ocean drilling is providing users with several new methods for rich-content data search and discovery. Data from the Deep Sea Drilling Project (DSDP), Ocean Drilling Program (ODP) and Integrated Ocean Drilling Program (IODP) have been translated and placed in RDF triple stores to provide access via SPARQL, linked open data patterns, and by embedded structured data through schema.org / RDFa. Existing search services have been re-encoded in this environment which allows the new and established architectures to be contrasted. Vocabularies including computed semantic relations between concepts, allow separate but related data sets to be connected on their concepts and resources even when they are expressed somewhat differently. Scientific ocean drilling produces a wide range of data types and data sets: borehole logging file-based data, images, measurements, visual observations and the physical sample data. The steps involved in connecting these data to concepts using vocabularies will be presented, including the connection of data sets through Vocabulary of Interlinked Datasets (VoID) and open entity collections such as Freebase and dbPedia. Demonstrated examples will include: (i) using RDF Schema for inferencing and in federated searches across NGDC and IODP data, (ii) using structured data in the data.oceandrilling.org web site, (iii) association through semantic methods of age models and depth recorded data to facilitate age based searches for data recorded by depth only.
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ERIC Educational Resources Information Center
Tuffrey-Wijne, Irene; Hogg, James; Curfs, Leopold
2007-01-01
Background: As patterns of morbidity and mortality are changing, more people with intellectual disabilities develop cancer or other life-limiting illness. This paper reviews the literature around the need of people with intellectual disabilities for palliative care. Methods: A range of databases and the World Wide Web were searched for relevant…
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A method for detecting and characterizing outbreaks of infectious disease from clinical reports.
Cooper, Gregory F; Villamarin, Ricardo; Rich Tsui, Fu-Chiang; Millett, Nicholas; Espino, Jeremy U; Wagner, Michael M
2015-02-01
Outbreaks of infectious disease can pose a significant threat to human health. Thus, detecting and characterizing outbreaks quickly and accurately remains an important problem. This paper describes a Bayesian framework that links clinical diagnosis of individuals in a population to epidemiological modeling of disease outbreaks in the population. Computer-based diagnosis of individuals who seek healthcare is used to guide the search for epidemiological models of population disease that explain the pattern of diagnoses well. We applied this framework to develop a system that detects influenza outbreaks from emergency department (ED) reports. The system diagnoses influenza in individuals probabilistically from evidence in ED reports that are extracted using natural language processing. These diagnoses guide the search for epidemiological models of influenza that explain the pattern of diagnoses well. Those epidemiological models with a high posterior probability determine the most likely outbreaks of specific diseases; the models are also used to characterize properties of an outbreak, such as its expected peak day and estimated size. We evaluated the method using both simulated data and data from a real influenza outbreak. The results provide support that the approach can detect and characterize outbreaks early and well enough to be valuable. We describe several extensions to the approach that appear promising. Copyright © 2014 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Wang, Li; Li, Feng; Xing, Jian
2017-10-01
In this paper, a hybrid artificial bee colony (ABC) algorithm and pattern search (PS) method is proposed and applied for recovery of particle size distribution (PSD) from spectral extinction data. To be more useful and practical, size distribution function is modelled as the general Johnson's ? function that can overcome the difficulty of not knowing the exact type beforehand encountered in many real circumstances. The proposed hybrid algorithm is evaluated through simulated examples involving unimodal, bimodal and trimodal PSDs with different widths and mean particle diameters. For comparison, all examples are additionally validated by the single ABC algorithm. In addition, the performance of the proposed algorithm is further tested by actual extinction measurements with real standard polystyrene samples immersed in water. Simulation and experimental results illustrate that the hybrid algorithm can be used as an effective technique to retrieve the PSDs with high reliability and accuracy. Compared with the single ABC algorithm, our proposed algorithm can produce more accurate and robust inversion results while taking almost comparative CPU time over ABC algorithm alone. The superiority of ABC and PS hybridization strategy in terms of reaching a better balance of estimation accuracy and computation effort increases its potentials as an excellent inversion technique for reliable and efficient actual measurement of PSD.
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A Method for Detecting and Characterizing Outbreaks of Infectious Disease from Clinical Reports
Cooper, Gregory F.; Villamarin, Ricardo; Tsui, Fu-Chiang (Rich); Millett, Nicholas; Espino, Jeremy U.; Wagner, Michael M.
2014-01-01
Outbreaks of infectious disease can pose a significant threat to human health. Thus, detecting and characterizing outbreaks quickly and accurately remains an important problem. This paper describes a Bayesian framework that links clinical diagnosis of individuals in a population to epidemiological modeling of disease outbreaks in the population. Computer-based diagnosis of individuals who seek healthcare is used to guide the search for epidemiological models of population disease that explain the pattern of diagnoses well. We applied this framework to develop a system that detects influenza outbreaks from emergency department (ED) reports. The system diagnoses influenza in individuals probabilistically from evidence in ED reports that are extracted using natural language processing. These diagnoses guide the search for epidemiological models of influenza that explain the pattern of diagnoses well. Those epidemiological models with a high posterior probability determine the most likely outbreaks of specific diseases; the models are also used to characterize properties of an outbreak, such as its expected peak day and estimated size. We evaluated the method using both simulated data and data from a real influenza outbreak. The results provide support that the approach can detect and characterize outbreaks early and well enough to be valuable. We describe several extensions to the approach that appear promising. PMID:25181466
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Lorence, Daniel; Abraham, Joanna
2006-01-01
Medical and health-related searches pose a special case of risk when using the web as an information resource. Uninsured consumers, lacking access to a trained provider, will often rely on information from the internet for self-diagnosis and treatment. In areas where treatments are uncertain or controversial, most consumers lack the knowledge to make an informed decision. This exploratory technology assessment examines the use of Keyword Effectiveness Indexing (KEI) analysis as a potential tool for profiling information search and keyword retrieval patterns. Results demonstrate that the KEI methodology can be useful in identifying e-health search patterns, but is limited by semantic or text-based web environments.
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LandEx - Fast, FOSS-Based Application for Query and Retrieval of Land Cover Patterns
NASA Astrophysics Data System (ADS)
Netzel, P.; Stepinski, T.
2012-12-01
The amount of satellite-based spatial data is continuously increasing making a development of efficient data search tools a priority. The bulk of existing research on searching satellite-gathered data concentrates on images and is based on the concept of Content-Based Image Retrieval (CBIR); however, available solutions are not efficient and robust enough to be put to use as deployable web-based search tools. Here we report on development of a practical, deployable tool that searches classified, rather than raw image. LandEx (Landscape Explorer) is a GeoWeb-based tool for Content-Based Pattern Retrieval (CBPR) contained within the National Land Cover Dataset 2006 (NLCD2006). The USGS-developed NLCD2006 is derived from Landsat multispectral images; it covers the entire conterminous U.S. with the resolution of 30 meters/pixel and it depicts 16 land cover classes. The size of NLCD2006 is about 10 Gpixels (161,000 x 100,000 pixels). LandEx is a multi-tier GeoWeb application based on Open Source Software. Main components are: GeoExt/OpenLayers (user interface), GeoServer (OGC WMS, WCS and WPS server), and GRASS (calculation engine). LandEx performs search using query-by-example approach: user selects a reference scene (exhibiting a chosen pattern of land cover classes) and the tool produces, in real time, a map indicating a degree of similarity between the reference pattern and all local patterns across the U.S. Scene pattern is encapsulated by a 2D histogram of classes and sizes of single-class clumps. Pattern similarity is based on the notion of mutual information. The resultant similarity map can be viewed and navigated in a web browser, or it can download as a GeoTiff file for more in-depth analysis. The LandEx is available at http://sil.uc.edu
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Pattern Recognition Using Artificial Neural Network: A Review
NASA Astrophysics Data System (ADS)
Kim, Tai-Hoon
Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.
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Use of Cognitive and Metacognitive Strategies in Online Search: An Eye-Tracking Study
ERIC Educational Resources Information Center
Zhou, Mingming; Ren, Jing
2016-01-01
This study used eye-tracking technology to track students' eye movements while searching information on the web. The research question guiding this study was "Do students with different search performance levels have different visual attention distributions while searching information online? If yes, what are the patterns for high and low…
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Wang, Dawei; Hao, Leilei; Maguire, Phil; Hu, Yixin
2016-12-01
This study investigated the effects of cognitive style and emotional trade-off difficulty (ETOD) on information processing in decision-making. Eighty undergraduates (73.75% female, M = 21.90), grouped according to their cognitive style (field-dependent or field-independent), conducted an Information Display Board (IDB) task, through which search time, search depth and search pattern were measured. Participants' emotional states were assessed both before and after the IDB task. The results showed that participants experienced significantly more negative emotion under high ETOD compared to those under low ETOD. While both cognitive style and ETOD had significant effects on search time and search depth, only ETOD significantly influenced search pattern; individuals in both cognitive style groups tended to use attribute-based processing under high ETOD and to use alternative-based processing under low ETOD. There was also a significant interaction between cognitive style and ETOD for search time and search depth. We propose that these results are best accounted for by the coping behaviour framework under high ETOD, and by the negative emotion hypothesis under low ETOD. © 2016 International Union of Psychological Science.
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Noppert, Grace A; Kubale, John T; Wilson, Mark L
2017-04-01
Infectious disease epidemiologists have long recognised the importance of social variables as drivers of epidemics and disease risk, yet few apply analytic approaches from social epidemiology. We quantified and evaluated the extent to which recent infectious disease research is employing the perspectives and methods of social epidemiology by replicating the methodology used by Cohen et al in a 2007 study. 2 search strategies were used to identify and review articles published from 1 January 2005 to 31 December 2013. First, we performed a keyword search of 'social epidemiology' in the title/abstract/text of published studies identified in PubMed, PsychInfo and ISI Web of Science, and classified each study as pertaining to infectious, non-infectious or other outcomes. A second PubMed search identified articles that were cross-referenced under non-infectious or infectious, and search terms relating to social variables. The abstracts of all articles were read, classified and examined to identify patterns over time. Findings suggest that infectious disease research publications that explicitly or implicitly incorporate social epidemiological approaches have stagnated in recent years. While the number of publications that were explicitly self-classified as 'social epidemiology' has risen, the proportion that investigated infectious disease outcomes has declined. Furthermore, infectious diseases accounted for the smallest proportion of articles that were cross-referenced with Medical Subject Headings (MeSH) terms related to social factors, and most of these involved sexually transmitted diseases. The current landscape of infectious disease epidemiology could benefit from new approaches to understanding how the social and biophysical environment sustains transmission and exacerbates disparities. The framework of social epidemiology provides infectious disease researchers with such a perspective and research opportunity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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Fast parallel tandem mass spectral library searching using GPU hardware acceleration.
Baumgardner, Lydia Ashleigh; Shanmugam, Avinash Kumar; Lam, Henry; Eng, Jimmy K; Martin, Daniel B
2011-06-03
Mass spectrometry-based proteomics is a maturing discipline of biologic research that is experiencing substantial growth. Instrumentation has steadily improved over time with the advent of faster and more sensitive instruments collecting ever larger data files. Consequently, the computational process of matching a peptide fragmentation pattern to its sequence, traditionally accomplished by sequence database searching and more recently also by spectral library searching, has become a bottleneck in many mass spectrometry experiments. In both of these methods, the main rate-limiting step is the comparison of an acquired spectrum with all potential matches from a spectral library or sequence database. This is a highly parallelizable process because the core computational element can be represented as a simple but arithmetically intense multiplication of two vectors. In this paper, we present a proof of concept project taking advantage of the massively parallel computing available on graphics processing units (GPUs) to distribute and accelerate the process of spectral assignment using spectral library searching. This program, which we have named FastPaSS (for Fast Parallelized Spectral Searching), is implemented in CUDA (Compute Unified Device Architecture) from NVIDIA, which allows direct access to the processors in an NVIDIA GPU. Our efforts demonstrate the feasibility of GPU computing for spectral assignment, through implementation of the validated spectral searching algorithm SpectraST in the CUDA environment.
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High-speed autoverifying technology for printed wiring boards
NASA Astrophysics Data System (ADS)
Ando, Moritoshi; Oka, Hiroshi; Okada, Hideo; Sakashita, Yorihiro; Shibutani, Nobumi
1996-10-01
We have developed an automated pattern verification technique. The output of an automated optical inspection system contains many false alarms. Verification is needed to distinguish between minor irregularities and serious defects. In the past, this verification was usually done manually, which led to unsatisfactory product quality. The goal of our new automated verification system is to detect pattern features on surface mount technology boards. In our system, we employ a new illumination method, which uses multiple colors and multiple direction illumination. Images are captured with a CCD camera. We have developed a new algorithm that uses CAD data for both pattern matching and pattern structure determination. This helps to search for patterns around a defect and to examine defect definition rules. These are processed with a high speed workstation and a hard-wired circuits. The system can verify a defect within 1.5 seconds. The verification system was tested in a factory. It verified 1,500 defective samples and detected all significant defects with only a 0.1 percent of error rate (false alarm).
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Jamnagerwalla, Juzar; Markowitz, Melissa A; Thum, D Joseph; McCarty, Philip; Medendorp, Andrew R; Raz, Shlomo; Kim, Ja-Hong
2018-01-01
Background Uterine power morcellation, where the uterus is shred into smaller pieces, is a widely used technique for removal of uterine specimens in patients undergoing minimally invasive abdominal hysterectomy or myomectomy. Complications related to power morcellation of uterine specimens led to US Food and Drug Administration (FDA) communications in 2014 ultimately recommending against the use of power morcellation for women undergoing minimally invasive hysterectomy. Subsequently, practitioners drastically decreased the use of morcellation. Objective We aimed to determine the effect of increased patient awareness on the decrease in use of the morcellator. Google Trends is a public tool that provides data on temporal patterns of search terms, and we correlated this data with the timing of the FDA communication. Methods Weekly relative search volume (RSV) was obtained from Google Trends using the term “morcellation.” Higher RSV corresponds to increases in weekly search volume. Search volumes were divided into 3 groups: the 2 years prior to the FDA communication, a 1-year period following, and thereafter, with the distribution of the weekly RSV over the 3 periods tested using 1-way analysis of variance. Additionally, we analyzed the total number of websites containing the term “morcellation” over this time. Results The mean RSV prior to the FDA communication was 12.0 (SD 15.8), with the RSV being 60.3 (SD 24.7) in the 1-year after and 19.3 (SD 5.2) thereafter (P<.001). The mean number of webpages containing the term “morcellation” in 2011 was 10,800, rising to 18,800 during 2014 and 36,200 in 2017. Conclusions Google search activity about morcellation of uterine specimens increased significantly after the FDA communications. This trend indicates an increased public awareness regarding morcellation and its complications. More extensive preoperative counseling and alteration of surgical technique and clinician practice may be necessary. PMID:29699965
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Inferring consistent functional interaction patterns from natural stimulus FMRI data
Sun, Jiehuan; Hu, Xintao; Huang, Xiu; Liu, Yang; Li, Kaiming; Li, Xiang; Han, Junwei; Guo, Lei
2014-01-01
There has been increasing interest in how the human brain responds to natural stimulus such as video watching in the neuroimaging field. Along this direction, this paper presents our effort in inferring consistent and reproducible functional interaction patterns under natural stimulus of video watching among known functional brain regions identified by task-based fMRI. Then, we applied and compared four statistical approaches, including Bayesian network modeling with searching algorithms: greedy equivalence search (GES), Peter and Clark (PC) analysis, independent multiple greedy equivalence search (IMaGES), and the commonly used Granger causality analysis (GCA), to infer consistent and reproducible functional interaction patterns among these brain regions. It is interesting that a number of reliable and consistent functional interaction patterns were identified by the GES, PC and IMaGES algorithms in different participating subjects when they watched multiple video shots of the same semantic category. These interaction patterns are meaningful given current neuroscience knowledge and are reasonably reproducible across different brains and video shots. In particular, these consistent functional interaction patterns are supported by structural connections derived from diffusion tensor imaging (DTI) data, suggesting the structural underpinnings of consistent functional interactions. Our work demonstrates that specific consistent patterns of functional interactions among relevant brain regions might reflect the brain's fundamental mechanisms of online processing and comprehension of video messages. PMID:22440644
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A novel tree-based algorithm to discover seismic patterns in earthquake catalogs
NASA Astrophysics Data System (ADS)
Florido, E.; Asencio-Cortés, G.; Aznarte, J. L.; Rubio-Escudero, C.; Martínez-Álvarez, F.
2018-06-01
A novel methodology is introduced in this research study to detect seismic precursors. Based on an existing approach, the new methodology searches for patterns in the historical data. Such patterns may contain statistical or soil dynamics information. It improves the original version in several aspects. First, new seismicity indicators have been used to characterize earthquakes. Second, a machine learning clustering algorithm has been applied in a very flexible way, thus allowing the discovery of new data groupings. Third, a novel search strategy is proposed in order to obtain non-overlapped patterns. And, fourth, arbitrary lengths of patterns are searched for, thus discovering long and short-term behaviors that may influence in the occurrence of medium-large earthquakes. The methodology has been applied to seven different datasets, from three different regions, namely the Iberian Peninsula, Chile and Japan. Reported results show a remarkable improvement with respect to the former version, in terms of all evaluated quality measures. In particular, the number of false positives has decreased and the positive predictive values increased, both of them in a very remarkable manner.
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Pernek, Igor; Stiglic, Gregor; Leskovec, Jure; Strasberg, Howard R; Shah, Nigam Haresh
2015-01-01
Background Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance. Objective To analyze health care professionals’ information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource. Methods Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert. Results Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert. Conclusions Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate. PMID:26293444
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Montague, Enid; Asan, Onur
2014-01-01
Objective The aim of this study was to examine eye gaze patterns between patients and physicians while electronic health records were used to support patient care. Background Eye gaze provides an indication of physician attention to patient, patient/physician interaction, and physician behaviors such as searching for information and documenting information. Methods A field study was conducted where 100 patient visits were observed and video recorded in a primary care clinic. Videos were then coded for gaze behaviors where patients’ and physicians’ gaze at each other and artifacts such as electronic health records were coded using a pre-established objective coding scheme. Gaze data were then analyzed using lag sequential methods. Results Results showed that there are several eye gaze patterns significantly dependent to each other. All doctor-initiated gaze patterns were followed by patient gaze patterns. Some patient-initiated gaze patterns were also followed by doctor gaze patterns significantly unlike the findings in previous studies. Health information technology appears to contribute to some of the new significant patterns that have emerged. Differences were also found in gaze patterns related to technology that differ from patterns identified in studies with paper charts. Several sequences related to patient-doctor- technology were also significant. Electronic health records affect the patient-physician eye contact dynamic differently than paper charts. Conclusion This study identified several patterns of patient-physician interaction with electronic health record systems. Consistent with previous studies, physician initiated gaze is an important driver of the interactions between patient and physician and patient and technology. PMID:24380671
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Investigating User Search Tactic Patterns and System Support in Using Digital Libraries
ERIC Educational Resources Information Center
Joo, Soohyung
2013-01-01
This study aims to investigate users' search tactic application and system support in using digital libraries. A user study was conducted with sixty digital library users. The study was designed to answer three research questions: 1) How do users engage in a search process by applying different types of search tactics while conducting different…
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NASA Astrophysics Data System (ADS)
Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping
2018-05-01
Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.
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A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns
Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.
2015-01-01
Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661
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Soft-Decision Decoding of Binary Linear Block Codes Based on an Iterative Search Algorithm
NASA Technical Reports Server (NTRS)
Lin, Shu; Kasami, Tadao; Moorthy, H. T.
1997-01-01
This correspondence presents a suboptimum soft-decision decoding scheme for binary linear block codes based on an iterative search algorithm. The scheme uses an algebraic decoder to iteratively generate a sequence of candidate codewords one at a time using a set of test error patterns that are constructed based on the reliability information of the received symbols. When a candidate codeword is generated, it is tested based on an optimality condition. If it satisfies the optimality condition, then it is the most likely (ML) codeword and the decoding stops. If it fails the optimality test, a search for the ML codeword is conducted in a region which contains the ML codeword. The search region is determined by the current candidate codeword and the reliability of the received symbols. The search is conducted through a purged trellis diagram for the given code using the Viterbi algorithm. If the search fails to find the ML codeword, a new candidate is generated using a new test error pattern, and the optimality test and search are renewed. The process of testing and search continues until either the MEL codeword is found or all the test error patterns are exhausted and the decoding process is terminated. Numerical results show that the proposed decoding scheme achieves either practically optimal performance or a performance only a fraction of a decibel away from the optimal maximum-likelihood decoding with a significant reduction in decoding complexity compared with the Viterbi decoding based on the full trellis diagram of the codes.
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NASA Astrophysics Data System (ADS)
Heidari, A. A.; Kazemizade, O.; Abbaspour, R. A.
2015-12-01
In this paper, a continuous harmony search (HS) approach is investigated for tackling the Uncapacitated Facility Location (UFL) task. This article proposes an efficient modified HS-based optimizer to improve the performance of HS on complex spatial tasks like UFL problems. For this aim, opposition-based learning (OBL) and chaotic patterns are utilized. The proposed technique is examined against several UFL benchmark challenges in specialized literature. Then, the modified HS is substantiated in detail and compared to the basic HS and some other methods. The results showed that new opposition-based chaotic HS (OBCHS) algorithm not only can exploit better solutions competently but it is able to outperform HS in solving UFL problems.
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Cloud-assisted mobile-access of health data with privacy and auditability.
Tong, Yue; Sun, Jinyuan; Chow, Sherman S M; Li, Pan
2014-03-01
Motivated by the privacy issues, curbing the adoption of electronic healthcare systems and the wild success of cloud service models, we propose to build privacy into mobile healthcare systems with the help of the private cloud. Our system offers salient features including efficient key management, privacy-preserving data storage, and retrieval, especially for retrieval at emergencies, and auditability for misusing health data. Specifically, we propose to integrate key management from pseudorandom number generator for unlinkability, a secure indexing method for privacy-preserving keyword search which hides both search and access patterns based on redundancy, and integrate the concept of attribute-based encryption with threshold signing for providing role-based access control with auditability to prevent potential misbehavior, in both normal and emergency cases.
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Detection of Bursts and Pauses in Spike Trains
Ko, D.; Wilson, C. J.; Lobb, C. J.; Paladini, C. A.
2012-01-01
Midbrain dopaminergic neurons in vivo exhibit a wide range of firing patterns. They normally fire constantly at a low rate, and speed up, firing a phasic burst when reward exceeds prediction, or pause when an expected reward does not occur. Therefore, the detection of bursts and pauses from spike train data is a critical problem when studying the role of phasic dopamine (DA) in reward related learning, and other DA dependent behaviors. However, few statistical methods have been developed that can identify bursts and pauses simultaneously. We propose a new statistical method, the Robust Gaussian Surprise (RGS) method, which performs an exhaustive search of bursts and pauses in spike trains simultaneously. We found that the RGS method is adaptable to various patterns of spike trains recorded in vivo, and is not influenced by baseline firing rate, making it applicable to all in vivo spike trains where baseline firing rates vary over time. We compare the performance of the RGS method to other methods of detecting bursts, such as the Poisson Surprise (PS), Rank Surprise (RS), and Template methods. Analysis of data using the RGS method reveals potential mechanisms underlying how bursts and pauses are controlled in DA neurons. PMID:22939922
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Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis
Xu, Rui; Zhen, Zonglei; Liu, Jia
2010-01-01
Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081
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Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers
Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric
2009-01-01
Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan. PMID:19822013
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Semi-supervised anomaly detection - towards model-independent searches of new physics
NASA Astrophysics Data System (ADS)
Kuusela, Mikael; Vatanen, Tommi; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu
2012-06-01
Most classification algorithms used in high energy physics fall under the category of supervised machine learning. Such methods require a training set containing both signal and background events and are prone to classification errors should this training data be systematically inaccurate for example due to the assumed MC model. To complement such model-dependent searches, we propose an algorithm based on semi-supervised anomaly detection techniques, which does not require a MC training sample for the signal data. We first model the background using a multivariate Gaussian mixture model. We then search for deviations from this model by fitting to the observations a mixture of the background model and a number of additional Gaussians. This allows us to perform pattern recognition of any anomalous excess over the background. We show by a comparison to neural network classifiers that such an approach is a lot more robust against misspecification of the signal MC than supervised classification. In cases where there is an unexpected signal, a neural network might fail to correctly identify it, while anomaly detection does not suffer from such a limitation. On the other hand, when there are no systematic errors in the training data, both methods perform comparably.
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Boyer-Moore Algorithm in Retrieving Deleted Short Message Service in Android Platform
NASA Astrophysics Data System (ADS)
Rahmat, R. F.; Prayoga, D. F.; Gunawan, D.; Sitompul, O. S.
2018-02-01
Short message service (SMS) can be used as digital evidence of disclosure of crime because it can strengthen the charges against the offenders. Criminals use various ways to destroy the evidence, including by deleting SMS. On the Android OS, SMS is stored in a SQLite database file. Deletion of SMS data is not followed by bit deletion in memory so that it is possible to rediscover the deleted SMS. Based on this case, the mobile forensic needs to be done to rediscover the short message service. The proposed method in this study is Boyer-Moore algorithm for searching string matching. An auto finds feature is designed to rediscover the short message service by searching using a particular pattern to rematch a text with the result of the hex value conversion in the database file. The system will redisplay the message for each of a match. From all the testing results, the proposed method has quite a high accuracy in rediscovering the short message service using the used dataset. The search results to rediscover the deleted SMS depend on the possibility of overwriting process and the vacuum procedure on the database file.
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Independent operation of implicit working memory under cognitive load.
Ji, Eunhee; Lee, Kyung Min; Kim, Min-Shik
2017-10-01
Implicit working memory (WM) has been known to operate non-consciously and unintentionally. The current study investigated whether implicit WM is a discrete mechanism from explicit WM in terms of cognitive resource. To induce cognitive resource competition, we used a conjunction search task (Experiment 1) and imposed spatial WM load (Experiment 2a and 2b). Each trial was composed of a set of five consecutive search displays. The location of the first four displays appeared as per pre-determined patterns, but the fifth display could follow the same pattern or not. If implicit WM can extract the moving pattern of stimuli, response times for the fifth target would be faster when it followed the pattern compared to when it did not. Our results showed implicit WM can operate when participants are searching for the conjunction target and even while maintaining spatial WM information. These results suggest that implicit WM is independent from explicit spatial WM. Copyright © 2017. Published by Elsevier Inc.
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Cogendez, Ebru; Eken, Meryem Kurek; Bakal, Nuray; Gun, Ismet; Kaygusuz, Ecmel Isik; Karateke, Ates
2015-10-01
The purpose of this prospective study was to assess the role of power Doppler imaging in the differential diagnosis of benign intrauterine focal lesions such as endometrial polyps and submucous myomas using the characteristics of power Doppler flow mapping. A total of 480 premenopausal patients with abnormal uterine bleeding were evaluated by transvaginal ultrasonography (TVS) searching for intrauterine pathology. Sixty-four patients with a suspicious focal endometrial lesion received saline infusion sonography (SIS) after TVS. Fifty-eight patients with focal endometrial lesions underwent power Doppler ultrasound (PDUS). Three different vascular flow patterns were defined: Single vessel pattern, multiple vessel pattern, and circular flow pattern. Finally, hysteroscopic resection was performed in all cases, and Doppler flow characteristics were then compared with the final histopathological findings. Histopathological results were as follows: endometrial polyp: 40 (69 %), submucous myoma: 18 (31 %). Of the cases with endometrial polyps, 80 % demonstrated a single vessel pattern, 7.5 % a multiple vessel pattern, and 0 % a circular pattern. Vascularization was not observed in 12.5 % of patients with polyps. Of the cases with submucousal myomas, 72.2 % demonstrated a circular flow pattern, 27.8 % a multiple vessel pattern, and none of them showed a single vessel pattern. The sensitivity, specificity, and positive and negative predictive values of the single vessel pattern in diagnosing endometrial polyps were 80, 100, 100, and 69.2 %, respectively; and for the circular pattern in diagnosing submucous myoma, these were 72.2, 100, 100, and 88.9 %, respectively. Power Doppler blood flow mapping is a useful, practical, and noninvasive diagnostic method for the differential diagnosis of benign intrauterine focal lesions. Especially in cases of recurrent abnormal uterine bleeding, recurrent abortion, and infertility, PDUS can be preferred as a first-line diagnostic method.
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Lifestyle and Outcomes of Assisted Reproductive Techniques: A Narrative Review
Zeinab, Hamzehgardeshi; Zohreh, Shahhosseini; Gelehkolaee, Keshvar Samadaee
2015-01-01
Background: Studies reveal that lifestyles such as physical activity patterns, obesity, nutrition, and smoking, are factors that affect laboratory test results and pregnancy outcomes induced by assisted fertility techniques in infertile couples. The present study is a narrative review of studies in this area. Methods: In this study, researchers conducted their computer search in public databases Google Scholar general search engine, and then more specific: Science Direct, ProQuest, SID, Magiran, Irandoc, Pubmed, Scopus, cochrane library, and Psych info; Cumulative Index to Nursing and Allied Health Literature (CINAHL), using Medical Subject Headings (MeSH) keywords: infertility (sterility, infertility), lifestyle (life behavior, lifestyle), Assisted Reproductive Techniques (ART), antioxidant and infertility, social health, spiritual health, mental health, Alcohol and drug abuse, preventive factors, and instruments., and selected relevant articles to the study subject from 2004 to 2013. Firstly, a list of 150 papers generated from the initial search. Then reviewers studied titles and abstracts. Secondly, 111 papers were included. Finally, quality assessment of full text studies was performed by two independent reviewers. Researchers reviewed summary of all articles sought, ultimately used data from 62 full articles to compile this review paper. Results: Review of literature led to arrangement of 9 general categories of ART results’ relationship with weight watch and diet, exercise and physical activity, psychological health, avoiding medications, alcohol and drugs, preventing diseases, environmental health, spiritual health, social health, and physical health. Conclusion: The following was obtained from review of studies: since lifestyle is among important, changeable, and influential factors in fertility, success of these methods can be greatly helped through assessment of lifestyle patterns of infertile couples, and design and implementation of healthy lifestyle counseling programs, before and during implementing assisted fertility techniques. PMID:26156898
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How task demands influence scanpath similarity in a sequential number-search task.
Dewhurst, Richard; Foulsham, Tom; Jarodzka, Halszka; Johansson, Roger; Holmqvist, Kenneth; Nyström, Marcus
2018-06-07
More and more researchers are considering the omnibus eye movement sequence-the scanpath-in their studies of visual and cognitive processing (e.g. Hayes, Petrov, & Sederberg, 2011; Madsen, Larson, Loschky, & Rebello, 2012; Ni et al., 2011; von der Malsburg & Vasishth, 2011). However, it remains unclear how recent methods for comparing scanpaths perform in experiments producing variable scanpaths, and whether these methods supplement more traditional analyses of individual oculomotor statistics. We address this problem for MultiMatch (Jarodzka et al., 2010; Dewhurst et al., 2012), evaluating its performance with a visual search-like task in which participants must fixate a series of target numbers in a prescribed order. This task should produce predictable sequences of fixations and thus provide a testing ground for scanpath measures. Task difficulty was manipulated by making the targets more or less visible through changes in font and the presence of distractors or visual noise. These changes in task demands led to slower search and more fixations. Importantly, they also resulted in a reduction in the between-subjects scanpath similarity, demonstrating that participants' gaze patterns became more heterogenous in terms of saccade length and angle, and fixation position. This implies a divergent strategy or random component to eye-movement behaviour which increases as the task becomes more difficult. Interestingly, the duration of fixations along aligned vectors showed the opposite pattern, becoming more similar between observers in 2 of the 3 difficulty manipulations. This provides important information for vision scientists who may wish to use scanpath metrics to quantify variations in gaze across a spectrum of perceptual and cognitive tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Sex-biased phoretic mite load on two seaweed flies: Coelopa frigida and Coelopa pilipes.
Gilburn, Andre S; Stewart, Katie M; Edward, Dominic A
2009-12-01
Two hypotheses explain male-biased parasitism. Physiological costs of male sexually selected characteristics can reduce immunocompetence. Alternatively, ecological differences could generate male-biased parasitism. One method of comparing the importance of the two theories is to investigate patterns of phoresy, which are only likely to be generated by ecological rather than immunological differences between the sexes. Here we studied the pattern of phoresy of the mite, Thinoseius fucicola, on two species of seaweed fly hosts, Coelopa frigida and Coelopa pilipes. We found a highly male-biased pattern of phoresy of T. fucicola on both species. These are the first reported instances of sex-biased phoresy in a solely phoretic parasite. We also show the first two cases of size-biased phoresy. We suggest that ecological factors, particularly, male mate searching, generated male biased patterns of phoresy. We highlight the potential importance of studies of phoresy in determining the relative roles of the immunocompetence and ecological theories in generating male-biased parasitism. We suggest that more studies of patterns of phoresy are carried out to allow detailed comparisons with patterns of parasitism.
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Guarato, Francesco; Windmill, James; Gachagan, Anthony; Harvey, Gerald
2013-06-01
Target localization can be accomplished through an ultrasonic sonar system equipped with an emitter and two receivers. Time of flight of the sonar echoes allows the calculation of the distance of the target. The orientation can be estimated from knowledge of the beam pattern of the receivers and the ratio, in the frequency domain, between the emitted and the received signals after compensation for distance effects and air absorption. The localization method is described and, as its performance strongly depends on the beam pattern, the search of the most appropriate sonar receiver in order to ensure the highest accuracy of target orientation estimations is developed in this paper. The structure designs considered are inspired by the ear shapes of some bat species. Parameters like flare rate, truncation angle, and tragus are considered in the design of the receiver structures. Simulations of the localization method allow us to state which combination of those parameters could provide the best real world implementation. Simulation results show the estimates of target orientations are, in the worst case, 2° with SNR = 50 dB using the receiver structure chosen for a potential practical implementation of a sonar system.
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Lee, Jeongmi; Geng, Joy J
2017-02-01
The efficiency of finding an object in a crowded environment depends largely on the similarity of nontargets to the search target. Models of attention theorize that the similarity is determined by representations stored within an "attentional template" held in working memory. However, the degree to which the contents of the attentional template are individually unique and where those idiosyncratic representations are encoded in the brain are unknown. We investigated this problem using representational similarity analysis of human fMRI data to measure the common and idiosyncratic representations of famous face morphs during an identity categorization task; data from the categorization task were then used to predict performance on a separate identity search task. We hypothesized that the idiosyncratic categorical representations of the continuous face morphs would predict their distractability when searching for each target identity. The results identified that patterns of activation in the lateral prefrontal cortex (LPFC) as well as in face-selective areas in the ventral temporal cortex were highly correlated with the patterns of behavioral categorization of face morphs and search performance that were common across subjects. However, the individually unique components of the categorization behavior were reliably decoded only in right LPFC. Moreover, the neural pattern in right LPFC successfully predicted idiosyncratic variability in search performance, such that reaction times were longer when distractors had a higher probability of being categorized as the target identity. These results suggest that the prefrontal cortex encodes individually unique components of categorical representations that are also present in attentional templates for target search. Everyone's perception of the world is uniquely shaped by personal experiences and preferences. Using functional MRI, we show that individual differences in the categorization of face morphs between two identities could be decoded from the prefrontal cortex and the ventral temporal cortex. Moreover, the individually unique representations in prefrontal cortex predicted idiosyncratic variability in attentional performance when looking for each identity in the "crowd" of another morphed face in a separate search task. Our results reveal that the representation of task-related information in prefrontal cortex is individually unique and preserved across categorization and search performance. This demonstrates the possibility of predicting individual behaviors across tasks with patterns of brain activity. Copyright © 2017 the authors 0270-6474/17/371257-12$15.00/0.
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The web server of IBM's Bioinformatics and Pattern Discovery group.
Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo
2003-07-01
We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.
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The web server of IBM's Bioinformatics and Pattern Discovery group
Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo
2003-01-01
We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/. PMID:12824385
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Bone marrow necrosis related to paracoccidioidomycosis: the first eight cases identified at autopsy
Resende, Lucilene S R; Mendes, Rinaldo P; Bacchi, Maura M; Marques, Sílvio A; Barraviera, Benedito; Souza, Lenice R; Meira, Domingos A; Niéro-Melo, Lígia
2009-01-01
Aims: To report the first eight bone marrow necrosis (BMN) cases related to paracoccidioidomycosis (PCM) from patient autopsies with well-documented bone marrow (BM) histology and cytology. Methods and results: A retrospective evaluation was performed on BM specimens from eight autopsied patients from Botucatu University Hospital with PCM-related BMN. Relevant BMN literature was searched and analysed. Conclusions: All eight patients had acute PCM. Six had histological only (biopsies) and two cytological only (smears) specimens. Five biopsy specimens revealed severe and one mild coagulation patterned necrotic areas. Five had osteonecrosis. The cytological specimens also showed typical BMN patterns. Paracoccidioides brasiliensis yeast forms were visible within necrotic areas in all cases. PMID:19309401
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Mortality Patterns in Patients with Multiple Trauma: A Systematic Review of Autopsy Studies
Pfeifer, Roman; Teuben, Michel; Andruszkow, Hagen; Barkatali, Bilal M.; Pape, Hans-Christoph
2016-01-01
Purpose A high percentage (50%-60%) of trauma patients die due to their injuries prior to arrival at the hospital. Studies on preclinical mortality including post-mortem examinations are rare. In this review, we summarized the literature focusing on clinical and preclinical mortality and studies included post-mortem examinations. Methods A literature search was conducted using PubMed/Medline database for relevant medical literature in English or German language published within the last four decades (1980–2015). The following MeSH search terms were used in different combinations: “multiple trauma”, “epidemiology”, “mortality “, “cause of death”, and “autopsy”. References from available studies were searched as well. Results Marked differences in demographic parameters and injury severity between studies were identified. Moreover, the incidence of penetrating injuries has shown a wide range (between 4% and 38%). Both unimodal and bimodal concepts of trauma mortality have been favored. Studies have shown a wide variation in time intervals used to analyze the distribution of death. Thus, it is difficult to say which distribution is correct. Conclusions We have identified variable results indicating bimodal or unimodal death distribution. Further more stundardized studies in this field are needed. We would like to encourage investigators to choose the inclusion criteria more critically and to consider factors affecting the pattern of mortality. PMID:26871937
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Context-Sensitive Grammar Transform: Compression and Pattern Matching
NASA Astrophysics Data System (ADS)
Maruyama, Shirou; Tanaka, Youhei; Sakamoto, Hiroshi; Takeda, Masayuki
A framework of context-sensitive grammar transform for speeding-up compressed pattern matching (CPM) is proposed. A greedy compression algorithm with the transform model is presented as well as a Knuth-Morris-Pratt (KMP)-type compressed pattern matching algorithm. The compression ratio is a match for gzip and Re-Pair, and the search speed of our CPM algorithm is almost twice faster than the KMP-type CPM algorithm on Byte-Pair-Encoding by Shibata et al.[18], and in the case of short patterns, faster than the Boyer-Moore-Horspool algorithm with the stopper encoding by Rautio et al.[14], which is regarded as one of the best combinations that allows a practically fast search.
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Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir
2004-01-01
Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586
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ERIC Educational Resources Information Center
Georgas, Helen
2014-01-01
This study examines the information-seeking behavior of undergraduate students within a research context. Student searches were recorded while the participants used Google and a library (federated) search tool to find sources (one book, two articles, and one other source of their choosing) for a selected topic. The undergraduates in this study…
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Pattern similarity study of functional sites in protein sequences: lysozymes and cystatins
Nakai, Shuryo; Li-Chan, Eunice CY; Dou, Jinglie
2005-01-01
Background Although it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families. Results Hydrophobicity and β-turn propensity of reference segments with 3–7 residues were used for the homology similarity search (HSS) for active sites. Hydrogen bonding was used as the side-chain property for searching the binding sites of lysozymes. The profiles of similarity constants and average values of these parameters as functions of their positions in the sequences could identify both active and substrate binding sites of the lysozyme of Streptomyces coelicolor, which has been reported as a new fold enzyme (Cellosyl). The same approach was successfully applied to cystatins, especially for postulating the mechanisms of amyloidosis of human cystatin C as well as human lysozyme. Conclusion Pattern similarity and average index values of structure-related properties of side chains in short segments of three residues or longer were, for the first time, successfully applied for predicting functional sites in sequences. This new approach may be applicable to studying functional sites in un-annotated proteins, for which complete 3D structures are not yet available. PMID:15904486
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Shemilt, Ian; Mugford, Miranda; Drummond, Michael; Eisenstein, Eric; Mallender, Jacqueline; McDaid, David; Vale, Luke; Walker, Damian
2006-11-15
Provision of evidence on costs alongside evidence on the effects of interventions can enhance the relevance of systematic reviews to decision-making. However, patterns of use of economics methods alongside systematic review remain unclear. Reviews of evidence on the effects of interventions are published by both the Cochrane and Campbell Collaborations. Although it is not a requirement that Cochrane or Campbell Reviews should consider economic aspects of interventions, many do. This study aims to explore and describe approaches to incorporating economics methods in a selection of Cochrane systematic reviews in the area of health promotion and public health, to help inform development of methodological guidance on economics for reviewers. The Cochrane Database of Systematic Reviews was searched using a search strategy for potential economic evaluation studies. We included current Cochrane reviews and review protocols retrieved using the search that are also identified as relevant to health promotion or public health topics. A reviewer extracted data which describe the economics components of included reviews. Extracted data were summarised in tables and analysed qualitatively. Twenty-one completed Cochrane reviews and seven review protocols met inclusion criteria. None incorporate formal economic evaluation methods. Ten completed reviews explicitly aim to incorporate economics studies and data. There is a lack of transparent reporting of methods underpinning the incorporation of economics studies and data. Some reviews are likely to exclude useful economics studies and data due to a failure to incorporate search strategies tailored to the retrieval of such data or use of key specialist databases, and application of inclusion criteria designed for effectiveness studies. There is a need for consistency and transparency in the reporting and conduct of the economics components of Cochrane reviews, as well as regular dialogue between Cochrane reviewers and economists to develop increased capacity for economic analyses alongside such reviews. Use of applicable economics methods in Cochrane reviews can help provide the international context within which economics data can be interpreted and assessed as a preliminary to full economic evaluation.
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A data mining method to facilitate SAR transfer.
Wassermann, Anne Mai; Bajorath, Jürgen
2011-08-22
A challenging practical problem in medicinal chemistry is the transfer of SAR information from one chemical series to another. Currently, there are no computational methods available to rationalize or support this process. Herein, we present a data mining approach that enables the identification of alternative analog series with different core structures, corresponding substitution patterns, and comparable potency progression. Scaffolds can be exchanged between these series and new analogs suggested that incorporate preferred R-groups. The methodology can be applied to search for alternative analog series if one series is known or, alternatively, to systematically assess SAR transfer potential in compound databases.
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LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics
NASA Astrophysics Data System (ADS)
Moura, Pedro; Laber, Eduardo; Lopes, Hélio; Mesejo, Daniel; Pavanelli, Lucas; Jardim, João; Thiesen, Francisco; Pujol, Gabriel
2017-10-01
Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.
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A Method for Search Engine Selection using Thesaurus for Selective Meta-Search Engine
NASA Astrophysics Data System (ADS)
Goto, Shoji; Ozono, Tadachika; Shintani, Toramatsu
In this paper, we propose a new method for selecting search engines on WWW for selective meta-search engine. In selective meta-search engine, a method is needed that would enable selecting appropriate search engines for users' queries. Most existing methods use statistical data such as document frequency. These methods may select inappropriate search engines if a query contains polysemous words. In this paper, we describe an search engine selection method based on thesaurus. In our method, a thesaurus is constructed from documents in a search engine and is used as a source description of the search engine. The form of a particular thesaurus depends on the documents used for its construction. Our method enables search engine selection by considering relationship between terms and overcomes the problems caused by polysemous words. Further, our method does not have a centralized broker maintaining data, such as document frequency for all search engines. As a result, it is easy to add a new search engine, and meta-search engines become more scalable with our method compared to other existing methods.
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Dietary Patterns and Overweight/Obesity: A Review Article
MU, Min; XU, Li-Fa; HU, Dong; WU, Jing; BAI, Ming-Jie
2017-01-01
Background: Dietary patterns analysis may provide insights into the influence of overall diet on overweight/obesity. In the past two decades, the relation between dietary patterns and overweight/obesity has been a research focus and a number of results were reported in the research field. Methods: An electronic literature search was conducted in PubMed and Web of Science, to identify human studies published by Mar 2015 and written in English. The following keywords or phrases were involved: dietary patterns, dietary pattern, factor analysis, principal component analysis, diet, obesity, adiposity, overweight and BMI. All the studies were retrieved and prudent/healthy (n=17) and western/unhealthy (n=18) dietary patterns were identified. Results: When compared with the lowest categories of a prudent/healthy dietary pattern, a reduced overweight/obesity risk was shown in the highest (OR=0.64; 95% CI: 0.52, 0.78; P<0.0001). While there was an increased overweight/obesity risk in the highest when compared with the lowest categories of a western/unhealthy dietary pattern (OR=1.65; 95% CI: 1.45, 1.87; P<0.0001). Conclusion: A prudent/healthy dietary pattern and limit intake of western/unhealthy dietary pattern should be followed, which helps to keep a healthy body mass. PMID:28845396
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Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers.
Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric
2009-10-12
The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*(pop); and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. For simulated data with outlier patterns, Tango's MEET, Moran's I and I*(pop) had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*(pop) (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*(pop) perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan.
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Evaluation of camouflage pattern performance of textiles by human observers and CAMAELEON
NASA Astrophysics Data System (ADS)
Heinrich, Daniela H.; Selj, Gorm K.
2017-10-01
Military textiles with camouflage pattern are an important part of the protection measures for soldiers. Military operational environments differ a lot depending on climate and vegetation. This requires very different camouflage pattern to achieve good protection. To find the best performing pattern for given environments we have in earlier evaluations mainly applied observer trials as evaluation method. In these camouflage evaluation test human observers were asked to search for targets (in natural settings) presented on a high resolution PC screen, and the corresponding detection times were recorded. Another possibility is to base the evaluation on simulations. CAMAELEON is a licensed tool that ranks camouflaged targets by their similarity with local backgrounds. The similarity is estimated through the parameters local contrast, orientation of structures in the pattern and spatial frequency, by mimicking the response and signal processing in the visual cortex of the human eye. Simulations have a number of advantages over observer trials, for example, that they are more flexible, cheaper, and faster. Applying these two methods to the same images of camouflaged targets we found that CAMAELEON simulation results didn't match observer trial results for targets with disruptive patterns. This finding now calls for follow up studies in order to learn more about the advantages and pitfalls of CAMAELEON. During recent observer trials we studied new camouflage patterns and the effect of additional equipment, such as combat vests. In this paper we will present the results from a study comparing evaluation results of human based observer trials and CAMAELEON.
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Hyun, Dai-Kyung; Ryu, Seung-Jin; Lee, Hae-Yeoun; Lee, Heung-Kyu
2013-01-01
In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN). We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB (Red, Green, Blue)/infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method. PMID:24051524
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Scavengers on the move: behavioural changes in foraging search patterns during the annual cycle.
López-López, Pascual; Benavent-Corai, José; García-Ripollés, Clara; Urios, Vicente
2013-01-01
Optimal foraging theory predicts that animals will tend to maximize foraging success by optimizing search strategies. However, how organisms detect sparsely distributed food resources remains an open question. When targets are sparse and unpredictably distributed, a Lévy strategy should maximize foraging success. By contrast, when resources are abundant and regularly distributed, simple brownian random movement should be sufficient. Although very different groups of organisms exhibit Lévy motion, the shift from a Lévy to a brownian search strategy has been suggested to depend on internal and external factors such as sex, prey density, or environmental context. However, animal response at the individual level has received little attention. We used GPS satellite-telemetry data of Egyptian vultures Neophron percnopterus to examine movement patterns at the individual level during consecutive years, with particular interest in the variations in foraging search patterns during the different periods of the annual cycle (i.e. breeding vs. non-breeding). Our results show that vultures followed a brownian search strategy in their wintering sojourn in Africa, whereas they exhibited a more complex foraging search pattern at breeding grounds in Europe, including Lévy motion. Interestingly, our results showed that individuals shifted between search strategies within the same period of the annual cycle in successive years. Results could be primarily explained by the different environmental conditions in which foraging activities occur. However, the high degree of behavioural flexibility exhibited during the breeding period in contrast to the non-breeding period is challenging, suggesting that not only environmental conditions explain individuals' behaviour but also individuals' cognitive abilities (e.g., memory effects) could play an important role. Our results support the growing awareness about the role of behavioural flexibility at the individual level, adding new empirical evidence about how animals in general, and particularly scavengers, solve the problem of efficiently finding food resources.
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Search query data to monitor interest in behavior change: application for public health.
Carr, Lucas J; Dunsiger, Shira I
2012-01-01
There is a need for effective interventions and policies that target the leading preventable causes of death in the U.S. (e.g., smoking, overweight/obesity, physical inactivity). Such efforts could be aided by the use of publicly available, real-time search query data that illustrate times and locations of high and low public interest in behaviors related to preventable causes of death. This study explored patterns of search query activity for the terms 'weight', 'diet', 'fitness', and 'smoking' using Google Insights for Search. Search activity for 'weight', 'diet', 'fitness', and 'smoking' conducted within the United States via Google between January 4(th), 2004 (first date data was available) and November 28(th), 2011 (date of data download and analysis) were analyzed. Using a generalized linear model, we explored the effects of time (month) on mean relative search volume for all four terms. Models suggest a significant effect of month on mean search volume for all four terms. Search activity for all four terms was highest in January with observable declines throughout the remainder of the year. These findings demonstrate discernable temporal patterns of search activity for four areas of behavior change. These findings could be used to inform the timing, location and messaging of interventions, campaigns and policies targeting these behaviors.
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Time Patterns in Remote OPAC Use.
ERIC Educational Resources Information Center
Lucas, Thomas A.
1993-01-01
Describes a transaction log analysis of the New York Public Library research libraries' OPAC (online public access catalog). Much of the remote searching occurred when the libraries were closed and was more evenly distributed than internal searching, demonstrating that remote searching could expand access and reduce peak system loads. (Contains…
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Fourier spatial frequency analysis for image classification: training the training set
NASA Astrophysics Data System (ADS)
Johnson, Timothy H.; Lhamo, Yigah; Shi, Lingyan; Alfano, Robert R.; Russell, Stewart
2016-04-01
The Directional Fourier Spatial Frequencies (DFSF) of a 2D image can identify similarity in spatial patterns within groups of related images. A Support Vector Machine (SVM) can then be used to classify images if the inter-image variance of the FSF in the training set is bounded. However, if variation in FSF increases with training set size, accuracy may decrease as the size of the training set increases. This calls for a method to identify a set of training images from among the originals that can form a vector basis for the entire class. Applying the Cauchy product method we extract the DFSF spectrum from radiographs of osteoporotic bone, and use it as a matched filter set to eliminate noise and image specific frequencies, and demonstrate that selection of a subset of superclassifiers from within a set of training images improves SVM accuracy. Central to this challenge is that the size of the search space can become computationally prohibitive for all but the smallest training sets. We are investigating methods to reduce the search space to identify an optimal subset of basis training images.
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Caldas, José; Gehlenborg, Nils; Kettunen, Eeva; Faisal, Ali; Rönty, Mikko; Nicholson, Andrew G; Knuutila, Sakari; Brazma, Alvis; Kaski, Samuel
2012-01-15
Genome-wide measurement of transcript levels is an ubiquitous tool in biomedical research. As experimental data continues to be deposited in public databases, it is becoming important to develop search engines that enable the retrieval of relevant studies given a query study. While retrieval systems based on meta-data already exist, data-driven approaches that retrieve studies based on similarities in the expression data itself have a greater potential of uncovering novel biological insights. We propose an information retrieval method based on differential expression. Our method deals with arbitrary experimental designs and performs competitively with alternative approaches, while making the search results interpretable in terms of differential expression patterns. We show that our model yields meaningful connections between biological conditions from different studies. Finally, we validate a previously unknown connection between malignant pleural mesothelioma and SIM2s suggested by our method, via real-time polymerase chain reaction in an independent set of mesothelioma samples. Supplementary data and source code are available from http://www.ebi.ac.uk/fg/research/rex.
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High activity and Levy searches: jellyfish can search the water column like fish.
Hays, Graeme C; Bastian, Thomas; Doyle, Thomas K; Fossette, Sabrina; Gleiss, Adrian C; Gravenor, Michael B; Hobson, Victoria J; Humphries, Nicolas E; Lilley, Martin K S; Pade, Nicolas G; Sims, David W
2012-02-07
Over-fishing may lead to a decrease in fish abundance and a proliferation of jellyfish. Active movements and prey search might be thought to provide a competitive advantage for fish, but here we use data-loggers to show that the frequently occurring coastal jellyfish (Rhizostoma octopus) does not simply passively drift to encounter prey. Jellyfish (327 days of data from 25 jellyfish with depth collected every 1 min) showed very dynamic vertical movements, with their integrated vertical movement averaging 619.2 m d(-1), more than 60 times the water depth where they were tagged. The majority of movement patterns were best approximated by exponential models describing normal random walks. However, jellyfish also showed switching behaviour from exponential patterns to patterns best fitted by a truncated Lévy distribution with exponents (mean μ=1.96, range 1.2-2.9) close to the theoretical optimum for searching for sparse prey (μopt≈2.0). Complex movements in these 'simple' animals may help jellyfish to compete effectively with fish for plankton prey, which may enhance their ability to increase in dominance in perturbed ocean systems.
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Phelan, Nigel; Davy, Shane; O'Keeffe, Gerard W; Barry, Denis S
2017-03-01
The role of e-learning platforms in anatomy education continues to expand as self-directed learning is promoted in higher education. Although a wide range of e-learning resources are available, determining student use of non-academic internet resources requires novel approaches. One such approach that may be useful is the Google Trends © web application. To determine the feasibility of Google Trends to gain insights into anatomy-related online searches, Google Trends data from the United States from January 2010 to December 2015 were analyzed. Data collected were based on the recurrence of keywords related to head and neck anatomy generated from the American Association of Clinical Anatomists and the Anatomical Society suggested anatomy syllabi. Relative search volume (RSV) data were analyzed for seasonal periodicity and their overall temporal trends. Following exclusions due to insufficient search volume data, 29 out of 36 search terms were analyzed. Significant seasonal patterns occurred in 23 search terms. Thirty-nine seasonal peaks were identified, mainly in October and April, coinciding with teaching periods in anatomy curricula. A positive correlation of RSV with time over the 6-year study period occurred in 25 out of 29 search terms. These data demonstrate how Google Trends may offer insights into the nature and timing of online search patterns of anatomical syllabi and may potentially inform the development and timing of targeted online supports to ensure that students of anatomy have the opportunity to engage with online content that is both accurate and fit for purpose. Anat Sci Educ 10: 152-159. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.
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Coupling artificial intelligence and numerical computation for engineering design (Invited paper)
NASA Astrophysics Data System (ADS)
Tong, S. S.
1986-01-01
The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.
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Stellefson, Michael; Hanik, Bruce; Chaney, J Don; Tennant, Bethany
2012-04-27
The current "Millennial Generation" of college students majoring in the health professions has unprecedented access to the Internet. Although some research has been initiated among medical professionals to investigate the cognitive basis for health information searches on the Internet, little is known about Internet search practices among health and medical professional students. To systematically identify health professional college student perspectives of personal eHealth search practices. Q methodology was used to examine subjective perspectives regarding personal eHealth search practices among allied health students majoring in a health education degree program. Thirteen (n = 13) undergraduate students were interviewed about their attitudes and experiences conducting eHealth searches. From the interviews, 36 statements were used in a structured ranking task to identify clusters and determine which specific perceptions of eHealth search practices discriminated students into different groups. Scores on an objective measure of eHealth literacy were used to help categorize participant perspectives. Q-technique factor analysis of the rankings identified 3 clusters of respondents with differing views on eHealth searches that generally coincided with participants' objective eHealth literacy scores. The proficient resourceful students (pattern/structure coefficient range 0.56-0.80) described themselves as using multiple resources to obtain eHealth information, as opposed to simply relying on Internet search engines. The intermediate reluctant students (pattern/structure coefficient range 0.75-0.90) reported engaging only Internet search engines to locate eHealth information, citing undeveloped evaluation skills when considering sources of information located on the Internet. Both groups of advanced students reported not knowing how to use Boolean operators to conduct Internet health searches. The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information. Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task. Subjective perspectives of eHealth search practices differed among students possessing different levels of eHealth literacy. These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet.
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Block Architecture Problem with Depth First Search Solution and Its Application
NASA Astrophysics Data System (ADS)
Rahim, Robbi; Abdullah, Dahlan; Simarmata, Janner; Pranolo, Andri; Saleh Ahmar, Ansari; Hidayat, Rahmat; Napitupulu, Darmawan; Nurdiyanto, Heri; Febriadi, Bayu; Zamzami, Z.
2018-01-01
Searching is a common process performed by many computer users, Raita algorithm is one algorithm that can be used to match and find information in accordance with the patterns entered. Raita algorithm applied to the file search application using java programming language and the results obtained from the testing process of the file search quickly and with accurate results and support many data types.
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Searching Process with Raita Algorithm and its Application
NASA Astrophysics Data System (ADS)
Rahim, Robbi; Saleh Ahmar, Ansari; Abdullah, Dahlan; Hartama, Dedy; Napitupulu, Darmawan; Putera Utama Siahaan, Andysah; Hasan Siregar, Muhammad Noor; Nasution, Nurliana; Sundari, Siti; Sriadhi, S.
2018-04-01
Searching is a common process performed by many computer users, Raita algorithm is one algorithm that can be used to match and find information in accordance with the patterns entered. Raita algorithm applied to the file search application using java programming language and the results obtained from the testing process of the file search quickly and with accurate results and support many data types.
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Using mixed-initiative human-robot interaction to bound performance in a search task
DOE Office of Scientific and Technical Information (OSTI.GOV)
Curtis W. Nielsen; Douglas A. Few; Devin S. Athey
2008-12-01
Mobile robots are increasingly used in dangerous domains, because they can keep humans out of harm’s way. Despite their advantages in hazardous environments, their general acceptance in other less dangerous domains has not been apparent and, even in dangerous environments, robots are often viewed as a “last-possible choice.” In order to increase the utility and acceptance of robots in hazardous domains researchers at the Idaho National Laboratory have both developed and tested novel mixed-initiative solutions that support the human-robot interactions. In a recent “dirty-bomb” experiment, participants exhibited different search strategies making it difficult to determine any performance benefits. This papermore » presents a method for categorizing the search patterns and shows that the mixed-initiative solution decreased the time to complete the task and decreased the performance spread between participants independent of prior training and of individual strategies used to accomplish the task.« less
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Implementing the Army NetCentric Data Strategy in a ServiceOriented Environment
2009-04-23
D a t a D i s c o v e r y Data Retrieval Data Subscription Data Discovery D a t a A c c e s s Artifact Discovery Federated Search Data Search Data...define common interfaces to search and retrieve data across the enterprise. • Patterns • Search • Status • Receive – Services • Federated Search • Artifact
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NASA Astrophysics Data System (ADS)
Sims, David W.
2015-09-01
The seminal papers by Viswanathan and colleagues in the late 1990s [1,2] proposed not only that scale-free, superdiffusive Lévy walks can describe the free-ranging movement patterns observed in animals such as the albatross [1], but that the Lévy walk was optimal for searching for sparsely and randomly distributed resource targets [2]. This distinct advantage, now shown to be present over a much broader set of conditions than originally theorised [3], implied that the Lévy walk is a search strategy that should be found very widely in organisms [4]. In the years since there have been several influential empirical studies showing that Lévy walks can indeed be detected in the movement patterns of a very broad range of taxa, from jellyfish, insects, fish, reptiles, seabirds, humans [5-10], and even in the fossilised trails of extinct invertebrates [11]. The broad optimality and apparent deep evolutionary origin of movement (search) patterns that are well approximated by Lévy walks led to the development of the Lévy flight foraging (LFF) hypothesis [12], which states that "since Lévy flights and walks can optimize search efficiencies, therefore natural selection should have led to adaptations for Lévy flight foraging".
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Fast parallel tandem mass spectral library searching using GPU hardware acceleration
Baumgardner, Lydia Ashleigh; Shanmugam, Avinash Kumar; Lam, Henry; Eng, Jimmy K.; Martin, Daniel B.
2011-01-01
Mass spectrometry-based proteomics is a maturing discipline of biologic research that is experiencing substantial growth. Instrumentation has steadily improved over time with the advent of faster and more sensitive instruments collecting ever larger data files. Consequently, the computational process of matching a peptide fragmentation pattern to its sequence, traditionally accomplished by sequence database searching and more recently also by spectral library searching, has become a bottleneck in many mass spectrometry experiments. In both of these methods, the main rate limiting step is the comparison of an acquired spectrum with all potential matches from a spectral library or sequence database. This is a highly parallelizable process because the core computational element can be represented as a simple but arithmetically intense multiplication of two vectors. In this paper we present a proof of concept project taking advantage of the massively parallel computing available on graphics processing units (GPUs) to distribute and accelerate the process of spectral assignment using spectral library searching. This program, which we have named FastPaSS (for Fast Parallelized Spectral Searching) is implemented in CUDA (Compute Unified Device Architecture) from NVIDIA which allows direct access to the processors in an NVIDIA GPU. Our efforts demonstrate the feasibility of GPU computing for spectral assignment, through implementation of the validated spectral searching algorithm SpectraST in the CUDA environment. PMID:21545112
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Hybrid Genetic Algorithm - Local Search Method for Ground-Water Management
NASA Astrophysics Data System (ADS)
Chiu, Y.; Nishikawa, T.; Martin, P.
2008-12-01
Ground-water management problems commonly are formulated as a mixed-integer, non-linear programming problem (MINLP). Relying only on conventional gradient-search methods to solve the management problem is computationally fast; however, the methods may become trapped in a local optimum. Global-optimization schemes can identify the global optimum, but the convergence is very slow when the optimal solution approaches the global optimum. In this study, we developed a hybrid optimization scheme, which includes a genetic algorithm and a gradient-search method, to solve the MINLP. The genetic algorithm identifies a near- optimal solution, and the gradient search uses the near optimum to identify the global optimum. Our methodology is applied to a conjunctive-use project in the Warren ground-water basin, California. Hi- Desert Water District (HDWD), the primary water-manager in the basin, plans to construct a wastewater treatment plant to reduce future septic-tank effluent from reaching the ground-water system. The treated wastewater instead will recharge the ground-water basin via percolation ponds as part of a larger conjunctive-use strategy, subject to State regulations (e.g. minimum distances and travel times). HDWD wishes to identify the least-cost conjunctive-use strategies that control ground-water levels, meet regulations, and identify new production-well locations. As formulated, the MINLP objective is to minimize water-delivery costs subject to constraints including pump capacities, available recharge water, water-supply demand, water-level constraints, and potential new-well locations. The methodology was demonstrated by an enumerative search of the entire feasible solution and comparing the optimum solution with results from the branch-and-bound algorithm. The results also indicate that the hybrid method identifies the global optimum within an affordable computation time. Sensitivity analyses, which include testing different recharge-rate scenarios, pond layouts, and water-supply constraints, indicate that the number of new wells is insensitive to water-supply constraints; however, pumping rates and patterns of the existing wells are sensitive. The locations of new wells are mildly sensitive to the pond layout.
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Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S; Sinha, Saurabh
2011-12-01
Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, 'enhancers'), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for 'motif-blind' CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to 'supervise' the search. We propose a new statistical method, based on 'Interpolated Markov Models', for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. © The Author(s) 2011. Published by Oxford University Press.
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Trust regions in Kriging-based optimization with expected improvement
NASA Astrophysics Data System (ADS)
Regis, Rommel G.
2016-06-01
The Kriging-based Efficient Global Optimization (EGO) method works well on many expensive black-box optimization problems. However, it does not seem to perform well on problems with steep and narrow global minimum basins and on high-dimensional problems. This article develops a new Kriging-based optimization method called TRIKE (Trust Region Implementation in Kriging-based optimization with Expected improvement) that implements a trust-region-like approach where each iterate is obtained by maximizing an Expected Improvement (EI) function within some trust region. This trust region is adjusted depending on the ratio of the actual improvement to the EI. This article also develops the Kriging-based CYCLONE (CYClic Local search in OptimizatioN using Expected improvement) method that uses a cyclic pattern to determine the search regions where the EI is maximized. TRIKE and CYCLONE are compared with EGO on 28 test problems with up to 32 dimensions and on a 36-dimensional groundwater bioremediation application in appendices supplied as an online supplement available at http://dx.doi.org/10.1080/0305215X.2015.1082350. The results show that both algorithms yield substantial improvements over EGO and they are competitive with a radial basis function method.
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NASA Astrophysics Data System (ADS)
Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi
2018-04-01
Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.
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NASA Astrophysics Data System (ADS)
Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Anzalone, A.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Bäcker, T.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Bäuml, J.; Beatty, J. J.; Becker, B. R.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Burton, R. E.; Caballero-Mora, K. S.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chou, A.; Chudoba, J.; Clay, R. W.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; De Donato, C.; de Jong, S. J.; De La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; Decerprit, G.; del Peral, L.; del Río, M.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Fajardo Tapia, I.; Falcke, H.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Ferrero, A.; Fick, B.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; García Gámez, D.; Garcia-Pinto, D.; Gascon, A.; Gemmeke, H.; Gesterling, K.; Ghia, P. L.; Giaccari, U.; Giller, M.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gonçalves, P.; Gonzalez, D.; Gonzalez, J. G.; Gookin, B.; Góra, D.; Gorgi, A.; Gouffon, P.; Gozzini, S. R.; Grashorn, E.; Grebe, S.; Griffith, N.; Grigat, M.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Guzman, A.; Hague, J. D.; Hansen, P.; Harari, D.; Harmsma, S.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horneffer, A.; Horvath, P.; Hrabovský, M.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuehn, F.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; Lautridou, P.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Lemiere, A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Meurer, C.; Mićanović, S.; Micheletti, M. I.; Miller, W.; Miramonti, L.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Morris, C.; Mostafá, M.; Moura, C. A.; Mueller, S.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niemietz, L.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Nyklicek, M.; Oehlschläger, J.; Olinto, A.; Oliva, P.; Olmos-Gilbaja, V. M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Parsons, R. D.; Pastor, S.; Paul, T.; Pech, M.; Pękala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrinca, P.; Petrolini, A.; Petrov, Y.; Petrovic, J.; Pfendner, C.; Phan, N.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Ponce, V. H.; Pontz, M.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Robledo, C.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Cabo, I.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Schmidt, F.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F.; Schulte, S.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Silva Lopez, H. H.; Śacute; Smiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Strazzeri, E.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tamashiro, A.; Tapia, A.; Tartare, M.; Taşąu, O.; Tavera Ruiz, C. G.; Tcaciuc, R.; Tegolo, D.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tiwari, D. K.; Tkaczyk, W.; Todero Peixoto, C. J.; Tomé, B.; Tonachini, A.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van den Berg, A. M.; Varela, E.; Vargas Cárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Warner, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Westerhoff, S.; Whelan, B. J.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Winnick, M. G.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zimbres Silva, M.; Ziolkowski, M.
2011-11-01
We present a comprehensive study of the influence of the geomagnetic field on the energy estimation of extensive air showers with a zenith angle smaller than 60°, detected at the Pierre Auger Observatory. The geomagnetic field induces an azimuthal modulation of the estimated energy of cosmic rays up to the ~ 2% level at large zenith angles. We present a method to account for this modulation of the reconstructed energy. We analyse the effect of the modulation on large scale anisotropy searches in the arrival direction distributions of cosmic rays. At a given energy, the geomagnetic effect is shown to induce a pseudo-dipolar pattern at the percent level in the declination distribution that needs to be accounted for.
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Barz Leahy, Allison; Li, Yimei; Schapira, Marilyn M; Bailey, L Charles; Merchant, Raina M
2018-01-01
Background In the United States, cancer is common, with high morbidity and mortality; cancer incidence varies between states. Online searches reflect public awareness, which could be driven by the underlying regional cancer epidemiology. Objective The objective of our study was to characterize the relationship between cancer incidence and online Google search volumes in the United States for 6 common cancers. A secondary objective was to evaluate the association of search activity with cancer-related public events and celebrity news coverage. Methods We performed a population-based, retrospective study of state-level cancer incidence from 2004 through 2013 reported by the Centers for Disease Control and Prevention for breast, prostate, colon, lung, and uterine cancers and leukemia compared to Google Trends (GT) relative search volume (RSV), a metric designed by Google to allow interest in search topics to be compared between regions. Participants included persons in the United States who searched for cancer terms on Google. The primary measures were the correlation between annual state-level cancer incidence and RSV as determined by Spearman correlation and linear regression with RSV and year as independent variables and cancer incidence as the dependent variable. Temporal associations between search activity and events raising public awareness such as cancer awareness months and cancer-related celebrity news were described. Results At the state level, RSV was significantly correlated to incidence for breast (r=.18, P=.001), prostate (r=–.27, P<.001), lung (r=.33, P<.001), and uterine cancers (r=.39, P<.001) and leukemia (r=.13, P=.003) but not colon cancer (r=–.02, P=.66). After adjusting for time, state-level RSV was positively correlated to cancer incidence for all cancers: breast (P<.001, 95% CI 0.06 to 0.19), prostate (P=.38, 95% CI –0.08 to 0.22), lung (P<.001, 95% CI 0.33 to 0.46), colon (P<.001, 95% CI 0.11 to 0.17), and uterine cancers (P<.001, 95% CI 0.07 to 0.12) and leukemia (P<.001, 95% CI 0.01 to 0.03). Temporal associations in GT were noted with breast cancer awareness month but not with other cancer awareness months and celebrity events. Conclusions Cancer incidence is correlated with online search volume at the state level. Search patterns were temporally associated with cancer awareness months and celebrity announcements. Online searches reflect public awareness. Advancing understanding of online search patterns could augment traditional epidemiologic surveillance, provide opportunities for targeted patient engagement, and allow public information campaigns to be evaluated in ways previously unable to be measured. PMID:29311051
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Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
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Optimizing human activity patterns using global sensitivity analysis
Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James M.
2014-01-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations. PMID:25580080
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Optimizing human activity patterns using global sensitivity analysis
Fairchild, Geoffrey; Hickmann, Kyle S.; Mniszewski, Susan M.; ...
2013-12-10
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimizationmore » problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. Here we use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Finally, though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.« less
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Hanigan, David; Ferrer, Imma; Thurman, E Michael; Herckes, Pierre; Westerhoff, Paul
2017-02-05
N-Nitrosodimethylamine (NDMA) is carcinogenic in rodents and occurs in chloraminated drinking water and wastewater effluents. NDMA forms via reactions between chloramines and mostly unidentified, N-containing organic matter. We developed a mass spectrometry technique to identify NDMA precursors by analyzing 25 model compounds with LC/QTOF-MS. We searched isolates of 11 drinking water sources and 1 wastewater using a custom MATLAB ® program and extracted ion chromatograms for two fragmentation patterns that were specific to the model compounds. Once a diagnostic fragment was discovered, we conducted MS/MS during a subsequent injection to confirm the precursor ion. Using non-target searches and two diagnostic fragmentation patterns, we discovered 158 potential NDMA precursors. Of these, 16 were identified using accurate mass combined with fragment and retention time matches of analytical standards when available. Five of these sixteen NDMA precursors were previously unidentified in the literature, three of which were metabolites of pharmaceuticals. Except methadone, the newly identified precursors all had NDMA molar yields of less than 5%, indicating that NDMA formation could be additive from multiple compounds, each with low yield. We demonstrate that the method is applicable to other disinfection by-product precursors by predicting and verifying the fragmentation patterns for one nitrosodiethylamine precursor. Copyright © 2016. Published by Elsevier B.V.
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Braun, J
1994-02-01
In more than one respect, visual search for the most salient or the least salient item in a display are different kinds of visual tasks. The present work investigated whether this difference is primarily one of perceptual difficulty, or whether it is more fundamental and relates to visual attention. Display items of different salience were produced by varying either size, contrast, color saturation, or pattern. Perceptual masking was employed and, on average, mask onset was delayed longer in search for the least salient item than in search for the most salient item. As a result, the two types of visual search presented comparable perceptual difficulty, as judged by psychophysical measures of performance, effective stimulus contrast, and stability of decision criterion. To investigate the role of attention in the two types of search, observers attempted to carry out a letter discrimination and a search task concurrently. To discriminate the letters, observers had to direct visual attention at the center of the display and, thus, leave unattended the periphery, which contained target and distractors of the search task. In this situation, visual search for the least salient item was severely impaired while visual search for the most salient item was only moderately affected, demonstrating a fundamental difference with respect to visual attention. A qualitatively identical pattern of results was encountered by Schiller and Lee (1991), who used similar visual search tasks to assess the effect of a lesion in extrastriate area V4 of the macaque.
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Concurrent design of quasi-random photonic nanostructures
Lee, Won-Kyu; Yu, Shuangcheng; Engel, Clifford J.; Reese, Thaddeus; Rhee, Dongjoon; Chen, Wei
2017-01-01
Nanostructured surfaces with quasi-random geometries can manipulate light over broadband wavelengths and wide ranges of angles. Optimization and realization of stochastic patterns have typically relied on serial, direct-write fabrication methods combined with real-space design. However, this approach is not suitable for customizable features or scalable nanomanufacturing. Moreover, trial-and-error processing cannot guarantee fabrication feasibility because processing–structure relations are not included in conventional designs. Here, we report wrinkle lithography integrated with concurrent design to produce quasi-random nanostructures in amorphous silicon at wafer scales that achieved over 160% light absorption enhancement from 800 to 1,200 nm. The quasi-periodicity of patterns, materials filling ratio, and feature depths could be independently controlled. We statistically represented the quasi-random patterns by Fourier spectral density functions (SDFs) that could bridge the processing–structure and structure–performance relations. Iterative search of the optimal structure via the SDF representation enabled concurrent design of nanostructures and processing. PMID:28760975
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Ramu, Chenna
2003-07-01
SIRW (http://sirw.embl.de/) is a World Wide Web interface to the Simple Indexing and Retrieval System (SIR) that is capable of parsing and indexing various flat file databases. In addition it provides a framework for doing sequence analysis (e.g. motif pattern searches) for selected biological sequences through keyword search. SIRW is an ideal tool for the bioinformatics community for searching as well as analyzing biological sequences of interest.
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2016-09-01
searching for lost car keys in a parking lot to prosecuting a submarine in the South China Sea. This research draws on oceanographic properties to...search area based on the oceanographic properties at 21N 119E. 14. SUBJECT TERMS Search Theory, Undersea Warfare, South China Sea, Anti- Submarine ...lot to prosecuting a submarine in the South China Sea. This research draws on oceanographic properties to develop a search radii for two surface ships
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Artificial bee colony in neuro - Symbolic integration
NASA Astrophysics Data System (ADS)
Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf
2017-08-01
Swarm intelligence is a research area that models the population of the swarm based on natural computation. Artificial bee colony (ABC) algorithm is a swarm based metaheuristic algorithm introduced by Karaboga to optimize numerical problem. Pattern-SAT is a pattern reconstruction paradigm that utilized 2SAT logical rule in representing the behavior of the desired pattern. The information of the desired pattern in terms of 2SAT logic is embedded to Hopfield neural network (HNN-P2SAT) and the desired pattern is reconstructed during the retrieval phase. Since the performance of HNN-P2SAT in Pattern-SAT deteriorates when the number of 2SAT clause increased, newly improved ABC is used to reduce the computation burden during the learning phase of HNN-P2SAT (HNN-P2SATABC). The aim of this study is to investigate the performance of Pattern-SAT produced by ABC incorporated with HNN-P2SAT and compare it with conventional standalone HNN. The comparison is examined by using Microsoft Visual Basic C++ 2013 software. The detailed comparison in doing Pattern-SAT is discussed based on global Pattern-SAT, ratio of activated clauses and computation time. The result obtained from computer simulation indicates the beneficial features of HNN-P2SATABC in doing Pattern-SAT. This finding is expected to result in a significant implication on the choice of searching method used to do Pattern-SAT.
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Adawi, Mohammad; Amital, Howard; Mahamid, Mahmud; Amital, Daniela; Bisharat, Bishara; Mahroum, Naim; Sharif, Kassem; Guy, Adi; Adawi, Amin; Mahagna, Hussein; Abu Much, Arsalan; Watad, Samaa; Bragazzi, Nicola Luigi; Watad, Abdulla
2018-01-01
Israel represents a complex and pluralistic society comprising two major ethno-national groups, Israeli Jews and Israeli Arabs, which differ in terms of religious and cultural values as well as social constructs. According to the so-called "diversification hypothesis", within the framework of e-health and in the era of new information and communication technologies, seeking online health information could be a channel to increase health literacy, especially among disadvantaged groups. However, little is known concerning digital seeking behavior and, in particular, digital mental health literacy. This study was conducted in order to fill in this gap. Concerning raw figures, unadjusted for confounding variables (time, population size, Internet penetration index, disease rate), "depression" searched in Hebrew was characterized by 1.5 times higher search volumes, slightly declining throughout time, whereas relative search volumes (RSVs) related to "depression" searched in Arabic tended to increase over the years. Similar patterns could be detected for "phobia" (in Hebrew 1.4-fold higher than in Arabic) and for "anxiety" (with the searches performed in Hebrew 2.3 times higher than in Arabic). "Suicide" in Hebrew was searched 2.0-fold more than in Arabic (interestingly for both languages search volumes exhibited seasonal cyclic patterns). Eating disorders were searched more in Hebrew: 8.0-times more for "bulimia", whilst "anorexia" was searched in Hebrew only. When adjusting for confounding variables, association between digital seeking behavior and ethnicity remained statistically significant ( p -value < 0.0001) for all psychiatric disorders considered in the current investigation, except for "bulimia" ( p = 0.989). More in details, Israeli Arabs searched for mental health disorders less than Jews, apart from "depression". Arab and Jewish Israelis, besides differing in terms of language, religion, social and cultural values, have different patterns of usage of healthcare services and provisions, as well as e-healthcare services concerning mental health. Policy- and decision-makers should be aware of this and make their best efforts to promote digital health literacy among the Arab population in Israel.
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Adawi, Mohammad; Amital, Howard; Mahamid, Mahmud; Amital, Daniela; Bisharat, Bishara; Mahroum, Naim; Sharif, Kassem; Guy, Adi; Adawi, Amin; Mahagna, Hussein; Abu Much, Arsalan; Watad, Samaa; Watad, Abdulla
2018-01-01
Israel represents a complex and pluralistic society comprising two major ethno-national groups, Israeli Jews and Israeli Arabs, which differ in terms of religious and cultural values as well as social constructs. According to the so-called “diversification hypothesis”, within the framework of e-health and in the era of new information and communication technologies, seeking online health information could be a channel to increase health literacy, especially among disadvantaged groups. However, little is known concerning digital seeking behavior and, in particular, digital mental health literacy. This study was conducted in order to fill in this gap. Concerning raw figures, unadjusted for confounding variables (time, population size, Internet penetration index, disease rate), “depression” searched in Hebrew was characterized by 1.5 times higher search volumes, slightly declining throughout time, whereas relative search volumes (RSVs) related to “depression” searched in Arabic tended to increase over the years. Similar patterns could be detected for “phobia” (in Hebrew 1.4-fold higher than in Arabic) and for “anxiety” (with the searches performed in Hebrew 2.3 times higher than in Arabic). “Suicide” in Hebrew was searched 2.0-fold more than in Arabic (interestingly for both languages search volumes exhibited seasonal cyclic patterns). Eating disorders were searched more in Hebrew: 8.0-times more for “bulimia”, whilst “anorexia” was searched in Hebrew only. When adjusting for confounding variables, association between digital seeking behavior and ethnicity remained statistically significant (p-value < 0.0001) for all psychiatric disorders considered in the current investigation, except for “bulimia” (p = 0.989). More in details, Israeli Arabs searched for mental health disorders less than Jews, apart from “depression”. Arab and Jewish Israelis, besides differing in terms of language, religion, social and cultural values, have different patterns of usage of healthcare services and provisions, as well as e-healthcare services concerning mental health. Policy- and decision-makers should be aware of this and make their best efforts to promote digital health literacy among the Arab population in Israel. PMID:29576974
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ERIC Educational Resources Information Center
Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.
2000-01-01
These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)
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Searching social networks for subgraph patterns
NASA Astrophysics Data System (ADS)
Ogaard, Kirk; Kase, Sue; Roy, Heather; Nagi, Rakesh; Sambhoos, Kedar; Sudit, Moises
2013-06-01
Software tools for Social Network Analysis (SNA) are being developed which support various types of analysis of social networks extracted from social media websites (e.g., Twitter). Once extracted and stored in a database such social networks are amenable to analysis by SNA software. This data analysis often involves searching for occurrences of various subgraph patterns (i.e., graphical representations of entities and relationships). The authors have developed the Graph Matching Toolkit (GMT) which provides an intuitive Graphical User Interface (GUI) for a heuristic graph matching algorithm called the Truncated Search Tree (TruST) algorithm. GMT is a visual interface for graph matching algorithms processing large social networks. GMT enables an analyst to draw a subgraph pattern by using a mouse to select categories and labels for nodes and links from drop-down menus. GMT then executes the TruST algorithm to find the top five occurrences of the subgraph pattern within the social network stored in the database. GMT was tested using a simulated counter-insurgency dataset consisting of cellular phone communications within a populated area of operations in Iraq. The results indicated GMT (when executing the TruST graph matching algorithm) is a time-efficient approach to searching large social networks. GMT's visual interface to a graph matching algorithm enables intelligence analysts to quickly analyze and summarize the large amounts of data necessary to produce actionable intelligence.
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Web-Based Surveillance of Public Information Needs for Informing Preconception Interventions
D’Ambrosio, Angelo; Agricola, Eleonora; Russo, Luisa; Gesualdo, Francesco; Pandolfi, Elisabetta; Bortolus, Renata; Castellani, Carlo; Lalatta, Faustina; Mastroiacovo, Pierpaolo; Tozzi, Alberto Eugenio
2015-01-01
Background The risk of adverse pregnancy outcomes can be minimized through the adoption of healthy lifestyles before pregnancy by women of childbearing age. Initiatives for promotion of preconception health may be difficult to implement. Internet can be used to build tailored health interventions through identification of the public's information needs. To this aim, we developed a semi-automatic web-based system for monitoring Google searches, web pages and activity on social networks, regarding preconception health. Methods Based on the American College of Obstetricians and Gynecologists guidelines and on the actual search behaviors of Italian Internet users, we defined a set of keywords targeting preconception care topics. Using these keywords, we analyzed the usage of Google search engine and identified web pages containing preconception care recommendations. We also monitored how the selected web pages were shared on social networks. We analyzed discrepancies between searched and published information and the sharing pattern of the topics. Results We identified 1,807 Google search queries which generated a total of 1,995,030 searches during the study period. Less than 10% of the reviewed pages contained preconception care information and in 42.8% information was consistent with ACOG guidelines. Facebook was the most used social network for sharing. Nutrition, Chronic Diseases and Infectious Diseases were the most published and searched topics. Regarding Genetic Risk and Folic Acid, a high search volume was not associated to a high web page production, while Medication pages were more frequently published than searched. Vaccinations elicited high sharing although web page production was low; this effect was quite variable in time. Conclusion Our study represent a resource to prioritize communication on specific topics on the web, to address misconceptions, and to tailor interventions to specific populations. PMID:25879682
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Yang, Albert C.; Huang, Norden E.; Peng, Chung-Kang; Tsai, Shih-Jen
2010-01-01
Background Seasonal depression has generated considerable clinical interest in recent years. Despite a common belief that people in higher latitudes are more vulnerable to low mood during the winter, it has never been demonstrated that human's moods are subject to seasonal change on a global scale. The aim of this study was to investigate large-scale seasonal patterns of depression using Internet search query data as a signature and proxy of human affect. Methodology/Principal Findings Our study was based on a publicly available search engine database, Google Insights for Search, which provides time series data of weekly search trends from January 1, 2004 to June 30, 2009. We applied an empirical mode decomposition method to isolate seasonal components of health-related search trends of depression in 54 geographic areas worldwide. We identified a seasonal trend of depression that was opposite between the northern and southern hemispheres; this trend was significantly correlated with seasonal oscillations of temperature (USA: r = −0.872, p<0.001; Australia: r = −0.656, p<0.001). Based on analyses of search trends over 54 geological locations worldwide, we found that the degree of correlation between searching for depression and temperature was latitude-dependent (northern hemisphere: r = −0.686; p<0.001; southern hemisphere: r = 0.871; p<0.0001). Conclusions/Significance Our findings indicate that Internet searches for depression from people in higher latitudes are more vulnerable to seasonal change, whereas this phenomenon is obscured in tropical areas. This phenomenon exists universally across countries, regardless of language. This study provides novel, Internet-based evidence for the epidemiology of seasonal depression. PMID:21060851
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Does the thinking aloud condition affect the search for pulmonary nodules?
NASA Astrophysics Data System (ADS)
Littlefair, Stephen; Brennan, Patrick; Reed, Warren; Williams, Mark; Pietrzyk, Mariusz W.
2012-02-01
Aim: To measure the effect of thinking aloud on perceptual accuracy and visual search behavior during chest radiograph interpretation for pulmonary nodules. Background: Thinking Aloud (TA) is an empirical research method used by researchers in cognitive psychology and behavioural analysis. In this pilot study we wanted to examine whether TA had an effect on the perceptual accuracy and search patterns of subjects looking for pulmonary nodules on adult posterioranterior chest radiographs (PA CxR). Method: Seven academics within Medical Radiation Sciences at The University of Sydney participated in two reading sessions with and without TA. Their task was to localize pulmonary nodules on 30 PA CxR using mouse clicks and rank their confidence levels of nodule presence. Eye-tracking recordings were collected during both viewing sessions. Time to first fixation, duration of first fixation, number of fixations, cumulative time of fixation and total viewing time were analysed. In addition, ROC analysis was conducted on collected outcome using DBM methodology. Results: Time to first nodule fixation was significantly longer (p=0.001) and duration of first fixation was significantly shorter (p=0.043). No significant difference was observed in ROC AUC scores between control and TA conditions. Conclusion: Our results confirm that TA has little effect on perceptual ability or performance, except for prolonging the task. However, there were significant differences in visual search behavior. Future researchers in radio-diagnosis could use the think aloud condition rather than silence so as to more closely replicate the clinical scenario.
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Attention-Deficit / Hyperactivity Disorder (ADHD): Data and Statistics
... Search Form Controls Cancel Submit Search the CDC Attention-Deficit / Hyperactivity Disorder (ADHD) Note: Javascript is disabled ... claims to understand diagnosis and treatment patterns for Attention-Deficit/Hyperactivity Disorder (ADHD). On this page you ...
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Fractal Analysis of Visual Search Activity for Mass Detection During Mammographic Screening
Alamudun, Folami T.; Yoon, Hong-Jun; Hudson, Kathy; ...
2017-02-21
Purpose: The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics. Methods: The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus data for this study. The fractal dimension of the readers’ visual scanning patternsmore » was computed with the Minkowski–Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined. Results: Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the visual scanning pattern complexity when screening for breast cancer. No higher order effects were found to be significant. Conclusions: Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics.« less
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ERIC Educational Resources Information Center
Ponomariov, Branco; Kingsley, Gordon; Boardman, Craig
2011-01-01
This paper compares over a 12-year period (1) patterns of contracting between a state transportation agency and its prime contractors providing engineering design services with (2) patterns between these prime contractors and their subcontractors. We find evidence of different contracting patterns at each level that emerge over time and coexist in…
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Recognition of functional sites in protein structures.
Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J
2004-06-04
Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.
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Shin, Soo-Yong; Kim, Taerim; Seo, Dong-Woo; Sohn, Chang Hwan; Kim, Sung-Hoon; Ryoo, Seung Mok; Lee, Yoon-Seon; Lee, Jae Ho; Kim, Won Young; Lim, Kyoung Soo
2016-01-01
Digital surveillance using internet search queries can improve both the sensitivity and timeliness of the detection of a health event, such as an influenza outbreak. While it has recently been estimated that the mobile search volume surpasses the desktop search volume and mobile search patterns differ from desktop search patterns, the previous digital surveillance systems did not distinguish mobile and desktop search queries. The purpose of this study was to compare the performance of mobile and desktop search queries in terms of digital influenza surveillance. The study period was from September 6, 2010 through August 30, 2014, which consisted of four epidemiological years. Influenza-like illness (ILI) and virologic surveillance data from the Korea Centers for Disease Control and Prevention were used. A total of 210 combined queries from our previous survey work were used for this study. Mobile and desktop weekly search data were extracted from Naver, which is the largest search engine in Korea. Spearman's correlation analysis was used to examine the correlation of the mobile and desktop data with ILI and virologic data in Korea. We also performed lag correlation analysis. We observed that the influenza surveillance performance of mobile search queries matched or exceeded that of desktop search queries over time. The mean correlation coefficients of mobile search queries and the number of queries with an r-value of ≥ 0.7 equaled or became greater than those of desktop searches over the four epidemiological years. A lag correlation analysis of up to two weeks showed similar trends. Our study shows that mobile search queries for influenza surveillance have equaled or even become greater than desktop search queries over time. In the future development of influenza surveillance using search queries, the recognition of changing trend of mobile search data could be necessary.
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A method for real-time visual stimulus selection in the study of cortical object perception.
Leeds, Daniel D; Tarr, Michael J
2016-06-01
The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit's image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across pre-determined 1cm(3) rain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds et al., 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) real-time estimation of cortical responses to stimuli is reasonably consistent; 3) search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. Copyright © 2016 Elsevier Inc. All rights reserved.
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A method for real-time visual stimulus selection in the study of cortical object perception
Leeds, Daniel D.; Tarr, Michael J.
2016-01-01
The properties utilized by visual object perception in the mid- and high-level ventral visual pathway are poorly understood. To better establish and explore possible models of these properties, we adopt a data-driven approach in which we repeatedly interrogate neural units using functional Magnetic Resonance Imaging (fMRI) to establish each unit’s image selectivity. This approach to imaging necessitates a search through a broad space of stimulus properties using a limited number of samples. To more quickly identify the complex visual features underlying human cortical object perception, we implemented a new functional magnetic resonance imaging protocol in which visual stimuli are selected in real-time based on BOLD responses to recently shown images. Two variations of this protocol were developed, one relying on natural object stimuli and a second based on synthetic object stimuli, both embedded in feature spaces based on the complex visual properties of the objects. During fMRI scanning, we continuously controlled stimulus selection in the context of a real-time search through these image spaces in order to maximize neural responses across predetermined 1 cm3 brain regions. Elsewhere we have reported the patterns of cortical selectivity revealed by this approach (Leeds 2014). In contrast, here our objective is to present more detailed methods and explore the technical and biological factors influencing the behavior of our real-time stimulus search. We observe that: 1) Searches converged more reliably when exploring a more precisely parameterized space of synthetic objects; 2) Real-time estimation of cortical responses to stimuli are reasonably consistent; 3) Search behavior was acceptably robust to delays in stimulus displays and subject motion effects. Overall, our results indicate that real-time fMRI methods may provide a valuable platform for continuing study of localized neural selectivity, both for visual object representation and beyond. PMID:26973168
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Young, Sean D; Yu, Wenchao; Wang, Wei
2017-02-01
"Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trends and transmission, the review process is time consuming and resource intensive. Machine learning methods derived from computer science might be used to assist HIV domain experts by learning how to rapidly and accurately identify patterns associated with HIV from a large set of social data. Using an existing social media data set that was associated with HIV and coded by an HIV domain expert, we tested whether 4 commonly used machine learning methods could learn the patterns associated with HIV risk behavior. We used the 10-fold cross-validation method to examine the speed and accuracy of these models in applying that knowledge to detect HIV content in social media data. Logistic regression and random forest resulted in the highest accuracy in detecting HIV-related social data (85.3%), whereas the Ridge Regression Classifier resulted in the lowest accuracy. Logistic regression yielded the fastest processing time (16.98 seconds). Machine learning can enable social big data to become a new and important tool in HIV research, helping to create a new field of "digital HIV epidemiology." If a domain expert can identify patterns in social data associated with HIV risk or HIV transmission, machine learning models could quickly and accurately learn those associations and identify potential HIV patterns in large social data sets.
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Influence of legislations and news on Indian internet search query patterns of e-cigarettes.
Thavarajah, Rooban; Mohandoss, Anusa Arunachalam; Ranganathan, Kannan; Kondalsamy-Chennakesavan, Srinivas
2017-01-01
There is a paucity of data on the use of electronic nicotine delivery systems (ENDS) in India. In addition, the Indian internet search pattern for ENDS has not been studied. We aimed to address this lacuna. Moreover, the influence of the tobacco legislations and news pieces on such search volume is not known. Given the fact that ENDS could cause oral lesions, these data are pertinent to dentists. Using a time series analysis, we examined the effect of tobacco-related legislations and news pieces on total search volume (TSV) from September 1, 2012, to August 31, 2016. TSV data were seasonally adjusted and analyzed using time series modeling. The TSV clocked during the month of legislations and news pieces were analyzed for their influence on search pattern of ENDS. The overall mean ± standard deviation (range) TSV was 22273.75 ± 6784.01 (12310-40510) during the study with seasonal variations. Individually, the best model for TSV-legislation and news pieces was autoregressive integrated moving average model, and when influence of legislations and news events were combined, it was the Winter's additive model. In the legislation alone model, the pre-event, event and post-event month TSV was not a better indicator of the effect, barring for post-event month of 2 nd legislation, which involved pictorial warnings on packages in the study period. Similarly, a news piece on Pan-India ban on ENDS influenced the model in the news piece model. When combined, no "events" emerged significant. These findings suggest that search for information on ENDS is increasing and that these tobacco control policies and news items, targeting tobacco usage reduction, have only a short-term effect on the rate of searching for information on ENDS.
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Threshold matrix for digital halftoning by genetic algorithm optimization
NASA Astrophysics Data System (ADS)
Alander, Jarmo T.; Mantere, Timo J.; Pyylampi, Tero
1998-10-01
Digital halftoning is used both in low and high resolution high quality printing technologies. Our method is designed to be mainly used for low resolution ink jet marking machines to produce both gray tone and color images. The main problem with digital halftoning is pink noise caused by the human eye's visual transfer function. To compensate for this the random dot patterns used are optimized to contain more blue than pink noise. Several such dot pattern generator threshold matrices have been created automatically by using genetic algorithm optimization, a non-deterministic global optimization method imitating natural evolution and genetics. A hybrid of genetic algorithm with a search method based on local backtracking was developed together with several fitness functions evaluating dot patterns for rectangular grids. By modifying the fitness function, a family of dot generators results, each with its particular statistical features. Several versions of genetic algorithms, backtracking and fitness functions were tested to find a reasonable combination. The generated threshold matrices have been tested by simulating a set of test images using the Khoros image processing system. Even though the work was focused on developing low resolution marking technology, the resulting family of dot generators can be applied also in other halftoning application areas including high resolution printing technology.
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Shemilt, Ian; Mugford, Miranda; Drummond, Michael; Eisenstein, Eric; Mallender, Jacqueline; McDaid, David; Vale, Luke; Walker, Damian
2006-01-01
Background Provision of evidence on costs alongside evidence on the effects of interventions can enhance the relevance of systematic reviews to decision-making. However, patterns of use of economics methods alongside systematic review remain unclear. Reviews of evidence on the effects of interventions are published by both the Cochrane and Campbell Collaborations. Although it is not a requirement that Cochrane or Campbell Reviews should consider economic aspects of interventions, many do. This study aims to explore and describe approaches to incorporating economics methods in a selection of Cochrane systematic reviews in the area of health promotion and public health, to help inform development of methodological guidance on economics for reviewers. Methods The Cochrane Database of Systematic Reviews was searched using a search strategy for potential economic evaluation studies. We included current Cochrane reviews and review protocols retrieved using the search that are also identified as relevant to health promotion or public health topics. A reviewer extracted data which describe the economics components of included reviews. Extracted data were summarised in tables and analysed qualitatively. Results Twenty-one completed Cochrane reviews and seven review protocols met inclusion criteria. None incorporate formal economic evaluation methods. Ten completed reviews explicitly aim to incorporate economics studies and data. There is a lack of transparent reporting of methods underpinning the incorporation of economics studies and data. Some reviews are likely to exclude useful economics studies and data due to a failure to incorporate search strategies tailored to the retrieval of such data or use of key specialist databases, and application of inclusion criteria designed for effectiveness studies. Conclusion There is a need for consistency and transparency in the reporting and conduct of the economics components of Cochrane reviews, as well as regular dialogue between Cochrane reviewers and economists to develop increased capacity for economic analyses alongside such reviews. Use of applicable economics methods in Cochrane reviews can help provide the international context within which economics data can be interpreted and assessed as a preliminary to full economic evaluation. PMID:17107612
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Evidence-based practice: extending the search to find material for the systematic review
Helmer, Diane; Savoie, Isabelle; Green, Carolyn; Kazanjian, Arminée
2001-01-01
Background: Cochrane-style systematic reviews increasingly require the participation of librarians. Guidelines on the appropriate search strategy to use for systematic reviews have been proposed. However, research evidence supporting these recommendations is limited. Objective: This study investigates the effectiveness of various systematic search methods used to uncover randomized controlled trials (RCTs) for systematic reviews. Effectiveness is defined as the proportion of relevant material uncovered for the systematic review using extended systematic review search methods. The following extended systematic search methods are evaluated: searching subject-specific or specialized databases (including trial registries), hand searching, scanning reference lists, and communicating personally. Methods: Two systematic review projects were prospectively monitored regarding the method used to identify items as well as the type of items retrieved. The proportion of RCTs identified by each systematic search method was calculated. Results: The extended systematic search methods uncovered 29.2% of all items retrieved for the systematic reviews. The search of specialized databases was the most effective method, followed by scanning of reference lists, communicating personally, and hand searching. Although the number of items identified through hand searching was small, these unique items would otherwise have been missed. Conclusions: Extended systematic search methods are effective tools for uncovering material for the systematic review. The quality of the items uncovered has yet to be assessed and will be key in evaluating the value of the systematic search methods. PMID:11837256
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A Western Dietary Pattern Increases Prostate Cancer Risk: A Systematic Review and Meta-Analysis.
Fabiani, Roberto; Minelli, Liliana; Bertarelli, Gaia; Bacci, Silvia
2016-10-12
Dietary patterns were recently applied to examine the relationship between eating habits and prostate cancer (PC) risk. While the associations between PC risk with the glycemic index and Mediterranean score have been reviewed, no meta-analysis is currently available on dietary patterns defined by "a posteriori" methods. A literature search was carried out (PubMed, Web of Science) to identify studies reporting the relationship between dietary patterns and PC risk. Relevant dietary patterns were selected and the risks estimated were calculated by a random-effect model. Multivariable-adjusted odds ratios (ORs), for a first-percentile increase in dietary pattern score, were combined by a dose-response meta-analysis. Twelve observational studies were included in the meta-analysis which identified a "Healthy pattern" and a "Western pattern". The Healthy pattern was not related to PC risk (OR = 0.96; 95% confidence interval (CI): 0.88-1.04) while the Western pattern significantly increased it (OR = 1.34; 95% CI: 1.08-1.65). In addition, the "Carbohydrate pattern", which was analyzed in four articles, was positively associated with a higher PC risk (OR = 1.64; 95% CI: 1.35-2.00). A significant linear trend between the Western ( p = 0.011) pattern, the Carbohydrate ( p = 0.005) pattern, and the increment of PC risk was observed. The small number of studies included in the meta-analysis suggests that further investigation is necessary to support these findings.
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Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina
2012-01-01
Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803
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Discovering significant evolution patterns from satellite image time series.
Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain
2011-12-01
Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.
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Cooper, Chris; Booth, Andrew; Britten, Nicky; Garside, Ruth
2017-11-28
The purpose and contribution of supplementary search methods in systematic reviews is increasingly acknowledged. Numerous studies have demonstrated their potential in identifying studies or study data that would have been missed by bibliographic database searching alone. What is less certain is how supplementary search methods actually work, how they are applied, and the consequent advantages, disadvantages and resource implications of each search method. The aim of this study is to compare current practice in using supplementary search methods with methodological guidance. Four methodological handbooks in informing systematic review practice in the UK were read and audited to establish current methodological guidance. Studies evaluating the use of supplementary search methods were identified by searching five bibliographic databases. Studies were included if they (1) reported practical application of a supplementary search method (descriptive) or (2) examined the utility of a supplementary search method (analytical) or (3) identified/explored factors that impact on the utility of a supplementary method, when applied in practice. Thirty-five studies were included in this review in addition to the four methodological handbooks. Studies were published between 1989 and 2016, and dates of publication of the handbooks ranged from 1994 to 2014. Five supplementary search methods were reviewed: contacting study authors, citation chasing, handsearching, searching trial registers and web searching. There is reasonable consistency between recommended best practice (handbooks) and current practice (methodological studies) as it relates to the application of supplementary search methods. The methodological studies provide useful information on the effectiveness of the supplementary search methods, often seeking to evaluate aspects of the method to improve effectiveness or efficiency. In this way, the studies advance the understanding of the supplementary search methods. Further research is required, however, so that a rational choice can be made about which supplementary search strategies should be used, and when.
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3D displacement field measurement with correlation based on the micro-geometrical surface texture
NASA Astrophysics Data System (ADS)
Bubaker-Isheil, Halima; Serri, Jérôme; Fontaine, Jean-François
2011-07-01
Image correlation methods are widely used in experimental mechanics to obtain displacement field measurements. Currently, these methods are applied using digital images of the initial and deformed surfaces sprayed with black or white paint. Speckle patterns are then captured and the correlation is performed with a high degree of accuracy to an order of 0.01 pixels. In 3D, however, stereo-correlation leads to a lower degree of accuracy. Correlation techniques are based on the search for a sub-image (or pattern) displacement field. The work presented in this paper introduces a new correlation-based approach for 3D displacement field measurement that uses an additional 3D laser scanner and a CMM (Coordinate Measurement Machine). Unlike most existing methods that require the presence of markers on the observed object (such as black speckle, grids or random patterns), this approach relies solely on micro-geometrical surface textures such as waviness, roughness and aperiodic random defects. The latter are assumed to remain sufficiently small thus providing an adequate estimate of the particle displacement. The proposed approach can be used in a wide range of applications such as sheet metal forming with large strains. The method proceeds by first obtaining cloud points using the 3D laser scanner mounted on a CMM. These points are used to create 2D maps that are then correlated. In this respect, various criteria have been investigated for creating maps consisting of patterns, which facilitate the correlation procedure. Once the maps are created, the correlation between both configurations (initial and moved) is carried out using traditional methods developed for field measurements. Measurement validation was conducted using experiments in 2D and 3D with good results for rigid displacements in 2D, 3D and 2D rotations.
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Moseley, Hunter N B; Riaz, Nadeem; Aramini, James M; Szyperski, Thomas; Montelione, Gaetano T
2004-10-01
We present an algorithm and program called Pattern Picker that performs editing of raw peak lists derived from multidimensional NMR experiments with characteristic peak patterns. Pattern Picker detects groups of correlated peaks within peak lists from reduced dimensionality triple resonance (RD-TR) NMR spectra, with high fidelity and high yield. With typical quality RD-TR NMR data sets, Pattern Picker performs almost as well as human analysis, and is very robust in discriminating real peak sets from noise and other artifacts in unedited peak lists. The program uses a depth-first search algorithm with short-circuiting to efficiently explore a search tree representing every possible combination of peaks forming a group. The Pattern Picker program is particularly valuable for creating an automated peak picking/editing process. The Pattern Picker algorithm can be applied to a broad range of experiments with distinct peak patterns including RD, G-matrix Fourier transformation (GFT) NMR spectra, and experiments to measure scalar and residual dipolar coupling, thus promoting the use of experiments that are typically harder for a human to analyze. Since the complexity of peak patterns becomes a benefit rather than a drawback, Pattern Picker opens new opportunities in NMR experiment design.
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Modulation of neuronal responses during covert search for visual feature conjunctions
Buracas, Giedrius T.; Albright, Thomas D.
2009-01-01
While searching for an object in a visual scene, an observer's attentional focus and eye movements are often guided by information about object features and spatial locations. Both spatial and feature-specific attention are known to modulate neuronal responses in visual cortex, but little is known of the dynamics and interplay of these mechanisms as visual search progresses. To address this issue, we recorded from directionally selective cells in visual area MT of monkeys trained to covertly search for targets defined by a unique conjunction of color and motion features and to signal target detection with an eye movement to the putative target. Two patterns of response modulation were observed. One pattern consisted of enhanced responses to targets presented in the receptive field (RF). These modulations occurred at the end-stage of search and were more potent during correct target identification than during erroneous saccades to a distractor in RF, thus suggesting that this modulation is not a mere presaccadic enhancement. A second pattern of modulation was observed when RF stimuli were nontargets that shared a feature with the target. The latter effect was observed during early stages of search and is consistent with a global feature-specific mechanism. This effect often terminated before target identification, thus suggesting that it interacts with spatial attention. This modulation was exhibited not only for motion but also for color cue, although MT neurons are known to be insensitive to color. Such cue-invariant attentional effects may contribute to a feature binding mechanism acting across visual dimensions. PMID:19805385
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Modulation of neuronal responses during covert search for visual feature conjunctions.
Buracas, Giedrius T; Albright, Thomas D
2009-09-29
While searching for an object in a visual scene, an observer's attentional focus and eye movements are often guided by information about object features and spatial locations. Both spatial and feature-specific attention are known to modulate neuronal responses in visual cortex, but little is known of the dynamics and interplay of these mechanisms as visual search progresses. To address this issue, we recorded from directionally selective cells in visual area MT of monkeys trained to covertly search for targets defined by a unique conjunction of color and motion features and to signal target detection with an eye movement to the putative target. Two patterns of response modulation were observed. One pattern consisted of enhanced responses to targets presented in the receptive field (RF). These modulations occurred at the end-stage of search and were more potent during correct target identification than during erroneous saccades to a distractor in RF, thus suggesting that this modulation is not a mere presaccadic enhancement. A second pattern of modulation was observed when RF stimuli were nontargets that shared a feature with the target. The latter effect was observed during early stages of search and is consistent with a global feature-specific mechanism. This effect often terminated before target identification, thus suggesting that it interacts with spatial attention. This modulation was exhibited not only for motion but also for color cue, although MT neurons are known to be insensitive to color. Such cue-invariant attentional effects may contribute to a feature binding mechanism acting across visual dimensions.
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Lavine, Barry K; White, Collin G; Ding, Tao
2018-03-01
Pattern recognition techniques have been applied to the infrared (IR) spectral libraries of the Paint Data Query (PDQ) database to differentiate between nonidentical but similar IR spectra of automotive paints. To tackle the problem of library searching, search prefilters were developed to identify the vehicle make from IR spectra of the clear coat, surfacer-primer, and e-coat layers. To develop these search prefilters with the appropriate degree of accuracy, IR spectra from the PDQ database were preprocessed using the discrete wavelet transform to enhance subtle but significant features in the IR spectral data. Wavelet coefficients characteristic of vehicle make were identified using a genetic algorithm for pattern recognition and feature selection. Search prefilters to identify automotive manufacturer through IR spectra obtained from a paint chip recovered at a crime scene were developed using 1596 original manufacturer's paint systems spanning six makes (General Motors, Chrysler, Ford, Honda, Nissan, and Toyota) within a limited production year range (2000-2006). Search prefilters for vehicle manufacturer that were developed as part of this study were successfully validated using IR spectra obtained directly from the PDQ database. Information obtained from these search prefilters can serve to quantify the discrimination power of original automotive paint encountered in casework and further efforts to succinctly communicate trace evidential significance to the courts.
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Kabekkodu, Soorya N; Faber, John; Fawcett, Tim
2002-06-01
The International Centre for Diffraction Data (ICDD) is responding to the changing needs in powder diffraction and materials analysis by developing the Powder Diffraction File (PDF) in a very flexible relational database (RDB) format. The PDF now contains 136,895 powder diffraction patterns. In this paper, an attempt is made to give an overview of the PDF-4, search/match methods and the advantages of having the PDF-4 in RDB format. Some case studies have been carried out to search for crystallization trends, properties, frequencies of space groups and prototype structures. These studies give a good understanding of the basic structural aspects of classes of compounds present in the database. The present paper also reports data-mining techniques and demonstrates the power of a relational database over the traditional (flat-file) database structures.
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NASA Astrophysics Data System (ADS)
Vo, Thanh Tu; Chen, Xiaopeng; Shen, Weixiang; Kapoor, Ajay
2015-01-01
In this paper, a new charging strategy of lithium-polymer batteries (LiPBs) has been proposed based on the integration of Taguchi method (TM) and state of charge estimation. The TM is applied to search an optimal charging current pattern. An adaptive switching gain sliding mode observer (ASGSMO) is adopted to estimate the SOC which controls and terminates the charging process. The experimental results demonstrate that the proposed charging strategy can successfully charge the same types of LiPBs with different capacities and cycle life. The proposed charging strategy also provides much shorter charging time, narrower temperature variation and slightly higher energy efficiency than the equivalent constant current constant voltage charging method.
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K-Nearest Neighbor Algorithm Optimization in Text Categorization
NASA Astrophysics Data System (ADS)
Chen, Shufeng
2018-01-01
K-Nearest Neighbor (KNN) classification algorithm is one of the simplest methods of data mining. It has been widely used in classification, regression and pattern recognition. The traditional KNN method has some shortcomings such as large amount of sample computation and strong dependence on the sample library capacity. In this paper, a method of representative sample optimization based on CURE algorithm is proposed. On the basis of this, presenting a quick algorithm QKNN (Quick k-nearest neighbor) to find the nearest k neighbor samples, which greatly reduces the similarity calculation. The experimental results show that this algorithm can effectively reduce the number of samples and speed up the search for the k nearest neighbor samples to improve the performance of the algorithm.
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A consensus algorithm for approximate string matching and its application to QRS complex detection
NASA Astrophysics Data System (ADS)
Alba, Alfonso; Mendez, Martin O.; Rubio-Rincon, Miguel E.; Arce-Santana, Edgar R.
2016-08-01
In this paper, a novel algorithm for approximate string matching (ASM) is proposed. The novelty resides in the fact that, unlike most other methods, the proposed algorithm is not based on the Hamming or Levenshtein distances, but instead computes a score for each symbol in the search text based on a consensus measure. Those symbols with sufficiently high scores will likely correspond to approximate instances of the pattern string. To demonstrate the usefulness of the proposed method, it has been applied to the detection of QRS complexes in electrocardiographic signals with competitive results when compared against the classic Pan-Tompkins (PT) algorithm. The proposed method outperformed PT in 72% of the test cases, with no extra computational cost.
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Implementing the Army NetCentric Data Strategy in a ServiceOriented Environment
2009-04-23
a Data Subscriptionc c e s s Federated Search Data Search D a t a A b s t r a c t i o n Adapter Configuration Adapter Data Service D a t a S e r...across t e enterpr se. • Patterns • Search • Status • Receive – Services • Federated Search • Artifact Discovery • Data Discovery 17 Data Discovery
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Shotgun metagenomic data streams: surfing without fear
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berendzen, Joel R
2010-12-06
Timely information about bio-threat prevalence, consequence, propagation, attribution, and mitigation is needed to support decision-making, both routinely and in a crisis. One DNA sequencer can stream 25 Gbp of information per day, but sampling strategies and analysis techniques are needed to turn raw sequencing power into actionable knowledge. Shotgun metagenomics can enable biosurveillance at the level of a single city, hospital, or airplane. Metagenomics characterizes viruses and bacteria from complex environments such as soil, air filters, or sewage. Unlike targeted-primer-based sequencing, shotgun methods are not blind to sequences that are truly novel, and they can measure absolute prevalence. Shotgun metagenomicmore » sampling can be non-invasive, efficient, and inexpensive while being informative. We have developed analysis techniques for shotgun metagenomic sequencing that rely upon phylogenetic signature patterns. They work by indexing local sequence patterns in a manner similar to web search engines. Our methods are laptop-fast and favorable scaling properties ensure they will be sustainable as sequencing methods grow. We show examples of application to soil metagenomic samples.« less
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Evaluating a Federated Medical Search Engine
Belden, J.; Williams, J.; Richardson, B.; Schuster, K.
2014-01-01
Summary Background Federated medical search engines are health information systems that provide a single access point to different types of information. Their efficiency as clinical decision support tools has been demonstrated through numerous evaluations. Despite their rigor, very few of these studies report holistic evaluations of medical search engines and even fewer base their evaluations on existing evaluation frameworks. Objectives To evaluate a federated medical search engine, MedSocket, for its potential net benefits in an established clinical setting. Methods This study applied the Human, Organization, and Technology (HOT-fit) evaluation framework in order to evaluate MedSocket. The hierarchical structure of the HOT-factors allowed for identification of a combination of efficiency metrics. Human fit was evaluated through user satisfaction and patterns of system use; technology fit was evaluated through the measurements of time-on-task and the accuracy of the found answers; and organization fit was evaluated from the perspective of system fit to the existing organizational structure. Results Evaluations produced mixed results and suggested several opportunities for system improvement. On average, participants were satisfied with MedSocket searches and confident in the accuracy of retrieved answers. However, MedSocket did not meet participants’ expectations in terms of download speed, access to information, and relevance of the search results. These mixed results made it necessary to conclude that in the case of MedSocket, technology fit had a significant influence on the human and organization fit. Hence, improving technological capabilities of the system is critical before its net benefits can become noticeable. Conclusions The HOT-fit evaluation framework was instrumental in tailoring the methodology for conducting a comprehensive evaluation of the search engine. Such multidimensional evaluation of the search engine resulted in recommendations for system improvement. PMID:25298813
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Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications
NASA Astrophysics Data System (ADS)
Thanaborvornwiwat, N.; Patanukhom, K.
2018-04-01
Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.
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Automatic Identification of Web-Based Risk Markers for Health Events
Borsa, Diana; Hayward, Andrew C; McKendry, Rachel A; Cox, Ingemar J
2015-01-01
Background The escalating cost of global health care is driving the development of new technologies to identify early indicators of an individual’s risk of disease. Traditionally, epidemiologists have identified such risk factors using medical databases and lengthy clinical studies but these are often limited in size and cost and can fail to take full account of diseases where there are social stigmas or to identify transient acute risk factors. Objective Here we report that Web search engine queries coupled with information on Wikipedia access patterns can be used to infer health events associated with an individual user and automatically generate Web-based risk markers for some of the common medical conditions worldwide, from cardiovascular disease to sexually transmitted infections and mental health conditions, as well as pregnancy. Methods Using anonymized datasets, we present methods to first distinguish individuals likely to have experienced specific health events, and classify them into distinct categories. We then use the self-controlled case series method to find the incidence of health events in risk periods directly following a user’s search for a query category, and compare to the incidence during other periods for the same individuals. Results Searches for pet stores were risk markers for allergy. We also identified some possible new risk markers; for example: searching for fast food and theme restaurants was associated with a transient increase in risk of myocardial infarction, suggesting this exposure goes beyond a long-term risk factor but may also act as an acute trigger of myocardial infarction. Dating and adult content websites were risk markers for sexually transmitted infections, such as human immunodeficiency virus (HIV). Conclusions Web-based methods provide a powerful, low-cost approach to automatically identify risk factors, and support more timely and personalized public health efforts to bring human and economic benefits. PMID:25626480
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Searching for exoplanets using artificial intelligence
NASA Astrophysics Data System (ADS)
Pearson, Kyle A.; Palafox, Leon; Griffith, Caitlin A.
2018-02-01
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called "deep learning" or "deep nets" are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time-series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.
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Diverse task scheduling for individualized requirements in cloud manufacturing
NASA Astrophysics Data System (ADS)
Zhou, Longfei; Zhang, Lin; Zhao, Chun; Laili, Yuanjun; Xu, Lida
2018-03-01
Cloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers' requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users' preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers' requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.
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Robotic Astrobiology: Searching for Life with Rovers
NASA Astrophysics Data System (ADS)
Cabrol, N. A.; Wettergreen, D. S.; Team, L.
2006-05-01
The Life In The Atacama (LITA) project has developed and field tested a long-range, solar-powered, automated rover platform (Zoe) and a science payload assembled to search for microbial life in the Atacama desert. Life is hardly detectable over most of the extent of the driest desert on Earth. Its geological, climatic, and biological evolution provides a unique training ground for designing and testing exploration strategies and life detection methods for the robotic search for life on Mars. LITA opens the path to a new generation of rover missions that will transition from the current study of habitability (MER) to the upcoming search for, and study of, habitats and life on Mars. Zoe's science payload reflects this transition by combining complementary elements, some directed towards the remote sensing of the environment (geology, morphology, mineralogy, weather/climate) for the detection of conditions favorable to microbial habitats and oases along survey traverses, others directed toward the in situ detection of life' signatures (biological and physical, such as biological constructs and patterns). New exploration strategies specifically adapted to the search for microbial life were designed and successfully tested in the Atacama between 2003-2005. They required the development and implementation in the field of new technological capabilities, including navigation beyond the horizon, obstacle avoidance, and "science-on-the-fly" (automated detection of targets of science value), and that of new rover planning tools in the remote science operation center.
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Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G
2016-08-02
Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.
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Derivation of Optimal Cropping Pattern in Part of Hirakud Command using Cuckoo Search
NASA Astrophysics Data System (ADS)
Rath, Ashutosh; Biswal, Sudarsan; Samantaray, Sandeep; Swain, Prakash Chandra, PROF.
2017-08-01
The economicgrowth of a Nation depends on agriculture which relies on the obtainable water resources, available land and crops. The contribution of water in an appropriate quantity at appropriate time plays avitalrole to increase the agricultural production. Optimal utilization of available resources can be achieved by proper planning and management of water resources projects and adoption of appropriate technology. In the present work, the command area of Sambalpur distribrutary System is taken up for investigation. Further, adoption of a fixed cropping pattern causes the reduction of yield. The present study aims at developing different crop planning strategies to increase the net benefit from the command area with minimum investment. Optimization models are developed for Kharif season using LINDO and Cuckoo Search (CS) algorithm for maximization of the net benefits. In process of development of Optimization model the factors such as cultivable land, seeds, fertilizers, man power, water cost, etc. are taken as constraints. The irrigation water needs of major crops and the total available water through canals in the command of Sambalpur Distributary are estimated. LINDO and Cuckoo Search models are formulated and used to derive the optimal cropping pattern yielding maximum net benefits. The net benefits of Rs.585.0 lakhs in Kharif Season are obtained by adopting LINGO and 596.07 lakhs from Cuckoo Search, respectively, whereas the net benefits of 447.0 lakhs is received by the farmers of the locality with the adopting present cropping pattern.
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Phelps, G.A.
2008-01-01
This report describes some simple spatial statistical methods to explore the relationships of scattered points to geologic or other features, represented by points, lines, or areas. It also describes statistical methods to search for linear trends and clustered patterns within the scattered point data. Scattered points are often contained within irregularly shaped study areas, necessitating the use of methods largely unexplored in the point pattern literature. The methods take advantage of the power of modern GIS toolkits to numerically approximate the null hypothesis of randomly located data within an irregular study area. Observed distributions can then be compared with the null distribution of a set of randomly located points. The methods are non-parametric and are applicable to irregularly shaped study areas. Patterns within the point data are examined by comparing the distribution of the orientation of the set of vectors defined by each pair of points within the data with the equivalent distribution for a random set of points within the study area. A simple model is proposed to describe linear or clustered structure within scattered data. A scattered data set of damage to pavement and pipes, recorded after the 1989 Loma Prieta earthquake, is used as an example to demonstrate the analytical techniques. The damage is found to be preferentially located nearer a set of mapped lineaments than randomly scattered damage, suggesting range-front faulting along the base of the Santa Cruz Mountains is related to both the earthquake damage and the mapped lineaments. The damage also exhibit two non-random patterns: a single cluster of damage centered in the town of Los Gatos, California, and a linear alignment of damage along the range front of the Santa Cruz Mountains, California. The linear alignment of damage is strongest between 45? and 50? northwest. This agrees well with the mean trend of the mapped lineaments, measured as 49? northwest.
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Women: Marriage, Career, and Job Satisfaction.
ERIC Educational Resources Information Center
Bisconti, Ann Stouffer
Marriage, childbearing, and employment patterns of women initially surveyed during their entrance to college in 1961 and subsequently surveyed in 1965, 1971, and 1974-5 were investigated. Subjects were questioned on marital status, number and timing of children in the family, employment patterns and shifts, job search patterns, preferred housework…
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The Myth of the L.D. WISC-R Profile.
ERIC Educational Resources Information Center
Miller, Maurice; Walker, Kenneth P.
1981-01-01
The review cites methodological and statistical flaws in studies attempting to identify subtest patterns on the Wechsler Intelligence Scale for Children-Revised indicative of learning disabilities (LD) and concludes that no LD pattern has been found and the search for such a pattern is not justified. (Author/CL)
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Effect of gravito-inertial cues on the coding of orientation in pre-attentive vision.
Stivalet, P; Marendaz, C; Barraclough, L; Mourareau, C
1995-01-01
To see if the spatial reference frame used by pre-attentive vision is specified in a retino-centered frame or in a reference frame integrating visual and nonvisual information (vestibular and somatosensory), subjects were centrifuged in a non-pendular cabin and were asked to search for a target distinguishable from distractors by difference in orientation (Treisman's "pop-out" paradigm [1]). In a control condition, in which subjects were sitting immobilized but not centrifuged, this task gave an asymmetric search pattern: Search was rapid and pre-attentional except when the target was aligned with the horizontal retinal/head axis, in which case search was slow and attentional (2). Results using a centrifuge showed that slow/serial search patterns were obtained when the target was aligned with the subjective horizontal axis (and not with the horizontal retinal/head axis). These data suggest that a multisensory reference frame is used in pre-attentive vision. The results are interpreted in terms of Riccio and Stoffregen's "ecological theory" of orientation in which the vertical and horizontal axes constitute independent reference frames (3).
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NASA Astrophysics Data System (ADS)
Murakami, Hisashi; Gunji, Yukio-Pegio
2017-07-01
Although foraging patterns have long been predicted to optimally adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, i.e., careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, i.e., the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an optimal change of strategy from Brownian-type to Lévy-type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.
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Martinez, Carlos A.; Barr, Kenneth; Kim, Ah-Ram; Reinitz, John
2013-01-01
Synthetic biology offers novel opportunities for elucidating transcriptional regulatory mechanisms and enhancer logic. Complex cis-regulatory sequences—like the ones driving expression of the Drosophila even-skipped gene—have proven difficult to design from existing knowledge, presumably due to the large number of protein-protein interactions needed to drive the correct expression patterns of genes in multicellular organisms. This work discusses two novel computational methods for the custom design of enhancers that employ a sophisticated, empirically validated transcriptional model, optimization algorithms, and synthetic biology. These synthetic elements have both utilitarian and academic value, including improving existing regulatory models as well as evolutionary questions. The first method involves the use of simulated annealing to explore the sequence space for synthetic enhancers whose expression output fit a given search criterion. The second method uses a novel optimization algorithm to find functionally accessible pathways between two enhancer sequences. These paths describe a set of mutations wherein the predicted expression pattern does not significantly vary at any point along the path. Both methods rely on a predictive mathematical framework that maps the enhancer sequence space to functional output. PMID:23732772
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NASA Astrophysics Data System (ADS)
Hew, Y. M.; Linscott, I.; Close, S.
2015-12-01
Meteoroids and orbital debris, collectively referred to as hypervelocity impactors, travel between 7 and 72 km/s in free space. Upon their impact onto the spacecraft, the energy conversion from kinetic to ionization/vaporization occurs within a very brief timescale and results in a small and dense expanding plasma with a very strong optical flash. The radio frequency (RF) emission produced by this plasma can potentially lead to electrical anomalies within the spacecraft. In addition, space weather, such as solar activity and background plasma, can establish spacecraft conditions which can exaggerate the damages done by these impacts. During the impact, a very strong impact flash will be generated. Through the studying of this emission spectrum of the impact, we hope to study the impact generated gas cloud/plasma properties. The impact flash emitted from a ground-based hypervelocity impact test is long expected by many scientists to contain the characteristics of the impact generated plasma, such as plasma temperature and density. This paper presents a method for the time-resolved plasma temperature estimation using three-color visible band photometry data with a global pattern search optimization method. The equilibrium temperature of the plasma can be estimated using an optical model which accounts for both the line emission and continuum emission from the plasma. Using a global pattern search based optimizer, the model can isolate the contribution of the continuum emission versus the line emission from the plasma. The plasma temperature can thus be estimated. Prior to the optimization step, a Gaussian process is also applied to extract the optical emission signal out of the noisy background. The resultant temperature and line-to-continuum emission weighting factor are consistent with the spectrum of the impactor material and current literature.
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Palm-Vein Classification Based on Principal Orientation Features
Zhou, Yujia; Liu, Yaqin; Feng, Qianjin; Yang, Feng; Huang, Jing; Nie, Yixiao
2014-01-01
Personal recognition using palm–vein patterns has emerged as a promising alternative for human recognition because of its uniqueness, stability, live body identification, flexibility, and difficulty to cheat. With the expanding application of palm–vein pattern recognition, the corresponding growth of the database has resulted in a long response time. To shorten the response time of identification, this paper proposes a simple and useful classification for palm–vein identification based on principal direction features. In the registration process, the Gaussian-Radon transform is adopted to extract the orientation matrix and then compute the principal direction of a palm–vein image based on the orientation matrix. The database can be classified into six bins based on the value of the principal direction. In the identification process, the principal direction of the test sample is first extracted to ascertain the corresponding bin. One-by-one matching with the training samples is then performed in the bin. To improve recognition efficiency while maintaining better recognition accuracy, two neighborhood bins of the corresponding bin are continuously searched to identify the input palm–vein image. Evaluation experiments are conducted on three different databases, namely, PolyU, CASIA, and the database of this study. Experimental results show that the searching range of one test sample in PolyU, CASIA and our database by the proposed method for palm–vein identification can be reduced to 14.29%, 14.50%, and 14.28%, with retrieval accuracy of 96.67%, 96.00%, and 97.71%, respectively. With 10,000 training samples in the database, the execution time of the identification process by the traditional method is 18.56 s, while that by the proposed approach is 3.16 s. The experimental results confirm that the proposed approach is more efficient than the traditional method, especially for a large database. PMID:25383715
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Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.
Notarnicola, Ippolito; Petrucci, Cristina; De Jesus Barbosa, Maria Rosimar; Giorgi, Fabio; Stievano, Alessandro; Rocco, Gennaro; Lancia, Loreto
2017-06-01
This study aimed to analyse the concept of "complex adaptive systems." The construct is still nebulous in the literature, and a further explanation of the idea is needed to have a shared knowledge of it. A concept analysis was conducted utilizing Rodgers evolutionary method. The inclusive years of bibliographic search started from 2005 to 2015. The search was conducted at PubMed©, CINAHL© (EBSCO host©), Scopus©, Web of Science©, and Academic Search Premier©. Retrieved papers were critically analysed to explore the attributes, antecedents, and consequences of the concept. Moreover, surrogates, related terms, and a pattern recognition scheme were identified. The concept analysis showed that complex systems are adaptive and have the ability to process information. They can adapt to the environment and consequently evolve. Nursing is a complex adaptive system, and the nursing profession in practice exhibits complex adaptive system characteristics. Complexity science through complex adaptive systems provides new ways of seeing and understanding the mechanisms that underpin the nursing profession. © 2017 John Wiley & Sons Australia, Ltd.
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Mayo-Wilson, Evan; Ng, Sueko Matsumura; Chuck, Roy S; Li, Tianjing
2017-09-05
Systematic reviews should inform American Academy of Ophthalmology (AAO) Preferred Practice Pattern® (PPP) guidelines. The quality of systematic reviews related to the forthcoming Preferred Practice Pattern® guideline (PPP) Refractive Errors & Refractive Surgery is unknown. We sought to identify reliable systematic reviews to assist the AAO Refractive Errors & Refractive Surgery PPP. Systematic reviews were eligible if they evaluated the effectiveness or safety of interventions included in the 2012 PPP Refractive Errors & Refractive Surgery. To identify potentially eligible systematic reviews, we searched the Cochrane Eyes and Vision United States Satellite database of systematic reviews. Two authors identified eligible reviews and abstracted information about the characteristics and quality of the reviews independently using the Systematic Review Data Repository. We classified systematic reviews as "reliable" when they (1) defined criteria for the selection of studies, (2) conducted comprehensive literature searches for eligible studies, (3) assessed the methodological quality (risk of bias) of the included studies, (4) used appropriate methods for meta-analyses (which we assessed only when meta-analyses were reported), (5) presented conclusions that were supported by the evidence provided in the review. We identified 124 systematic reviews related to refractive error; 39 met our eligibility criteria, of which we classified 11 to be reliable. Systematic reviews classified as unreliable did not define the criteria for selecting studies (5; 13%), did not assess methodological rigor (10; 26%), did not conduct comprehensive searches (17; 44%), or used inappropriate quantitative methods (3; 8%). The 11 reliable reviews were published between 2002 and 2016. They included 0 to 23 studies (median = 9) and analyzed 0 to 4696 participants (median = 666). Seven reliable reviews (64%) assessed surgical interventions. Most systematic reviews of interventions for refractive error are low methodological quality. Following widely accepted guidance, such as Cochrane or Institute of Medicine standards for conducting systematic reviews, would contribute to improved patient care and inform future research.
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Restricted random search method based on taboo search in the multiple minima problem
NASA Astrophysics Data System (ADS)
Hong, Seung Do; Jhon, Mu Shik
1997-03-01
The restricted random search method is proposed as a simple Monte Carlo sampling method to search minima fast in the multiple minima problem. This method is based on taboo search applied recently to continuous test functions. The concept of the taboo region instead of the taboo list is used and therefore the sampling of a region near an old configuration is restricted in this method. This method is applied to 2-dimensional test functions and the argon clusters. This method is found to be a practical and efficient method to search near-global configurations of test functions and the argon clusters.
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White, Ryen W; Horvitz, Eric
2014-01-01
Objective To better understand the relationship between online health-seeking behaviors and in-world healthcare utilization (HU) by studies of online search and access activities before and after queries that pursue medical professionals and facilities. Materials and methods We analyzed data collected from logs of online searches gathered from consenting users of a browser toolbar from Microsoft (N=9740). We employed a complementary survey (N=489) to seek a deeper understanding of information-gathering, reflection, and action on the pursuit of professional healthcare. Results We provide insights about HU through the survey, breaking out its findings by different respondent marginalizations as appropriate. Observations made from search logs may be explained by trends observed in our survey responses, even though the user populations differ. Discussion The results provide insights about how users decide if and when to utilize healthcare resources, and how online health information seeking transitions to in-world HU. The findings from both the survey and the logs reveal behavioral patterns and suggest a strong relationship between search behavior and HU. Although the diversity of our survey respondents is limited and we cannot be certain that users visited medical facilities, we demonstrate that it may be possible to infer HU from long-term search behavior by the apparent influence that health concerns and professional advice have on search activity. Conclusions Our findings highlight different phases of online activities around queries pursuing professional healthcare facilities and services. We also show that it may be possible to infer HU from logs without tracking people's physical location, based on the effect of HU on pre- and post-HU search behavior. This allows search providers and others to develop more robust models of interests and preferences by modeling utilization rather than simply the intention to utilize that is expressed in search queries. PMID:23666794
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Chang, Lin-Chau; Mahmood, Riaz; Qureshi, Samina
2017-01-01
Purpose Standardised MedDRA Queries (SMQs) have been developed since the early 2000’s and used by academia, industry, public health, and government sectors for detecting safety signals in adverse event safety databases. The purpose of the present study is to characterize how SMQs are used and the impact in safety analyses for New Drug Application (NDA) and Biologics License Application (BLA) submissions to the United States Food and Drug Administration (USFDA). Methods We used the PharmaPendium database to capture SMQ use in Summary Basis of Approvals (SBoAs) of drugs and biologics approved by the USFDA. Characteristics of the drugs and the SMQ use were employed to evaluate the role of SMQ safety analyses in regulatory decisions and the veracity of signals they revealed. Results A comprehensive search of the SBoAs yielded 184 regulatory submissions approved from 2006 to 2015. Search strategies more frequently utilized restrictive searches with “narrow terms” to enhance specificity over strategies using “broad terms” to increase sensitivity, while some involved modification of search terms. A majority (59%) of 1290 searches used descriptive statistics, however inferential statistics were utilized in 35% of them. Commentary from reviewers and supervisory staff suggested that a small, yet notable percentage (18%) of 1290 searches supported regulatory decisions. The searches with regulatory impact were found in 73 submissions (40% of the submissions investigated). Most searches (75% of 227 searches) with regulatory implications described how the searches were confirmed, indicating prudence in the decision-making process. Conclusions SMQs have an increasing role in the presentation and review of safety analysis for NDAs/BLAs and their regulatory reviews. This study suggests that SMQs are best used for screening process, with descriptive statistics, description of SMQ modifications, and systematic verification of cases which is crucial for drawing regulatory conclusions. PMID:28570569
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Oscillatory patterns in the light curves of five long-term monitored type 1 active galactic nuclei
NASA Astrophysics Data System (ADS)
Kovačević, Andjelka B.; Pérez-Hernández, Ernesto; Popović, Luka Č.; Shapovalova, Alla I.; Kollatschny, Wolfram; Ilić, Dragana
2018-04-01
New combined data of five well-known type 1 active galactic nuclei (AGNs) are probed with a novel hybrid method in a search for oscillatory behaviour. Additional analysis of artificial light curves obtained from the coupled oscillatory models gives confirmation for detected periods that could have a physical background. We find periodic variations in the long-term light curves of 3C 390.3, NGC 4151 and NGC 5548, and E1821 + 643, with correlation coefficients larger than 0.6. We show that the oscillatory patterns of two binary black hole candidates, NGC 5548 and E1821 + 643, correspond to qualitatively different dynamical regimes of chaos and stability, respectively. We demonstrate that the absence of oscillatory patterns in Arp 102B could be the result of a weak coupling between oscillatory mechanisms. This is the first good evidence that 3C 390.3 and Arp 102B, categorized as double-peaked Balmer line objects, have qualitative different dynamics. Our analysis shows a novelty in the oscillatory dynamical patterns of the light curves of these type 1 AGNs.
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Gridless, pattern-driven point cloud completion and extension
NASA Astrophysics Data System (ADS)
Gravey, Mathieu; Mariethoz, Gregoire
2016-04-01
While satellites offer Earth observation with a wide coverage, other remote sensing techniques such as terrestrial LiDAR can acquire very high-resolution data on an area that is limited in extension and often discontinuous due to shadow effects. Here we propose a numerical approach to merge these two types of information, thereby reconstructing high-resolution data on a continuous large area. It is based on a pattern matching process that completes the areas where only low-resolution data is available, using bootstrapped high-resolution patterns. Currently, the most common approach to pattern matching is to interpolate the point data on a grid. While this approach is computationally efficient, it presents major drawbacks for point clouds processing because a significant part of the information is lost in the point-to-grid resampling, and that a prohibitive amount of memory is needed to store large grids. To address these issues, we propose a gridless method that compares point clouds subsets without the need to use a grid. On-the-fly interpolation involves a heavy computational load, which is met by using a GPU high-optimized implementation and a hierarchical pattern searching strategy. The method is illustrated using data from the Val d'Arolla, Swiss Alps, where high-resolution terrestrial LiDAR data are fused with lower-resolution Landsat and WorldView-3 acquisitions, such that the density of points is homogeneized (data completion) and that it is extend to a larger area (data extension).
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NASA Technical Reports Server (NTRS)
McGreevy, Michael W.; Connors, Mary M. (Technical Monitor)
2001-01-01
To support Search Requests and Quick Responses at the Aviation Safety Reporting System (ASRS), four new QUORUM methods have been developed: keyword search, phrase search, phrase generation, and phrase discovery. These methods build upon the core QUORUM methods of text analysis, modeling, and relevance-ranking. QUORUM keyword search retrieves ASRS incident narratives that contain one or more user-specified keywords in typical or selected contexts, and ranks the narratives on their relevance to the keywords in context. QUORUM phrase search retrieves narratives that contain one or more user-specified phrases, and ranks the narratives on their relevance to the phrases. QUORUM phrase generation produces a list of phrases from the ASRS database that contain a user-specified word or phrase. QUORUM phrase discovery finds phrases that are related to topics of interest. Phrase generation and phrase discovery are particularly useful for finding query phrases for input to QUORUM phrase search. The presentation of the new QUORUM methods includes: a brief review of the underlying core QUORUM methods; an overview of the new methods; numerous, concrete examples of ASRS database searches using the new methods; discussion of related methods; and, in the appendices, detailed descriptions of the new methods.
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Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo
2004-05-01
Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).
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NASA Astrophysics Data System (ADS)
Franck, Bas A. M.; Dreschler, Wouter A.; Lyzenga, Johannes
2004-12-01
In this study we investigated the reliability and convergence characteristics of an adaptive multidirectional pattern search procedure, relative to a nonadaptive multidirectional pattern search procedure. The procedure was designed to optimize three speech-processing strategies. These comprise noise reduction, spectral enhancement, and spectral lift. The search is based on a paired-comparison paradigm, in which subjects evaluated the listening comfort of speech-in-noise fragments. The procedural and nonprocedural factors that influence the reliability and convergence of the procedure are studied using various test conditions. The test conditions combine different tests, initial settings, background noise types, and step size configurations. Seven normal hearing subjects participated in this study. The results indicate that the reliability of the optimization strategy may benefit from the use of an adaptive step size. Decreasing the step size increases accuracy, while increasing the step size can be beneficial to create clear perceptual differences in the comparisons. The reliability also depends on starting point, stop criterion, step size constraints, background noise, algorithms used, as well as the presence of drifting cues and suboptimal settings. There appears to be a trade-off between reliability and convergence, i.e., when the step size is enlarged the reliability improves, but the convergence deteriorates. .
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Category-Specific Neural Oscillations Predict Recall Organization During Memory Search
Morton, Neal W.; Kahana, Michael J.; Rosenberg, Emily A.; Baltuch, Gordon H.; Litt, Brian; Sharan, Ashwini D.; Sperling, Michael R.; Polyn, Sean M.
2013-01-01
Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material. PMID:22875859
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Scaling laws of marine predator search behaviour.
Sims, David W; Southall, Emily J; Humphries, Nicolas E; Hays, Graeme C; Bradshaw, Corey J A; Pitchford, Jonathan W; James, Alex; Ahmed, Mohammed Z; Brierley, Andrew S; Hindell, Mark A; Morritt, David; Musyl, Michael K; Righton, David; Shepard, Emily L C; Wearmouth, Victoria J; Wilson, Rory P; Witt, Matthew J; Metcalfe, Julian D
2008-02-28
Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. Lévy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators-sharks, bony fishes, sea turtles and penguins-exhibit Lévy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions.
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Cervellin, Gianfranco; Comelli, Ivan; Lippi, Giuseppe
2017-09-01
Internet-derived information has been recently recognized as a valuable tool for epidemiological investigation. Google Trends, a Google Inc. portal, generates data on geographical and temporal patterns according to specified keywords. The aim of this study was to compare the reliability of Google Trends in different clinical settings, for both common diseases with lower media coverage, and for less common diseases attracting major media coverage. We carried out a search in Google Trends using the keywords "renal colic", "epistaxis", and "mushroom poisoning", selected on the basis of available and reliable epidemiological data. Besides this search, we carried out a second search for three clinical conditions (i.e., "meningitis", "Legionella Pneumophila pneumonia", and "Ebola fever"), which recently received major focus by the Italian media. In our analysis, no correlation was found between data captured from Google Trends and epidemiology of renal colics, epistaxis and mushroom poisoning. Only when searching for the term "mushroom" alone the Google Trends search generated a seasonal pattern which almost overlaps with the epidemiological profile, but this was probably mostly due to searches for harvesting and cooking rather than to for poisoning. The Google Trends data also failed to reflect the geographical and temporary patterns of disease for meningitis, Legionella Pneumophila pneumonia and Ebola fever. The results of our study confirm that Google Trends has modest reliability for defining the epidemiology of relatively common diseases with minor media coverage, or relatively rare diseases with higher audience. Overall, Google Trends seems to be more influenced by the media clamor than by true epidemiological burden. Copyright © 2017 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.
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Emery, Sherry L; Vera, Lisa; Huang, Jidong; Szczypka, Glen
2014-07-01
Awareness and use of electronic cigarettes has rapidly grown in the USA recently, in step with increased product marketing. Using responses to a population survey of US adults, we analysed demographic patterns of exposure to, searching for and sharing of e-cigarette-related information across media platforms. An online survey of 17,522 US adults was conducted in 2013. The nationally representative sample was drawn from GfK Group's KnowledgePanel plus off-panel recruitment. Fixed effects logit models were applied to analyse relationships between exposure to, searching for and sharing of e-cigarette-related information and demographic characteristics, e-cigarette and tobacco use, and media behaviours. High levels of awareness about e-cigarettes were indicated (86% aware; 47% heard through media channels). Exposure to e-cigarette-related information was associated with tobacco use, age, gender, more education, social media use and time spent online. Although relatively small proportions of the sample had searched for (∼5%) or shared (∼2%) e-cigarette information, our analyses indicated demographic patterns to those behaviours. Gender, high income and using social media were associated with searching for e-cigarette information; lesbian, gay and bisexual and less education were associated with sharing. Current tobacco use, age, being Hispanic and time spent online were associated with both searching and sharing. US adults are widely exposed to e-cigarette marketing through the media; such marketing may differentially target specific demographic groups. Further research should longitudinally examine how exposure to, searching for and sharing of e-cigarette information relate to subsequent use of e-cigarettes and/or combustible tobacco. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Searching the Cambridge Structural Database for polymorphs.
van de Streek, Jacco; Motherwell, Sam
2005-10-01
In order to identify all pairs of polymorphs in the Cambridge Structural Database (CSD), a method was devised to automatically compare two crystal structures. The comparison is based on simulated powder diffraction patterns, but with special provisions to deal with differences in unit-cell volumes caused by temperature or pressure. Among the 325,000 crystal structures in the Cambridge Structural Database, 35,000 pairs of crystal structures of the same chemical compound were identified and compared. A total of 7300 pairs of polymorphs were identified, of which 154 previously were unknown.
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Manual of phosphoric acid fuel cell power plant optimization model and computer program
NASA Technical Reports Server (NTRS)
Lu, C. Y.; Alkasab, K. A.
1984-01-01
An optimized cost and performance model for a phosphoric acid fuel cell power plant system was derived and developed into a modular FORTRAN computer code. Cost, energy, mass, and electrochemical analyses were combined to develop a mathematical model for optimizing the steam to methane ratio in the reformer, hydrogen utilization in the PAFC plates per stack. The nonlinear programming code, COMPUTE, was used to solve this model, in which the method of mixed penalty function combined with Hooke and Jeeves pattern search was chosen to evaluate this specific optimization problem.
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Forsetlund, Louise; Kirkehei, Ingvild; Harboe, Ingrid; Odgaard-Jensen, Jan
2012-01-01
This study aims to compare two different search methods for determining the scope of a requested systematic review or health technology assessment. The first method (called the Direct Search Method) included performing direct searches in the Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessments (HTA). Using the comparison method (called the NHS Search Engine) we performed searches by means of the search engine of the British National Health Service, NHS Evidence. We used an adapted cross-over design with a random allocation of fifty-five requests for systematic reviews. The main analyses were based on repeated measurements adjusted for the order in which the searches were conducted. The Direct Search Method generated on average fewer hits (48 percent [95 percent confidence interval {CI} 6 percent to 72 percent], had a higher precision (0.22 [95 percent CI, 0.13 to 0.30]) and more unique hits than when searching by means of the NHS Search Engine (50 percent [95 percent CI, 7 percent to 110 percent]). On the other hand, the Direct Search Method took longer (14.58 minutes [95 percent CI, 7.20 to 21.97]) and was perceived as somewhat less user-friendly than the NHS Search Engine (-0.60 [95 percent CI, -1.11 to -0.09]). Although the Direct Search Method had some drawbacks such as being more time-consuming and less user-friendly, it generated more unique hits than the NHS Search Engine, retrieved on average fewer references and fewer irrelevant results.
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A Western Dietary Pattern Increases Prostate Cancer Risk: A Systematic Review and Meta-Analysis
Fabiani, Roberto; Minelli, Liliana; Bertarelli, Gaia; Bacci, Silvia
2016-01-01
Dietary patterns were recently applied to examine the relationship between eating habits and prostate cancer (PC) risk. While the associations between PC risk with the glycemic index and Mediterranean score have been reviewed, no meta-analysis is currently available on dietary patterns defined by “a posteriori” methods. A literature search was carried out (PubMed, Web of Science) to identify studies reporting the relationship between dietary patterns and PC risk. Relevant dietary patterns were selected and the risks estimated were calculated by a random-effect model. Multivariable-adjusted odds ratios (ORs), for a first-percentile increase in dietary pattern score, were combined by a dose-response meta-analysis. Twelve observational studies were included in the meta-analysis which identified a “Healthy pattern” and a “Western pattern”. The Healthy pattern was not related to PC risk (OR = 0.96; 95% confidence interval (CI): 0.88–1.04) while the Western pattern significantly increased it (OR = 1.34; 95% CI: 1.08–1.65). In addition, the “Carbohydrate pattern”, which was analyzed in four articles, was positively associated with a higher PC risk (OR = 1.64; 95% CI: 1.35–2.00). A significant linear trend between the Western (p = 0.011) pattern, the Carbohydrate (p = 0.005) pattern, and the increment of PC risk was observed. The small number of studies included in the meta-analysis suggests that further investigation is necessary to support these findings. PMID:27754328
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Query-seeded iterative sequence similarity searching improves selectivity 5–20-fold
Li, Weizhong; Lopez, Rodrigo
2017-01-01
Abstract Iterative similarity search programs, like psiblast, jackhmmer, and psisearch, are much more sensitive than pairwise similarity search methods like blast and ssearch because they build a position specific scoring model (a PSSM or HMM) that captures the pattern of sequence conservation characteristic to a protein family. But models are subject to contamination; once an unrelated sequence has been added to the model, homologs of the unrelated sequence will also produce high scores, and the model can diverge from the original protein family. Examination of alignment errors during psiblast PSSM contamination suggested a simple strategy for dramatically reducing PSSM contamination. psiblast PSSMs are built from the query-based multiple sequence alignment (MSA) implied by the pairwise alignments between the query model (PSSM, HMM) and the subject sequences in the library. When the original query sequence residues are inserted into gapped positions in the aligned subject sequence, the resulting PSSM rarely produces alignment over-extensions or alignments to unrelated sequences. This simple step, which tends to anchor the PSSM to the original query sequence and slightly increase target percent identity, can reduce the frequency of false-positive alignments more than 20-fold compared with psiblast and jackhmmer, with little loss in search sensitivity. PMID:27923999
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A novel harmony search-K means hybrid algorithm for clustering gene expression data
Nazeer, KA Abdul; Sebastian, MP; Kumar, SD Madhu
2013-01-01
Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms. PMID:23390351
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A novel harmony search-K means hybrid algorithm for clustering gene expression data.
Nazeer, Ka Abdul; Sebastian, Mp; Kumar, Sd Madhu
2013-01-01
Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.
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NASA Technical Reports Server (NTRS)
Johnson, Jay K.
1991-01-01
Data recovered as the result of a recent field project designed to test a model of the distribution of protohistoric settlement in an unusual physiographic zone in eastern Mississippi are examined using GIS based techniques to manipulate soil and stream distance information. Significant patterning is derived. The generally thin soils and uniform substratum of the Black Prairie in combination with a distinctive settlement pattern offer a promising opportunity for the search for site specific characteristics within airborne imagery. Landsat TM data provide information on modern ground cover which is used as a mask to select areas in which a multivariate search for archaeological site signatures within a TIMS image is most likely to prove fruitful.
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Nadzirin, Nurul; Willett, Peter; Artymiuk, Peter J.; Firdaus-Raih, Mohd
2013-01-01
We describe a server that allows the interrogation of the Protein Data Bank for hypothetical 3D side chain patterns that are not limited to known patterns from existing 3D structures. A minimal side chain description allows a variety of side chain orientations to exist within the pattern, and generic side chain types such as acid, base and hydroxyl-containing can be additionally deployed in the search query. Moreover, only a subset of distances between the side chains need be specified. We illustrate these capabilities in case studies involving arginine stacks, serine-acid group arrangements and multiple catalytic triad-like configurations. The IMAAAGINE server can be accessed at http://mfrlab.org/grafss/imaaagine/. PMID:23716645
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Supervised learning of tools for content-based search of image databases
NASA Astrophysics Data System (ADS)
Delanoy, Richard L.
1996-03-01
A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.
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GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns
Senin, Pavel; Lin, Jessica; Wang, Xing; ...
2018-02-23
The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discoverymore » that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.« less
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GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Senin, Pavel; Lin, Jessica; Wang, Xing
The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discoverymore » that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.« less
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GeNemo: a search engine for web-based functional genomic data.
Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng
2016-07-08
A set of new data types emerged from functional genomic assays, including ChIP-seq, DNase-seq, FAIRE-seq and others. The results are typically stored as genome-wide intensities (WIG/bigWig files) or functional genomic regions (peak/BED files). These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. GeNemo searches user-input data against online functional genomic datasets, including the entire collection of ENCODE and mouse ENCODE datasets. Unlike text-based search engines, GeNemo's searches are based on pattern matching of functional genomic regions. This distinguishes GeNemo from text or DNA sequence searches. The user can input any complete or partial functional genomic dataset, for example, a binding intensity file (bigWig) or a peak file. GeNemo reports any genomic regions, ranging from hundred bases to hundred thousand bases, from any of the online ENCODE datasets that share similar functional (binding, modification, accessibility) patterns. This is enabled by a Markov Chain Monte Carlo-based maximization process, executed on up to 24 parallel computing threads. By clicking on a search result, the user can visually compare her/his data with the found datasets and navigate the identified genomic regions. GeNemo is available at www.genemo.org. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Specialized microbial databases for inductive exploration of microbial genome sequences
Fang, Gang; Ho, Christine; Qiu, Yaowu; Cubas, Virginie; Yu, Zhou; Cabau, Cédric; Cheung, Frankie; Moszer, Ivan; Danchin, Antoine
2005-01-01
Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison. PMID:15698474
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Plumb, Andrew A; Phillips, Peter; Spence, Graeme; Mallett, Susan; Taylor, Stuart A; Halligan, Steve; Fanshawe, Thomas
2017-08-01
Purpose To investigate the effect of increasing navigation speed on the visual search and decision making during polyp identification for computed tomography (CT) colonography Materials and Methods Institutional review board permission was obtained to use deidentified CT colonography data for this prospective reader study. After obtaining informed consent from the readers, 12 CT colonography fly-through examinations that depicted eight polyps were presented at four different fixed navigation speeds to 23 radiologists. Speeds ranged from 1 cm/sec to 4.5 cm/sec. Gaze position was tracked by using an infrared eye tracker, and readers indicated that they saw a polyp by clicking a mouse. Patterns of searching and decision making by speed were investigated graphically and by multilevel modeling. Results Readers identified polyps correctly in 56 of 77 (72.7%) of viewings at the slowest speed but in only 137 of 225 (60.9%) of viewings at the fastest speed (P = .004). They also identified fewer false-positive features at faster speeds (42 of 115; 36.5%) of videos at slowest speed, 89 of 345 (25.8%) at fastest, P = .02). Gaze location was highly concentrated toward the central quarter of the screen area at faster speeds (mean gaze points at slowest speed vs fastest speed, 86% vs 97%, respectively). Conclusion Faster navigation speed at endoluminal CT colonography led to progressive restriction of visual search patterns. Greater speed also reduced both true-positive and false-positive colorectal polyp identification. © RSNA, 2017 Online supplemental material is available for this article.
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Characterizing Internet Searchers of Smoking Cessation Information
Graham, Amanda L
2006-01-01
Background The Internet is a viable channel to deliver evidence-based smoking cessation treatment that has the potential to make a large population impact on reducing smoking prevalence. There is high demand for smoking cessation information and support on the Internet. Approximately 7% (10.2 million) of adult American Internet users have searched for information on quitting smoking. Little is known about these individuals, their smoking status, what type of cessation services they are seeking on the Internet, or how frequently these searches for cessation information are conducted. Objective The primary goal of this study was to characterize individuals who search for smoking cessation information on the Internet to determine appropriate triage and treatment strategies. The secondary goal was to estimate the incidence of searches for cessation information using publicly available search engine data. Methods We recruited individuals who clicked on a link to a leading smoking cessation website (QuitNet) from within the results of a search engine query. Individuals were “intercepted” before seeing the QuitNet home page and were invited to participate in the study. Those accepting the invitation were routed to an online survey about demographics, smoking characteristics, preferences for specific cessation services, and Internet search patterns. To determine the generalizability of our sample, national datasets on search engine usage patterns, market share, and keyword rankings were examined. These datasets were then used to estimate the number of queries for smoking cessation information each year. Results During the 10-day study period, 2265 individuals were recruited and 29% (N = 655) responded. Of these, 59% were female and overall tended to be younger than the previously characterized general Internet population. Most (76%) respondents were current smokers; 17% had quit within the last 7 days, and 7% had quit more than 7 days ago. Slightly more than half of active smokers (53%) indicated that they were planning to quit in the next 30 days. Smokers were more likely to seek information on how to quit and on medications; former smokers were more interested in how to cope with withdrawal. All participants rated withdrawal information and individually tailored information as being more useful, while displaying little interest in telephone counseling, expert support, or peer support. Publicly available data from large search engines suggest that 4 million Americans search for resources on smoking cessation each year. Conclusions This study adds to the limited data available on individuals who search for smoking cessation information on the Internet, supports the prior estimates of the size of the population, and indicates that these individuals are in appropriate stages for both active cessation interventions and aggressive relapse prevention efforts. Continued development and evaluation of online interventions is warranted, and organizations seeking to promote cessation should carefully evaluate the Internet as a possible modality for treatment and as a gateway to other traditional programs. PMID:17032633
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Expertise in complex decision making: the role of search in chess 70 years after de Groot.
Connors, Michael H; Burns, Bruce D; Campitelli, Guillermo
2011-01-01
One of the most influential studies in all expertise research is de Groot's (1946) study of chess players, which suggested that pattern recognition, rather than search, was the key determinant of expertise. Many changes have occurred in the chess world since de Groot's study, leading some authors to argue that the cognitive mechanisms underlying expertise have also changed. We decided to replicate de Groot's study to empirically test these claims and to examine whether the trends in the data have changed over time. Six Grandmasters, five International Masters, six Experts, and five Class A players completed the think-aloud procedure for two chess positions. Findings indicate that Grandmasters and International Masters search more quickly than Experts and Class A players, and that both groups today search substantially faster than players in previous studies. The findings, however, support de Groot's overall conclusions and are consistent with predictions made by pattern recognition models. Copyright © 2011 Cognitive Science Society, Inc.
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Evaluating, Comparing, and Interpreting Protein Domain Hierarchies
2014-01-01
Abstract Arranging protein domain sequences hierarchically into evolutionarily divergent subgroups is important for investigating evolutionary history, for speeding up web-based similarity searches, for identifying sequence determinants of protein function, and for genome annotation. However, whether or not a particular hierarchy is optimal is often unclear, and independently constructed hierarchies for the same domain can often differ significantly. This article describes methods for statistically evaluating specific aspects of a hierarchy, for probing the criteria underlying its construction and for direct comparisons between hierarchies. Information theoretical notions are used to quantify the contributions of specific hierarchical features to the underlying statistical model. Such features include subhierarchies, sequence subgroups, individual sequences, and subgroup-associated signature patterns. Underlying properties are graphically displayed in plots of each specific feature's contributions, in heat maps of pattern residue conservation, in “contrast alignments,” and through cross-mapping of subgroups between hierarchies. Together, these approaches provide a deeper understanding of protein domain functional divergence, reveal uncertainties caused by inconsistent patterns of sequence conservation, and help resolve conflicts between competing hierarchies. PMID:24559108
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The web server of IBM's Bioinformatics and Pattern Discovery group: 2004 update
Huynh, Tien; Rigoutsos, Isidore
2004-01-01
In this report, we provide an update on the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server, which is operational around the clock, provides access to a large number of methods that have been developed and published by the group's members. There is an increasing number of problems that these tools can help tackle; these problems range from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences, the identification—directly from sequence—of structural deviations from α-helicity and the annotation of amino acid sequences for antimicrobial activity. Additionally, annotations for more than 130 archaeal, bacterial, eukaryotic and viral genomes are now available on-line and can be searched interactively. The tools and code bundles continue to be accessible from http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/. PMID:15215340
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The web server of IBM's Bioinformatics and Pattern Discovery group: 2004 update.
Huynh, Tien; Rigoutsos, Isidore
2004-07-01
In this report, we provide an update on the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server, which is operational around the clock, provides access to a large number of methods that have been developed and published by the group's members. There is an increasing number of problems that these tools can help tackle; these problems range from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences, the identification--directly from sequence--of structural deviations from alpha-helicity and the annotation of amino acid sequences for antimicrobial activity. Additionally, annotations for more than 130 archaeal, bacterial, eukaryotic and viral genomes are now available on-line and can be searched interactively. The tools and code bundles continue to be accessible from http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.
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Decay Pattern of Pygmy States Observed in Neutron-Rich Ne26
NASA Astrophysics Data System (ADS)
Gibelin, J.; Beaumel, D.; Motobayashi, T.; Blumenfeld, Y.; Aoi, N.; Baba, H.; Elekes, Z.; Fortier, S.; Frascaria, N.; Fukuda, N.; Gomi, T.; Ishikawa, K.; Kondo, Y.; Kubo, T.; Lima, V.; Nakamura, T.; Saito, A.; Satou, Y.; Scarpaci, J.-A.; Takeshita, E.; Takeuchi, S.; Teranishi, T.; Togano, Y.; Vinodkumar, A. M.; Yanagisawa, Y.; Yoshida, K.
2008-11-01
Coulomb excitation of the exotic neutron-rich nucleus Ne26 on a Pb208 target was measured at 58MeV/u in order to search for low-lying E1 strength above the neutron emission threshold. This radioactive beam experiment was carried out at the RIKEN Accelerator Research Facility. Using the invariant mass method in the Ne25+n channel, we observe a sizable amount of E1 strength between 6 and 10 MeV excitation energy. By performing a multipole decomposition of the differential cross section, a reduced dipole transition probability of B(E1)=0.49±0.16e2fm2 is deduced, corresponding to 4.9±1.6% of the Thomas-Reiche-Kuhn sum rule. For the first time, the decay pattern of low-lying strength in a neutron-rich nucleus is measured. The extracted decay pattern is not consistent with several mean-field theory descriptions of the pygmy states.
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Detecting submerged objects: the application of side scan sonar to forensic contexts.
Schultz, John J; Healy, Carrie A; Parker, Kenneth; Lowers, Bim
2013-09-10
Forensic personnel must deal with numerous challenges when searching for submerged objects. While traditional water search methods have generally involved using dive teams, remotely operated vehicles (ROVs), and water scent dogs for cases involving submerged objects and bodies, law enforcement is increasingly integrating multiple methods that include geophysical technologies. There are numerous advantages for integrating geophysical technologies, such as side scan sonar and ground penetrating radar (GPR), with more traditional search methods. Overall, these methods decrease the time involved searching, in addition to increasing area searched. However, as with other search methods, there are advantages and disadvantages when using each method. For example, in instances with excessive aquatic vegetation or irregular bottom terrain, it may not be possible to discern a submersed body with side scan sonar. As a result, forensic personnel will have the highest rate of success during searches for submerged objects when integrating multiple search methods, including deploying multiple geophysical technologies. The goal of this paper is to discuss the methodology of various search methods that are employed for submerged objects and how these various methods can be integrated as part of a comprehensive protocol for water searches depending upon the type of underwater terrain. In addition, two successful case studies involving the search and recovery of a submerged human body using side scan sonar are presented to illustrate the successful application of integrating a geophysical technology with divers when searching for a submerged object. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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Small-Tip-Angle Spokes Pulse Design Using Interleaved Greedy and Local Optimization Methods
Grissom, William A.; Khalighi, Mohammad-Mehdi; Sacolick, Laura I.; Rutt, Brian K.; Vogel, Mika W.
2013-01-01
Current spokes pulse design methods can be grouped into methods based either on sparse approximation or on iterative local (gradient descent-based) optimization of the transverse-plane spatial frequency locations visited by the spokes. These two classes of methods have complementary strengths and weaknesses: sparse approximation-based methods perform an efficient search over a large swath of candidate spatial frequency locations but most are incompatible with off-resonance compensation, multifrequency designs, and target phase relaxation, while local methods can accommodate off-resonance and target phase relaxation but are sensitive to initialization and suboptimal local cost function minima. This article introduces a method that interleaves local iterations, which optimize the radiofrequency pulses, target phase patterns, and spatial frequency locations, with a greedy method to choose new locations. Simulations and experiments at 3 and 7 T show that the method consistently produces single- and multifrequency spokes pulses with lower flip angle inhomogeneity compared to current methods. PMID:22392822
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ERIC Educational Resources Information Center
Mancall, Jacqueline C.; Deskins, Dreama
This report assesses the impact of instruction in online bibliographic database searching on high school students' use of library materials and facilities in three Delaware secondary schools (one public, one parochial, and one private) during the spring of 1984. Most students involved in the analysis were given a brief explanation of online…
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Going beyond Google for Faster and Smarter Web Searching
ERIC Educational Resources Information Center
Vine, Rita
2004-01-01
With more than 4 billion web pages in its database, Google is suitable for many different kinds of searches. When you know what you are looking for, Google can be a pretty good first choice, as long as you want to search a word pattern that can be expected to appear on any results pages. The problem starts when you don't know exactly what you're…
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Ling, Rebecca; Lee, Joon
2016-10-12
Infodemiology can offer practical and feasible health research applications through the practice of studying information available on the Web. Google Trends provides publicly accessible information regarding search behaviors in a population, which may be studied and used for health campaign evaluation and disease monitoring. Additional studies examining the use and effectiveness of Google Trends for these purposes remain warranted. The objective of our study was to explore the use of infodemiology in the context of health campaign evaluation and chronic disease monitoring. It was hypothesized that following a launch of a campaign, there would be an increase in information seeking behavior on the Web. Second, increasing and decreasing disease patterns in a population would be associated with search activity patterns. This study examined 4 different diseases: human immunodeficiency virus (HIV) infection, stroke, colorectal cancer, and marijuana use. Using Google Trends, relative search volume data were collected throughout the period of February 2004 to January 2015. Campaign information and disease statistics were obtained from governmental publications. Search activity trends were graphed and assessed with disease trends and the campaign interval. Pearson product correlation statistics and joinpoint methodology analyses were used to determine significance. Disease patterns and online activity across all 4 diseases were significantly correlated: HIV infection (r=.36, P<.001), stroke (r=.40, P<.001), colorectal cancer (r= -.41, P<.001), and substance use (r=.64, P<.001). Visual inspection and the joinpoint analysis showed significant correlations for the campaigns on colorectal cancer and marijuana use in stimulating search activity. No significant correlations were observed for the campaigns on stroke and HIV regarding search activity. The use of infoveillance shows promise as an alternative and inexpensive solution to disease surveillance and health campaign evaluation. Further research is needed to understand Google Trends as a valid and reliable tool for health research.
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[Selective attention and schizophrenia before the administration of neuroleptics].
Lussier, I; Stip, E
1999-01-01
In recent years, the presence of attention deficits has been recognized as a key feature of schizophrenia. Past studies reveal that selective attention, or the ability to select relevant information while ignoring simultaneously irrelevant information, is disturbed in schizophrenic patients. According to Treisman feature-integration theory of selective attention, visual search for conjunctive targets (e.g., shape and color) requires controlled processes, that necessitate attention and operate in a serial manner. Reaction times (RTs) are therefore function of the number of stimuli in the display. When subjects are asked to detect the presence or absence of a target in an array of a variable number of stimuli, different performance patterns are expected for positive (present target) and negative trials (absent target). For positive trials, a self-terminating search is triggered, that is, the search is ended when the target is encountered. For negative trials, an exhaustive search strategy is displayed, where each stimulus is examined before the search can end; the RT slope pattern is thus double that of the positive trials. To assess the integrity of these processes, thirteen drug naive schizophrenic patients were compared to twenty normal control subjects. Neuroleptic naive patients were chosen as subjects to avoid the potential influence of medication and chronicity-related factors on performance. The subjects had to specify as fast as possible the presence or absence of the target in an array of a variable number of stimuli presented in a circular display, and comprising or not the target. Results showed that the patients can use self-terminating search strategies as well as normal control subjects. However, their ability to trigger exhaustive search strategies is impaired. Not only were patients slower than controls, but their pattern of RT results was different. These results argue in favor of an early impairment in selective attention capacities in schizophrenia, which appears before the introduction of neuroleptics. The attention performance was also shown to present some association to clinical symptoms.
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Rapid Prototyping Technologies and their Applications in Prosthodontics, a Review of Literature
Torabi, Kianoosh; Farjood, Ehsan; Hamedani, Shahram
2015-01-01
The early computer-aided design/computer-aided manufacturing (CAD/CAM) systems were relied exclusively on subtractive methods. In recent years, additive methods by employing rapid prototyping (RP) have progressed rapidly in various fields of dentistry as they have the potential to overcome known drawbacks of subtractive techniques such as fit problems. RP techniques have been exploited to build complex 3D models in medicine since the 1990s. RP has recently proposed successful applications in various dental fields, such as fabrication of implant surgical guides, frameworks for fixed and removable partial dentures, wax patterns for the dental prosthesis, zirconia prosthesis and molds for metal castings, and maxillofacial prosthesis and finally, complete dentures. This paper aimed to offer a comprehensive literature review of various RP methods, particularly in dentistry, that are expected to bring many improvements to the field. A search was made through MEDLINE database and Google scholar search engine. The keywords; ‘rapid prototyping’ and ‘dentistry’ were searched in title/abstract of publications; limited to 2003 to 2013, concerning past decade. The inclusion criterion was the technical researches that predominately included laboratory procedures. The exclusion criterion was meticulous clinical and excessive technical procedures. A total of 106 articles were retrieved, recited by authors and only 50 met the specified inclusion criteria for this review. Selected articles had used rapid prototyping techniques in various fields in dentistry through different techniques. This review depicted the different laboratory procedures employed in this method and confirmed that RP technique have been substantially feasible in dentistry. With advancement in various RP systems, it is possible to benefit from this technique in different dental practices, particularly in implementing dental prostheses for different applications. PMID:25759851
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Rapid Prototyping Technologies and their Applications in Prosthodontics, a Review of Literature.
Torabi, Kianoosh; Farjood, Ehsan; Hamedani, Shahram
2015-03-01
The early computer-aided design/computer-aided manufacturing (CAD/CAM) systems were relied exclusively on subtractive methods. In recent years, additive methods by employing rapid prototyping (RP) have progressed rapidly in various fields of dentistry as they have the potential to overcome known drawbacks of subtractive techniques such as fit problems. RP techniques have been exploited to build complex 3D models in medicine since the 1990s. RP has recently proposed successful applications in various dental fields, such as fabrication of implant surgical guides, frameworks for fixed and removable partial dentures, wax patterns for the dental prosthesis, zirconia prosthesis and molds for metal castings, and maxillofacial prosthesis and finally, complete dentures. This paper aimed to offer a comprehensive literature review of various RP methods, particularly in dentistry, that are expected to bring many improvements to the field. A search was made through MEDLINE database and Google scholar search engine. The keywords; 'rapid prototyping' and 'dentistry' were searched in title/abstract of publications; limited to 2003 to 2013, concerning past decade. The inclusion criterion was the technical researches that predominately included laboratory procedures. The exclusion criterion was meticulous clinical and excessive technical procedures. A total of 106 articles were retrieved, recited by authors and only 50 met the specified inclusion criteria for this review. Selected articles had used rapid prototyping techniques in various fields in dentistry through different techniques. This review depicted the different laboratory procedures employed in this method and confirmed that RP technique have been substantially feasible in dentistry. With advancement in various RP systems, it is possible to benefit from this technique in different dental practices, particularly in implementing dental prostheses for different applications.
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Effect of environmental factors on Internet searches related to sinusitis.
Willson, Thomas J; Lospinoso, Joshua; Weitzel, Erik K; McMains, Kevin C
2015-11-01
Sinusitis significantly affects the population of the United States, exacting direct cost and lost productivity. Patients are likely to search the Internet for information related to their health before seeking care by a healthcare professional. Utilizing data generated from these searches may serve as an epidemiologic surrogate. A retrospective time series analysis was performed. Google search trend data from the Dallas-Fort Worth metro region for the years 2012 and 2013 were collected from www.google.com/trends for terms related to sinusitis based on literature outlining the most important symptoms for diagnosis. Additional terms were selected based on common English language terms used to describe the disease. Twelve months of data from the same time period and location for common pollutants (nitrogen dioxide, ozone, sulfur dioxide, and particulates), pollen and mold counts, and influenza-like illness were also collected. Statistical analysis was performed using Pearson correlation coefficients, and potential search activity predictors were assessed using autoregressive integrated moving average. Pearson correlation was strongest between the terms congestion and influenza-like illness (r=0.615), and sinus and influenza-like illness (r=0.534) and nitrogen dioxide (r=0.487). Autoregressive integrated moving average analysis revealed ozone, influenza-like illness, and nitrogen dioxide levels to be potential predictors for sinus pressure searches, with estimates of 0.118, 0.349, and 0.438, respectively. Nitrogen dioxide was also a potential predictor for the terms congestion and sinus, with estimates of 0.191 and 0.272, respectively. Google search activity for related terms follow the pattern of seasonal influenza-like illness and nitrogen dioxide. These data highlight the epidemiologic potential of this novel surveillance method. NA. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.
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Adolescents Searching for Health Information on the Internet: An Observational Study
Derry, Holly A; Resnick, Paul J; Richardson, Caroline R
2003-01-01
Background Adolescents' access to health information on the Internet is partly a function of their ability to search for and find answers to their health-related questions. Adolescents may have unique health and computer literacy needs. Although many surveys, interviews, and focus groups have been utilized to understand the information-seeking and information-retrieval behavior of adolescents looking for health information online, we were unable to locate observations of individual adolescents that have been conducted in this context. Objective This study was designed to understand how adolescents search for health information using the Internet and what implications this may have on access to health information. Methods A convenience sample of 12 students (age 12-17 years) from 1 middle school and 2 high schools in southeast Michigan were provided with 6 health-related questions and asked to look for answers using the Internet. Researchers recorded 68 specific searches using software that captured screen images as well as synchronized audio recordings. Recordings were reviewed later and specific search techniques and strategies were coded. A qualitative review of the verbal communication was also performed. Results Out of 68 observed searches, 47 (69%) were successful in that the adolescent found a correct and useful answer to the health question. The majority of sites that students attempted to access were retrieved directly from search engine results (77%) or a search engine's recommended links (10%); only a small percentage were directly accessed (5%) or linked from another site (7%). The majority (83%) of followed links from search engine results came from the first 9 results. Incorrect spelling (30 of 132 search terms), number of pages visited within a site (ranging from 1-15), and overall search strategy (eg, using a search engine versus directly accessing a site), were each important determinants of success. Qualitative analysis revealed that participants used a trial-and-error approach to formulate search strings, scanned pages randomly instead of systematically, and did not consider the source of the content when searching for health information. Conclusions This study provides a useful snapshot of current adolescent searching patterns. The results have implications for constructing realistic simulations of adolescent search behavior, improving distribution and usefulness of Web sites with health information relevant to adolescents, and enhancing educators' knowledge of what specific pitfalls students are likely to encounter. PMID:14713653
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Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.
2016-01-01
Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831
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Interactive design of generic chemical patterns.
Schomburg, Karen T; Wetzer, Lars; Rarey, Matthias
2013-07-01
Every medicinal chemist has to create chemical patterns occasionally for querying databases, applying filters or describing functional groups. However, the representations of chemical patterns have been so far limited to languages with highly complex syntax, handicapping the application of patterns. Graphic pattern editors similar to chemical editors can facilitate the work with patterns. In this article, we review the interfaces of frequently used web search engines for chemical patterns. We take a look at pattern editing concepts of standalone chemical editors and finally present a completely new, unpublished graphical approach to pattern design, the SMARTSeditor. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Infodemiology of Alcohol Use in Hong Kong Mentioned on Blogs: Infoveillance Study
2013-01-01
Background In 2007 and 2008, the beer and wine tax in Hong Kong was halved and then abolished, resulting in an increase of alcohol consumption. The prevalence of the Internet and a high blogging rate by adolescents and adults present a unique opportunity to study drinking patterns by infodemiology. Objective To assess and explain the online use of alcohol-related Chinese keywords and to validate blog searching as an infoveillance method for surveying changes in drinking patterns (eg, alcohol type) in Hong Kong people (represented by bloggers on a Hong Kong–based Chinese blogging site) in 2005-2010. Methods Blog searching was done using a blog search engine, Google Blog Search, in the archives of a Hong Kong–based blog service provider, MySinaBlog from 2005-2010. Three groups of Chinese keywords, each representing a specific alcohol-related concept, were used: (1) “alcohol” (ie, the control concept), (2) “beer or wine”, and (3) “spirit”. The resulting blog posts were analyzed quantitatively using infodemiological metrics and correlation coefficients, and qualitatively by manual effort. The infodemiological metrics were (1) apparent prevalence, (2) actual prevalence, (3) prevalence rate, and (4) prevalence ratio. Pearson and Spearman correlations were calculated for prevalence rates and ratios with respect to per capita alcohol consumption. Manual analysis focused on (1) blog author characteristics (ie, authorship, sex, and age), and (2) blog content (ie, frequency of keywords, description of a discrete episode of alcohol drinking, drinking amount, and genres). Results The online use of alcohol-related concepts increased noticeably for “alcohol” in 2008 and “spirit” in 2008-2009 but declined for “beer or wine” over the years. Correlation between infodemiological and epidemiological data was only significant for the “alcohol” prevalence rate. Most blogs were managed by single authors. Their sex distribution was even, and the majority were aged 18 and above. Not all Chinese keywords were found. Many of the blog posts did not describe a discrete episode of alcohol drinking and were classified as personal diary, opinion, or emotional outlets. The rest lacked information on drinking amount, which hindered assessment of binge drinking. Conclusions The prevalence of alcohol-related Chinese keywords online was attributed to many different factors, including spam, and hence not a specific reflection of local drinking patterns. Correlation between infodemiological data (represented by prevalence rates and ratios of alcohol-related concepts) and epidemiological data (represented by per capita alcohol consumption) was poor. Many blog posts were affective rather than informative in nature. Semantic analysis of blog content was recommended given enough expertise and resources. PMID:23999327
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qPMS9: An Efficient Algorithm for Quorum Planted Motif Search
NASA Astrophysics Data System (ADS)
Nicolae, Marius; Rajasekaran, Sanguthevar
2015-01-01
Discovering patterns in biological sequences is a crucial problem. For example, the identification of patterns in DNA sequences has resulted in the determination of open reading frames, identification of gene promoter elements, intron/exon splicing sites, and SH RNAs, location of RNA degradation signals, identification of alternative splicing sites, etc. In protein sequences, patterns have led to domain identification, location of protease cleavage sites, identification of signal peptides, protein interactions, determination of protein degradation elements, identification of protein trafficking elements, discovery of short functional motifs, etc. In this paper we focus on the identification of an important class of patterns, namely, motifs. We study the (l, d) motif search problem or Planted Motif Search (PMS). PMS receives as input n strings and two integers l and d. It returns all sequences M of length l that occur in each input string, where each occurrence differs from M in at most d positions. Another formulation is quorum PMS (qPMS), where the motif appears in at least q% of the strings. We introduce qPMS9, a parallel exact qPMS algorithm that offers significant runtime improvements on DNA and protein datasets. qPMS9 solves the challenging DNA (l, d)-instances (28, 12) and (30, 13). The source code is available at https://code.google.com/p/qpms9/.
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Dunn, Julia C; Turner, Hugo C; Tun, Aung; Anderson, Roy M
2016-01-27
Soil-transmitted helminth (STH) infections of humans fall within the World Health Organization's (WHO) grouping termed the neglected tropical diseases (NTDs). It is estimated that they affect approximately 1.4 billion people worldwide. A significant proportion of these infections are in the population of Southeast Asia. This review analyses published data on STH prevalence and intensity in Southeast Asia over the time period of 1900 to the present to describe age related patterns in these epidemiological measures. This is with a focus on the four major parasite species affecting humans; namely Ascaris lumbricoides, Trichuris trichiura and the hookworms; Necator americanus and Ancylostoma duodenale. Data were also collected on the diagnostic methods used in the published surveys and how the studies were designed to facilitate comparative analyses of recorded patterns and changes therein over time. PubMed, Google Scholar, EMBASE, ISI Web of Science, Cochrane Database of Systematic Reviews and the Global Atlas of Helminth Infections search engines were used to identify studies on STH in Southeast Asia with the search based on the major key words, and variants on, "soil-transmitted helminth" "Ascaris" "Trichuris" "hookworm" and the country name. A total of 280 studies satisfied the inclusion criteria from 11 Southeast Asian countries; Brunei, Cambodia, Indonesia, Lao People's Democratic Republic (Lao PDR), Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste and Vietnam. It was concluded that the epidemiological patterns of STH infection by age and species mix in Southeast Asia are similar to those reported in other parts of the world. In the published studies there were a large number of different diagnostic methods used with differing sensitivities and specificities, which makes comparison of the results both within and between countries difficult. There is a clear requirement to standardise the methods of both STH diagnosis in faecal material and how the intensity of infection is recorded and reported in future STH research and in monitoring and evaluation (M&E) of the impact of continuing and expanding mass drug administration (MDA) programmes.
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High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike
2010-01-01
We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139
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Modifying patterns of movement in people with low back pain -does it help? A systematic review.
Laird, Robert A; Kent, Peter; Keating, Jennifer L
2012-09-07
Physiotherapy for people with low back pain frequently includes assessment and modification of lumbo-pelvic movement. Interventions commonly aim to restore normal movement and thereby reduce pain and improve activity limitation. The objective of this systematic review was to investigate: (i) the effect of movement-based interventions on movement patterns (muscle activation, lumbo-pelvic kinematics or postural patterns) of people with low back pain (LBP), and (ii) the relationship between changes in movement patterns and subsequent changes in pain and activity limitation. MEDLINE, Cochrane Central, EMBASE, AMI, CINAHL, Scopus, AMED, ISI Web of Science were searched from inception until January 2012. Randomised controlled trials or controlled clinical trials of people with LBP were eligible for inclusion. The intervention must have been designed to influence (i) muscle activity patterns, (ii) lumbo-pelvic kinematic patterns or (iii) postural patterns, and included measurement of such deficits before and after treatment, to allow determination of the success of the intervention on the lumbo-pelvic movement. Twelve trials (25% of retrieved studies) met the inclusion criteria. Two reviewers independently identified, assessed and extracted data. The PEDro scale was used to assess method quality. Intervention effects were described using standardised differences between group means and 95% confidence intervals. The included trials showed inconsistent, mostly small to moderate intervention effects on targeted movement patterns. There was considerable heterogeneity in trial design, intervention type and outcome measures. A relationship between changes to movement patterns and improvements in pain or activity limitation was observed in one of six studies on muscle activation patterns, one of four studies that examined the flexion relaxation response pattern and in two of three studies that assessed lumbo-pelvic kinematics or postural characteristics. Movement-based interventions were infrequently effective for changing observable movement patterns. A relationship between changes in movement patterns and improvement in pain or activity limitation was also infrequently observed. No independent studies confirm any observed relationships. Challenges for future research include defining best methods for measuring (i) movement aberrations, (ii) improvements in movements, and (iii) the relationship between changes in how people move and associated changes in other health indicators such as activity limitation.
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Kettunen, Jyrki; Eirola, Emil; Paakkonen, Heikki
2018-01-01
Background Some of the temporal variations and clock-like rhythms that govern several different health-related behaviors can be traced in near real-time with the help of search engine data. This is especially useful when studying phenomena where little or no traditional data exist. One specific area where traditional data are incomplete is the study of diurnal mood variations, or daily changes in individuals’ overall mood state in relation to depression-like symptoms. Objective The objective of this exploratory study was to analyze diurnal variations for interest in depression on the Web to discover hourly patterns of depression interest and help seeking. Methods Hourly query volume data for 6 depression-related queries in Finland were downloaded from Google Trends in March 2017. A continuous wavelet transform (CWT) was applied to the hourly data to focus on the diurnal variation. Longer term trends and noise were also eliminated from the data to extract the diurnal variation for each query term. An analysis of variance was conducted to determine the statistical differences between the distributions of each hour. Data were also trichotomized and analyzed in 3 time blocks to make comparisons between different time periods during the day. Results Search volumes for all depression-related query terms showed a unimodal regular pattern during the 24 hours of the day. All queries feature clear peaks during the nighttime hours around 11 PM to 4 AM and troughs between 5 AM and 10 PM. In the means of the CWT-reconstructed data, the differences in nighttime and daytime interest are evident, with a difference of 37.3 percentage points (pp) for the term “Depression,” 33.5 pp for “Masennustesti,” 30.6 pp for “Masennus,” 12.8 pp for “Depression test,” 12.0 pp for “Masennus testi,” and 11.8 pp for “Masennus oireet.” The trichotomization showed peaks in the first time block (00.00 AM-7.59 AM) for all 6 terms. The search volumes then decreased significantly during the second time block (8.00 AM-3.59 PM) for the terms “Masennus oireet” (P<.001), “Masennus” (P=.001), “Depression” (P=.005), and “Depression test” (P=.004). Higher search volumes for the terms “Masennus” (P=.14), “Masennustesti” (P=.07), and “Depression test” (P=.10) were present between the second and third time blocks. Conclusions Help seeking for depression has clear diurnal patterns, with significant rise in depression-related query volumes toward the evening and night. Thus, search engine query data support the notion of the evening-worse pattern in diurnal mood variation. Information on the timely nature of depression-related interest on an hourly level could improve the chances for early intervention, which is beneficial for positive health outcomes. PMID:29792291
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ERIC Educational Resources Information Center
Dimopoulos, Kostas; Asimakopoulos, Apostolos
2010-01-01
This study aims to explore navigation patterns and preferred pages' characteristics of ten secondary school students searching the web for information about cloning. The students navigated the Web for as long as they wished in a context of minimum support of teaching staff. Their navigation patterns were analyzed using audit trail data software.…
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Using Search Engines to Investigate Shared Migraine Experiences.
Burns, Sara M; Turner, Dana P; Sexton, Katherine E; Deng, Hao; Houle, Timothy T
2017-09-01
To investigate migraine patterns in the United States using Google search data and utilize this information to better understand societal-level trends. Additionally, we aimed to evaluate time-series relationships between migraines and social factors. Extensive research has been done on clinical factors associated with migraines, yet population-level social factors have not been widely explored. Migraine internet search data may provide insight into migraine trends beyond information that can be gleaned from other sources. In this longitudinal analysis of open access data, we performed a time-series analysis in which about 12 years of Google Trends data (January 1, 2004 to August 15, 2016) were assessed. Data points were captured at a daily level and Google's 0-100 adjusted scale was used as the primary outcome to enable the comparison of relative popularity in the migraine search term. We hypothesized that the volume of relative migraine Google searches would be affected by societal aspects such as day of the week, holidays, and novel social events. Several recurrent social factors that drive migraine searches were identified. Of these, day of the week had the most significant impact on the volume of Google migraine searches. On average, Mondays accumulated 13.31 higher relative search volume than Fridays (95% CI: 11.12-15.51, P ≤ .001). Surprisingly, holidays were associated with lower relative migraine search volumes. Christmas Day had 13.84 lower relative search volumes (95% CI: 6.26-21.43, P ≤ .001) and Thanks giving had 20.18 lower relative search volumes (95% CI: 12.55-27.82, P ≤ .001) than days that were not holidays. Certain novel social events and extreme weather also appear to be associated with relative migraine Google search volume. Social factors play a crucial role in explaining population level migraine patterns, and thus, warrant further exploration. © 2017 American Headache Society.
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Lewis, Stephen P; Klauninger, Laura; Marcincinova, Ivana
2016-01-01
Pro eating disorder websites often contain celebrity-focused content (e.g., images) used as thinspiration to engage in unhealthy eating disorder behaviours. The current study was conducted to examine whether news media stories covering eating disorder disclosures of celebrities corresponded with increases in Internet searches for pro eating disorder material. Results indicated that search volumes for pro eating disorder terms spiked in the month immediately following such news coverage but only for particularly high-profile celebrities. Hence, there may be utility in providing recovery-oriented resources within the search results for pro-eating disorder Internet searches and within news stories of this nature.
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PIRIA: a general tool for indexing, search, and retrieval of multimedia content
NASA Astrophysics Data System (ADS)
Joint, Magali; Moellic, Pierre-Alain; Hede, P.; Adam, P.
2004-05-01
The Internet is a continuously expanding source of multimedia content and information. There are many products in development to search, retrieve, and understand multimedia content. But most of the current image search/retrieval engines, rely on a image database manually pre-indexed with keywords. Computers are still powerless to understand the semantic meaning of still or animated image content. Piria (Program for the Indexing and Research of Images by Affinity), the search engine we have developed brings this possibility closer to reality. Piria is a novel search engine that uses the query by example method. A user query is submitted to the system, which then returns a list of images ranked by similarity, obtained by a metric distance that operates on every indexed image signature. These indexed images are compared according to several different classifiers, not only Keywords, but also Form, Color and Texture, taking into account geometric transformations and variance like rotation, symmetry, mirroring, etc. Form - Edges extracted by an efficient segmentation algorithm. Color - Histogram, semantic color segmentation and spatial color relationship. Texture - Texture wavelets and local edge patterns. If required, Piria is also able to fuse results from multiple classifiers with a new classification of index categories: Single Indexer Single Call (SISC), Single Indexer Multiple Call (SIMC), Multiple Indexers Single Call (MISC) or Multiple Indexers Multiple Call (MIMC). Commercial and industrial applications will be explored and discussed as well as current and future development.
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A novel algorithm for validating peptide identification from a shotgun proteomics search engine.
Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J
2013-03-01
Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.
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Configurable pattern-based evolutionary biclustering of gene expression data
2013-01-01
Background Biclustering algorithms for microarray data aim at discovering functionally related gene sets under different subsets of experimental conditions. Due to the problem complexity and the characteristics of microarray datasets, heuristic searches are usually used instead of exhaustive algorithms. Also, the comparison among different techniques is still a challenge. The obtained results vary in relevant features such as the number of genes or conditions, which makes it difficult to carry out a fair comparison. Moreover, existing approaches do not allow the user to specify any preferences on these properties. Results Here, we present the first biclustering algorithm in which it is possible to particularize several biclusters features in terms of different objectives. This can be done by tuning the specified features in the algorithm or also by incorporating new objectives into the search. Furthermore, our approach bases the bicluster evaluation in the use of expression patterns, being able to recognize both shifting and scaling patterns either simultaneously or not. Evolutionary computation has been chosen as the search strategy, naming thus our proposal Evo-Bexpa (Evolutionary Biclustering based in Expression Patterns). Conclusions We have conducted experiments on both synthetic and real datasets demonstrating Evo-Bexpa abilities to obtain meaningful biclusters. Synthetic experiments have been designed in order to compare Evo-Bexpa performance with other approaches when looking for perfect patterns. Experiments with four different real datasets also confirm the proper performing of our algorithm, whose results have been biologically validated through Gene Ontology. PMID:23433178
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Configural learning in contextual cuing of visual search.
Beesley, Tom; Vadillo, Miguel A; Pearson, Daniel; Shanks, David R
2016-08-01
Two experiments were conducted to explore the role of configural representations in contextual cuing of visual search. Repeating patterns of distractors (contexts) were trained incidentally as predictive of the target location. Training participants with repeating contexts of consistent configurations led to stronger contextual cuing than when participants were trained with contexts of inconsistent configurations. Computational simulations with an elemental associative learning model of contextual cuing demonstrated that purely elemental representations could not account for the results. However, a configural model of associative learning was able to simulate the ordinal pattern of data. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Skull base lesions: extracranial origins.
Mosier, Kristine M
2013-10-01
A number of extracranial anatomical sites, including the nasopharynx, paranasal sinuses, and masticator space, may give rise to lesions involving the skull base. Implicit in the nature of an invasive lesion, the majority of these lesions are malignant. Accordingly, for optimal patient outcomes and treatment planning, it is imperative to include a search pattern for extracranial sites and to assess accurately the character and extent of these diverse lesions. Of particular importance to radiologists are lesions arising from each extracranial site, the search patterns, and relevant information important to convey to the referring clinician. Copyright © 2013 Elsevier Inc. All rights reserved.
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ERIC Educational Resources Information Center
Falkmer, Marita; Bjallmark, Anna; Larsson, Matilda; Falkmer, Torbjorn
2011-01-01
Can the disadvantages persons with Asperger syndrome frequently experience with reading facially expressed emotions be attributed to a different visual perception, affecting their scanning patterns? Visual search strategies, particularly regarding the importance of information from the eye area, and the ability to recognise facially expressed…
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Coherent correlator and equalizer using a reconfigurable all-optical tapped delay line.
Chitgarha, Mohammad Reza; Khaleghi, Salman; Yilmaz, Omer F; Tur, Moshe; Haney, Michael W; Langrock, Carsten; Fejer, Martin M; Willner, Alan E
2013-07-01
We experimentally demonstrate a reconfigurable optical tapped delay line in conjunction with coherent detection to search multiple patterns among quadrature phase shift keying (QPSK) symbols in 20 Gbaud data channel and also to equalize 20 and 31 Gbaud QPSK, 20 Gbaud 8 phase shift keying (PSK), and 16 QAM signals. Multiple patterns are searched successfully on QPSK signals, and correlation peaks are obtained at the matched patterns. QPSK, 8 PSK, and 16 QAM signals are also successfully recovered after 25 km of SMF-28 with average EVMs of 8.3%, 8.9%, and 7.8%. A penalty of <1 dB optical signal to noise penalty is achieved for a 20 Gbaud QPSK signal distorted by up to 400 ps/nm dispersion.
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Modeling the role of parallel processing in visual search.
Cave, K R; Wolfe, J M
1990-04-01
Treisman's Feature Integration Theory and Julesz's Texton Theory explain many aspects of visual search. However, these theories require that parallel processing mechanisms not be used in many visual searches for which they would be useful, and they imply that visual processing should be much slower than it is. Most importantly, they cannot account for recent data showing that some subjects can perform some conjunction searches very efficiently. Feature Integration Theory can be modified so that it accounts for these data and helps to answer these questions. In this new theory, which we call Guided Search, the parallel stage guides the serial stage as it chooses display elements to process. A computer simulation of Guided Search produces the same general patterns as human subjects in a number of different types of visual search.
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White, Ryen W; Horvitz, Eric
2017-03-01
A statistical model that predicts the appearance of strong evidence of a lung carcinoma diagnosis via analysis of large-scale anonymized logs of web search queries from millions of people across the United States. To evaluate the feasibility of screening patients at risk of lung carcinoma via analysis of signals from online search activity. We identified people who issue special queries that provide strong evidence of a recent diagnosis of lung carcinoma. We then considered patterns of symptoms expressed as searches about concerning symptoms over several months prior to the appearance of the landmark web queries. We built statistical classifiers that predict the future appearance of landmark queries based on the search log signals. This was a retrospective log analysis of the online activity of millions of web searchers seeking health-related information online. Of web searchers who queried for symptoms related to lung carcinoma, some (n = 5443 of 4 813 985) later issued queries that provide strong evidence of recent clinical diagnosis of lung carcinoma and are regarded as positive cases in our analysis. Additional evidence on the reliability of these queries as representing clinical diagnoses is based on the significant increase in follow-on searches for treatments and medications for these searchers and on the correlation between lung carcinoma incidence rates and our log-based statistics. The remaining symptom searchers (n = 4 808 542) are regarded as negative cases. Performance of the statistical model for early detection from online search behavior, for different lead times, different sets of signals, and different cohorts of searchers stratified by potential risk. The statistical classifier predicting the future appearance of landmark web queries based on search log signals identified searchers who later input queries consistent with a lung carcinoma diagnosis, with a true-positive rate ranging from 3% to 57% for false-positive rates ranging from 0.00001 to 0.001, respectively. The methods can be used to identify people at highest risk up to a year in advance of the inferred diagnosis time. The 5 factors associated with the highest relative risk (RR) were evidence of family history (RR = 7.548; 95% CI, 3.937-14.470), age (RR = 3.558; 95% CI, 3.357-3.772), radon (RR = 2.529; 95% CI, 1.137-5.624), primary location (RR = 2.463; 95% CI, 1.364-4.446), and occupation (RR = 1.969; 95% CI, 1.143-3.391). Evidence of smoking (RR = 1.646; 95% CI, 1.032-2.260) was important but not top-ranked, which was due to the difficulty of identifying smoking history from search terms. Pattern recognition based on data drawn from large-scale web search queries holds opportunity for identifying risk factors and frames new directions with early detection of lung carcinoma.
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Callahan, Alison; Pernek, Igor; Stiglic, Gregor; Leskovec, Jure; Strasberg, Howard R; Shah, Nigam Haresh
2015-08-20
Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance. To analyze health care professionals' information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource. Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert. Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert. Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate.
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Falk, Bryan; Snow, Raymond W.; Reed, Robert
2016-01-01
Citizen-science programs have the potential to contribute to the management of invasive species, including Python molurus bivittatus (Burmese Python) in Florida. We characterized citizen-science–generated Burmese Python information from Everglades National Park (ENP) to explore how citizen science may be useful in this effort. As an initial step, we compiled and summarized records of Burmese Python observations and removals collected by both professional and citizen scientists in ENP during 2000–2014 and found many patterns of possible significance, including changes in annual observations and in demographic composition after a cold event. These patterns are difficult to confidently interpret because the records lack search-effort information, however, and differences among years may result from differences in search effort. We began collecting search-effort information in 2014 by leveraging an ongoing citizen-science program in ENP. Program participation was generally low, with most authorized participants in 2014 not searching for the snakes at all. We discuss the possible explanations for low participation, especially how the low likelihood of observing pythons weakens incentives to search. The monthly rate of Burmese Python observations for 2014 averaged ~1 observation for every 8 h of searching, but during several months, the rate was 1 python per >40 h of searching. These low observation-rates are a natural outcome of the snakes’ low detectability—few Burmese Pythons are likely to be observed even if many are present. The general inaccessibility of the southern Florida landscape also severely limits the effectiveness of using visual searches to find and remove pythons for the purposes of population control. Instead, and despite the difficulties in incentivizing voluntary participation, the value of citizen-science efforts in the management of the Burmese Python population is in collecting search-effort information.
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EMAGE mouse embryo spatial gene expression database: 2010 update
Richardson, Lorna; Venkataraman, Shanmugasundaram; Stevenson, Peter; Yang, Yiya; Burton, Nicholas; Rao, Jianguo; Fisher, Malcolm; Baldock, Richard A.; Davidson, Duncan R.; Christiansen, Jeffrey H.
2010-01-01
EMAGE (http://www.emouseatlas.org/emage) is a freely available online database of in situ gene expression patterns in the developing mouse embryo. Gene expression domains from raw images are extracted and integrated spatially into a set of standard 3D virtual mouse embryos at different stages of development, which allows data interrogation by spatial methods. An anatomy ontology is also used to describe sites of expression, which allows data to be queried using text-based methods. Here, we describe recent enhancements to EMAGE including: the release of a completely re-designed website, which offers integration of many different search functions in HTML web pages, improved user feedback and the ability to find similar expression patterns at the click of a button; back-end refactoring from an object oriented to relational architecture, allowing associated SQL access; and the provision of further access by standard formatted URLs and a Java API. We have also increased data coverage by sourcing from a greater selection of journals and developed automated methods for spatial data annotation that are being applied to spatially incorporate the genome-wide (∼19 000 gene) ‘EURExpress’ dataset into EMAGE. PMID:19767607
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Stable isotope, site-specific mass tagging for protein identification
Chen, Xian
2006-10-24
Proteolytic peptide mass mapping as measured by mass spectrometry provides an important method for the identification of proteins, which are usually identified by matching the measured and calculated m/z values of the proteolytic peptides. A unique identification is, however, heavily dependent upon the mass accuracy and sequence coverage of the fragment ions generated by peptide ionization. The present invention describes a method for increasing the specificity, accuracy and efficiency of the assignments of particular proteolytic peptides and consequent protein identification, by the incorporation of selected amino acid residue(s) enriched with stable isotope(s) into the protein sequence without the need for ultrahigh instrumental accuracy. Selected amino acid(s) are labeled with .sup.13C/.sup.15N/.sup.2H and incorporated into proteins in a sequence-specific manner during cell culturing. Each of these labeled amino acids carries a defined mass change encoded in its monoisotopic distribution pattern. Through their characteristic patterns, the peptides with mass tag(s) can then be readily distinguished from other peptides in mass spectra. The present method of identifying unique proteins can also be extended to protein complexes and will significantly increase data search specificity, efficiency and accuracy for protein identifications.
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The CTBTO Link to the database of the International Seismological Centre (ISC)
NASA Astrophysics Data System (ADS)
Bondar, I.; Storchak, D. A.; Dando, B.; Harris, J.; Di Giacomo, D.
2011-12-01
The CTBTO Link to the database of the International Seismological Centre (ISC) is a project to provide access to seismological data sets maintained by the ISC using specially designed interactive tools. The Link is open to National Data Centres and to the CTBTO. By means of graphical interfaces and database queries tailored to the needs of the monitoring community, the users are given access to a multitude of products. These include the ISC and ISS bulletins, covering the seismicity of the Earth since 1904; nuclear and chemical explosions; the EHB bulletin; the IASPEI Reference Event list (ground truth database); and the IDC Reviewed Event Bulletin. The searches are divided into three main categories: The Area Based Search (a spatio-temporal search based on the ISC Bulletin), the REB search (a spatio-temporal search based on specific events in the REB) and the IMS Station Based Search (a search for historical patterns in the reports of seismic stations close to a particular IMS seismic station). The outputs are HTML based web-pages with a simplified version of the ISC Bulletin showing the most relevant parameters with access to ISC, GT, EHB and REB Bulletins in IMS1.0 format for single or multiple events. The CTBTO Link offers a tool to view REB events in context within the historical seismicity, look at observations reported by non-IMS networks, and investigate station histories and residual patterns for stations registered in the International Seismographic Station Registry.
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Li, Yuanqing; Wang, Guangyi; Long, Jinyi; Yu, Zhuliang; Huang, Biao; Li, Xiaojian; Yu, Tianyou; Liang, Changhong; Li, Zheng; Sun, Pei
2011-01-01
One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: "old people" and "young people." These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration.
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Long, Jinyi; Yu, Zhuliang; Huang, Biao; Li, Xiaojian; Yu, Tianyou; Liang, Changhong; Li, Zheng; Sun, Pei
2011-01-01
One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: “old people” and “young people.” These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration. PMID:21750692
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Rigoutsos, Isidore; Riek, Peter; Graham, Robert M.; Novotny, Jiri
2003-01-01
One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular α-helical character (i.e. π-helices, 310-helices and kinks). A ‘search engine’ derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above ‘non-canonical’ helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from α-helicity are encoded locally in sequence patterns only about 7–9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure–function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html. PMID:12888523
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Rigoutsos, Isidore; Riek, Peter; Graham, Robert M; Novotny, Jiri
2003-08-01
One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular alpha-helical character (i.e. pi-helices, 3(10)-helices and kinks). A 'search engine' derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above 'non-canonical' helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from alpha-helicity are encoded locally in sequence patterns only about 7-9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure-function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html.
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A coarse-to-fine kernel matching approach for mean-shift based visual tracking
NASA Astrophysics Data System (ADS)
Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.
2009-03-01
Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.
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Applying Suffix Rules to Organization Name Recognition
NASA Astrophysics Data System (ADS)
Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi
This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.
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NASA Astrophysics Data System (ADS)
Ghani, N. H. A.; Mohamed, N. S.; Zull, N.; Shoid, S.; Rivaie, M.; Mamat, M.
2017-09-01
Conjugate gradient (CG) method is one of iterative techniques prominently used in solving unconstrained optimization problems due to its simplicity, low memory storage, and good convergence analysis. This paper presents a new hybrid conjugate gradient method, named NRM1 method. The method is analyzed under the exact and inexact line searches in given conditions. Theoretically, proofs show that the NRM1 method satisfies the sufficient descent condition with both line searches. The computational result indicates that NRM1 method is capable in solving the standard unconstrained optimization problems used. On the other hand, the NRM1 method performs better under inexact line search compared with exact line search.
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Montague, Enid; Asan, Onur
2014-03-01
The aim of this study was to examine eye gaze patterns between patients and physicians while electronic health records were used to support patient care. Eye gaze provides an indication of physician attention to patient, patient/physician interaction, and physician behaviors such as searching for information and documenting information. A field study was conducted where 100 patient visits were observed and video recorded in a primary care clinic. Videos were then coded for gaze behaviors where patients' and physicians' gaze at each other and artifacts such as electronic health records were coded using a pre-established objective coding scheme. Gaze data were then analyzed using lag sequential methods. Results showed that there are several eye gaze patterns significantly dependent to each other. All doctor-initiated gaze patterns were followed by patient gaze patterns. Some patient-initiated gaze patterns were also followed by doctor gaze patterns significantly unlike the findings in previous studies. Health information technology appears to contribute to some of the new significant patterns that have emerged. Differences were also found in gaze patterns related to technology that differ from patterns identified in studies with paper charts. Several sequences related to patient-doctor-technology were also significant. Electronic health records affect the patient-physician eye contact dynamic differently than paper charts. This study identified several patterns of patient-physician interaction with electronic health record systems. Consistent with previous studies, physician initiated gaze is an important driver of the interactions between patient and physician and patient and technology. Published by Elsevier Ireland Ltd.
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Nunes, Rita G; Hajnal, Joseph V
2018-06-01
Point spread function (PSF) mapping enables estimating the displacement fields required for distortion correction of echo planar images. Recently, a highly accelerated approach was introduced for estimating displacements from the phase slope of under-sampled PSF mapping data. Sampling schemes with varying spacing were proposed requiring stepwise phase unwrapping. To avoid unwrapping errors, an alternative approach applying the concept of finite rate of innovation to PSF mapping (FRIP) is introduced, using a pattern search strategy to locate the PSF peak, and the two methods are compared. Fully sampled PSF data was acquired in six subjects at 3.0 T, and distortion maps were estimated after retrospective under-sampling. The two methods were compared for both previously published and newly optimized sampling patterns. Prospectively under-sampled data were also acquired. Shift maps were estimated and deviations relative to the fully sampled reference map were calculated. The best performance was achieved when using FRIP with a previously proposed sampling scheme. The two methods were comparable for the remaining schemes. The displacement field errors tended to be lower as the number of samples or their spacing increased. A robust method for estimating the position of the PSF peak has been introduced.
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Enriching Great Britain's National Landslide Database by searching newspaper archives
NASA Astrophysics Data System (ADS)
Taylor, Faith E.; Malamud, Bruce D.; Freeborough, Katy; Demeritt, David
2015-11-01
Our understanding of where landslide hazard and impact will be greatest is largely based on our knowledge of past events. Here, we present a method to supplement existing records of landslides in Great Britain by searching an electronic archive of regional newspapers. In Great Britain, the British Geological Survey (BGS) is responsible for updating and maintaining records of landslide events and their impacts in the National Landslide Database (NLD). The NLD contains records of more than 16,500 landslide events in Great Britain. Data sources for the NLD include field surveys, academic articles, grey literature, news, public reports and, since 2012, social media. We aim to supplement the richness of the NLD by (i) identifying additional landslide events, (ii) acting as an additional source of confirmation of events existing in the NLD and (iii) adding more detail to existing database entries. This is done by systematically searching the Nexis UK digital archive of 568 regional newspapers published in the UK. In this paper, we construct a robust Boolean search criterion by experimenting with landslide terminology for four training periods. We then apply this search to all articles published in 2006 and 2012. This resulted in the addition of 111 records of landslide events to the NLD over the 2 years investigated (2006 and 2012). We also find that we were able to obtain information about landslide impact for 60-90% of landslide events identified from newspaper articles. Spatial and temporal patterns of additional landslides identified from newspaper articles are broadly in line with those existing in the NLD, confirming that the NLD is a representative sample of landsliding in Great Britain. This method could now be applied to more time periods and/or other hazards to add richness to databases and thus improve our ability to forecast future events based on records of past events.
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Tinnemann, Peter; Özbay, Jonas; Saint, Victoria A.; Willich, Stefan N.
2010-01-01
Background Patents are one of the most important forms of intellectual property. They grant a time-limited exclusivity on the use of an invention allowing the recuperation of research costs. The use of patents is fiercely debated for medical innovation and especially controversial for publicly funded research, where the patent holder is an institution accountable to public interest. Despite this controversy, for the situation in Germany almost no empirical information exists. The purpose of this study is to examine the amount, types and trends of patent applications for health products submitted by German public research organisations. Methods/Principal Findings We conducted a systematic search for patent documents using the publicly accessible database search interface of the German Patent and Trademark Office. We defined keywords and search criteria and developed search patterns for the database request. We retrieved documents with application date between 1988 and 2006 and processed the collected data stepwise to compile the most relevant documents in patent families for further analysis. We developed a rationale and present individual steps of a systematic method to request and process patent data from a publicly accessible database. We retrieved and processed 10194 patent documents. Out of these, we identified 1772 relevant patent families, applied for by 193 different universities and non-university public research organisations. 827 (47%) of these patent families contained granted patents. The number of patent applications submitted by universities and university-affiliated institutions more than tripled since the introduction of legal reforms in 2002, constituting almost half of all patent applications and accounting for most of the post-reform increase. Patenting of most non-university public research organisations remained stable. Conclusions We search, process and analyse patent applications from publicly accessible databases. Internationally mounting evidence questions the viability of policies to increase commercial exploitation of publicly funded research results. To evaluate the outcome of research policies a transparent evidence base for public debate is needed in Germany. PMID:21124982
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Till, Benedikt; Niederkrotenthaler, Thomas
2014-08-01
The Internet provides a variety of resources for individuals searching for suicide-related information. Structured content-analytic approaches to assess intercultural differences in web contents retrieved with method-related and help-related searches are scarce. We used the 2 most popular search engines (Google and Yahoo/Bing) to retrieve US-American and Austrian search results for the term suicide, method-related search terms (e.g., suicide methods, how to kill yourself, painless suicide, how to hang yourself), and help-related terms (e.g., suicidal thoughts, suicide help) on February 11, 2013. In total, 396 websites retrieved with US search engines and 335 websites from Austrian searches were analyzed with content analysis on the basis of current media guidelines for suicide reporting. We assessed the quality of websites and compared findings across search terms and between the United States and Austria. In both countries, protective outweighed harmful website characteristics by approximately 2:1. Websites retrieved with method-related search terms (e.g., how to hang yourself) contained more harmful (United States: P < .001, Austria: P < .05) and fewer protective characteristics (United States: P < .001, Austria: P < .001) compared to the term suicide. Help-related search terms (e.g., suicidal thoughts) yielded more websites with protective characteristics (United States: P = .07, Austria: P < .01). Websites retrieved with U.S. search engines generally had more protective characteristics (P < .001) than searches with Austrian search engines. Resources with harmful characteristics were better ranked than those with protective characteristics (United States: P < .01, Austria: P < .05). The quality of suicide-related websites obtained depends on the search terms used. Preventive efforts to improve the ranking of preventive web content, particularly regarding method-related search terms, seem necessary. © Copyright 2014 Physicians Postgraduate Press, Inc.
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Association between Stock Market Gains and Losses and Google Searches
Arditi, Eli; Yechiam, Eldad; Zahavi, Gal
2015-01-01
Experimental studies in the area of Psychology and Behavioral Economics have suggested that people change their search pattern in response to positive and negative events. Using Internet search data provided by Google, we investigated the relationship between stock-specific events and related Google searches. We studied daily data from 13 stocks from the Dow-Jones and NASDAQ100 indices, over a period of 4 trading years. Focusing on periods in which stocks were extensively searched (Intensive Search Periods), we found a correlation between the magnitude of stock returns at the beginning of the period and the volume, peak, and duration of search generated during the period. This relation between magnitudes of stock returns and subsequent searches was considerably magnified in periods following negative stock returns. Yet, we did not find that intensive search periods following losses were associated with more Google searches than periods following gains. Thus, rather than increasing search, losses improved the fit between people’s search behavior and the extent of real-world events triggering the search. The findings demonstrate the robustness of the attentional effect of losses. PMID:26513371
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Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.
Behrisch, Michael; Bach, Benjamin; Hund, Michael; Delz, Michael; Von Ruden, Laura; Fekete, Jean-Daniel; Schreck, Tobias
2017-01-01
In this work we address the problem of retrieving potentially interesting matrix views to support the exploration of networks. We introduce Matrix Diagnostics (or Magnostics), following in spirit related approaches for rating and ranking other visualization techniques, such as Scagnostics for scatter plots. Our approach ranks matrix views according to the appearance of specific visual patterns, such as blocks and lines, indicating the existence of topological motifs in the data, such as clusters, bi-graphs, or central nodes. Magnostics can be used to analyze, query, or search for visually similar matrices in large collections, or to assess the quality of matrix reordering algorithms. While many feature descriptors for image analyzes exist, there is no evidence how they perform for detecting patterns in matrices. In order to make an informed choice of feature descriptors for matrix diagnostics, we evaluate 30 feature descriptors-27 existing ones and three new descriptors that we designed specifically for MAGNOSTICS-with respect to four criteria: pattern response, pattern variability, pattern sensibility, and pattern discrimination. We conclude with an informed set of six descriptors as most appropriate for Magnostics and demonstrate their application in two scenarios; exploring a large collection of matrices and analyzing temporal networks.
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Comparison of methods for the detection of gravitational waves from unknown neutron stars
NASA Astrophysics Data System (ADS)
Walsh, S.; Pitkin, M.; Oliver, M.; D'Antonio, S.; Dergachev, V.; Królak, A.; Astone, P.; Bejger, M.; Di Giovanni, M.; Dorosh, O.; Frasca, S.; Leaci, P.; Mastrogiovanni, S.; Miller, A.; Palomba, C.; Papa, M. A.; Piccinni, O. J.; Riles, K.; Sauter, O.; Sintes, A. M.
2016-12-01
Rapidly rotating neutron stars are promising sources of continuous gravitational wave radiation for the LIGO and Virgo interferometers. The majority of neutron stars in our galaxy have not been identified with electromagnetic observations. All-sky searches for isolated neutron stars offer the potential to detect gravitational waves from these unidentified sources. The parameter space of these blind all-sky searches, which also cover a large range of frequencies and frequency derivatives, presents a significant computational challenge. Different methods have been designed to perform these searches within acceptable computational limits. Here we describe the first benchmark in a project to compare the search methods currently available for the detection of unknown isolated neutron stars. The five methods compared here are individually referred to as the PowerFlux, sky Hough, frequency Hough, Einstein@Home, and time domain F -statistic methods. We employ a mock data challenge to compare the ability of each search method to recover signals simulated assuming a standard signal model. We find similar performance among the four quick-look search methods, while the more computationally intensive search method, Einstein@Home, achieves up to a factor of two higher sensitivity. We find that the absence of a second derivative frequency in the search parameter space does not degrade search sensitivity for signals with physically plausible second derivative frequencies. We also report on the parameter estimation accuracy of each search method, and the stability of the sensitivity in frequency and frequency derivative and in the presence of detector noise.
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An ontology-based search engine for protein-protein interactions
2010-01-01
Background Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. Results We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Conclusion Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology. PMID:20122195
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An ontology-based search engine for protein-protein interactions.
Park, Byungkyu; Han, Kyungsook
2010-01-18
Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.
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Study on Hybrid Image Search Technology Based on Texts and Contents
NASA Astrophysics Data System (ADS)
Wang, H. T.; Ma, F. L.; Yan, C.; Pan, H.
2018-05-01
Image search was studied first here based on texts and contents, respectively. The text-based image feature extraction was put forward by integrating the statistical and topic features in view of the limitation of extraction of keywords only by means of statistical features of words. On the other hand, a search-by-image method was put forward based on multi-feature fusion in view of the imprecision of the content-based image search by means of a single feature. The layered-searching method depended on primarily the text-based image search method and additionally the content-based image search was then put forward in view of differences between the text-based and content-based methods and their difficult direct fusion. The feasibility and effectiveness of the hybrid search algorithm were experimentally verified.
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A Practical, Robust and Fast Method for Location Localization in Range-Based Systems.
Huang, Shiping; Wu, Zhifeng; Misra, Anil
2017-12-11
Location localization technology is used in a number of industrial and civil applications. Real time location localization accuracy is highly dependent on the quality of the distance measurements and efficiency of solving the localization equations. In this paper, we provide a novel approach to solve the nonlinear localization equations efficiently and simultaneously eliminate the bad measurement data in range-based systems. A geometric intersection model was developed to narrow the target search area, where Newton's Method and the Direct Search Method are used to search for the unknown position. Not only does the geometric intersection model offer a small bounded search domain for Newton's Method and the Direct Search Method, but also it can self-correct bad measurement data. The Direct Search Method is useful for the coarse localization or small target search domain, while the Newton's Method can be used for accurate localization. For accurate localization, by utilizing the proposed Modified Newton's Method (MNM), challenges of avoiding the local extrema, singularities, and initial value choice are addressed. The applicability and robustness of the developed method has been demonstrated by experiments with an indoor system.
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Feature selection methods for big data bioinformatics: A survey from the search perspective.
Wang, Lipo; Wang, Yaoli; Chang, Qing
2016-12-01
This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid methods, where heuristic search methods may further be categorized into those with or without data-distilled feature ranking measures. Copyright © 2016 Elsevier Inc. All rights reserved.
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Fractal analysis of radiologists' visual scanning pattern in screening mammography
NASA Astrophysics Data System (ADS)
Alamudun, Folami T.; Yoon, Hong-Jun; Hudson, Kathy; Morin-Ducote, Garnetta; Tourassi, Georgia
2015-03-01
Several researchers have investigated radiologists' visual scanning patterns with respect to features such as total time examining a case, time to initially hit true lesions, number of hits, etc. The purpose of this study was to examine the complexity of the radiologists' visual scanning pattern when viewing 4-view mammographic cases, as they typically do in clinical practice. Gaze data were collected from 10 readers (3 breast imaging experts and 7 radiology residents) while reviewing 100 screening mammograms (24 normal, 26 benign, 50 malignant). The radiologists' scanpaths across the 4 mammographic views were mapped to a single 2-D image plane. Then, fractal analysis was applied on the composite 4- view scanpaths. For each case, the complexity of each radiologist's scanpath was measured using fractal dimension estimated with the box counting method. The association between the fractal dimension of the radiologists' visual scanpath, case pathology, case density, and radiologist experience was evaluated using fixed effects ANOVA. ANOVA showed that the complexity of the radiologists' visual search pattern in screening mammography is dependent on case specific attributes (breast parenchyma density and case pathology) as well as on reader attributes, namely experience level. Visual scanning patterns are significantly different for benign and malignant cases than for normal cases. There is also substantial inter-observer variability which cannot be explained only by experience level.
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Multimodality approach to classifying hand utilization for the clinical breast examination.
Laufer, Shlomi; Cohen, Elaine R; Maag, Anne-Lise D; Kwan, Calvin; Vanveen, Barry; Pugh, Carla M
2014-01-01
The clinical breast examination (CBE) is performed to detect breast pathology. However, little is known regarding clinical technique and how it relates to diagnostic accuracy. We sought to quantify breast examination search patterns and hand utilization with a new data collection and analysis system. Participants performed the CBE while the sensor mapping and video camera system collected performance data. From this data, algorithms were developed that measured the number of hands used during the exam and active examination time. This system is a feasible and reliable method to collect new information on CBE techniques.
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Search Regimes and the Industrial Dynamics of Science
ERIC Educational Resources Information Center
Bonaccorsi, Andrea
2008-01-01
The article addresses the issue of dynamics of science, in particular of new sciences born in twentieth century and developed after the Second World War (information science, materials science, life science). The article develops the notion of search regime as an abstract characterization of dynamic patterns, based on three dimensions: the rate of…
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A Semiotic Analysis of Icons on the World Wide Web.
ERIC Educational Resources Information Center
Ma, Yan
The World Wide Web allows users to interact with a graphic interface to search information in a hypermedia and multimedia environment. Graphics serve as reference points on the World Wide Web for searching and retrieving information. This study analyzed the culturally constructed syntax patterns, or codes, embedded in the icons of library…
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ERIC Educational Resources Information Center
Solomon, Paul
1994-01-01
Examines elementary school students' use of an online public access catalog to investigate the interaction between children, technology, curriculum, instruction, and learning. Highlights include patterns of successes and breakdowns; search strategies; instructional approaches and childrens' interests; structure of interaction; search terms; and…
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Cooperative Control of UAVs for Localization of Intermittently Emitting Mobile Targets
2009-08-01
as lawn - mower serpentine patterns [21]. Second, due to the limited energy supplies intrinsic to UAV applications, it is also important that the search...Robotic Embedded Systems Laboratory, Univ. Southern Calif., Los Angeles, CA, 2002. Tech. Rep. [21] J. Ousingsawat and M. G. Earl, “Modified lawn - mower search
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Starke, Sandra D; Baber, Chris
2018-07-01
User interface (UI) design can affect the quality of decision making, where decisions based on digitally presented content are commonly informed by visually sampling information through eye movements. Analysis of the resulting scan patterns - the order in which people visually attend to different regions of interest (ROIs) - gives an insight into information foraging strategies. In this study, we quantified scan pattern characteristics for participants engaging with conceptually different user interface designs. Four interfaces were modified along two dimensions relating to effort in accessing information: data presentation (either alpha-numerical data or colour blocks), and information access time (all information sources readily available or sequential revealing of information required). The aim of the study was to investigate whether a) people develop repeatable scan patterns and b) different UI concepts affect information foraging and task performance. Thirty-two participants (eight for each UI concept) were given the task to correctly classify 100 credit card transactions as normal or fraudulent based on nine transaction attributes. Attributes varied in their usefulness of predicting the correct outcome. Conventional and more recent (network analysis- and bioinformatics-based) eye tracking metrics were used to quantify visual search. Empirical findings were evaluated in context of random data and possible accuracy for theoretical decision making strategies. Results showed short repeating sequence fragments within longer scan patterns across participants and conditions, comprising a systematic and a random search component. The UI design concept showing alpha-numerical data in full view resulted in most complete data foraging, while the design concept showing colour blocks in full view resulted in the fastest task completion time. Decision accuracy was not significantly affected by UI design. Theoretical calculations showed that the difference in achievable accuracy between very complex and simple decision making strategies was small. We conclude that goal-directed search of familiar information results in repeatable scan pattern fragments (often corresponding to information sources considered particularly important), but no repeatable complete scan pattern. The underlying concept of the UI affects how visual search is performed, and a decision making strategy develops. This should be taken in consideration when designing for applied domains. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Adaptation of video game UVW mapping to 3D visualization of gene expression patterns
NASA Astrophysics Data System (ADS)
Vize, Peter D.; Gerth, Victor E.
2007-01-01
Analysis of gene expression patterns within an organism plays a critical role in associating genes with biological processes in both health and disease. During embryonic development the analysis and comparison of different gene expression patterns allows biologists to identify candidate genes that may regulate the formation of normal tissues and organs and to search for genes associated with congenital diseases. No two individual embryos, or organs, are exactly the same shape or size so comparing spatial gene expression in one embryo to that in another is difficult. We will present our efforts in comparing gene expression data collected using both volumetric and projection approaches. Volumetric data is highly accurate but difficult to process and compare. Projection methods use UV mapping to align texture maps to standardized spatial frameworks. This approach is less accurate but is very rapid and requires very little processing. We have built a database of over 180 3D models depicting gene expression patterns mapped onto the surface of spline based embryo models. Gene expression data in different models can easily be compared to determine common regions of activity. Visualization software, both Java and OpenGL optimized for viewing 3D gene expression data will also be demonstrated.
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Idiosyncratic characteristics of saccadic eye movements when viewing different visual environments.
Andrews, T J; Coppola, D M
1999-08-01
Eye position was recorded in different viewing conditions to assess whether the temporal and spatial characteristics of saccadic eye movements in different individuals are idiosyncratic. Our aim was to determine the degree to which oculomotor control is based on endogenous factors. A total of 15 naive subjects viewed five visual environments: (1) The absence of visual stimulation (i.e. a dark room); (2) a repetitive visual environment (i.e. simple textured patterns); (3) a complex natural scene; (4) a visual search task; and (5) reading text. Although differences in visual environment had significant effects on eye movements, idiosyncrasies were also apparent. For example, the mean fixation duration and size of an individual's saccadic eye movements when passively viewing a complex natural scene covaried significantly with those same parameters in the absence of visual stimulation and in a repetitive visual environment. In contrast, an individual's spatio-temporal characteristics of eye movements during active tasks such as reading text or visual search covaried together, but did not correlate with the pattern of eye movements detected when viewing a natural scene, simple patterns or in the dark. These idiosyncratic patterns of eye movements in normal viewing reveal an endogenous influence on oculomotor control. The independent covariance of eye movements during different visual tasks shows that saccadic eye movements during active tasks like reading or visual search differ from those engaged during the passive inspection of visual scenes.
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Moving Object Detection Using a Parallax Shift Vector Algorithm
NASA Astrophysics Data System (ADS)
Gural, Peter S.; Otto, Paul R.; Tedesco, Edward F.
2018-07-01
There are various algorithms currently in use to detect asteroids from ground-based observatories, but they are generally restricted to linear or mildly curved movement of the target object across the field of view. Space-based sensors in high inclination, low Earth orbits can induce significant parallax in a collected sequence of images, especially for objects at the typical distances of asteroids in the inner solar system. This results in a highly nonlinear motion pattern of the asteroid across the sensor, which requires a more sophisticated search pattern for detection processing. Both the classical pattern matching used in ground-based asteroid search and the more sensitive matched filtering and synthetic tracking techniques, can be adapted to account for highly complex parallax motion. A new shift vector generation methodology is discussed along with its impacts on commonly used detection algorithms, processing load, and responsiveness to asteroid track reporting. The matched filter, template generator, and pattern matcher source code for the software described herein are available via GitHub.
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Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags
NASA Astrophysics Data System (ADS)
Ohnishi, Kei; Yoshida, Kaori; Oie, Yuji
We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.
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McCrea, Simon M.; Robinson, Thomas P.
2011-01-01
In this study, five consecutive patients with focal strokes and/or cortical excisions were examined with the Wechsler Adult Intelligence Scale and Wechsler Memory Scale—Fourth Editions along with a comprehensive battery of other neuropsychological tasks. All five of the lesions were large and typically involved frontal, temporal, and/or parietal lobes and were lateralized to one hemisphere. The clinical case method was used to determine the cognitive neuropsychological correlates of mental rotation (Visual Puzzles), Piagetian balance beam (Figure Weights), and visual search (Cancellation) tasks. The pattern of results on Visual Puzzles and Figure Weights suggested that both subtests involve predominately right frontoparietal networks involved in visual working memory. It appeared that Visual Puzzles could also critically rely on the integrity of the left temporoparietal junction. The left temporoparietal junction could be involved in temporal ordering and integration of local elements into a nonverbal gestalt. In contrast, the Figure Weights task appears to critically involve the right temporoparietal junction involved in numerical magnitude estimation. Cancellation was sensitive to left frontotemporal lesions and not right posterior parietal lesions typical of other visual search tasks. In addition, the Cancellation subtest was sensitive to verbal search strategies and perhaps object-based attention demands, thereby constituting a unique task in comparison with previous visual search tasks. PMID:22389807
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Hyperopt: a Python library for model selection and hyperparameter optimization
NASA Astrophysics Data System (ADS)
Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.
2015-01-01
Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.
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Dalton, Jane; Booth, Andrew; Noyes, Jane; Sowden, Amanda J
2017-08-01
Systematic reviews of quantitative evidence are well established in health and social care. Systematic reviews of qualitative evidence are increasingly available, but volume, topics covered, methods used, and reporting quality are largely unknown. We provide a descriptive overview of systematic reviews of qualitative evidence assessing health and social care interventions included on the Database of Abstracts of Reviews of Effects (DARE). We searched DARE for reviews published between January 1, 2009, and December 31, 2014. We extracted data on review content and methods, summarized narratively, and explored patterns over time. We identified 145 systematic reviews conducted worldwide (64 in the UK). Interventions varied but largely covered treatment or service delivery in community and hospital settings. There were no discernible patterns over time. Critical appraisal of primary studies was conducted routinely. Most reviews were poorly reported. Potential exists to use systematic reviews of qualitative evidence when driving forward user-centered health and social care. We identify where more research is needed and propose ways to improve review methodology and reporting. Copyright © 2017 Elsevier Inc. All rights reserved.
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Intelligent web image retrieval system
NASA Astrophysics Data System (ADS)
Hong, Sungyong; Lee, Chungwoo; Nah, Yunmook
2001-07-01
Recently, the web sites such as e-business sites and shopping mall sites deal with lots of image information. To find a specific image from these image sources, we usually use web search engines or image database engines which rely on keyword only retrievals or color based retrievals with limited search capabilities. This paper presents an intelligent web image retrieval system. We propose the system architecture, the texture and color based image classification and indexing techniques, and representation schemes of user usage patterns. The query can be given by providing keywords, by selecting one or more sample texture patterns, by assigning color values within positional color blocks, or by combining some or all of these factors. The system keeps track of user's preferences by generating user query logs and automatically add more search information to subsequent user queries. To show the usefulness of the proposed system, some experimental results showing recall and precision are also explained.
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Neglect assessment as an application of virtual reality.
Broeren, J; Samuelsson, H; Stibrant-Sunnerhagen, K; Blomstrand, C; Rydmark, M
2007-09-01
In this study a cancellation task in a virtual environment was applied to describe the pattern of search and the kinematics of hand movements in eight patients with right hemisphere stroke. Four of these patients had visual neglect and four had recovered clinically from initial symptoms of neglect. The performance of the patients was compared with that of a control group consisting of eight subjects with no history of neurological deficits. Patients with neglect as well as patients clinically recovered from neglect showed aberrant search performance in the virtual reality (VR) task, such as mixed search pattern, repeated target pressures and deviating hand movements. The results indicate that in patients with a right hemispheric stroke, this VR application can provide an additional tool for assessment that can identify small variations otherwise not detectable with standard paper-and-pencil tests. VR technology seems to be well suited for the assessment of visually guided manual exploration in space.
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Investigating Intrinsic and Extrinsic Variables During Simulated Internet Search
NASA Technical Reports Server (NTRS)
Liechty, Molly M.; Madhavan, Poornima
2011-01-01
Using an eye tracker we examined decision-making processes during an internet search task. Twenty experienced homebuyers and twenty-five undergraduates from Old Dominion University viewed homes on a simulated real estate website. Several of the homes included physical properties that had the potential to negatively impact individual perceptions. These negative externalities were either easy to change (Level 1) or impossible to change (Level 2). Eye movements were analyzed to examine the relationship between participants' "stated preferences"[verbalized preferences], "revealed preferences" [actual decisions[, and experience. Dwell times, fixation durations/counts, and saccade counts/amplitudes were analyzed. Results revealed that experienced homebuyers demonstrated a more refined search pattern than novice searchers. Experienced homebuyers were also less impacted by negative externalities. Furthermore, stated preferences were discrepant from revealed preferences; although participants initially stated they liked/disliked a graphic, their eye movement patterns did not reflect this trend. These results have important implications for design of user-friendly web interfaces.
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Song, Jiangning; Yuan, Zheng; Tan, Hao; Huber, Thomas; Burrage, Kevin
2007-12-01
Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications. We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects. The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide
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Task demands determine the specificity of the search template.
Bravo, Mary J; Farid, Hany
2012-01-01
When searching for an object, an observer holds a representation of the target in mind while scanning the scene. If the observer repeats the search, performance may become more efficient as the observer hones this target representation, or "search template," to match the specific demands of the search task. An effective search template must have two characteristics: It must reliably discriminate the target from the distractors, and it must tolerate variability in the appearance of the target. The present experiment examined how the tolerance of the search template is affected by the search task. Two groups of 18 observers trained on the same set of stimuli blocked either by target image (block-by-image group) or by target category (block-by-category group). One or two days after training, both groups were tested on a related search task. The pattern of test results revealed that the two groups of observers had developed different search templates, and that the templates of the block-by-category observers better captured the general characteristics of the category. These results demonstrate that observers match their search templates to the demands of the search task.
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RSA migration of total knee replacements.
Pijls, Bart G; Plevier, José W M; Nelissen, Rob G H H
2018-06-01
Purpose - We performed a systematic review and meta-analyses to evaluate the early and long-term migration patterns of tibial components of TKR of all known RSA studies. Methods - Migration pattern was defined as at least 2 postoperative RSA follow-up moments. Maximal total point motion (MTPM) at 6 weeks, 3 months, 6 months, 1 year, 2 years, 5 years, and 10 years were considered. Results - The literature search yielded 1,167 hits of which 53 studies were included, comprising 111 study groups and 2,470 knees. The majority of the early migration occurred in the first 6 months postoperatively followed by a period of stability, i.e., no or very little migration. Cemented and uncemented tibial components had different migration patterns. For cemented tibial components there was no difference in migration between all-poly and metal-backed components, between mobile bearing and fixed bearing, between cruciate retaining and posterior stabilized. Furthermore, no difference existed between TKR measured with model-based RSA or marker-based RSA methods. For uncemented TKR there was some variation in migration with the highest migration for uncoated TKR. Interpretation - The results from this meta-analysis on RSA migration of TKR are in line with both the survival analyses results from joint registries of these TKRs as well as revision rates results from meta-analyses, thus providing further proof for the association between early migration and late revision for loosening. The pooled migration patterns can be used both as benchmarks and for defining migration thresholds for future evaluation of new TKR.
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Guiding Conformation Space Search with an All-Atom Energy Potential
Brunette, TJ; Brock, Oliver
2009-01-01
The most significant impediment for protein structure prediction is the inadequacy of conformation space search. Conformation space is too large and the energy landscape too rugged for existing search methods to consistently find near-optimal minima. To alleviate this problem, we present model-based search, a novel conformation space search method. Model-based search uses highly accurate information obtained during search to build an approximate, partial model of the energy landscape. Model-based search aggregates information in the model as it progresses, and in turn uses this information to guide exploration towards regions most likely to contain a near-optimal minimum. We validate our method by predicting the structure of 32 proteins, ranging in length from 49 to 213 amino acids. Our results demonstrate that model-based search is more effective at finding low-energy conformations in high-dimensional conformation spaces than existing search methods. The reduction in energy translates into structure predictions of increased accuracy. PMID:18536015
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The use of geoscience methods for terrestrial forensic searches
NASA Astrophysics Data System (ADS)
Pringle, J. K.; Ruffell, A.; Jervis, J. R.; Donnelly, L.; McKinley, J.; Hansen, J.; Morgan, R.; Pirrie, D.; Harrison, M.
2012-08-01
Geoscience methods are increasingly being utilised in criminal, environmental and humanitarian forensic investigations, and the use of such methods is supported by a growing body of experimental and theoretical research. Geoscience search techniques can complement traditional methodologies in the search for buried objects, including clandestine graves, weapons, explosives, drugs, illegal weapons, hazardous waste and vehicles. This paper details recent advances in search and detection methods, with case studies and reviews. Relevant examples are given, together with a generalised workflow for search and suggested detection technique(s) table. Forensic geoscience techniques are continuing to rapidly evolve to assist search investigators to detect hitherto difficult to locate forensic targets.
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Comparison of optimization algorithms in intensity-modulated radiation therapy planning
NASA Astrophysics Data System (ADS)
Kendrick, Rachel
Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.
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Controlled trials to improve antibiotic utilization: a systematic review of experience, 1984-2004.
Parrino, Thomas A
2005-02-01
To review the effectiveness of interventions designed to improve antibiotic prescribing patterns in clinical practice and to draw inferences about the most practical methods for optimizing antibiotic utilization in hospital and ambulatory settings. A literature search using online databases for the years 1975-2004 identified controlled trials of strategies for improving antibiotic utilization. Due to variation in study settings and design, quantitative meta-analysis was not feasible. Therefore, a qualitative literature review was conducted. Forty-one controlled trials met the search criteria. Interventions consisted of education, peer review and feedback, physician participation, rewards and penalties, administrative methods, and combined approaches. Social marketing directed at patients and prescribers was effective in varying contexts, as was implementation of practice guidelines. Authorization systems with structured order entry, formulary restriction, and mandatory consultation were also effective. Peer review and feedback were more effective when combined with dissemination of relevant information or social marketing than when used alone. Several practices were effective in improving antibiotic utilization: social marketing, practice guidelines, authorization systems, and peer review and feedback. Online systems providing clinical information, structured order entry, and decision support may be the most promising approach. Further studies, including economic analyses, are needed to confirm or refute this hypothesis.
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Pattern Search in Multi-structure Data: A Framework for the Next-Generation Evidence-based Medicine
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sukumar, Sreenivas R; Ainsworth, Keela C
With the advent of personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledge-bases) to predict diagnostic risks is fast emerging. Addressing this need, we pose and address the following questions (i) How can we jointly analyze both qualitative and quantitative data ? (ii) Is the fusion of multi-structure data expected to provide better insights than either of them individually ? We present experiments on two bio-medical data sets - mammography and traumatic brain studies to demonstrate architectures and tools for evidence-pattern search.
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Vasconcellos-Silva, Paulo Roberto; Griep, Rosane Harter; de Souza, Miriam Carvalho
2015-08-01
Internet search patterns associated with "windows" of collective interest have been increasingly investigated in the field of public health. This article sets out to identify search patterns relating to the quest for information on skin protection after the perception of excessive exposure to UV radiation - the so-called "summer effect" as it is commonly referred to in Brazil. To calculate the number of hits on the Brazilian National Cancer Institute website - a renowned source of information resources on prevention - log analyzer software was used to measure the volume of hits on specific content pages. The pages on skin protection and self-examination (pages of interest) were monitored over a 48-month period. It was seen that, although the monthly average of hits on pages of interest revealed statistically significant annual growth, the results for the analysis of variance showed no significant differences between the number of hits in the summer compared with other months (p = 0.7491). In short, the perception of intense exposure to the summer sun did not encourage further interest to search for information on prevention.
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cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on CPU+GPU.
Zhang, Jing; Wang, Hao; Feng, Wu-Chun
2017-01-01
BLAST, short for Basic Local Alignment Search Tool, is a ubiquitous tool used in the life sciences for pairwise sequence search. However, with the advent of next-generation sequencing (NGS), whether at the outset or downstream from NGS, the exponential growth of sequence databases is outstripping our ability to analyze the data. While recent studies have utilized the graphics processing unit (GPU) to speedup the BLAST algorithm for searching protein sequences (i.e., BLASTP), these studies use coarse-grained parallelism, where one sequence alignment is mapped to only one thread. Such an approach does not efficiently utilize the capabilities of a GPU, particularly due to the irregularity of BLASTP in both execution paths and memory-access patterns. To address the above shortcomings, we present a fine-grained approach to parallelize BLASTP, where each individual phase of sequence search is mapped to many threads on a GPU. This approach, which we refer to as cuBLASTP, reorders data-access patterns and reduces divergent branches of the most time-consuming phases (i.e., hit detection and ungapped extension). In addition, cuBLASTP optimizes the remaining phases (i.e., gapped extension and alignment with trace back) on a multicore CPU and overlaps their execution with the phases running on the GPU.
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AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.
Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y
2018-06-07
The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.
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A systematic review of data mining and machine learning for air pollution epidemiology.
Bellinger, Colin; Mohomed Jabbar, Mohomed Shazan; Zaïane, Osmar; Osornio-Vargas, Alvaro
2017-11-28
Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets offer great potential, but also challenge traditional epidemiological methods. This has motivated the exploration of alternative methods to make predictions, find patterns and extract information. To this end, data mining and machine learning algorithms are increasingly being applied to air pollution epidemiology. We conducted a systematic literature review on the application of data mining and machine learning methods in air pollution epidemiology. We carried out our search process in PubMed, the MEDLINE database and Google Scholar. Research articles applying data mining and machine learning methods to air pollution epidemiology were queried and reviewed. Our search queries resulted in 400 research articles. Our fine-grained analysis employed our inclusion/exclusion criteria to reduce the results to 47 articles, which we separate into three primary areas of interest: 1) source apportionment; 2) forecasting/prediction of air pollution/quality or exposure; and 3) generating hypotheses. Early applications had a preference for artificial neural networks. In more recent work, decision trees, support vector machines, k-means clustering and the APRIORI algorithm have been widely applied. Our survey shows that the majority of the research has been conducted in Europe, China and the USA, and that data mining is becoming an increasingly common tool in environmental health. For potential new directions, we have identified that deep learning and geo-spacial pattern mining are two burgeoning areas of data mining that have good potential for future applications in air pollution epidemiology. We carried out a systematic review identifying the current trends, challenges and new directions to explore in the application of data mining methods to air pollution epidemiology. This work shows that data mining is increasingly being applied in air pollution epidemiology. The potential to support air pollution epidemiology continues to grow with advancements in data mining related to temporal and geo-spacial mining, and deep learning. This is further supported by new sensors and storage mediums that enable larger, better quality data. This suggests that many more fruitful applications can be expected in the future.
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Fast and Flexible Multivariate Time Series Subsequence Search
NASA Technical Reports Server (NTRS)
Bhaduri, Kanishka; Oza, Nikunj C.; Zhu, Qiang; Srivastava, Ashok N.
2010-01-01
Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.
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Lévy-taxis: a novel search strategy for finding odor plumes in turbulent flow-dominated environments
NASA Astrophysics Data System (ADS)
Pasternak, Zohar; Bartumeus, Frederic; Grasso, Frank W.
2009-10-01
Locating chemical plumes in aquatic or terrestrial environments is important for many economic, conservation, security and health related human activities. The localization process is composed mainly of two phases: finding the chemical plume and then tracking it to its source. Plume tracking has been the subject of considerable study whereas plume finding has received little attention. We address here the latter issue, where the searching agent must find the plume in a region often many times larger than the plume and devoid of the relevant chemical cues. The probability of detecting the plume not only depends on the movements of the searching agent but also on the fluid mechanical regime, shaping plume intermittency in space and time; this is a basic, general problem when exploring for ephemeral resources (e.g. moving and/or concealing targets). Here we present a bio-inspired search strategy named Lévy-taxis that, under certain conditions, located odor plumes significantly faster and with a better success rate than other search strategies such as Lévy walks (LW), correlated random walks (CRW) and systematic zig-zag. These results are based on computer simulations which contain, for the first time ever, digitalized real-world water flow and chemical plume instead of their theoretical model approximations. Combining elements of LW and CRW, Lévy-taxis is particularly efficient for searching in flow-dominated environments: it adaptively controls the stochastic search pattern using environmental information (i.e. flow) that is available throughout the course of the search and shows correlation with the source providing the cues. This strategy finds natural application in real-world search missions, both by humans and autonomous robots, since it accomodates the stochastic nature of chemical mixing in turbulent flows. In addition, it may prove useful in the field of behavioral ecology, explaining and predicting the movement patterns of various animals searching for food or mates.
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Nanopatterning reconfigurable magnetic landscapes via thermally assisted scanning probe lithography
NASA Astrophysics Data System (ADS)
Albisetti, E.; Petti, D.; Pancaldi, M.; Madami, M.; Tacchi, S.; Curtis, J.; King, W. P.; Papp, A.; Csaba, G.; Porod, W.; Vavassori, P.; Riedo, E.; Bertacco, R.
2016-06-01
The search for novel tools to control magnetism at the nanoscale is crucial for the development of new paradigms in optics, electronics and spintronics. So far, the fabrication of magnetic nanostructures has been achieved mainly through irreversible structural or chemical modifications. Here, we propose a new concept for creating reconfigurable magnetic nanopatterns by crafting, at the nanoscale, the magnetic anisotropy landscape of a ferromagnetic layer exchange-coupled to an antiferromagnetic layer. By performing localized field cooling with the hot tip of a scanning probe microscope, magnetic structures, with arbitrarily oriented magnetization and tunable unidirectional anisotropy, are reversibly patterned without modifying the film chemistry and topography. This opens unforeseen possibilities for the development of novel metamaterials with finely tuned magnetic properties, such as reconfigurable magneto-plasmonic and magnonic crystals. In this context, we experimentally demonstrate spatially controlled spin wave excitation and propagation in magnetic structures patterned with the proposed method.
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Nanopatterning reconfigurable magnetic landscapes via thermally assisted scanning probe lithography.
Albisetti, E; Petti, D; Pancaldi, M; Madami, M; Tacchi, S; Curtis, J; King, W P; Papp, A; Csaba, G; Porod, W; Vavassori, P; Riedo, E; Bertacco, R
2016-06-01
The search for novel tools to control magnetism at the nanoscale is crucial for the development of new paradigms in optics, electronics and spintronics. So far, the fabrication of magnetic nanostructures has been achieved mainly through irreversible structural or chemical modifications. Here, we propose a new concept for creating reconfigurable magnetic nanopatterns by crafting, at the nanoscale, the magnetic anisotropy landscape of a ferromagnetic layer exchange-coupled to an antiferromagnetic layer. By performing localized field cooling with the hot tip of a scanning probe microscope, magnetic structures, with arbitrarily oriented magnetization and tunable unidirectional anisotropy, are reversibly patterned without modifying the film chemistry and topography. This opens unforeseen possibilities for the development of novel metamaterials with finely tuned magnetic properties, such as reconfigurable magneto-plasmonic and magnonic crystals. In this context, we experimentally demonstrate spatially controlled spin wave excitation and propagation in magnetic structures patterned with the proposed method.
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Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias
2012-03-01
In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.
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Graumann, Johannes; Scheltema, Richard A.; Zhang, Yong; Cox, Jürgen; Mann, Matthias
2012-01-01
In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides “on-the-fly” within 30 ms, well within the time constraints of a shotgun fragmentation “topN” method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available. PMID:22171319
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Plans, Patterns, and Move Categories Guiding a Highly Selective Search
NASA Astrophysics Data System (ADS)
Trippen, Gerhard
In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move generation to moves in certain move categories to reduce the number of moves considered by the bot significantly. Arimaa is a modern board game that can be played with a standard Chess set. However, the rules of the game are not at all like those of Chess. Furthermore, Arimaa was designed to be as simple and intuitive as possible for humans, yet challenging for computers. While all established Arimaa bots use alpha-beta search with a variety of pruning techniques and other heuristics ending in an extensive positional leaf node evaluation, our new bot, Rat, starts with a positional evaluation of the current position. Based on features found in the current position - supported by pattern matching using a directed position graph - our bot Rat decides which of a given set of plans to follow. The plan then dictates what types of moves can be chosen. This is another major difference from bots that generate "all" possible moves for a particular position. Rat is only allowed to generate moves that belong to certain categories. Leaf nodes are evaluated only by a straightforward material evaluation to help avoid moves that lose material. This highly selective search looks, on average, at only 5 moves out of 5,000 to over 40,000 possible moves in a middle game position.
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Shorofsky, Stephen R; Peters, Robert W; Rashba, Eric J; Gold, Michael R
2004-02-01
Determination of DFT is an integral part of ICD implantation. Two commonly used methods of DFT determination, the step-down method and the binary search method, were compared in 44 patients undergoing ICD testing for standard clinical indications. The step-down protocol used an initial shock of 18 J. The binary search method began with a shock energy of 9 J and successive shock energies were increased or decreased depending on the success of the previous shock. The DFT was defined as the lowest energy that successfully terminated ventricular fibrillation. The binary search method has the advantage of requiring a predetermined number of shocks, but some have questioned its accuracy. The study found that (mean) DFT obtained by the step-down method was 8.2 +/- 5.0, whereas by the binary search method DFT was 8.1 +/- 0.7 J, P = NS. DFT differed by no more than one step between methods in 32 (71%) of patients. The number of shocks required to determine DFT by the step-down method was 4.6 +/- 1.4, whereas by definition, the binary search method always required three shocks. In conclusion, the binary search method is preferable because it is of comparable efficacy and requires fewer shocks.
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Dehkordy, Soudabeh Fazeli; Carlos, Ruth C.; Hall, Kelli S.; Dalton, Vanessa K.
2015-01-01
Rationale and Objectives Millions of people use online search engines every day to find health-related information and voluntarily share their personal health status and behaviors in various Web sites. Thus, data from tracking of online information seeker’s behavior offer potential opportunities for use in public health surveillance and research. Google Trends is a feature of Google which allows internet users to graph the frequency of searches for a single term or phrase over time or by geographic region. We used Google Trends to describe patterns of information seeking behavior in the subject of dense breasts and to examine their correlation with the passage or introduction of dense breast notification legislation. Materials and Methods In order to capture the temporal variations of information seeking about dense breasts, the web search query “dense breast” was entered in the Google Trends tool. We then mapped the dates of legislative actions regarding dense breasts that received widespread coverage in the lay media to information seeking trends about dense breasts over time. Results Newsworthy events and legislative actions appear to correlate well with peaks in search volume of “dense breast”. Geographic regions with the highest search volumes have either passed, denied, or are currently considering the dense breast legislation. Conclusions Our study demonstrated that any legislative action and respective news coverage correlate with increase in information seeking for “dense breast” on Google, suggesting that Google Trends has the potential to serve as a data source for policy-relevant research. PMID:24998689
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Two Distinct Exploratory Behaviors in Decisions from Experience: Comment on Gonzalez and Dutt (2011)
ERIC Educational Resources Information Center
Hills, Thomas T.; Hertwig, Ralph
2012-01-01
Gonzalez and Dutt (2011) recently reported that trends during sampling, prior to a consequential risky decision, reveal a gradual movement from exploration to exploitation. That is, even when search imposes no immediate costs, people adopt the same pattern manifest in costly search: early exploration followed by later exploitation. From this…
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A main path domain map as digital library interface
NASA Astrophysics Data System (ADS)
Demaine, Jeffrey
2009-01-01
The shift to electronic publishing of scientific journals is an opportunity for the digital library to provide non-traditional ways of accessing the literature. One method is to use citation metadata drawn from a collection of electronic journals to generate maps of science. These maps visualize the communication patterns in the collection, giving the user an easy-tograsp view of the semantic structure underlying the scientific literature. For this visualization to be understandable the complexity of the citation network must be reduced through an algorithm. This paper describes the Citation Pathfinder application and its integration into a prototype digital library. This application generates small-scale citation networks that expand upon the search results of the digital library. These domain maps are linked to the collection, creating an interface that is based on the communication patterns in science. The Main Path Analysis technique is employed to simplify these networks into linear, sequential structures. By identifying patterns that characterize the evolution of the research field, Citation Pathfinder uses citations to give users a deeper understanding of the scientific literature.
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Leung, Doris G
2017-07-01
A growing body of the literature supports the use of magnetic resonance imaging as a potential biomarker for disease severity in the hereditary myopathies. We performed a systematic review of the medical literature to evaluate patterns of fat infiltration observed in magnetic resonance imaging studies of muscular dystrophy and congenital myopathy. Searches were performed using MEDLINE, EMBASE, and grey literature databases. Studies that described fat infiltration of muscles in patients with muscular dystrophy or congenital myopathy were selected for full-length review. Data on preferentially involved or spared muscles were extracted for analysis. A total of 2172 titles and abstracts were screened, and 70 publications met our criteria for inclusion in the systematic review. There were 23 distinct genetic disorders represented in this analysis. In most studies, preferential involvement and sparing of specific muscles were reported. We conclude that magnetic resonance imaging studies can be used to identify distinct patterns of muscle involvement in the hereditary myopathies. However, larger studies and standardized methods of reporting are needed to develop imaging as a diagnostic tool in these diseases.
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A novel high-frequency encoding algorithm for image compression
NASA Astrophysics Data System (ADS)
Siddeq, Mohammed M.; Rodrigues, Marcos A.
2017-12-01
In this paper, a new method for image compression is proposed whose quality is demonstrated through accurate 3D reconstruction from 2D images. The method is based on the discrete cosine transform (DCT) together with a high-frequency minimization encoding algorithm at compression stage and a new concurrent binary search algorithm at decompression stage. The proposed compression method consists of five main steps: (1) divide the image into blocks and apply DCT to each block; (2) apply a high-frequency minimization method to the AC-coefficients reducing each block by 2/3 resulting in a minimized array; (3) build a look up table of probability data to enable the recovery of the original high frequencies at decompression stage; (4) apply a delta or differential operator to the list of DC-components; and (5) apply arithmetic encoding to the outputs of steps (2) and (4). At decompression stage, the look up table and the concurrent binary search algorithm are used to reconstruct all high-frequency AC-coefficients while the DC-components are decoded by reversing the arithmetic coding. Finally, the inverse DCT recovers the original image. We tested the technique by compressing and decompressing 2D images including images with structured light patterns for 3D reconstruction. The technique is compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results demonstrate that the proposed compression method is perceptually superior to JPEG with equivalent quality to JPEG2000. Concerning 3D surface reconstruction from images, it is demonstrated that the proposed method is superior to both JPEG and JPEG2000.
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De Monte, Silvia; Cotté, Cedric; d'Ovidio, Francesco; Lévy, Marina; Le Corre, Matthieu; Weimerskirch, Henri
2012-12-07
Marine top predators such as seabirds are useful indicators of the integrated response of the marine ecosystem to environmental variability at different scales. Large-scale physical gradients constrain seabird habitat. Birds however respond behaviourally to physical heterogeneity at much smaller scales. Here, we use, for the first time, three-dimensional GPS tracking of a seabird, the great frigatebird (Fregata minor), in the Mozambique Channel. These data, which provide at the same time high-resolution vertical and horizontal positions, allow us to relate the behaviour of frigatebirds to the physical environment at the (sub-)mesoscale (10-100 km, days-weeks). Behavioural patterns are classified based on the birds' vertical displacement (e.g. fast/slow ascents and descents), and are overlaid on maps of physical properties of the ocean-atmosphere interface, obtained by a nonlinear analysis of multi-satellite data. We find that frigatebirds modify their behaviours concurrently to transport and thermal fronts. Our results suggest that the birds' co-occurrence with these structures is a consequence of their search not only for food (preferentially searched over thermal fronts) but also for upward vertical wind. This is also supported by their relationship with mesoscale patterns of wind divergence. Our multi-disciplinary method can be applied to forthcoming high-resolution animal tracking data, and aims to provide a mechanistic understanding of animals' habitat choice and of marine ecosystem responses to environmental change.
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Foraging interactions of small Hawaiian forest birds
C. John Ralph; Barry R. Noon
1986-01-01
In a search for competition, limiting factors, and other patterns in a community of small passerine birds in Hawaii, we recorded the foraging behaviors, resource abundances, and climatic variables believed to influence resource levels. Some definite patterns were found, showing that the rare, endangered birds were specialists; however, some specialists were quite...
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A Vector Space Model for Automatic Indexing.
ERIC Educational Resources Information Center
Salton, G.; And Others
In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other, or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; that is, retrieval performance correlates inversely…
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Algebraic Algorithm Design and Local Search
1996-12-01
method for performing algorithm design that is more purely algebraic than that of KIDS. This method is then applied to local search. Local search is a...synthesis. Our approach was to follow KIDS in spirit, but to adopt a pure algebraic formalism, supported by Kestrel’s SPECWARE environment (79), that...design was developed that is more purely algebraic than that of KIDS. This method was then applied to local search. A general theory of local search was
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NASA Astrophysics Data System (ADS)
Wang, Lynn T.-N.; Schroeder, Uwe Paul; Madhavan, Sriram
2017-03-01
A pattern-based methodology for optimizing SADP-compliant layout designs is developed based on identifying cut mask patterns and replacing them with pre-characterized fixing solutions. A pattern-based library of difficult-tomanufacture cut patterns with pre-characterized fixing solutions is built. A pattern-based engine searches for matching patterns in the decomposed layouts. When a match is found, the engine opportunistically replaces the detected pattern with a pre-characterized fixing solution. The methodology was demonstrated on a 7nm routed metal2 block. A small library of 30 cut patterns increased the number of more manufacturable cuts by 38% and metal-via enclosure by 13% with a small parasitic capacitance impact of 0.3%.
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Comparative homology agreement search: An effective combination of homology-search methods
Alam, Intikhab; Dress, Andreas; Rehmsmeier, Marc; Fuellen, Georg
2004-01-01
Many methods have been developed to search for homologous members of a protein family in databases, and the reliability of results and conclusions may be compromised if only one method is used, neglecting the others. Here we introduce a general scheme for combining such methods. Based on this scheme, we implemented a tool called comparative homology agreement search (chase) that integrates different search strategies to obtain a combined “E value.” Our results show that a consensus method integrating distinct strategies easily outperforms any of its component algorithms. More specifically, an evaluation based on the Structural Classification of Proteins database reveals that, on average, a coverage of 47% can be obtained in searches for distantly related homologues (i.e., members of the same superfamily but not the same family, which is a very difficult task), accepting only 10 false positives, whereas the individual methods obtain a coverage of 28–38%. PMID:15367730
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The 3of5 web application for complex and comprehensive pattern matching in protein sequences.
Seiler, Markus; Mehrle, Alexander; Poustka, Annemarie; Wiemann, Stefan
2006-03-16
The identification of patterns in biological sequences is a key challenge in genome analysis and in proteomics. Frequently such patterns are complex and highly variable, especially in protein sequences. They are frequently described using terms of regular expressions (RegEx) because of the user-friendly terminology. Limitations arise for queries with the increasing complexity of patterns and are accompanied by requirements for enhanced capabilities. This is especially true for patterns containing ambiguous characters and positions and/or length ambiguities. We have implemented the 3of5 web application in order to enable complex pattern matching in protein sequences. 3of5 is named after a special use of its main feature, the novel n-of-m pattern type. This feature allows for an extensive specification of variable patterns where the individual elements may vary in their position, order, and content within a defined stretch of sequence. The number of distinct elements can be constrained by operators, and individual characters may be excluded. The n-of-m pattern type can be combined with common regular expression terms and thus also allows for a comprehensive description of complex patterns. 3of5 increases the fidelity of pattern matching and finds ALL possible solutions in protein sequences in cases of length-ambiguous patterns instead of simply reporting the longest or shortest hits. Grouping and combined search for patterns provides a hierarchical arrangement of larger patterns sets. The algorithm is implemented as internet application and freely accessible. The application is available at http://dkfz.de/mga2/3of5/3of5.html. The 3of5 application offers an extended vocabulary for the definition of search patterns and thus allows the user to comprehensively specify and identify peptide patterns with variable elements. The n-of-m pattern type offers an improved accuracy for pattern matching in combination with the ability to find all solutions, without compromising the user friendliness of regular expression terms.
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Sowpati, Divya Tej; Srivastava, Surabhi; Dhawan, Jyotsna; Mishra, Rakesh K
2017-09-13
Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.
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Where Am I? Location Archetype Keyword Extraction from Urban Mobility Patterns
Kostakos, Vassilis; Juntunen, Tomi; Goncalves, Jorge; Hosio, Simo; Ojala, Timo
2013-01-01
Can online behaviour be used as a proxy for studying urban mobility? The increasing availability of digital mobility traces has provided new insights into collective human behaviour. Mobility datasets have been shown to be an accurate proxy for daily behaviour and social patterns, and behavioural data from Twitter has been used to predict real world phenomena such as cinema ticket sale volumes, stock prices, and disease outbreaks. In this paper we correlate city-scale urban traffic patterns with online search trends to uncover keywords describing the pedestrian traffic location. By analysing a 3-year mobility dataset we show that our approach, called Location Archetype Keyword Extraction (LAKE), is capable of uncovering semantically relevant keywords for describing a location. Our findings demonstrate an overarching relationship between online and offline collective behaviour, and allow for advancing analysis of community-level behaviour by using online search keywords as a practical behaviour proxy. PMID:23704964
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Where am I? Location archetype keyword extraction from urban mobility patterns.
Kostakos, Vassilis; Juntunen, Tomi; Goncalves, Jorge; Hosio, Simo; Ojala, Timo
2013-01-01
Can online behaviour be used as a proxy for studying urban mobility? The increasing availability of digital mobility traces has provided new insights into collective human behaviour. Mobility datasets have been shown to be an accurate proxy for daily behaviour and social patterns, and behavioural data from Twitter has been used to predict real world phenomena such as cinema ticket sale volumes, stock prices, and disease outbreaks. In this paper we correlate city-scale urban traffic patterns with online search trends to uncover keywords describing the pedestrian traffic location. By analysing a 3-year mobility dataset we show that our approach, called Location Archetype Keyword Extraction (LAKE), is capable of uncovering semantically relevant keywords for describing a location. Our findings demonstrate an overarching relationship between online and offline collective behaviour, and allow for advancing analysis of community-level behaviour by using online search keywords as a practical behaviour proxy.
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Johnson, M M
1990-03-01
This study explored the use of process tracing techniques in examining the decision-making processes of older and younger adults. Thirty-six college-age and thirty-six retirement-age participants decided which one of six cars they would purchase on the basis of computer-accessed data. They provided information search protocols. Results indicate that total time to reach a decision did not differ according to age. However, retirement-age participants used less information, spent more time viewing, and re-viewed fewer bits of information than college-age participants. Information search patterns differed markedly between age groups. Patterns of retirement-age adults indicated their use of noncompensatory decision rules which, according to decision-making literature (Payne, 1976), reduce cognitive processing demands. The patterns of the college-age adults indicated their use of compensatory decision rules, which have higher processing demands.
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2014-01-01
In the current practice, to determine the safety factor of a slope with two-dimensional circular potential failure surface, one of the searching methods for the critical slip surface is Genetic Algorithm (GA), while the method to calculate the slope safety factor is Fellenius' slices method. However GA needs to be validated with more numeric tests, while Fellenius' slices method is just an approximate method like finite element method. This paper proposed a new method to determine the minimum slope safety factor which is the determination of slope safety factor with analytical solution and searching critical slip surface with Genetic-Traversal Random Method. The analytical solution is more accurate than Fellenius' slices method. The Genetic-Traversal Random Method uses random pick to utilize mutation. A computer automatic search program is developed for the Genetic-Traversal Random Method. After comparison with other methods like slope/w software, results indicate that the Genetic-Traversal Random Search Method can give very low safety factor which is about half of the other methods. However the obtained minimum safety factor with Genetic-Traversal Random Search Method is very close to the lower bound solutions of slope safety factor given by the Ansys software. PMID:24782679
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Solving Fuzzy Optimization Problem Using Hybrid Ls-Sa Method
NASA Astrophysics Data System (ADS)
Vasant, Pandian
2011-06-01
Fuzzy optimization problem has been one of the most and prominent topics inside the broad area of computational intelligent. It's especially relevant in the filed of fuzzy non-linear programming. It's application as well as practical realization can been seen in all the real world problems. In this paper a large scale non-linear fuzzy programming problem has been solved by hybrid optimization techniques of Line Search (LS), Simulated Annealing (SA) and Pattern Search (PS). As industrial production planning problem with cubic objective function, 8 decision variables and 29 constraints has been solved successfully using LS-SA-PS hybrid optimization techniques. The computational results for the objective function respect to vagueness factor and level of satisfaction has been provided in the form of 2D and 3D plots. The outcome is very promising and strongly suggests that the hybrid LS-SA-PS algorithm is very efficient and productive in solving the large scale non-linear fuzzy programming problem.
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NASA Astrophysics Data System (ADS)
Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood
2015-10-01
Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.
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Intermittent search strategies
NASA Astrophysics Data System (ADS)
Bénichou, O.; Loverdo, C.; Moreau, M.; Voituriez, R.
2011-01-01
This review examines intermittent target search strategies, which combine phases of slow motion, allowing the searcher to detect the target, and phases of fast motion during which targets cannot be detected. It is first shown that intermittent search strategies are actually widely observed at various scales. At the macroscopic scale, this is, for example, the case of animals looking for food; at the microscopic scale, intermittent transport patterns are involved in a reaction pathway of DNA-binding proteins as well as in intracellular transport. Second, generic stochastic models are introduced, which show that intermittent strategies are efficient strategies that enable the minimization of search time. This suggests that the intrinsic efficiency of intermittent search strategies could justify their frequent observation in nature. Last, beyond these modeling aspects, it is proposed that intermittent strategies could also be used in a broader context to design and accelerate search processes.
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Loading Patterns of the Posterior Cruciate Ligament in the Healthy Knee: A Systematic Review
List, Renate; Oberhofer, Katja; Fucentese, Sandro F.; Snedeker, Jess G.; Taylor, William R.
2016-01-01
Background The posterior cruciate ligament (PCL) is the strongest ligament of the knee, serving as one of the major passive stabilizers of the tibio-femoral joint. However, despite a number of experimental and modelling approaches to understand the kinematics and kinetics of the ligament, the normal loading conditions of the PCL and its functional bundles are still controversially discussed. Objectives This study aimed to generate science-based evidence for understanding the functional loading of the PCL, including the anterolateral and posteromedial bundles, in the healthy knee joint through systematic review and statistical analysis of the literature. Data sources MEDLINE, EMBASE and CENTRAL Eligibility criteria for selecting studies Databases were searched for articles containing any numerical strain or force data on the healthy PCL and its functional bundles. Studied activities were as follows: passive flexion, flexion under 100N and 134N posterior tibial load, walking, stair ascent and descent, body-weight squatting and forward lunge. Method Statistical analysis was performed on the reported load data, which was weighted according to the number of knees tested to extract average strain and force trends of the PCL and identify deviations from the norms. Results From the 3577 articles retrieved by the initial electronic search, only 66 met all inclusion criteria. The results obtained by aggregating data reported in the eligible studies indicate that the loading patterns of the PCL vary with activity type, knee flexion angle, but importantly also the technique used for assessment. Moreover, different fibres of the PCL exhibit different strain patterns during knee flexion, with higher strain magnitudes reported in the anterolateral bundle. While during passive flexion the posteromedial bundle is either lax or very slightly elongated, it experiences higher strain levels during forward lunge and has a synergetic relationship with the anterolateral bundle. The strain patterns obtained for virtual fibres that connect the origin and insertion of the bundles in a straight line show similar trends to those of the real bundles but with different magnitudes. Conclusion This review represents what is now the best available understanding of the biomechanics of the PCL, and may help to improve programs for injury prevention, diagnosis methods as well as reconstruction and rehabilitation techniques. PMID:27880849
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Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M
2011-07-01
Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.
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Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.
2011-01-01
Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652
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Semi-automating the manual literature search for systematic reviews increases efficiency.
Chapman, Andrea L; Morgan, Laura C; Gartlehner, Gerald
2010-03-01
To minimise retrieval bias, manual literature searches are a key part of the search process of any systematic review. Considering the need to have accurate information, valid results of the manual literature search are essential to ensure scientific standards; likewise efficient approaches that minimise the amount of personnel time required to conduct a manual literature search are of great interest. The objective of this project was to determine the validity and efficiency of a new manual search method that utilises the scopus database. We used the traditional manual search approach as the gold standard to determine the validity and efficiency of the proposed scopus method. Outcome measures included completeness of article detection and personnel time involved. Using both methods independently, we compared the results based on accuracy of the results, validity and time spent conducting the search, efficiency. Regarding accuracy, the scopus method identified the same studies as the traditional approach indicating its validity. In terms of efficiency, using scopus led to a time saving of 62.5% compared with the traditional approach (3 h versus 8 h). The scopus method can significantly improve the efficiency of manual searches and thus of systematic reviews.
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Dietary pattern analysis: a comparison between matched vegetarian and omnivorous subjects
2013-01-01
Background Dietary pattern analysis, based on the concept that foods eaten together are as important as a reductive methodology characterized by a single food or nutrient analysis, has emerged as an alternative approach to study the relation between nutrition and disease. The aim of the present study was to compare nutritional intake and the results of dietary pattern analysis in properly matched vegetarian and omnivorous subjects. Methods Vegetarians (n = 69) were recruited via purposeful sampling and matched non-vegetarians (n = 69) with same age, gender, health and lifestyle characteristics were searched for via convenience sampling. Two dietary pattern analysis methods, the Healthy Eating Index-2010 (HEI-2010) and the Mediterranean Diet Score (MDS) were calculated and analysed in function of the nutrient intake. Results Mean total energy intake was comparable between vegetarians and omnivorous subjects (p > 0.05). Macronutrient analysis revealed significant differences between the mean values for vegetarians and omnivorous subjects (absolute and relative protein and total fat intake were significantly lower in vegetarians, while carbohydrate and fibre intakes were significantly higher in vegetarians than in omnivorous subjects). The HEI and MDS were significantly higher for the vegetarians (HEI = 53.8.1 ± 11.2; MDS = 4.3 ± 1.3) compared to the omnivorous subjects (HEI = 46.4 ± 15.3; MDS = 3.8 ± 1.4). Conclusions Our results indicate a more nutrient dense pattern, closer to the current dietary recommendations for the vegetarians compared to the omnivorous subjects. Both indexing systems were able to discriminate between the vegetarians and the non-vegetarians with higher scores for the vegetarian subjects. PMID:23758767