Massively parallel support for a case-based planning system

NASA Technical Reports Server (NTRS)

Kettler, Brian P.; Hendler, James A.; Anderson, William A.

1993-01-01

Case-based planning (CBP), a kind of case-based reasoning, is a technique in which previously generated plans (cases) are stored in memory and can be reused to solve similar planning problems in the future. CBP can save considerable time over generative planning, in which a new plan is produced from scratch. CBP thus offers a potential (heuristic) mechanism for handling intractable problems. One drawback of CBP systems has been the need for a highly structured memory to reduce retrieval times. This approach requires significant domain engineering and complex memory indexing schemes to make these planners efficient. In contrast, our CBP system, CaPER, uses a massively parallel frame-based AI language (PARKA) and can do extremely fast retrieval of complex cases from a large, unindexed memory. The ability to do fast, frequent retrievals has many advantages: indexing is unnecessary; very large case bases can be used; memory can be probed in numerous alternate ways; and queries can be made at several levels, allowing more specific retrieval of stored plans that better fit the target problem with less adaptation. In this paper we describe CaPER's case retrieval techniques and some experimental results showing its good performance, even on large case bases.

Adaptive semi-supervised recursive tree partitioning: The ART towards large scale patient indexing in personalized healthcare.

PubMed

Wang, Fei

2015-06-01

With the rapid development of information technologies, tremendous amount of data became readily available in various application domains. This big data era presents challenges to many conventional data analytics research directions including data capture, storage, search, sharing, analysis, and visualization. It is no surprise to see that the success of next-generation healthcare systems heavily relies on the effective utilization of gigantic amounts of medical data. The ability of analyzing big data in modern healthcare systems plays a vital role in the improvement of the quality of care delivery. Specifically, patient similarity evaluation aims at estimating the clinical affinity and diagnostic proximity of patients. As one of the successful data driven techniques adopted in healthcare systems, patient similarity evaluation plays a fundamental role in many healthcare research areas such as prognosis, risk assessment, and comparative effectiveness analysis. However, existing algorithms for patient similarity evaluation are inefficient in handling massive patient data. In this paper, we propose an Adaptive Semi-Supervised Recursive Tree Partitioning (ART) framework for large scale patient indexing such that the patients with similar clinical or diagnostic patterns can be correctly and efficiently retrieved. The framework is designed for semi-supervised settings since it is crucial to leverage experts' supervision knowledge in medical scenario, which are fairly limited compared to the available data. Starting from the proposed ART framework, we will discuss several specific instantiations and validate them on both benchmark and real world healthcare data. Our results show that with the ART framework, the patients can be efficiently and effectively indexed in the sense that (1) similarity patients can be retrieved in a very short time; (2) the retrieval performance can beat the state-of-the art indexing methods. Copyright © 2015. Published by Elsevier Inc.

Diffractive optical elements for transformation of modes in lasers

DOEpatents

Sridharan, Arun K.; Pax, Paul H.; Heebner, John E.; Drachenberg, Derrek R.; Armstrong, James P.; Dawson, Jay W.

2015-09-01

Spatial mode conversion modules are described, with the capability of efficiently transforming a given optical beam profile, at one plane in space into another well-defined optical beam profile at a different plane in space, whose detailed spatial features and symmetry properties can, in general, differ significantly. The modules are comprised of passive, high-efficiency, low-loss diffractive optical elements, combined with Fourier transform optics. Design rules are described that employ phase retrieval techniques and associated algorithms to determine the necessary profiles of the diffractive optical components. System augmentations are described that utilize real-time adaptive optical techniques for enhanced performance as well as power scaling.

Diffractive optical elements for transformation of modes in lasers

DOEpatents

Sridharan, Arun K; Pax, Paul H; Heebner, John E; Drachenberg, Derrek R.; Armstrong, James P.; Dawson, Jay W.

2016-06-21

Spatial mode conversion modules are described, with the capability of efficiently transforming a given optical beam profile, at one plane in space into another well-defined optical beam profile at a different plane in space, whose detailed spatial features and symmetry properties can, in general, differ significantly. The modules are comprised of passive, high-efficiency, low-loss diffractive optical elements, combined with Fourier transform optics. Design rules are described that employ phase retrieval techniques and associated algorithms to determine the necessary profiles of the diffractive optical components. System augmentations are described that utilize real-time adaptive optical techniques for enhanced performance as well as power scaling.

Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

NASA Astrophysics Data System (ADS)

Roslund, Jonathan; Shir, Ofer M.; Bäck, Thomas; Rabitz, Herschel

2009-10-01

Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to ˜9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem’s Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape’s local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed Central

Frankewitsch, T.; Prokosch, U.

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval. PMID:10566463

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed

Frankewitsch, T; Prokosch, U

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval.

Striatal contributions to declarative memory retrieval

PubMed Central

Scimeca, Jason M.; Badre, David

2012-01-01

Declarative memory is known to depend on the medial temporal lobe memory system. Recently, there has been renewed focus on the relationship between the basal ganglia and declarative memory, including the involvement of striatum. However, the contribution of striatum to declarative memory retrieval remains unknown. Here, we review neuroimaging and neuropsychological evidence for the involvement of the striatum in declarative memory retrieval. From this review, we propose that, along with the prefrontal cortex (PFC), the striatum primarily supports cognitive control of memory retrieval. We conclude by proposing three hypotheses for the specific role of striatum in retrieval: (1) Striatum modulates the re-encoding of retrieved items in accord with their expected utility (adaptive encoding), (2) striatum selectively admits information into working memory that is expected to increase the likelihood of successful retrieval (adaptive gating), and (3) striatum enacts adjustments in cognitive control based on the outcome of retrieval (reinforcement learning). PMID:22884322

Connectionist Interaction Information Retrieval.

ERIC Educational Resources Information Center

Dominich, Sandor

2003-01-01

Discussion of connectionist views for adaptive clustering in information retrieval focuses on a connectionist clustering technique and activation spreading-based information retrieval model using the interaction information retrieval method. Presents theoretical as well as simulation results as regards computational complexity and includes…

Neural Differentiation Tracks Improved Recall of Competing Memories Following Interleaved Study and Retrieval Practice

PubMed Central

Hulbert, J. C.; Norman, K. A.

2015-01-01

Selective retrieval of overlapping memories can generate competition. How does the brain adaptively resolve this competition? One possibility is that competing memories are inhibited; in support of this view, numerous studies have found that selective retrieval leads to forgetting of memories that are related to the just-retrieved memory. However, this retrieval-induced forgetting (RIF) effect can be eliminated or even reversed if participants are given opportunities to restudy the materials between retrieval attempts. Here, we outline an explanation for such a reversal, rooted in a neural network model of RIF that predicts representational differentiation when restudy is interleaved with selective retrieval. To test this hypothesis, we measured changes in pattern similarity of the BOLD fMRI signal elicited by related memories after undergoing interleaved competitive retrieval and restudy. Reduced pattern similarity within the hippocampus positively correlated with retrieval-induced facilitation of competing memories. This result is consistent with an adaptive differentiation process that allows individuals to learn to distinguish between once-confusable memories. PMID:25477369

Modeling Clinical Information Needs in the Context of a Specific Patient

PubMed Central

Price, Susan L.

2000-01-01

Investigators have tried various approaches to link clinical information directly to information sources that may contain answers to clinical questions. Developing a model of clinical information needs that may arise in the context of viewing information about a specific patient is a preliminary step to finding an efficient, useful solution to the information retrieval problem. This poster illustrates a method of modeling clinical information needs in the context of a specific patient that that is adapted from entity-relationship models used in database design.

Making a Library Catalog Adaptive.

ERIC Educational Resources Information Center

Buckland, Michael K.; And Others

1992-01-01

Describes the design of a prototype adaptive online catalog that was implemented as a transparent workstation-based front end system to MELVYL, the online catalog for the University of California libraries. Problems with searching bibliographic retrieval systems are reviewed, including irrelevant retrievals and the inexperience of most users.…

Efficient retrieval of landscape Hessian: Forced optimal covariance adaptive learning

NASA Astrophysics Data System (ADS)

Shir, Ofer M.; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

2014-06-01

Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳104). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

OntoADR a semantic resource describing adverse drug reactions to support searching, coding, and information retrieval.

PubMed

Souvignet, Julien; Declerck, Gunnar; Asfari, Hadyl; Jaulent, Marie-Christine; Bousquet, Cédric

2016-10-01

Efficient searching and coding in databases that use terminological resources requires that they support efficient data retrieval. The Medical Dictionary for Regulatory Activities (MedDRA) is a reference terminology for several countries and organizations to code adverse drug reactions (ADRs) for pharmacovigilance. Ontologies that are available in the medical domain provide several advantages such as reasoning to improve data retrieval. The field of pharmacovigilance does not yet benefit from a fully operational ontology to formally represent the MedDRA terms. Our objective was to build a semantic resource based on formal description logic to improve MedDRA term retrieval and aid the generation of on-demand custom groupings by appropriately and efficiently selecting terms: OntoADR. The method consists of the following steps: (1) mapping between MedDRA terms and SNOMED-CT, (2) generation of semantic definitions using semi-automatic methods, (3) storage of the resource and (4) manual curation by pharmacovigilance experts. We built a semantic resource for ADRs enabling a new type of semantics-based term search. OntoADR adds new search capabilities relative to previous approaches, overcoming the usual limitations of computation using lightweight description logic, such as the intractability of unions or negation queries, bringing it closer to user needs. Our automated approach for defining MedDRA terms enabled the association of at least one defining relationship with 67% of preferred terms. The curation work performed on our sample showed an error level of 14% for this automated approach. We tested OntoADR in practice, which allowed us to build custom groupings for several medical topics of interest. The methods we describe in this article could be adapted and extended to other terminologies which do not benefit from a formal semantic representation, thus enabling better data retrieval performance. Our custom groupings of MedDRA terms were used while performing signal detection, which suggests that the graphical user interface we are currently implementing to process OntoADR could be usefully integrated into specialized pharmacovigilance software that rely on MedDRA. Copyright © 2016 Elsevier Inc. All rights reserved.

Knowledge Retrieval Solutions.

ERIC Educational Resources Information Center

Khan, Kamran

1998-01-01

Excalibur RetrievalWare offers true knowledge retrieval solutions. Its fundamental technologies, Adaptive Pattern Recognition Processing and Semantic Networks, have capabilities for knowledge discovery and knowledge management of full-text, structured and visual information. The software delivers a combination of accuracy, extensibility,…

Ventral striatum and the evaluation of memory retrieval strategies.

PubMed

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M; Scimeca, Jason M

2014-09-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant's subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.

Retrieval of long and short lists from long term memory: a functional magnetic resonance imaging study with human subjects.

PubMed

Zysset, S; Müller, K; Lehmann, C; Thöne-Otto, A I; von Cramon, D Y

2001-11-13

Previous studies have shown that reaction time in an item-recognition task with both short and long lists is a quadratic function of list length. This suggests that either different memory retrieval processes are implied for short and long lists or an adaptive process is involved. An event-related functional magnetic resonance imaging study with nine subjects and list lengths varying between 3 and 18 words was conducted to identify the underlying neuronal structures of retrieval from long and short lists. For the retrieval and processing of word-lists a single fronto-parietal network, including premotor, left prefrontal, left precuneal and left parietal regions, was activated. With increasing list length, no additional regions became involved in retrieving information from long-term memory, suggesting that not necessarily different, but highly adaptive retrieval processes are involved.

Adaptive neuro-fuzzy inference system for temperature and humidity profile retrieval from microwave radiometer observations

NASA Astrophysics Data System (ADS)

Ramesh, K.; Kesarkar, A. P.; Bhate, J.; Venkat Ratnam, M.; Jayaraman, A.

2015-01-01

The retrieval of accurate profiles of temperature and water vapour is important for the study of atmospheric convection. Recent development in computational techniques motivated us to use adaptive techniques in the retrieval algorithms. In this work, we have used an adaptive neuro-fuzzy inference system (ANFIS) to retrieve profiles of temperature and humidity up to 10 km over the tropical station Gadanki (13.5° N, 79.2° E), India. ANFIS is trained by using observations of temperature and humidity measurements by co-located Meisei GPS radiosonde (henceforth referred to as radiosonde) and microwave brightness temperatures observed by radiometrics multichannel microwave radiometer MP3000 (MWR). ANFIS is trained by considering these observations during rainy and non-rainy days (ANFIS(RD + NRD)) and during non-rainy days only (ANFIS(NRD)). The comparison of ANFIS(RD + NRD) and ANFIS(NRD) profiles with independent radiosonde observations and profiles retrieved using multivariate linear regression (MVLR: RD + NRD and NRD) and artificial neural network (ANN) indicated that the errors in the ANFIS(RD + NRD) are less compared to other retrieval methods. The Pearson product movement correlation coefficient (r) between retrieved and observed profiles is more than 92% for temperature profiles for all techniques and more than 99% for the ANFIS(RD + NRD) technique Therefore this new techniques is relatively better for the retrieval of temperature profiles. The comparison of bias, mean absolute error (MAE), RMSE and symmetric mean absolute percentage error (SMAPE) of retrieved temperature and relative humidity (RH) profiles using ANN and ANFIS also indicated that profiles retrieved using ANFIS(RD + NRD) are significantly better compared to the ANN technique. The analysis of profiles concludes that retrieved profiles using ANFIS techniques have improved the temperature retrievals substantially; however, the retrieval of RH by all techniques considered in this paper (ANN, MVLR and ANFIS) has limited success.

Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits.

PubMed

Boguslawski, Bartosz; Gripon, Vincent; Seguin, Fabrice; Heitzmann, Frédéric

2016-02-01

Associative memories are data structures that allow retrieval of previously stored messages given part of their content. They, thus, behave similarly to the human brain's memory that is capable, for instance, of retrieving the end of a song, given its beginning. Among different families of associative memories, sparse ones are known to provide the best efficiency (ratio of the number of bits stored to that of the bits used). Recently, a new family of sparse associative memories achieving almost optimal efficiency has been proposed. Their structure, relying on binary connections and neurons, induces a direct mapping between input messages and stored patterns. Nevertheless, it is well known that nonuniformity of the stored messages can lead to a dramatic decrease in performance. In this paper, we show the impact of nonuniformity on the performance of this recent model, and we exploit the structure of the model to improve its performance in practical applications, where data are not necessarily uniform. In order to approach the performance of networks with uniformly distributed messages presented in theoretical studies, twin neurons are introduced. To assess the adapted model, twin neurons are used with the real-world data to optimize power consumption of electronic circuits in practical test cases.

NASA develops teleoperator retrieval system

NASA Technical Reports Server (NTRS)

1978-01-01

The teleoperator retrieval system vehicle was designed to reboost and/or deorbit the Skylab; however, usefulness in survey, stabilization, retrieval and delivery was examined. Thrusters, designed for cold gas propulsion, were adapted to hydrazine propulsion. Design specifications and cost analysis are given.

Increased gamma band power during movement planning coincides with motor memory retrieval.

PubMed

Thürer, Benjamin; Stockinger, Christian; Focke, Anne; Putze, Felix; Schultz, Tanja; Stein, Thorsten

2016-01-15

The retrieval of motor memory requires a previous memory encoding and subsequent consolidation of the specific motor memory. Previous work showed that motor memory seems to rely on different memory components (e.g., implicit, explicit). However, it is still unknown if explicit components contribute to the retrieval of motor memories formed by dynamic adaptation tasks and which neural correlates are linked to memory retrieval. We investigated the lower and higher gamma bands of subjects' electroencephalography during encoding and retrieval of a dynamic adaptation task. A total of 24 subjects were randomly assigned to a treatment and control group. Both groups adapted to a force field A on day 1 and were re-exposed to the same force field A on day 3 of the experiment. On day 2, treatment group learned an interfering force field B whereas control group had a day rest. Kinematic analyses showed that control group improved their initial motor performance from day 1 to day 3 but treatment group did not. This behavioral result coincided with an increased higher gamma band power in the electrodes over prefrontal areas on the initial trials of day 3 for control but not treatment group. Intriguingly, this effect vanished with the subsequent re-adaptation on day 3. We suggest that improved re-test performance in a dynamic motor adaptation task is contributed by explicit memory and that gamma bands in the electrodes over the prefrontal cortex are linked to these explicit components. Furthermore, we suggest that the contribution of explicit memory vanishes with the subsequent re-adaptation while task automaticity increases. Copyright © 2015 Elsevier Inc. All rights reserved.

Highly retrievable spin-wave-photon entanglement source.

PubMed

Yang, Sheng-Jun; Wang, Xu-Jie; Li, Jun; Rui, Jun; Bao, Xiao-Hui; Pan, Jian-Wei

2015-05-29

Entanglement between a single photon and a quantum memory forms the building blocks for a quantum repeater and quantum network. Previous entanglement sources are typically with low retrieval efficiency, which limits future larger-scale applications. Here, we report a source of highly retrievable spin-wave-photon entanglement. Polarization entanglement is created through interaction of a single photon with an ensemble of atoms inside a low-finesse ring cavity. The cavity is engineered to be resonant for dual spin-wave modes, which thus enables efficient retrieval of the spin-wave qubit. An intrinsic retrieval efficiency up to 76(4)% has been observed. Such a highly retrievable atom-photon entanglement source will be very useful in future larger-scale quantum repeater and quantum network applications.

Improving the utility of the fine motor skills subscale of the comprehensive developmental inventory for infants and toddlers: a computerized adaptive test.

PubMed

Huang, Chien-Yu; Tung, Li-Chen; Chou, Yeh-Tai; Chou, Willy; Chen, Kuan-Lin; Hsieh, Ching-Lin

2017-07-27

This study aimed at improving the utility of the fine motor subscale of the comprehensive developmental inventory for infants and toddlers (CDIIT) by developing a computerized adaptive test of fine motor skills. We built an item bank for the computerized adaptive test of fine motor skills using the fine motor subscale of the CDIIT items fitting the Rasch model. We also examined the psychometric properties and efficiency of the computerized adaptive test of fine motor skills with simulated computerized adaptive tests. Data from 1742 children with suspected developmental delays were retrieved. The mean scores of the fine motor subscale of the CDIIT increased along with age groups (mean scores = 1.36-36.97). The computerized adaptive test of fine motor skills contains 31 items meeting the Rasch model's assumptions (infit mean square = 0.57-1.21, outfit mean square = 0.11-1.17). For children of 6-71 months, the computerized adaptive test of fine motor skills had high Rasch person reliability (average reliability >0.90), high concurrent validity (rs = 0.67-0.99), adequate to excellent diagnostic accuracy (area under receiver operating characteristic = 0.71-1.00), and large responsiveness (effect size = 1.05-3.93). The computerized adaptive test of fine motor skills used 48-84% fewer items than the fine motor subscale of the CDIIT. The computerized adaptive test of fine motor skills used fewer items for assessment but was as reliable and valid as the fine motor subscale of the CDIIT. Implications for Rehabilitation We developed a computerized adaptive test based on the comprehensive developmental inventory for infants and toddlers (CDIIT) for assessing fine motor skills. The computerized adaptive test has been shown to be efficient because it uses fewer items than the original measure and automatically presents the results right after the test is completed. The computerized adaptive test is as reliable and valid as the CDIIT.

Effects of Individualized Word Retrieval in Kindergarten Vocabulary Intervention

ERIC Educational Resources Information Center

Damhuis, Carmen M. P.; Segers, Eliane; Scheltinga, Femke; Verhoeven, Ludo

2016-01-01

We examined the effects of adaptive word retrieval intervention on a classroom vocabulary program on children's vocabulary acquisition in kindergarten. In the experimental condition, word retrieval was provided in a classroom vocabulary program, combining implicit and explicit vocabulary instructions. Children performed extra word retrieval…

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Ventral Striatum and the Evaluation of Memory Retrieval Strategies

PubMed Central

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M.; Scimeca, Jason M.

2015-01-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant’s subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies. PMID:24564466

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Information Retrieval on social network: An Adaptive Proof

NASA Astrophysics Data System (ADS)

Elveny, M.; Syah, R.; Elfida, M.; Nasution, M. K. M.

2018-01-01

Information Retrieval has become one of the areas for studying to get the trusty information, with which the recall and precision become the measurement form that represents it. Nevertheless, development in certain scientific fields make it possible to improve the performance of the Information Retrieval. In this case, through social networks whereby the role of social actor degrees plays a role. This is an implication of the query in which co-occurrence becomes an indication of social networks. An adaptive approach we use by involving this query in sequence to a stand-alone query, it has proven the relationship among them.

Flexible Retrieval: When True Inferences Produce False Memories

ERIC Educational Resources Information Center

Carpenter, Alexis C.; Schacter, Daniel L.

2017-01-01

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave…

Intrinsic retrieval efficiency for quantum memories: A three-dimensional theory of light interaction with an atomic ensemble

NASA Astrophysics Data System (ADS)

Gujarati, Tanvi P.; Wu, Yukai; Duan, Luming

2018-03-01

Duan-Lukin-Cirac-Zoller quantum repeater protocol, which was proposed to realize long distance quantum communication, requires usage of quantum memories. Atomic ensembles interacting with optical beams based on off-resonant Raman scattering serve as convenient on-demand quantum memories. Here, a complete free space, three-dimensional theory of the associated read and write process for this quantum memory is worked out with the aim of understanding intrinsic retrieval efficiency. We develop a formalism to calculate the transverse mode structure for the signal and the idler photons and use the formalism to study the intrinsic retrieval efficiency under various configurations. The effects of atomic density fluctuations and atomic motion are incorporated by numerically simulating this system for a range of realistic experimental parameters. We obtain results that describe the variation in the intrinsic retrieval efficiency as a function of the memory storage time for skewed beam configuration at a finite temperature, which provides valuable information for optimization of the retrieval efficiency in experiments.

On the retrieval efficiency of light storage in an EIT medium

NASA Astrophysics Data System (ADS)

Chough, Young-Tak

2016-08-01

We investigate the retrieval efficiency of light slowed and/or stored in a medium with electromagnetically-induced transparency (an EIT medium) by numerical simulations based on first principles. Starting from the master equation formulation, we derive the full dynamics of the system and then show how the approximations are applied to reduce the number of dynamical equations. While operating the system as an optical "retarder," a "reflector," and a "beam-splitter," we find that the total retrieval efficiency in the case of the "beam-splitter" operation is lower than that in either of the other two operations. Nevertheless, we find that (1) when an appropriate value of detuning is applied between the two counter-propagating " read"-fields, the retrieval efficiency in the latter case can be significantly improved, (2) storing the signal in the form of the atomic spin wave is more advantageous than storing it in the form of a stationary light pulse (SLP), and (3) the retrieval efficiency can be augmented by increasing the strengths of the " read"-fields.

An Expressive and Efficient Language for XML Information Retrieval.

ERIC Educational Resources Information Center

Chinenyanga, Taurai Tapiwa; Kushmerick, Nicholas

2002-01-01

Discusses XML and information retrieval and describes a query language, ELIXIR (expressive and efficient language for XML information retrieval), with a textual similarity operator that can be used for similarity joins. Explains the algorithm for answering ELIXIR queries to generate intermediate relational data. (Author/LRW)

The present status and problems in document retrieval system : document input type retrieval system

NASA Astrophysics Data System (ADS)

Inagaki, Hirohito

The office-automation (OA) made many changes. Many documents were begun to maintained in an electronic filing system. Therefore, it is needed to establish efficient document retrieval system to extract useful information. Current document retrieval systems are using simple word-matching, syntactic-matching, semantic-matching to obtain high retrieval efficiency. On the other hand, the document retrieval systems using special hardware devices, such as ISSP, were developed for aiming high speed retrieval. Since these systems can accept a single sentence or keywords as input, it is difficult to explain searcher's request. We demonstrated document input type retrieval system, which can directly accept document as an input, and can search similar documents from document data-base.

Long-term moderate elevation of corticosterone facilitates avian food-caching behaviour and enhances spatial memory.

PubMed

Pravosudov, Vladimir V

2003-12-22

It is widely assumed that chronic stress and corresponding chronic elevations of glucocorticoid levels have deleterious effects on animals' brain functions such as learning and memory. Some animals, however, appear to maintain moderately elevated levels of glucocorticoids over long periods of time under natural energetically demanding conditions, and it is not clear whether such chronic but moderate elevations may be adaptive. I implanted wild-caught food-caching mountain chickadees (Poecile gambeli), which rely at least in part on spatial memory to find their caches, with 90-day continuous time-release corticosterone pellets designed to approximately double the baseline corticosterone levels. Corticosterone-implanted birds cached and consumed significantly more food and showed more efficient cache recovery and superior spatial memory performance compared with placebo-implanted birds. Thus, contrary to prevailing assumptions, long-term moderate elevations of corticosterone appear to enhance spatial memory in food-caching mountain chickadees. These results suggest that moderate chronic elevation of corticosterone may serve as an adaptation to unpredictable environments by facilitating feeding and food-caching behaviour and by improving cache-retrieval efficiency in food-caching birds.

Retrieval as a Fast Route to Memory Consolidation.

PubMed

Antony, James W; Ferreira, Catarina S; Norman, Kenneth A; Wimber, Maria

2017-08-01

Retrieval-mediated learning is a powerful way to make memories last, but its neurocognitive mechanisms remain unclear. We propose that retrieval acts as a rapid consolidation event, supporting the creation of adaptive hippocampal-neocortical representations via the 'online' reactivation of associative information. We describe parallels between online retrieval and offline consolidation and offer testable predictions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive and accelerated tracking-learning-detection

NASA Astrophysics Data System (ADS)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

User centered and ontology based information retrieval system for life sciences.

PubMed

Sy, Mohameth-François; Ranwez, Sylvie; Montmain, Jacky; Regnault, Armelle; Crampes, Michel; Ranwez, Vincent

2012-01-25

Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

User centered and ontology based information retrieval system for life sciences

PubMed Central

2012-01-01

Background Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help. PMID:22373375

Water Planetary and Cometary Atmospheres: H2O/HDO Transmittance and Fluorescence Models

NASA Technical Reports Server (NTRS)

Villanueva, G. L.; Mumma, M. J.; Bonev, B. P.; Novak, R. E.; Barber, R. J.; DiSanti, M. A.

2012-01-01

We developed a modern methodology to retrieve water (H2O) and deuterated water (HDO) in planetary and cometary atmospheres, and constructed an accurate spectral database that combines theoretical and empirical results. Based on a greatly expanded set of spectroscopic parameters, we built a full non-resonance cascade fluorescence model and computed fluorescence efficiencies for H2O (500 million lines) and HDO (700 million lines). The new line list was also integrated into an advanced terrestrial radiative transfer code (LBLRTM) and adapted to the CO2 rich atmosphere of Mars, for which we adopted the complex Robert-Bonamy formalism for line shapes. We then retrieved water and D/H in the atmospheres of Mars, comet C/2007 WI, and Earth by applying the new formalism to spectra obtained with the high-resolution spectrograph NIRSPEC/Keck II atop Mauna Kea (Hawaii). The new model accurately describes the complex morphology of the water bands and greatly increases the accuracy of the retrieved abundances (and the D/H ratio in water) with respect to previously available models. The new model provides improved agreement of predicted and measured intensities for many H2O lines already identified in comets, and it identifies several unassigned cometary emission lines as new emission lines of H2O. The improved spectral accuracy permits retrieval of more accurate rotational temperatures and production rates for cometary water.

Retrieval Constraints on the Front End Create Differences in Recollection on a Subsequent Test

ERIC Educational Resources Information Center

Marsh, Richard L.; Meeks, J. Thadeus; Cook, Gabriel I.; Clark-Foos, Arlo; Hicks, Jason L.; Brewer, Gene A.

2009-01-01

Four experiments were conducted to investigate how the cognitive control of memory retrieval selects particular qualitative characteristics as a consequence of instantiating a retrieval mode for recognition memory. Adapting the memory for foils paradigm from Jacoby, Shimizu, Daniels, and Rhodes (Jacoby, L. L., Shimizu, Y., Daniels, K. A., &…

Digital adaptive optics confocal microscopy based on iterative retrieval of optical aberration from a guidestar hologram

PubMed Central

Liu, Changgeng; Thapa, Damber; Yao, Xincheng

2017-01-01

Guidestar hologram based digital adaptive optics (DAO) is one recently emerging active imaging modality. It records each complex distorted line field reflected or scattered from the sample by an off-axis digital hologram, measures the optical aberration from a separate off-axis digital guidestar hologram, and removes the optical aberration from the distorted line fields by numerical processing. In previously demonstrated DAO systems, the optical aberration was directly retrieved from the guidestar hologram by taking its Fourier transform and extracting the phase term. For the direct retrieval method (DRM), when the sample is not coincident with the guidestar focal plane, the accuracy of the optical aberration retrieved by DRM undergoes a fast decay, leading to quality deterioration of corrected images. To tackle this problem, we explore here an image metrics-based iterative method (MIM) to retrieve the optical aberration from the guidestar hologram. Using an aberrated objective lens and scattering samples, we demonstrate that MIM can improve the accuracy of the retrieved aberrations from both focused and defocused guidestar holograms, compared to DRM, to improve the robustness of the DAO. PMID:28380937

[A retrieval method of drug molecules based on graph collapsing].

PubMed

Qu, J W; Lv, X Q; Liu, Z M; Liao, Y; Sun, P H; Wang, B; Tang, Z

2018-04-18

To establish a compact and efficient hypergraph representation and a graph-similarity-based retrieval method of molecules to achieve effective and efficient medicine information retrieval. Chemical structural formula (CSF) was a primary search target as a unique and precise identifier for each compound at the molecular level in the research field of medicine information retrieval. To retrieve medicine information effectively and efficiently, a complete workflow of the graph-based CSF retrieval system was introduced. This system accepted the photos taken from smartphones and the sketches drawn on tablet personal computers as CSF inputs, and formalized the CSFs with the corresponding graphs. Then this paper proposed a compact and efficient hypergraph representation for molecules on the basis of analyzing factors that directly affected the efficiency of graph matching. According to the characteristics of CSFs, a hierarchical collapsing method combining graph isomorphism and frequent subgraph mining was adopted. There was yet a fundamental challenge, subgraph overlapping during the collapsing procedure, which hindered the method from establishing the correct compact hypergraph of an original CSF graph. Therefore, a graph-isomorphism-based algorithm was proposed to select dominant acyclic subgraphs on the basis of overlapping analysis. Finally, the spatial similarity among graphical CSFs was evaluated by multi-dimensional measures of similarity. To evaluate the performance of the proposed method, the proposed system was firstly compared with Wikipedia Chemical Structure Explorer (WCSE), the state-of-the-art system that allowed CSF similarity searching within Wikipedia molecules dataset, on retrieval accuracy. The system achieved higher values on mean average precision, discounted cumulative gain, rank-biased precision, and expected reciprocal rank than WCSE from the top-2 to the top-10 retrieved results. Specifically, the system achieved 10%, 1.41, 6.42%, and 1.32% higher than WCSE on these metrics for top-10 retrieval results, respectively. Moreover, several retrieval cases were presented to intuitively compare with WCSE. The results of the above comparative study demonstrated that the proposed method outperformed the existing method with regard to accuracy and effectiveness. This paper proposes a graph-similarity-based retrieval approach for medicine information. To obtain satisfactory retrieval results, an isomorphism-based algorithm is proposed for dominant subgraph selection based on the subgraph overlapping analysis, as well as an effective and efficient hypergraph representation of molecules. Experiment results demonstrate the effectiveness of the proposed approach.

Distributed Two-Dimensional Fourier Transforms on DSPs with an Application for Phase Retrieval

NASA Technical Reports Server (NTRS)

Smith, Jeffrey Scott

2006-01-01

Many applications of two-dimensional Fourier Transforms require fixed timing as defined by system specifications. One example is image-based wavefront sensing. The image-based approach has many benefits, yet it is a computational intensive solution for adaptive optic correction, where optical adjustments are made in real-time to correct for external (atmospheric turbulence) and internal (stability) aberrations, which cause image degradation. For phase retrieval, a type of image-based wavefront sensing, numerous two-dimensional Fast Fourier Transforms (FFTs) are used. To meet the required real-time specifications, a distributed system is needed, and thus, the 2-D FFT necessitates an all-to-all communication among the computational nodes. The 1-D floating point FFT is very efficient on a digital signal processor (DSP). For this study, several architectures and analysis of such are presented which address the all-to-all communication with DSPs. Emphasis of this research is on a 64-node cluster of Analog Devices TigerSharc TS-101 DSPs.

Efficient view based 3-D object retrieval using Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jain, Yogendra Kumar; Singh, Roshan Kumar

2013-12-01

Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

Optical technique for inner-scale measurement: possible astronomical applications.

PubMed

Masciadri, E; Vernin, J

1997-02-20

We propose an optical technique that allows us to estimate the inner scale by measuring the variance of angle of arrival fluctuations of collimated laser beams of different sections w (i) passing through a turbulent layer. To test the potential efficiency of the system, we made measurements on a turbulent air flow generated in the laboratory, the statistical properties of which are known and controlled, unlike atmospheric turbulence. We deduced a Kolmogorov behavior with a 6-mm inner scale and a 90-mm outer scale in accordance with measurements by a more complicated technique using the same turbulent channel. Our proposed method is especially sensitive to inner-scale measurement and can be adapted easily to atmospheric turbulence analysis. We propose an outdoor experimental setup that should work in less controlled conditions that can affect astronomical observations. The inner-scale assessment might be important when phase retrieval with Laplacian methods is used for adaptive optics purposes.

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality

NASA Astrophysics Data System (ADS)

Cherukuru, Nihanth Wagmi

Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars. Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona's Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities.

Transformed Neural Pattern Reinstatement during Episodic Memory Retrieval.

PubMed

Xiao, Xiaoqian; Dong, Qi; Gao, Jiahong; Men, Weiwei; Poldrack, Russell A; Xue, Gui

2017-03-15

Contemporary models of episodic memory posit that remembering involves the reenactment of encoding processes. Although encoding-retrieval similarity has been consistently reported and linked to memory success, the nature of neural pattern reinstatement is poorly understood. Using high-resolution fMRI on human subjects, our results obtained clear evidence for item-specific pattern reinstatement in the frontoparietal cortex, even when the encoding-retrieval pairs shared no perceptual similarity. No item-specific pattern reinstatement was found in the ventral visual cortex. Importantly, the brain regions and voxels carrying item-specific representation differed significantly between encoding and retrieval, and the item specificity for encoding-retrieval similarity was smaller than that for encoding or retrieval, suggesting different nature of representations between encoding and retrieval. Moreover, cross-region representational similarity analysis suggests that the encoded representation in the ventral visual cortex was reinstated in the frontoparietal cortex during retrieval. Together, these results suggest that, in addition to reinstatement of the originally encoded pattern in the brain regions that perform encoding processes, retrieval may also involve the reinstatement of a transformed representation of the encoded information. These results emphasize the constructive nature of memory retrieval that helps to serve important adaptive functions. SIGNIFICANCE STATEMENT Episodic memory enables humans to vividly reexperience past events, yet how this is achieved at the neural level is barely understood. A long-standing hypothesis posits that memory retrieval involves the faithful reinstatement of encoding-related activity. We tested this hypothesis by comparing the neural representations during encoding and retrieval. We found strong pattern reinstatement in the frontoparietal cortex, but not in the ventral visual cortex, that represents visual details. Critically, even within the same brain regions, the nature of representation during retrieval was qualitatively different from that during encoding. These results suggest that memory retrieval is not a faithful replay of past event but rather involves additional constructive processes to serve adaptive functions. Copyright © 2017 the authors 0270-6474/17/372986-13$15.00/0.

Adaptive optics compensation of orbital angular momentum beams with a modified Gerchberg-Saxton-based phase retrieval algorithm

NASA Astrophysics Data System (ADS)

Chang, Huan; Yin, Xiao-li; Cui, Xiao-zhou; Zhang, Zhi-chao; Ma, Jian-xin; Wu, Guo-hua; Zhang, Li-jia; Xin, Xiang-jun

2017-12-01

Practical orbital angular momentum (OAM)-based free-space optical (FSO) communications commonly experience serious performance degradation and crosstalk due to atmospheric turbulence. In this paper, we propose a wave-front sensorless adaptive optics (WSAO) system with a modified Gerchberg-Saxton (GS)-based phase retrieval algorithm to correct distorted OAM beams. We use the spatial phase perturbation (SPP) GS algorithm with a distorted probe Gaussian beam as the only input. The principle and parameter selections of the algorithm are analyzed, and the performance of the algorithm is discussed. The simulation results show that the proposed adaptive optics (AO) system can significantly compensate for distorted OAM beams in single-channel or multiplexed OAM systems, which provides new insights into adaptive correction systems using OAM beams.

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

The development of strategy use in elementary school children: working memory and individual differences.

PubMed

Imbo, Ineke; Vandierendonck, André

2007-04-01

The current study tested the development of working memory involvement in children's arithmetic strategy selection and strategy efficiency. To this end, an experiment in which the dual-task method and the choice/no-choice method were combined was administered to 10- to 12-year-olds. Working memory was needed in retrieval, transformation, and counting strategies, but the ratio between available working memory resources and arithmetic task demands changed across development. More frequent retrieval use, more efficient memory retrieval, and more efficient counting processes reduced the working memory requirements. Strategy efficiency and strategy selection were also modified by individual differences such as processing speed, arithmetic skill, gender, and math anxiety. Short-term memory capacity, in contrast, was not related to children's strategy selection or strategy efficiency.

Realistic and efficient 2D crack simulation

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing; Singh, Abhishek

2010-04-01

Although numerical algorithms for 2D crack simulation have been studied in Modeling and Simulation (M&S) and computer graphics for decades, realism and computational efficiency are still major challenges. In this paper, we introduce a high-fidelity, scalable, adaptive and efficient/runtime 2D crack/fracture simulation system by applying the mathematically elegant Peano-Cesaro triangular meshing/remeshing technique to model the generation of shards/fragments. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level-of-detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanism used for mesh element splitting and merging with minimal memory requirements essential for realistic 2D fragment formation. Upon load impact/contact/penetration, a number of factors including impact angle, impact energy, and material properties are all taken into account to produce the criteria of crack initialization, propagation, and termination leading to realistic fractal-like rubble/fragments formation. The aforementioned parameters are used as variables of probabilistic models of cracks/shards formation, making the proposed solution highly adaptive by allowing machine learning mechanisms learn the optimal values for the variables/parameters based on prior benchmark data generated by off-line physics based simulation solutions that produce accurate fractures/shards though at highly non-real time paste. Crack/fracture simulation has been conducted on various load impacts with different initial locations at various impulse scales. The simulation results demonstrate that the proposed system has the capability to realistically and efficiently simulate 2D crack phenomena (such as window shattering and shards generation) with diverse potentials in military and civil M&S applications such as training and mission planning.

A safe and efficient method to retrieve mesenchymal stem cells from three-dimensional fibrin gels.

PubMed

Carrion, Bita; Janson, Isaac A; Kong, Yen P; Putnam, Andrew J

2014-03-01

Mesenchymal stem cells (MSCs) display multipotent characteristics that make them ideal for potential therapeutic applications. MSCs are typically cultured as monolayers on tissue culture plastic, but there is increasing evidence suggesting that they may lose their multipotency over time in vitro and eventually cease to retain any resemblance to in vivo resident MSCs. Three-dimensional (3D) culture systems that more closely recapitulate the physiological environment of MSCs and other cell types are increasingly explored for their capacity to support and maintain the cell phenotypes. In much of our own work, we have utilized fibrin, a natural protein-based material that serves as the provisional extracellular matrix during wound healing. Fibrin has proven to be useful in numerous tissue engineering applications and has been used clinically as a hemostatic material. Its rapid self-assembly driven by thrombin-mediated alteration of fibrinogen makes fibrin an attractive 3D substrate, in which cells can adhere, spread, proliferate, and undergo complex morphogenetic programs. However, there is a significant need for simple cost-effective methods to safely retrieve cells encapsulated within fibrin hydrogels to perform additional analyses or use the cells for therapy. Here, we present a safe and efficient protocol for the isolation of MSCs from 3D fibrin gels. The key ingredient of our successful extraction method is nattokinase, a serine protease of the subtilisin family that has a strong fibrinolytic activity. Our data show that MSCs recovered from 3D fibrin gels using nattokinase are not only viable but also retain their proliferative and multilineage potentials. Demonstrated for MSCs, this method can be readily adapted to retrieve any other cell type from 3D fibrin gel constructs for various applications, including expansion, bioassays, and in vivo implantation.

A Safe and Efficient Method to Retrieve Mesenchymal Stem Cells from Three-Dimensional Fibrin Gels

PubMed Central

Carrion, Bita; Janson, Isaac A.; Kong, Yen P.

2014-01-01

Mesenchymal stem cells (MSCs) display multipotent characteristics that make them ideal for potential therapeutic applications. MSCs are typically cultured as monolayers on tissue culture plastic, but there is increasing evidence suggesting that they may lose their multipotency over time in vitro and eventually cease to retain any resemblance to in vivo resident MSCs. Three-dimensional (3D) culture systems that more closely recapitulate the physiological environment of MSCs and other cell types are increasingly explored for their capacity to support and maintain the cell phenotypes. In much of our own work, we have utilized fibrin, a natural protein-based material that serves as the provisional extracellular matrix during wound healing. Fibrin has proven to be useful in numerous tissue engineering applications and has been used clinically as a hemostatic material. Its rapid self-assembly driven by thrombin-mediated alteration of fibrinogen makes fibrin an attractive 3D substrate, in which cells can adhere, spread, proliferate, and undergo complex morphogenetic programs. However, there is a significant need for simple cost-effective methods to safely retrieve cells encapsulated within fibrin hydrogels to perform additional analyses or use the cells for therapy. Here, we present a safe and efficient protocol for the isolation of MSCs from 3D fibrin gels. The key ingredient of our successful extraction method is nattokinase, a serine protease of the subtilisin family that has a strong fibrinolytic activity. Our data show that MSCs recovered from 3D fibrin gels using nattokinase are not only viable but also retain their proliferative and multilineage potentials. Demonstrated for MSCs, this method can be readily adapted to retrieve any other cell type from 3D fibrin gel constructs for various applications, including expansion, bioassays, and in vivo implantation. PMID:23808842

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. PMID:28737699

Lower Tropospheric Ozone Retrievals from Infrared Satellite Observations Using a Self-Adapting Regularization Method

NASA Astrophysics Data System (ADS)

Eremenko, M.; Sgheri, L.; Ridolfi, M.; Dufour, G.; Cuesta, J.

2017-12-01

Lower tropospheric ozone (O3) retrievals from nadir sounders is challenging due to the lack of vertical sensitivity of the measurements and towards the lowest layers. If improvements have been made during the last decade, it is still important to explore possibilities to improve the retrieval algorithms themselves. O3 retrieval from nadir satellite observations is an ill-conditioned problem, which requires regularization using constraint matrices. Up to now, most of the retrieval algorithms rely on a fixed constraint. The constraint is determined and fixed beforehand, on the basis of sensitivity tests. This does not allow ones to take advantage of the entire capabilities of the satellite measurements, which vary with the thermal conditions of the observed scenes. To overcome this limitation, we developed a self-adapting and altitude-dependent regularization scheme. A crucial step is the choice of the strength of the constraint. This choice is done during an iterative process and depends on the measurement errors and on the sensitivity of the measurements to the target parameters at the different altitudes. The challenge is to limit the use of a priori constraints to the minimal amount needed to perform the inversion. The algorithm has been tested on synthetic observations matching the future IASI-NG satellite instrument. IASI-NG measurements are simulated on the basis of O3 concentrations taken from an atmospheric model and retrieved using two retrieval schemes (the standard and self-adapting ones). Comparison of the results shows that the sensitivity of the observations to the O3 amount in the lowest layers (given by the degrees of freedom for the solution) is increased, which allows a better description of the ozone distribution, especially in the case of large ozone plumes. Biases are reduced and the spatial correlation is improved. Tentative of application to real observations from IASI, currently onboard the Metop satellite will also be presented.

Indexing and retrieval of MPEG compressed video

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; Doermann, David S.

1998-04-01

To keep pace with the increased popularity of digital video as an archival medium, the development of techniques for fast and efficient analysis of ideo streams is essential. In particular, solutions to the problems of storing, indexing, browsing, and retrieving video data from large multimedia databases are necessary to a low access to these collections. Given that video is often stored efficiently in a compressed format, the costly overhead of decompression can be reduced by analyzing the compressed representation directly. In earlier work, we presented compressed domain parsing techniques which identified shots, subshots, and scenes. In this article, we present efficient key frame selection, feature extraction, indexing, and retrieval techniques that are directly applicable to MPEG compressed video. We develop a frame type independent representation which normalizes spatial and temporal features including frame type, frame size, macroblock encoding, and motion compensation vectors. Features for indexing are derived directly from this representation and mapped to a low- dimensional space where they can be accessed using standard database techniques. Spatial information is used as primary index into the database and temporal information is used to rank retrieved clips and enhance the robustness of the system. The techniques presented enable efficient indexing, querying, and retrieval of compressed video as demonstrated by our system which typically takes a fraction of a second to retrieve similar video scenes from a database, with over 95 percent recall.

An efficient approach for video information retrieval

NASA Astrophysics Data System (ADS)

Dong, Daoguo; Xue, Xiangyang

2005-01-01

Today, more and more video information can be accessed through internet, satellite, etc.. Retrieving specific video information from large-scale video database has become an important and challenging research topic in the area of multimedia information retrieval. In this paper, we introduce a new and efficient index structure OVA-File, which is a variant of VA-File. In OVA-File, the approximations close to each other in data space are stored in close positions of the approximation file. The benefit is that only a part of approximations close to the query vector need to be visited to get the query result. Both shot query algorithm and video clip algorithm are proposed to support video information retrieval efficiently. The experimental results showed that the queries based on OVA-File were much faster than that based on VA-File with small loss of result quality.

Use of Co-occurrences for Temporal Expressions Annotation

NASA Astrophysics Data System (ADS)

Craveiro, Olga; Macedo, Joaquim; Madeira, Henrique

The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora.

Network and User-Perceived Performance of Web Page Retrievals

NASA Technical Reports Server (NTRS)

Kruse, Hans; Allman, Mark; Mallasch, Paul

1998-01-01

The development of the HTTP protocol has been driven by the need to improve the network performance of the protocol by allowing the efficient retrieval of multiple parts of a web page without the need for multiple simultaneous TCP connections between a client and a server. We suggest that the retrieval of multiple page elements sequentially over a single TCP connection may result in a degradation of the perceived performance experienced by the user. We attempt to quantify this perceived degradation through the use of a model which combines a web retrieval simulation and an analytical model of TCP operation. Starting with the current HTTP/l.1 specification, we first suggest a client@side heuristic to improve the perceived transfer performance. We show that the perceived speed of the page retrieval can be increased without sacrificing data transfer efficiency. We then propose a new client/server extension to the HTTP/l.1 protocol to allow for the interleaving of page element retrievals. We finally address the issue of the display of advertisements on web pages, and in particular suggest a number of mechanisms which can make efficient use of IP multicast to send advertisements to a number of clients within the same network.

High speed phase retrieval of in-line holograms by the assistance of corresponding off-axis holograms.

PubMed

Orzó, László

2015-06-29

Retrieving correct phase information from an in-line hologram is difficult as the object wave field and the diffractions of the zero order and the conjugate object term overlap. The existing iterative numerical phase retrieval methods are slow, especially in the case of high Fresnel number systems. Conversely, the reconstruction of the object wave field from an off-axis hologram is simple, but due to the applied spatial frequency filtering the achievable resolution is confined. Here, a new, high-speed algorithm is introduced that efficiently incorporates the data of an auxiliary off-axis hologram in the phase retrieval of the corresponding in-line hologram. The efficiency of the introduced combined phase retrieval method is demonstrated by simulated and measured holograms.

Retrieval Demands Adaptively Change Striatal Old/New Signals and Boost Subsequent Long-Term Memory.

PubMed

Herweg, Nora A; Sommer, Tobias; Bunzeck, Nico

2018-01-17

The striatum is a central part of the dopaminergic mesolimbic system and contributes both to the encoding and retrieval of long-term memories. In this regard, the co-occurrence of striatal novelty and retrieval success effects in independent studies underlines the structure's double duty and suggests dynamic contextual adaptation. To test this hypothesis and further investigate the underlying mechanisms of encoding and retrieval dynamics, human subjects viewed pre-familiarized scene images intermixed with new scenes and classified them as indoor versus outdoor (encoding task) or old versus new (retrieval task), while fMRI and eye tracking data were recorded. Subsequently, subjects performed a final recognition task. As hypothesized, striatal activity and pupil size reflected task-conditional salience of old and new stimuli, but, unexpectedly, this effect was not reflected in the substantia nigra and ventral tegmental area (SN/VTA), medial temporal lobe, or subsequent memory performance. Instead, subsequent memory generally benefitted from retrieval, an effect possibly driven by task difficulty and activity in a network including different parts of the striatum and SN/VTA. Our findings extend memory models of encoding and retrieval dynamics by pinpointing a specific contextual factor that differentially modulates the functional properties of the mesolimbic system. SIGNIFICANCE STATEMENT The mesolimbic system is involved in the encoding and retrieval of information but it is unclear how these two processes are achieved within the same network of brain regions. In particular, memory retrieval and novelty encoding were considered in independent studies, implying that novelty (new > old) and retrieval success (old > new) effects may co-occur in the striatum. Here, we used a common framework implicating the striatum, but not other parts of the mesolimbic system, in tracking context-dependent salience of old and new information. The current study, therefore, paves the way for a more comprehensive understanding of the functional properties of the mesolimbic system during memory encoding and retrieval. Copyright © 2018 the authors 0270-6474/18/380745-10$15.00/0.

Investigating Storage and Retrieval Processes of Directed Forgetting: A Model-Based Approach

ERIC Educational Resources Information Center

Rummel, Jan; Marevic, Ivan; Kuhlmann, Beatrice G.

2016-01-01

Intentional forgetting of previously learned information is an adaptive cognitive capability of humans but its cognitive underpinnings are not yet well understood. It has been argued that it strongly depends on the presentation method whether forgetting instructions alter storage or retrieval stages (Basden, Basden, & Gargano, 1993). In…

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

NASA Astrophysics Data System (ADS)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.

The self in conflict: actors and agency in the mediated sequential Simon task.

PubMed

Spapé, Michiel M; Ahmed, Imtiaj; Jacucci, Giulio; Ravaja, Niklas

2015-01-01

Executive control refers to the ability to withstand interference in order to achieve task goals. The effect of conflict adaptation describes that after experiencing interference, subsequent conflict effects are weaker. However, changes in the source of conflict have been found to disrupt conflict adaptation. Previous studies indicated that this specificity is determined by the degree to which one source causes episodic retrieval of a previous source. A virtual reality version of the Simon task was employed to investigate whether changes in a visual representation of the self would similarly affect conflict adaptation. Participants engaged in a mediated Simon task via 3D "avatar" models that either mirrored the participants' movements, or were presented statically. A retrieval cue was implemented as the identity of the avatar: switching it from a male to a female avatar was expected to disrupt the conflict adaptation effect (CAE). The results show that only in static conditions did the CAE depend on the avatar identity, while in dynamic conditions, changes did not cause disruption. We also explored the effect of conflict and adaptation on the degree of movement made with the task-irrelevant hand and replicated the reaction time pattern. The findings add to earlier studies of source-specific conflict adaptation by showing that a visual representation of the self in action can provide a cue that determines episodic retrieval. Furthermore, the novel paradigm is made openly available to the scientific community and is described in its significance for studies of social cognition, cognitive psychology, and human-computer interaction.

Better Care Teams: A Stepwise Skill Reinforcement Model.

PubMed

Christopher, Beth-Anne; Grantner, Mary; Coke, Lola A; Wideman, Marilyn; Kwakwa, Francis

2016-06-01

The Building Healthy Urban Communities initiative presents a path for organizations partnering to improve patient outcomes with continuing education (CE) as a key component. Components of the CE initiative included traditional CE delivery formats with an essential element of adaptability and new methods, with rigorous evaluation over time that included evaluation prior to the course, immediately following the CE session, 6 to 8 weeks after the CE session, and then subsequent monthly "testlets." Outcome measures were designed to allow for ongoing adaptation of content, reinforcement of key learning objectives, and use of innovative concordant testing and retrieval practice techniques. The results after 1 year of programming suggest the stepwise skill reinforcement model is effective for learning and is an efficient use of financial and human resources. More important, its design is one that could be adopted at low cost by organizations willing to work in close partnership. J Contin Educ Nurs. 2016;47(6):283-288. Copyright 2016, SLACK Incorporated.

A contradictory phenomenon of deshelving pulses in a dilute medium used for lengthened photon storage time.

PubMed

Ham, Byoung S

2010-08-16

Lengthening of photon storage time has been an important issue in quantum memories for long distance quantum communications utilizing quantum repeaters. Atom population transfer into an auxiliary spin state has been adapted to increase photon storage time of photon echoes. In this population transfer process phase shift to the collective atoms is inevitable, where the phase recovery condition must be multiple of 2pi to satisfy rephasing mechanism. Recent adaptation of the population transfer method to atomic frequency comb (AFC) echoes [Afzelius et al., Phys. Rev. Lett. 104, 040503 (2010)], where the population transfer method is originated in a controlled reversible inhomogeneous broadening technique [Moiseev and Kroll, Phys. Rev. Lett. 87, 173601 (2001)], however, shows contradictory phenomenon violating the phase recovery condition. This contradiction in AFC is reviewed as a general case of optical locking applied to a dilute medium for an optical depth-dependent coherence leakage resulting in partial retrieval efficiency.

Regression techniques for oceanographic parameter retrieval using space-borne microwave radiometry

NASA Technical Reports Server (NTRS)

Hofer, R.; Njoku, E. G.

1981-01-01

Variations of conventional multiple regression techniques are applied to the problem of remote sensing of oceanographic parameters from space. The techniques are specifically adapted to the scanning multichannel microwave radiometer (SMRR) launched on the Seasat and Nimbus 7 satellites to determine ocean surface temperature, wind speed, and atmospheric water content. The retrievals are studied primarily from a theoretical viewpoint, to illustrate the retrieval error structure, the relative importances of different radiometer channels, and the tradeoffs between spatial resolution and retrieval accuracy. Comparisons between regressions using simulated and actual SMMR data are discussed; they show similar behavior.

A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

NASA Technical Reports Server (NTRS)

Mathe, Nathalie; Chen, James

1994-01-01

Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City.

PubMed

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-10-29

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

PubMed

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2017-01-01

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches. PMID:28771497

An Algorithm For Climate-Quality Atmospheric Profiling Continuity From EOS Aqua To Suomi-NPP

NASA Astrophysics Data System (ADS)

Moncet, J. L.

2015-12-01

We will present results from an algorithm that is being developed to produce climate-quality atmospheric profiling earth system data records (ESDRs) for application to hyperspectral sounding instrument data from Suomi-NPP, EOS Aqua, and other spacecraft. The current focus is on data from the S-NPP Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) instruments as well as the Atmospheric InfraRed Sounder (AIRS) on EOS Aqua. The algorithm development at Atmospheric and Environmental Research (AER) has common heritage with the optimal estimation (OE) algorithm operationally processing S-NPP data in the Interface Data Processing Segment (IDPS), but the ESDR algorithm has a flexible, modular software structure to support experimentation and collaboration and has several features adapted to the climate orientation of ESDRs. Data record continuity benefits from the fact that the same algorithm can be applied to different sensors, simply by providing suitable configuration and data files. The radiative transfer component uses an enhanced version of optimal spectral sampling (OSS) with updated spectroscopy, treatment of emission that is not in local thermodynamic equilibrium (non-LTE), efficiency gains with "global" optimal sampling over all channels, and support for channel selection. The algorithm is designed for adaptive treatment of clouds, with capability to apply "cloud clearing" or simultaneous cloud parameter retrieval, depending on conditions. We will present retrieval results demonstrating the impact of a new capability to perform the retrievals on sigma or hybrid vertical grid (as opposed to a fixed pressure grid), which particularly affects profile accuracy over land with variable terrain height and with sharp vertical structure near the surface. In addition, we will show impacts of alternative treatments of regularization of the inversion. While OE algorithms typically implement regularization by using background estimates from climatological or numerical forecast data, those sources are problematic for climate applications due to the imprint of biases from past climate analyses or from model error.

Medical Language Processing for Knowledge Representation and Retrievals

PubMed Central

Lyman, Margaret; Sager, Naomi; Chi, Emile C.; Tick, Leo J.; Nhan, Ngo Thanh; Su, Yun; Borst, Francois; Scherrer, Jean-Raoul

1989-01-01

The Linguistic String Project-Medical Language Processor, a system for computer analysis of narrative patient documents in English, is being adapted for French Lettres de Sortie. The system converts the free-text input to a semantic representation which is then mapped into a relational database. Retrievals of clinical data from the database are described.

A Study of Adaptive Relevance Feedback - UIUC TREC-2008 Relevance Feedback Experiments

DTIC Science & Technology

2008-11-01

terms. Journal of the American Society for Information Science, 27(3):129–146, 1976. [7] J . J . Rocchio. Relevance feedback in information retrieval. In...In The SMART Retrieval System: Experiments in Automatic Document Processing, pages 313–323. Prentice-Hall Inc., 1971. [8] Gerard Salton and Chris

Loss of Retrieval Information in Prose Recall.

ERIC Educational Resources Information Center

Sehulster, Jerome R.; And Others

The purpose of this research was to experimentally manipulate input and output orders of information and separate storage and retrieval components of prose free recall. The cued partial recall method, used in word list recall, was adapted to a prose learning task. Four short biographical stories of about 55 words each were systematically combined…

Software Helps Retrieve Information Relevant to the User

NASA Technical Reports Server (NTRS)

Mathe, Natalie; Chen, James

2003-01-01

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Archetype relational mapping - a practical openEHR persistence solution.

PubMed

Wang, Li; Min, Lingtong; Wang, Rui; Lu, Xudong; Duan, Huilong

2015-11-05

One of the primary obstacles to the widespread adoption of openEHR methodology is the lack of practical persistence solutions for future-proof electronic health record (EHR) systems as described by the openEHR specifications. This paper presents an archetype relational mapping (ARM) persistence solution for the archetype-based EHR systems to support healthcare delivery in the clinical environment. First, the data requirements of the EHR systems are analysed and organized into archetype-friendly concepts. The Clinical Knowledge Manager (CKM) is queried for matching archetypes; when necessary, new archetypes are developed to reflect concepts that are not encompassed by existing archetypes. Next, a template is designed for each archetype to apply constraints related to the local EHR context. Finally, a set of rules is designed to map the archetypes to data tables and provide data persistence based on the relational database. A comparison study was conducted to investigate the differences among the conventional database of an EHR system from a tertiary Class A hospital in China, the generated ARM database, and the Node + Path database. Five data-retrieving tests were designed based on clinical workflow to retrieve exams and laboratory tests. Additionally, two patient-searching tests were designed to identify patients who satisfy certain criteria. The ARM database achieved better performance than the conventional database in three of the five data-retrieving tests, but was less efficient in the remaining two tests. The time difference of query executions conducted by the ARM database and the conventional database is less than 130 %. The ARM database was approximately 6-50 times more efficient than the conventional database in the patient-searching tests, while the Node + Path database requires far more time than the other two databases to execute both the data-retrieving and the patient-searching tests. The ARM approach is capable of generating relational databases using archetypes and templates for archetype-based EHR systems, thus successfully adapting to changes in data requirements. ARM performance is similar to that of conventionally-designed EHR systems, and can be applied in a practical clinical environment. System components such as ARM can greatly facilitate the adoption of openEHR architecture within EHR systems.

Mutual information based feature selection for medical image retrieval

NASA Astrophysics Data System (ADS)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Closed loop adaptive optics for microscopy without a wavefront sensor.

PubMed

Kner, Peter; Winoto, Lukman; Agard, David A; Sedat, John W

2010-02-24

A three-dimensional wide-field image of a small fluorescent bead contains more than enough information to accurately calculate the wavefront in the microscope objective back pupil plane using the phase retrieval technique. The phase-retrieved wavefront can then be used to set a deformable mirror to correct the point-spread function (PSF) of the microscope without the use of a wavefront sensor. This technique will be useful for aligning the deformable mirror in a widefield microscope with adaptive optics and could potentially be used to correct aberrations in samples where small fluorescent beads or other point sources are used as reference beacons. Another advantage is the high resolution of the retrieved wavefont as compared with current Shack-Hartmann wavefront sensors. Here we demonstrate effective correction of the PSF in 3 iterations. Starting from a severely aberrated system, we achieve a Strehl ratio of 0.78 and a greater than 10-fold increase in maximum intensity.

Instance-based categorization: automatic versus intentional forms of retrieval.

PubMed

Neal, A; Hesketh, B; Andrews, S

1995-03-01

Two experiments are reported which attempt to disentangle the relative contribution of intentional and automatic forms of retrieval to instance-based categorization. A financial decision-making task was used in which subjects had to decide whether a bank would approve loans for a series of applicants. Experiment 1 found that categorization was sensitive to instance-specific knowledge, even when subjects had practiced using a simple rule. L. L. Jacoby's (1991) process-dissociation procedure was adapted for use in Experiment 2 to infer the relative contribution of intentional and automatic retrieval processes to categorization decisions. The results provided (1) strong evidence that intentional retrieval processes influence categorization, and (2) some preliminary evidence suggesting that automatic retrieval processes may also contribute to categorization decisions.

Global-Context Based Salient Region Detection in Nature Images

NASA Astrophysics Data System (ADS)

Bao, Hong; Xu, De; Tang, Yingjun

Visually saliency detection provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. One of the main aims of visual attention in computer vision is to detect and segment the salient regions in an image. In this paper, we employ matrix decomposition to detect salient object in nature images. To efficiently eliminate high contrast noise regions in the background, we integrate global context information into saliency detection. Therefore, the most salient region can be easily selected as the one which is globally most isolated. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art methods.

An Intelligent System for Document Retrieval in Distributed Office Environments.

ERIC Educational Resources Information Center

Mukhopadhyay, Uttam; And Others

1986-01-01

MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns and user interests and preferences during system usage, it customizes document retrievals for…

User-Centered Indexing for Adaptive Information Access

NASA Technical Reports Server (NTRS)

Chen, James R.; Mathe, Nathalie

1996-01-01

We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Leading and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.

A new hybrid case-based reasoning approach for medical diagnosis systems.

PubMed

Sharaf-El-Deen, Dina A; Moawad, Ibrahim F; Khalifa, M E

2014-02-01

Case-Based Reasoning (CBR) has been applied in many different medical applications. Due to the complexities and the diversities of this domain, most medical CBR systems become hybrid. Besides, the case adaptation process in CBR is often a challenging issue as it is traditionally carried out manually by domain experts. In this paper, a new hybrid case-based reasoning approach for medical diagnosis systems is proposed to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and also applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose breast cancer and thyroid diseases. The final results show that the proposed approach increases the diagnosing accuracy of the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer and thyroid diagnosis systems.

Time-Quality Tradeoff of Waiting Strategies for Tutors to Retrieve Relevant Teaching Methods

ERIC Educational Resources Information Center

Shih, Wen-Chung; Tseng, Shian-Shyong; Yang, Che-Ching; Liang, Tyne

2011-01-01

As more and more undergraduate students act as voluntary tutors to rural pupils after school, there is a growing need for a supporting environment to facilitate adaptive instruction. Among others, a teaching method retrieval system is intended to help tutors find relevant teaching methods for teaching a particular concept. However, teaching…

Less we forget: retrieval cues and release from retrieval-induced forgetting.

PubMed

Jonker, Tanya R; Seli, Paul; Macleod, Colin M

2012-11-01

Retrieving some items from memory can impair the subsequent recall of other related but not retrieved items, a phenomenon called retrieval-induced forgetting (RIF). The dominant explanation of RIF-the inhibition account-asserts that forgetting occurs because related items are suppressed during retrieval practice to reduce retrieval competition. This item inhibition persists, making it more difficult to recall the related items on a later test. In our set of experiments, each category was designed such that each exemplar belonged to one of two subcategories (e.g., each BIRD exemplar was either a bird of prey or a pet bird), but this subcategory information was not made explicit during study or retrieval practice. Practicing retrieval of items from only one subcategory led to RIF for items from the other subcategory when cued only with the overall category label (BIRD) at test. However, adapting the technique of Gardiner, Craik, and Birtwistle (Journal of Learning and Verbal Behavior 11:778-783, 1972), providing subcategory cues during the final test eliminated RIF. The results challenge the inhibition account's fundamental assumption of cue independence but are consistent with a cue-based interference account.

Working memory capacity and recall from long-term memory: Examining the influences of encoding strategies, study time allocation, search efficiency, and monitoring abilities.

PubMed

Unsworth, Nash

2016-01-01

The relation between working memory capacity (WMC) and recall from long-term memory (LTM) was examined in the current study. Participants performed multiple measures of delayed free recall varying in presentation duration and self-reported their strategy usage after each task. Participants also performed multiple measures of WMC. The results suggested that WMC and LTM recall were related, and part of this relation was due to effective strategy use. However, adaptive changes in strategy use and study time allocation were not related to WMC. Examining multiple variables with structural equation modeling suggested that the relation between WMC and LTM recall was due to variation in effective strategy use, search efficiency, and monitoring abilities. Furthermore, all variables were shown to account for individual differences in LTM recall. These results suggest that the relation between WMC and recall from LTM is due to multiple strategic factors operating at both encoding and retrieval. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Retrieval practice is an efficient method of enhancing the retention of anatomy and physiology information.

PubMed

Dobson, John L

2013-06-01

Although a great deal of empirical evidence has indicated that retrieval practice is an effective means of promoting learning and memory, very few studies have investigated the strategy in the context of an actual class. The primary purpose of this study was to determine if a series of very brief retrieval quizzes could significantly improve the retention of previously tested information throughout an anatomy and physiology course. A second purpose was to determine if there were any significant differences between expanding and uniform patterns of retrieval that followed a standardized initial retrieval delay. Anatomy and physiology students were assigned to either a control group or groups that were repeatedly prompted to retrieve a subset of previously tested course information via a series of quizzes that were administered on either an expanding or a uniform schedule. Each retrieval group completed a total of 10 retrieval quizzes, and the series of quizzes required (only) a total of 2 h to complete. Final retention of the exam subset material was assessed during the last week of the semester. There were no significant differences between the expanding and uniform retrieval groups, but both retained an average of 41% more of the subset material than did the control group (ANOVA, F = 129.8, P = 0.00, ηp(2) = 0.36). In conclusion, retrieval practice is a highly efficient and effective strategy for enhancing the retention of anatomy and physiology material.

On the Use of Adaptive Instructional Images Based on the Sequential-Global Dimension of the Felder-Silverman Learning Style Theory

ERIC Educational Resources Information Center

Filippidis, Stavros K.; Tsoukalas, Ioannis A.

2009-01-01

An adaptive educational system that uses adaptive presentation is presented. In this system fragments of different images present the same content and the system can choose the one most relevant to the user based on the sequential-global dimension of Felder-Silverman's learning style theory. In order to retrieve the learning style of each student…

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

PubMed Central

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-01-01

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems. PMID:27801869

Global and Local Processing of Incidental Information and Memory Retrieval at 6 Months.

ERIC Educational Resources Information Center

Bhatt, Ramesh S.; And Others

1994-01-01

Five experiments examined the role of global and local cues in memory retrieval in infancy. Results showed that infants encode and remember for substantial periods of time not only the shape of figures displayed in their periphery but also the global organization of these figures. They also adapt this information when responding to new events.…

Rab5 and its effector FHF contribute to neuronal polarity through dynein-dependent retrieval of somatodendritic proteins from the axon

PubMed Central

Guo, Xiaoli; Farías, Ginny G.; Mattera, Rafael; Bonifacino, Juan S.

2016-01-01

An open question in cell biology is how the general intracellular transport machinery is adapted to perform specialized functions in polarized cells such as neurons. Here we illustrate this adaptation by elucidating a role for the ubiquitous small GTPase Ras-related protein in brain 5 (Rab5) in neuronal polarity. We show that inactivation or depletion of Rab5 in rat hippocampal neurons abrogates the somatodendritic polarity of the transferrin receptor and several glutamate receptor types, resulting in their appearance in the axon. This loss of polarity is not caused primarily by increased transport from the soma to the axon but rather by decreased retrieval from the axon to the soma. Retrieval is also dependent on the Rab5 effector Fused Toes (FTS)–Hook–FTS and Hook-interacting protein (FHIP) (FHF) complex, which interacts with the minus-end–directed microtubule motor dynein and its activator dynactin to drive a population of axonal retrograde carriers containing somatodendritic proteins toward the soma. These findings emphasize the importance of both biosynthetic sorting and axonal retrieval for the polarized distribution of somatodendritic receptors at steady state. PMID:27559088

Aging and Memory as Discrimination: Influences of Encoding Specificity, Cue Overload, and Prior Knowledge

PubMed Central

2016-01-01

From the perspective of memory-as-discrimination, whether a cue leads to correct retrieval simultaneously depends on the cue’s relationship to (a) the memory target and (b) the other retrieval candidates. A corollary of the view is that increasing encoding-retrieval match may only help memory if it improves the cue’s capacity to discriminate the target from competitors. Here, age differences in this discrimination process were assessed by manipulating the overlap between cues present at encoding and retrieval orthogonally with cue–target distinctiveness. In Experiment 1, associative memory differences for cue–target sets between young and older adults were minimized through training and retrieval efficiency was assessed through response time. In Experiment 2, age-group differences in associative memory were left to vary and retrieval efficiency was assessed through accuracy. Both experiments showed age-invariance in memory-as-discrimination: cues increasing encoding-retrieval match did not benefit memory unless they also improved discrimination between the target and competitors. Predictions based on the age-related associative deficit were also supported: prior knowledge alleviated age-related associative deficits (Experiment 1), and increasing encoding-retrieval match benefited older more than young adults (Experiment 2). We suggest that the latter occurred because older adults’ associative memory deficits reduced the impact of competing retrieval candidates—hence the age-related benefit was not attributable to encoding-retrieval match per se, but rather it was a joint function of an increased probability of the cue connecting to the target combined with a decrease in competing retrieval candidates. PMID:27831714

Aging and memory as discrimination: Influences of encoding specificity, cue overload, and prior knowledge.

PubMed

Badham, Stephen P; Poirier, Marie; Gandhi, Navina; Hadjivassiliou, Anna; Maylor, Elizabeth A

2016-11-01

From the perspective of memory-as-discrimination, whether a cue leads to correct retrieval simultaneously depends on the cue's relationship to (a) the memory target and (b) the other retrieval candidates. A corollary of the view is that increasing encoding-retrieval match may only help memory if it improves the cue's capacity to discriminate the target from competitors. Here, age differences in this discrimination process were assessed by manipulating the overlap between cues present at encoding and retrieval orthogonally with cue-target distinctiveness. In Experiment 1, associative memory differences for cue-target sets between young and older adults were minimized through training and retrieval efficiency was assessed through response time. In Experiment 2, age-group differences in associative memory were left to vary and retrieval efficiency was assessed through accuracy. Both experiments showed age-invariance in memory-as-discrimination: cues increasing encoding-retrieval match did not benefit memory unless they also improved discrimination between the target and competitors. Predictions based on the age-related associative deficit were also supported: prior knowledge alleviated age-related associative deficits (Experiment 1), and increasing encoding-retrieval match benefited older more than young adults (Experiment 2). We suggest that the latter occurred because older adults' associative memory deficits reduced the impact of competing retrieval candidates-hence the age-related benefit was not attributable to encoding-retrieval match per se, but rather it was a joint function of an increased probability of the cue connecting to the target combined with a decrease in competing retrieval candidates. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

PubMed

G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

2015-01-01

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.

CrIS/ATMS Retrievals Using the Latest AIRS/AMSU Retrieval Methodology

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis C.; Blaisdell, John; Iredell, Lena

2015-01-01

This research is being done under the NPP Science Team Proposal: Analysis of CrISATMS Using an AIRS Version 6-like Retrieval Algorithm Objective: Generate a long term CrISATMS level-3 data set that is consistent with that of AIRSAMSU Approach: Adapt the currently operational AIRS Science Team Version-6 Retrieval Algorithm, or an improved version of it, for use with CrISATMS data. Metric: Generate monthly mean level-3 CrISATMS climate data sets and evaluate the results by comparison of monthly mean AIRSAMSU and CrISATMS products, and more significantly, their inter-annual differences and, eventually, anomaly time series. The goal is consistency between the AIRSAMSU and CrISATMS climate data sets.

A novel image retrieval algorithm based on PHOG and LSH

NASA Astrophysics Data System (ADS)

Wu, Hongliang; Wu, Weimin; Peng, Jiajin; Zhang, Junyuan

2017-08-01

PHOG can describe the local shape of the image and its relationship between the spaces. The using of PHOG algorithm to extract image features in image recognition and retrieval and other aspects have achieved good results. In recent years, locality sensitive hashing (LSH) algorithm has been superior to large-scale data in solving near-nearest neighbor problems compared with traditional algorithms. This paper presents a novel image retrieval algorithm based on PHOG and LSH. First, we use PHOG to extract the feature vector of the image, then use L different LSH hash table to reduce the dimension of PHOG texture to index values and map to different bucket, and finally extract the corresponding value of the image in the bucket for second image retrieval using Manhattan distance. This algorithm can adapt to the massive image retrieval, which ensures the high accuracy of the image retrieval and reduces the time complexity of the retrieval. This algorithm is of great significance.

Retrieval medicine: a review and guide for UK practitioners. Part 2: safety in patient retrieval systems

PubMed Central

Hearns, S; Shirley, P J

2006-01-01

Retrieval and transfer of critically ill and injured patients is a high risk activity. Risk can be minimised with robust safety and clinical governance systems in place. This article describes the various governance systems that can be employed to optimise safety and efficiency in retrieval services. These include operating procedure development, equipment management, communications procedures, crew resource management, significant event analysis, audit and training. PMID:17130608

Anxiety and retrieval inhibition: support for an enhanced inhibition account.

PubMed

Nuñez, Mia; Gregory, Josh; Zinbarg, Richard E

2017-02-01

Retrieval inhibition of negative associations is important for exposure therapy for anxiety, but the relationship between memory inhibition and anxiety is not well understood-anxiety could either be associated with enhanced or deficient inhibition. The present study tested these two competing hypotheses by measuring retrieval inhibition of negative stimuli by related neutral stimuli. Non-clinically anxious undergraduates completed measures of trait and state anxiety and completed a retrieval induced forgetting task. Adaptive forgetting varied with state anxiety. Low levels of state anxiety were associated with no evidence for retrieval inhibition for either threatening or non-threatening categories. Participants in the middle tertile of state anxiety scores exhibited retrieval inhibition for non-threatening categories but not for threatening categories. Participants in the highest tertile of state anxiety, however, exhibited retrieval inhibition for both threatening and non-threatening categories with the magnitude of retrieval inhibition being greater for threatening than non-threatening categories. The data are in line with the avoidance aspect of the vigilance-avoidance theory of anxiety and inhibition. Implications for cognitive behavioural therapy practices are discussed.

Intelligence as the efficiency of cue-driven retrieval from secondary memory.

PubMed

Liesefeld, Heinrich René; Hoffmann, Eugenia; Wentura, Dirk

2016-01-01

Complex-span (working-memory-capacity) tasks are among the most successful predictors of intelligence. One important contributor to this relationship is the ability to efficiently employ cues for the retrieval from secondary memory. Presumably, intelligent individuals can considerably restrict their memory search sets by using such cues and can thereby improve recall performance. We here test this assumption by experimentally manipulating the validity of retrieval cues. When memoranda are drawn from the same semantic category on two successive trials of a verbal complex-span task, the category is a very strong retrieval cue on its first occurrence (strong-cue trial) but loses some of its validity on its second occurrence (weak-cue trial). If intelligent individuals make better use of semantic categories as retrieval cues, their recall accuracy suffers more from this loss of cue validity. Accordingly, our results show that less variance in intelligence is explained by recall accuracy on weak-cue compared with strong-cue trials.

Talbot-Lau x-ray deflectometry phase-retrieval methods for electron density diagnostics in high-energy density experiments.

PubMed

Valdivia, Maria Pia; Stutman, Dan; Stoeckl, Christian; Mileham, Chad; Begishev, Ildar A; Bromage, Jake; Regan, Sean P

2018-01-10

Talbot-Lau x-ray interferometry uses incoherent x-ray sources to measure refraction index changes in matter. These measurements can provide accurate electron density mapping through phase retrieval. An adaptation of the interferometer has been developed in order to meet the specific requirements of high-energy density experiments. This adaptation is known as a moiré deflectometer, which allows for single-shot capabilities in the form of interferometric fringe patterns. The moiré x-ray deflectometry technique requires a set of object and reference images in order to provide electron density maps, which can be costly in the high-energy density environment. In particular, synthetic reference phase images obtained ex situ through a phase-scan procedure, can provide a feasible solution. To test this procedure, an object phase map was retrieved from a single-shot moiré image obtained from a plasma-produced x-ray source. A reference phase map was then obtained from phase-stepping measurements using a continuous x-ray tube source in a small laboratory setting. The two phase maps were used to retrieve an electron density map. A comparison of the moiré and phase-stepping phase-retrieval methods was performed to evaluate single-exposure plasma electron density mapping for high-energy density and other transient plasma experiments. It was found that a combination of phase-retrieval methods can deliver accurate refraction angle mapping. Once x-ray backlighter quality is optimized, the ex situ method is expected to deliver electron density mapping with improved resolution. The steps necessary for improved diagnostic performance are discussed.

Closed loop adaptive optics for microscopy without a wavefront sensor

PubMed Central

Kner, Peter; Winoto, Lukman; Agard, David A.; Sedat, John W.

2013-01-01

A three-dimensional wide-field image of a small fluorescent bead contains more than enough information to accurately calculate the wavefront in the microscope objective back pupil plane using the phase retrieval technique. The phase-retrieved wavefront can then be used to set a deformable mirror to correct the point-spread function (PSF) of the microscope without the use of a wavefront sensor. This technique will be useful for aligning the deformable mirror in a widefield microscope with adaptive optics and could potentially be used to correct aberrations in samples where small fluorescent beads or other point sources are used as reference beacons. Another advantage is the high resolution of the retrieved wavefont as compared with current Shack-Hartmann wavefront sensors. Here we demonstrate effective correction of the PSF in 3 iterations. Starting from a severely aberrated system, we achieve a Strehl ratio of 0.78 and a greater than 10-fold increase in maximum intensity. PMID:24392198

Rethinking infant knowledge: toward an adaptive process account of successes and failures in object permanence tasks.

PubMed

Munakata, Y; McClelland, J L; Johnson, M H; Siegler, R S

1997-10-01

Infants seem sensitive to hidden objects in habituation tasks at 3.5 months but fail to retrieve hidden objects until 8 months. The authors first consider principle-based accounts of these successes and failures, in which early successes imply knowledge of principles and failures are attributed to ancillary deficits. One account is that infants younger than 8 months have the object permanence principle but lack means-ends abilities. To test this, 7-month-olds were trained on means-ends behaviors and were tested on retrieval of visible and occluded toys. Means-ends demands were the same, yet infants made more toy-guided retrievals in the visible case. The authors offer an adaptive process account in which knowledge is graded and embedded in specific behavioral processes. Simulation models that learn gradually to represent occluded objects show how this approach can account for success and failure in object permanence tasks without assuming principles and ancillary deficits.

Inefficiency and Bias of Search Engines in Retrieving References Containing Scientific Names of Fossil Amphibians

ERIC Educational Resources Information Center

Brown, Lauren E.; Dubois, Alain; Shepard, Donald B.

2008-01-01

Retrieval efficiencies of paper-based references in journals and other serials containing 10 scientific names of fossil amphibians were determined for seven major search engines. Retrievals were compared to the number of references obtained covering the period 1895-2006 by a Comprehensive Search. The latter was primarily a traditional…

Improving the Efficiency of Problem-Solving Practice for Children with Retrieval Difficulties

ERIC Educational Resources Information Center

Hopkins, Sarah; de Villiers, Celeste

2016-01-01

Despite the importance placed on how children come to solve single-digit addition problems, many children count on to solve these problems when they are expected to use accurate retrieval-based strategies. In this study, we assessed if a subitising intervention improved the rate at which problem-solving practice promoted retrieval, using a…

When Practice Doesn't Lead to Retrieval: An Analysis of Children's Errors with Simple Addition

ERIC Educational Resources Information Center

de Villiers, Celéste; Hopkins, Sarah

2013-01-01

Counting strategies initially used by young children to perform simple addition are often replaced by more efficient counting strategies, decomposition strategies and rule-based strategies until most answers are encoded in memory and can be directly retrieved. Practice is thought to be the key to developing fluent retrieval of addition facts. This…

Mobile medical image retrieval

NASA Astrophysics Data System (ADS)

Duc, Samuel; Depeursinge, Adrien; Eggel, Ivan; Müller, Henning

2011-03-01

Images are an integral part of medical practice for diagnosis, treatment planning and teaching. Image retrieval has gained in importance mainly as a research domain over the past 20 years. Both textual and visual retrieval of images are essential. In the process of mobile devices becoming reliable and having a functionality equaling that of formerly desktop clients, mobile computing has gained ground and many applications have been explored. This creates a new field of mobile information search & access and in this context images can play an important role as they often allow understanding complex scenarios much quicker and easier than free text. Mobile information retrieval in general has skyrocketed over the past year with many new applications and tools being developed and all sorts of interfaces being adapted to mobile clients. This article describes constraints of an information retrieval system including visual and textual information retrieval from the medical literature of BioMedCentral and of the RSNA journals Radiology and Radiographics. Solutions for mobile data access with an example on an iPhone in a web-based environment are presented as iPhones are frequently used and the operating system is bound to become the most frequent smartphone operating system in 2011. A web-based scenario was chosen to allow for a use by other smart phone platforms such as Android as well. Constraints of small screens and navigation with touch screens are taken into account in the development of the application. A hybrid choice had to be taken to allow for taking pictures with the cell phone camera and upload them for visual similarity search as most producers of smart phones block this functionality to web applications. Mobile information access and in particular access to images can be surprisingly efficient and effective on smaller screens. Images can be read on screen much faster and relevance of documents can be identified quickly through the use of images contained in the text. Problems with the many, often incompatible mobile platforms were discovered and are listed in the text. Mobile information access is a quickly growing domain and the constraints of mobile access also need to be taken into account for image retrieval. The demonstrated access to the medical literature is most relevant as the medical literature and their images are clearly the largest knowledge source in the medical field.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Monacos, Steve P. (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Slide Library of the History of Art Department, Cornell University: Classification and Retrieval System.

ERIC Educational Resources Information Center

Nemethy, Judith

A study was conducted to develop a retrieval system for slides in the History of Art Collection at Cornell University to make it more consistent and easier for patrons from other academic disciplines to use than the system currently in use. To determine whether slide library systems at other institutions could be adapted to the History of Art…

SkZpipe: A Python3 module to produce efficiently PSF-fitting photometry with DAOPHOT, and much more

NASA Astrophysics Data System (ADS)

Mauro, F.

2017-07-01

In an era characterized by big sky surveys and the availability of large amount of photometric data, it is important for astronomers to have tools to process their data in an efficient, accurate and easy way, minimizing reduction time. We present SkZpipe, a Python3 module designed mainly to process generic data, performing point-spread function (PSF) fitting photometry with the DAOPHOT suite (Stetson 1987). The software has already demonstrated its accuracy and efficiency with the adaptation VVV-SkZ_pipeline (Mauro et al. 2013) for the "VISTA Variables in the Vía Láctea" ESO survey, showing how it can replace the users, avoiding repetitive interaction in all the operations, retaining all of the benefits of the power and accuracy of the DAOPHOT suite, detaching them from the burden of data precessing. This software provides not only a pipeline, but also all the tools to run easily each atomic step of the photometric procedure, to match the results, and to retrieve information from fits headers and the internal instrumental database. We plan to add the support to other photometric softwares in the future.

Adaptable Learning Assistant for Item Bank Management

ERIC Educational Resources Information Center

Nuntiyagul, Atorn; Naruedomkul, Kanlaya; Cercone, Nick; Wongsawang, Damras

2008-01-01

We present PKIP, an adaptable learning assistant tool for managing question items in item banks. PKIP is not only able to automatically assist educational users to categorize the question items into predefined categories by their contents but also to correctly retrieve the items by specifying the category and/or the difficulty level. PKIP adapts…

Roogle: an information retrieval engine for clinical data warehouse.

PubMed

Cuggia, Marc; Garcelon, Nicolas; Campillo-Gimenez, Boris; Bernicot, Thomas; Laurent, Jean-François; Garin, Etienne; Happe, André; Duvauferrier, Régis

2011-01-01

High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different hospital information systems. Information retrieval is performed using metadata-based semantic and full-text search methods (as Google). Applications may be biomarkers identification in a translational approach, search of specific cases, and constitution of cohorts, professional practice evaluation, and quality control assessment.

Searching for evidence or approval? A commentary on database search in systematic reviews and alternative information retrieval methodologies.

PubMed

Delaney, Aogán; Tamás, Peter A

2018-03-01

Despite recognition that database search alone is inadequate even within the health sciences, it appears that reviewers in fields that have adopted systematic review are choosing to rely primarily, or only, on database search for information retrieval. This commentary reminds readers of factors that call into question the appropriateness of default reliance on database searches particularly as systematic review is adapted for use in new and lower consensus fields. It then discusses alternative methods for information retrieval that require development, formalisation, and evaluation. Our goals are to encourage reviewers to reflect critically and transparently on their choice of information retrieval methods and to encourage investment in research on alternatives. Copyright © 2017 John Wiley & Sons, Ltd.

Retrieval Practice Is an Efficient Method of Enhancing the Retention of Anatomy and Physiology Information

ERIC Educational Resources Information Center

Dobson, John L.

2013-01-01

Although a great deal of empirical evidence has indicated that retrieval practice is an effective means of promoting learning and memory, very few studies have investigated the strategy in the context of an actual class. The primary purpose of this study was to determine if a series of very brief retrieval quizzes could significantly improve the…

Lexical Retrieval Processes and Strategies in Second Language Writing: A Synthesis of Empirical Research

ERIC Educational Resources Information Center

Manchon, Rosa M.; Murphy, Liz; Roca, Julio

2007-01-01

Lexical access and retrieval are essential processes in fluent and efficient second language (L2) oral and written productive uses of language. In the case of L2 writing, attention to vocabulary is of paramount importance, although the retrieval of relevant lexis while composing in an L2 frequently entails different degrees of problem-solving…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donofrio, David

A method and apparatus for performing stencil computations efficiently are disclosed. In one embodiment, a processor receives an offset, and in response, retrieves a value from a memory via a single instruction, where the retrieving comprises: identifying, based on the offset, one of a plurality of registers of the processor; loading an address stored in the identified register; and retrieving from the memory the value at the address.

A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

PubMed

Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

2012-04-01

We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

A semantic medical multimedia retrieval approach using ontology information hiding.

PubMed

Guo, Kehua; Zhang, Shigeng

2013-01-01

Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches.

A content-based news video retrieval system: NVRS

NASA Astrophysics Data System (ADS)

Liu, Huayong; He, Tingting

2009-10-01

This paper focus on TV news programs and design a content-based news video browsing and retrieval system, NVRS, which is convenient for users to fast browsing and retrieving news video by different categories such as political, finance, amusement, etc. Combining audiovisual features and caption text information, the system automatically segments a complete news program into separate news stories. NVRS supports keyword-based news story retrieval, category-based news story browsing and generates key-frame-based video abstract for each story. Experiments show that the method of story segmentation is effective and the retrieval is also efficient.

An empirical analysis of executive behaviour with hospital executive information systems in Taiwan.

PubMed

Huang, Wei-Min

2013-01-01

Existing health information systems largely only support the daily operations of a medical centre, and are unable to generate the information required by executives for decision-making. Building on past research concerning information retrieval behaviour and learning through mental models, this study examines the use of information systems by hospital executives in medical centres. It uses a structural equation model to help find ways hospital executives might use information systems more effectively. The results show that computer self-efficacy directly affects the maintenance of mental models, and that system characteristics directly impact learning styles and information retrieval behaviour. Other results include the significant impact of perceived environmental uncertainty on scan searches; information retrieval behaviour and focused searches on mental models and perceived efficiency; scan searches on mental model building; learning styles and model building on perceived efficiency; and finally the impact of mental model maintenance on perceived efficiency and effectiveness.

Atomic Oxygen Density Retrievals using FUV Observations by the Imaging Ultraviolet Spectrograph on MAVEN

NASA Astrophysics Data System (ADS)

Evans, J. Scott; Stevens, Michael H.; Schneider, Nicholas M.; Stewart, Ian; Deighan, Justin; Jain, Sonal Kumar; Eparvier, Francis; Thiemann, E. M.; Bougher, Stephen W.; Jakosky, Bruce

2016-10-01

We present the first direct retrievals of neutral atomic oxygen in Mars's upper atmosphere using daytime FUV periapse limb scan observations from 130 - 200 km tangent altitude. Atmospheric composition is inferred using the Atmospheric Ultraviolet Radiance Integrated Code [Strickland et al., 1999] adapted to the Martian atmosphere [Evans et al., 2015]. For our retrievals we use O I 135.6 nm emission observed by IUVS on MAVEN under daytime conditions (solar zenith angle < 60 degrees) over both northern and southern hemispheres (latitudes between -65 and +35 degrees) from October 2014 to August 2016. We investigate the sensitivity of atomic oxygen density retrievals to variability in solar irradiance, solar longitude, and local time. We compare our retrievals to predictions from the Mars Global Ionosphere-Thermosphere Model [MGITM, Bougher et al., 2015] and the Mars Climate Database [MCD, Forget et al., 1999] and quantify the differences throughout the altitude region of interest. The retrieved densities are used to characterize global transport of atomic oxygen in the Martian thermosphere.

Adaptive and Adaptable Automation Design: A Critical Review of the Literature and Recommendations for Future Research

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Kaber, David B.

2006-01-01

This report presents a review of literature on approaches to adaptive and adaptable task/function allocation and adaptive interface technologies for effective human management of complex systems that are likely to be issues for the Next Generation Air Transportation System, and a focus of research under the Aviation Safety Program, Integrated Intelligent Flight Deck Project. Contemporary literature retrieved from an online database search is summarized and integrated. The major topics include the effects of delegation-type, adaptable automation on human performance, workload and situation awareness, the effectiveness of various automation invocation philosophies and strategies to function allocation in adaptive systems, and the role of user modeling in adaptive interface design and the performance implications of adaptive interface technology.

Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

NASA Technical Reports Server (NTRS)

Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.

2013-01-01

The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center

The Development of Knowledge of an External Retrieval Cue Strategy.

ERIC Educational Resources Information Center

Ritter, Kenneth

1978-01-01

Investigated preschool and third grade children's metamnemonic knowledge that in order to serve as an efficient retrieval cue of the location of a hidden object, an external marker sign must differentiate it from other locations. (JMB)

Information retrieval algorithms: A survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raghavan, P.

We give an overview of some algorithmic problems arising in the representation of text/image/multimedia objects in a form amenable to automated searching, and in conducting these searches efficiently. These operations are central to information retrieval and digital library systems.

Supervised graph hashing for histopathology image retrieval and classification.

PubMed

Shi, Xiaoshuang; Xing, Fuyong; Xu, KaiDi; Xie, Yuanpu; Su, Hai; Yang, Lin

2017-12-01

In pathology image analysis, morphological characteristics of cells are critical to grade many diseases. With the development of cell detection and segmentation techniques, it is possible to extract cell-level information for further analysis in pathology images. However, it is challenging to conduct efficient analysis of cell-level information on a large-scale image dataset because each image usually contains hundreds or thousands of cells. In this paper, we propose a novel image retrieval based framework for large-scale pathology image analysis. For each image, we encode each cell into binary codes to generate image representation using a novel graph based hashing model and then conduct image retrieval by applying a group-to-group matching method to similarity measurement. In order to improve both computational efficiency and memory requirement, we further introduce matrix factorization into the hashing model for scalable image retrieval. The proposed framework is extensively validated with thousands of lung cancer images, and it achieves 97.98% classification accuracy and 97.50% retrieval precision with all cells of each query image used. Copyright © 2017 Elsevier B.V. All rights reserved.

Age differences in memory control: evidence from updating and retrieval-practice tasks.

PubMed

Lechuga, Maria Teresa; Moreno, Virginia; Pelegrina, Santiago; Gómez-Ariza, Carlos J; Bajo, Maria Teresa

2006-11-01

Some contemporary approaches suggest that inhibitory mechanisms play an important role in cognitive development. In addition, several authors distinguish between intentional and unintentional inhibitory processes in cognition. We report two experiments aimed at exploring possible developmental changes in these two types of inhibitory mechanisms. In Experiment 1, an updating task was used. This task requires that participants intentionally suppress irrelevant information from working memory. In Experiment 2, the retrieval-practice task was used. Retrieval practice of a subset of studied items is thought to involve unintentional inhibitory processes to overcome interference from competing memories. As a result, suppressed items become forgotten in a later memory test. Results of the experiments indicated that younger children (8) were less efficient than older children (12) and adults at intentionally suppressing information (updating task). However, when the task required unintentional inhibition of competing items (retrieval-practice task), this developmental trend was not found and children and adults showed similar levels of retrieval-induced forgetting. The results are discussed in terms of the development of efficient inhibition and the distinction between intentional and unintentional inhibitions.

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

Detecting Crop Functional Response to a Heat Wave using Airborne Reflectance and Sun-induced Chlorophyll Fluorescence Measurements

NASA Astrophysics Data System (ADS)

Yang, P.; Van der Tol, C.; Rascher, U.; Damm, A.; Schickling, A.; Verhoef, W.

2016-12-01

This study presents an analysis of airborne measured reflectance (R) and solar-induced chlorophyll fluorescence (SIF) as indicators of high temperature stress in agricultural crops. We used atmospherically corrected R and retrievals of SIF in the O2-A band as obtained from HyPlant data over C3 crops (rapeseed, wheat and barley) and a C4 crop (corn) in Germany before (30th June) and during (2nd July) a heat wave in 2015. The availability of airborne data during this heat wave allowed us to detect fluorescence emission efficiency changes as an indicator of crop photosynthetic performance in response to temperature fluctuations. We found that SIF is affected relatively stronger by heat stress than R. This is according to expectation, because the R spectrum is determined by leaf properties and canopy structure, whereas top-of-canopy (TOC) SIF is also affected by the temperature dependent efficiencies of photochemical and non-photochemical quenching of fluorescence. With the model 'Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE), we differentiated leaf optical parameters and canopy structure from the fluorescence quantum emission efficiency (FQE), i.e. the ratio of fluorescence production to light absorption of photosystems. The leaf optical and canopy structure parameters were retrieved from R by inversion of the radiative transfer module 'RTMo' of SCOPE. The retrieved parameters were further used to estimate the FQE from SIF measurements. It appeared that both the leaf water content CW and the FQE responded to the heat wave, but the responses were different for C3 and C4 crops. A slight reduction of CW occurred in C3 crops between the two days, but not in the C4 crop. The reduction of FQE was only significant in C3 crops, and ranged from 18% to 31% for various C3 species. These findings agree with the general knowledge that C4 plants are better adapted to high temperature than C3 plants, and comply with simulations from a biochemical model for C3 and C4 crops in SCOPE. It is concluded that the combination of hyperspectral R and SIF enables the differentiation of long-term and short term responses to heat stress.

Does constraining memory maintenance reduce visual search efficiency?

PubMed

Buttaccio, Daniel R; Lange, Nicholas D; Thomas, Rick P; Dougherty, Michael R

2018-03-01

We examine whether constraining memory retrieval processes affects performance in a cued recall visual search task. In the visual search task, participants are first presented with a memory prompt followed by a search array. The memory prompt provides diagnostic information regarding a critical aspect of the target (its colour). We assume that upon the presentation of the memory prompt, participants retrieve and maintain hypotheses (i.e., potential target characteristics) in working memory in order to improve their search efficiency. By constraining retrieval through the manipulation of time pressure (Experiments 1A and 1B) or a concurrent working memory task (Experiments 2A, 2B, and 2C), we directly test the involvement of working memory in visual search. We find some evidence that visual search is less efficient under conditions in which participants were likely to be maintaining fewer hypotheses in working memory (Experiments 1A, 2A, and 2C), suggesting that the retrieval of representations from long-term memory into working memory can improve visual search. However, these results should be interpreted with caution, as the data from two experiments (Experiments 1B and 2B) did not lend support for this conclusion.

Quantification of signal detection performance degradation induced by phase-retrieval in propagation-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Chou, Cheng-Ying; Anastasio, Mark A.

2016-04-01

In propagation-based X-ray phase-contrast (PB XPC) imaging, the measured image contains a mixture of absorption- and phase-contrast. To obtain separate images of the projected absorption and phase (i.e., refractive) properties of a sample, phase retrieval methods can be employed. It has been suggested that phase-retrieval can always improve image quality in PB XPC imaging. However, when objective (task-based) measures of image quality are employed, this is not necessarily true and phase retrieval can be detrimental. In this work, signal detection theory is utilized to quantify the performance of a Hotelling observer (HO) for detecting a known signal in a known background. Two cases are considered. In the first case, the HO acts directly on the measured intensity data. In the second case, the HO acts on either the retrieved phase or absorption image. We demonstrate that the performance of the HO is superior when acting on the measured intensity data. The loss of task-specific information induced by phase-retrieval is quantified by computing the efficiency of the HO as the ratio of the test statistic signal-to-noise ratio (SNR) for the two cases. The effect of the system geometry on this efficiency is systematically investigated. Our findings confirm that phase-retrieval can impair signal detection performance in XPC imaging.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2001-01-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

A Semantic Medical Multimedia Retrieval Approach Using Ontology Information Hiding

PubMed Central

Guo, Kehua; Zhang, Shigeng

2013-01-01

Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches. PMID:24082915

Document image retrieval through word shape coding.

PubMed

Lu, Shijian; Li, Linlin; Tan, Chew Lim

2008-11-01

This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

Extinction Interferes with the Retrieval of Visuomotor Memories Through a Mechanism Involving the Sensorimotor Cortex

PubMed Central

Villalta, Jorge I.; Landi, Sofia M.; Fló, Ana; Della-Maggiore, Valeria

2015-01-01

Savings is a fundamental property of learning. In motor adaptation, it refers to the improvement in learning observed when adaptation to a perturbation A (A1) is followed by re-adaptation to the same perturbation (A2). A common procedure to equate the initial level of error across sessions consists of restoring native sensorimotor coordinates by inserting null—unperturbed—trials (N) just before re-adaptation (washout). Here, we hypothesized that the washout is not innocuous but interferes with the expression of the new memory at recall. To assess this possibility, we measured savings following the A1NA2 protocol, where A was a 40° visual rotation. In Experiment 1, we increased the time window between N and A2 from 1 min to 24 h. This manipulation increased the amount of savings during middle to late phases of adaptation, suggesting that N interfered with the retrieval of A. In Experiment 2, we used repetitive TMS to evaluate if this interference was partly mediated by the sensorimotor cortex (SM). We conclude that the washout does not just restore the unperturbed sensorimotor coordinates, but inhibits the expression of the recently acquired visuomotor map through a mechanism involving SM. Our results resemble the phenomenon of extinction in classical conditioning. PMID:24363266

Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load.

PubMed

Holper, L; Van Brussel, L D; Schmidt, L; Schulthess, S; Burke, C J; Louie, K; Seifritz, E; Tobler, P N

2017-01-01

Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain's capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations.

Inquiry Teaching in Clinical Periodontics.

ERIC Educational Resources Information Center

Heins, Paul J.; Mackenzie, Richard S.

1987-01-01

An adaptation of the inquiry method of teaching, which develops skills of information retrieval and reasoning through systematic questioning by the teacher, is proposed for instruction in clinical periodontics. (MSE)

A tutorial on information retrieval: basic terms and concepts

PubMed Central

Zhou, Wei; Smalheiser, Neil R; Yu, Clement

2006-01-01

This informal tutorial is intended for investigators and students who would like to understand the workings of information retrieval systems, including the most frequently used search engines: PubMed and Google. Having a basic knowledge of the terms and concepts of information retrieval should improve the efficiency and productivity of searches. As well, this knowledge is needed in order to follow current research efforts in biomedical information retrieval and text mining that are developing new systems not only for finding documents on a given topic, but extracting and integrating knowledge across documents. PMID:16722601

Northeast Artificial Intelligence Consortium (NAIC). Volume 14. Knowledge Base Retrieval Using Plausible Inference

DTIC Science & Technology

1990-12-01

Improvements to Research Environment ............... 6 14.3 Overview of Research ....... .......................... 7 14.3.1 An Experimental Study of...efficient inference methods. The critical issue we have studied is the effectiveness of retrieval. By this, we mean how well the system does at...locating objects that are judged relevant by the user . Designing effective retrieval strategies is difficult because in real environments the query

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

PubMed

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

High-performance Raman memory with spatio-temporal reversal

NASA Astrophysics Data System (ADS)

Vernaz-Gris, Pierre; Tranter, Aaron D.; Everett, Jesse L.; Leung, Anthony C.; Paul, Karun V.; Campbell, Geoff T.; Lam, Ping Koy; Buchler, Ben C.

2018-05-01

A number of techniques exist to use an ensemble of atoms as a quantum memory for light. Many of these propose to use backward retrieval as a way to improve the storage and recall efficiency. We report on a demonstration of an off-resonant Raman memory that uses backward retrieval to achieve an efficiency of $65\\pm6\\%$ at a storage time of one pulse duration. The memory has a characteristic decay time of 60 $\\mu$s, corresponding to a delay-bandwidth product of $160$.

Self control of when and how much to test face-name pairs in a novel spaced retrieval paradigm: an examination of age-related differences.

PubMed

Maddox, Geoffrey B; Balota, David A

2012-09-01

Although the mnemonic benefit of spaced retrieval is well established, the way in which participants naturally space their own retrieval is relatively unexplored. To examine this question, a novel experimental paradigm was developed in which young and healthy older adults were given control over the frequency and timing of retrieval practice in the context of an ongoing reading task. Results showed that both age groups naturally expanded the intervals of their retrieval practice. When instructed, younger adults but not older adults were better able to employ equal spaced retrieval during retrieval practice. However, even under equal spaced retrieval instructions, young adults included an early retrieval attempt prior to equally spacing their retrieval. Although memory performance was equivalent, secondary task performance was reduced in the experimenter-instructed condition compared with the participant-selected condition. The results overall indicate that both younger and older participants naturally monitor their memory and efficiently use testing to titrate the number and timing of retrieval attempts used during the acquisition phase.

An adaptive controller for enhancing operator performance during teleoperation

NASA Technical Reports Server (NTRS)

Carignan, Craig R.; Tarrant, Janice M.; Mosier, Gary E.

1989-01-01

An adaptive controller is developed for adjusting robot arm parameters while manipulating payloads of unknown mass and inertia. The controller is tested experimentally in a master/slave configuration where the adaptive slave arm is commanded via human operator inputs from a master. Kinematically similar six-joint master and slave arms are used with the last three joints locked for simplification. After a brief initial adaptation period for the unloaded arm, the slave arm retrieves different size payloads and maneuvers them about the workspace. Comparisons are then drawn with similar tasks where the adaptation is turned off. Several simplifications of the controller dynamics are also addressed and experimentally verified.

[Realization of an adaptive method of simulating the process of temperature change of a cadaver on a microcomputer].

PubMed

Shved, E F; Novikov, P I; Vlasov, A Iu

1989-01-01

Programme based on mathematical model of the process of dead body temperature changing was developed for estimation of postmortem interval. Automatic retrieval of problem solution was performed on programmable microcalculators of "Electronica MK-61" type using adaptive approach. Diagnostical accuracy in case of dead body being preserved in permanent cooling conditions is +/- 3%.

Interactive Exploration for Continuously Expanding Neuron Databases.

PubMed

Li, Zhongyu; Metaxas, Dimitris N; Lu, Aidong; Zhang, Shaoting

2017-02-15

This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to associate neuronal morphologies with their functional properties. We design a coarse-to-fine framework for efficient and effective data retrieval from large-scale neuron databases. In the coarse-level, for efficiency in large-scale, we employ a binary coding method to compress morphological features into binary codes of tens of bits. Short binary codes allow for real-time similarity searching in Hamming space. Because the neuron databases are continuously expanding, it is inefficient to re-train the binary coding model from scratch when adding new neurons. To solve this problem, we extend binary coding with online updating schemes, which only considers the newly added neurons and update the model on-the-fly, without accessing the whole neuron databases. In the fine-grained level, we introduce domain experts/users in the framework, which can give relevance feedback for the binary coding based retrieval results. This interactive strategy can improve the retrieval performance through re-ranking the above coarse results, where we design a new similarity measure and take the feedback into account. Our framework is validated on more than 17,000 neuron cells, showing promising retrieval accuracy and efficiency. Moreover, we demonstrate its use case in assisting biologists to identify and explore unknown neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data

NASA Astrophysics Data System (ADS)

Kliewer, A.; Forsythe, J. M.; Fletcher, S. J.; Jones, A. S.

2017-12-01

The Cooperative Institute for Research in the Atmosphere at Colorado State University has recently developed two different versions of a mixed-distribution (lognormal combined with a Gaussian) based microwave temperature and mixing ratio retrieval system as well as the original Gaussian-based approach. These retrieval systems are based upon 1DVAR theory but have been adapted to use different descriptive statistics of the lognormal distribution to minimize the background errors. The input radiance data is from the AMSU-A and MHS instruments on the NOAA series of spacecraft. To help illustrate how the three retrievals are affected by the change in the distribution we are in the process of creating a new website to show the output from the different retrievals. Here we present initial results from different dynamical situations to show how the tool could be used by forecasters as well as for educators. However, as the new retrieved values are from a non-Gaussian based 1DVAR then they will display non-Gaussian behaviors that need to pass a quality control measure that is consistent with this distribution, and these new measures are presented here along with initial results for checking the retrievals.

A Neuroanatomical Model of Prefrontal Inhibitory Modulation of Memory Retrieval

PubMed Central

Depue, Brendan E.

2012-01-01

Memory of past experience is essential for guiding goal-related behavior. Being able to control accessibility of memory through modulation of retrieval enables humans to flexibly adapt to their environment. Understanding the specific neural pathways of how this control is achieved has largely eluded cognitive neuroscience. Accordingly, in the current paper I review literature that examines the overt control over retrieval in order to reduce accessibility. I first introduce three hypotheses of inhibition of retrieval. These hypotheses involve: i) attending to other stimuli as a form of diversionary attention, ii) inhibiting the specific individual neural representation of the memory, and iii) inhibiting the hippocampus and retrieval process more generally to prevent reactivation of the representation. I then analyze literature taken from the White Bear Suppression, Directed Forgetting and Think/No-Think tasks to provide evidence for these hypotheses. Finally, a neuroanatomical model is developed to indicate three pathways from PFC to the hippocampal complex that support inhibition of memory retrieval. Describing these neural pathways increases our understanding of control over memory in general. PMID:22374224

Motor Action and Emotional Memory

ERIC Educational Resources Information Center

Casasanto, Daniel; Dijkstra, Katinka

2010-01-01

Can simple motor actions affect how efficiently people retrieve emotional memories, and influence what they choose to remember? In Experiment 1, participants were prompted to retell autobiographical memories with either positive or negative valence, while moving marbles either upward or downward. They retrieved memories faster when the direction…

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Strategic development in exact calculation: group and individual differences in four achievement subtypes.

PubMed

Wylie, Judith; Jordan, Julie-Ann; Mulhern, Gerry

2012-09-01

This longitudinal study sought to identify developmental changes in strategy use between 5 and 7 years of age when solving exact calculation problems. Four mathematics and reading achievement subtypes were examined at four time points. Five strategies were considered: finger counting, verbal counting, delayed retrieval, automatic retrieval, and derived fact retrieval. Results provided unique insights into children's strategic development in exact calculation at this early stage. Group analysis revealed relationships between mathematical and/or reading difficulties and strategy choice, shift, and adaptiveness. Use of derived fact retrieval by 7 years of age distinguished children with mathematical difficulties from other achievement subtypes. Analysis of individual differences revealed marked heterogeneity within all subtypes, suggesting (inter alia) no marked qualitative distinction between our two mathematical difficulty subtypes. Copyright © 2012 Elsevier Inc. All rights reserved.

A climate index indicative of cloudiness derived from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Abel, M. D.; Cox, S. K.

1981-01-01

In many current studies conducted to enhance the usefulness of meteorological satellite radiance data, one common objective is to infer conventional weather variables. The present investigation, on the other hand, is mainly concerned with the efficient retrieval (minimization of errors) of a nonstandard atmospheric descriptor. The atmosphere's Vertical Infrared Radiative Emitting Structure (VIRES) is retrieved. VIRES is described by the broadband infrared weighting function curve. The shapes of these weighting curves are primarily a function of the three-dimensional cloud structure. The weighting curves are retrieved by a method which uses satellite spectral radiance data. The basic theory involved in the VIRES retrieval procedure parallels the technique used to retrieve temperature soundings.

A comparison of direct aspiration versus stent retriever as a first approach ('COMPASS'): protocol.

PubMed

Turk, Aquilla S; Siddiqui, Adnan H; Mocco, J

2018-02-20

Acute ischemic stroke is a potentially devastating condition and leading cause of morbidity and mortality, affecting an estimated 800 000 people per year in the USA. The natural history of untreated or unrevascularized large vessel occlusions in acute stroke patients results in mortality rates approaching 30%, with only 25% achieving good neurologic outcomes at 90 days. Recently, data have demonstrated that early endovascular recanalization of large vessel occlusions results in better outcomes than medical therapy alone. However, the majority of patients in these studies were treated with a stent retriever based approach. The purpose of COMPASS is to evaluate whether patients treated with a direct aspiration first pass (ADAPT) approach have non-inferior functional outcomes to those treated with a stent retriever as the firstline (SRFL) approach. All patients who meet the inclusion and exclusion criteria and consent to participate will be enrolled at participating centers. Treatment will be randomly assigned by a central web based system in a 1:1 manner to treatment with either ADAPT or SRFL thrombectomy. Statistical methodology is prespecified with details available in the statistical analysis plan. The trial recently completed enrollment, and data collection/verification is ongoing. The final results will be made available on completion of enrollment and follow-up. This paper details the design of the COMPASS trial, a randomized, blinded adjudicator, concurrent, controlled trial of patients treated with either ADAPT or SRFL approaches in order to evaluate whether ADAPT results in non-inferior functional outcome. NCT02466893, Results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

FPGA implementation of sparse matrix algorithm for information retrieval

NASA Astrophysics Data System (ADS)

Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio

2005-06-01

Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.

Dynamic semantic cognition: Characterising coherent and controlled conceptual retrieval through time using magnetoencephalography and chronometric transcranial magnetic stimulation.

PubMed

Teige, Catarina; Mollo, Giovanna; Millman, Rebecca; Savill, Nicola; Smallwood, Jonathan; Cornelissen, Piers L; Jefferies, Elizabeth

2018-06-01

Distinct neural processes are thought to support the retrieval of semantic information that is (i) coherent with strongly-encoded aspects of knowledge, and (ii) non-dominant yet relevant for the current task or context. While the brain regions that support readily coherent and more controlled patterns of semantic retrieval are relatively well-characterised, the temporal dynamics of these processes are not well-understood. This study used magnetoencephalography (MEG) and dual-pulse chronometric transcranial magnetic stimulation (cTMS) in two separate experiments to examine temporal dynamics during the retrieval of strong and weak associations. MEG results revealed a dissociation within left temporal cortex: anterior temporal lobe (ATL) showed greater oscillatory response for strong than weak associations, while posterior middle temporal gyrus (pMTG) showed the reverse pattern. Left inferior frontal gyrus (IFG), a site associated with semantic control and retrieval, showed both patterns at different time points. In the cTMS experiment, stimulation of ATL at ∼150 msec disrupted the efficient retrieval of strong associations, indicating a necessary role for ATL in coherent conceptual activations. Stimulation of pMTG at the onset of the second word disrupted the retrieval of weak associations, suggesting this site may maintain information about semantic context from the first word, allowing efficient engagement of semantic control. Together these studies provide converging evidence for a functional dissociation within the temporal lobe, across both tasks and time. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

Reducing costs of managing and accessing navigation and ancillary data by relying on the extensive capabilities of NASA's spice system

NASA Technical Reports Server (NTRS)

Semenov, Boris V.; Acton, Charles H., Jr.; Bachman, Nathaniel J.; Elson, Lee S.; Wright, Edward D.

2005-01-01

The SPICE system of navigation and ancillary data possesses a number of traits that make its use in modern space missions of all types highly cost efficient. The core of the system is a software library providing API interfaces for storing and retrieving such data as trajectories, orientations, time conversions, and instrument geometry parameters. Applications used at any stage of a mission life cycle can call SPICE APIs to access this data and compute geometric quantities required for observation planning, engineering assessment and science data analysis. SPICE is implemented in three different languages, supported on 20+ computer environments, and distributed with complete source code and documentation. It includes capabilities that are extensively tested by everyday use in many active projects and are applicable to all types of space missions - flyby, orbiters, observatories, landers and rovers. While a customer's initial SPICE adaptation for the first mission or experiment requires a modest effort, this initial effort pays off because adaptation for subsequent missions/experiments is just a small fraction of the initial investment, with the majority of tools based on SPICE requiring no or very minor changes.

Storage, retrieval, and edit of digital video using Motion JPEG

NASA Astrophysics Data System (ADS)

Sudharsanan, Subramania I.; Lee, D. H.

1994-04-01

In a companion paper we describe a Micro Channel adapter card that can perform real-time JPEG (Joint Photographic Experts Group) compression of a 640 by 480 24-bit image within 1/30th of a second. Since this corresponds to NTSC video rates at considerably good perceptual quality, this system can be used for real-time capture and manipulation of continuously fed video. To facilitate capturing the compressed video in a storage medium, an IBM Bus master SCSI adapter with cache is utilized. Efficacy of the data transfer mechanism is considerably improved using the System Control Block architecture, an extension to Micro Channel bus masters. We show experimental results that the overall system can perform at compressed data rates of about 1.5 MBytes/second sustained and with sporadic peaks to about 1.8 MBytes/second depending on the image sequence content. We also describe mechanisms to access the compressed data very efficiently through special file formats. This in turn permits creation of simpler sequence editors. Another advantage of the special file format is easy control of forward, backward and slow motion playback. The proposed method can be extended for design of a video compression subsystem for a variety of personal computing systems.

Stackfile Database

NASA Technical Reports Server (NTRS)

deVarvalho, Robert; Desai, Shailen D.; Haines, Bruce J.; Kruizinga, Gerhard L.; Gilmer, Christopher

2013-01-01

This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

A viable circulating tumor cell isolation device with high retrieval efficiency using a reversibly deformable membrane barrier

NASA Astrophysics Data System (ADS)

Kim, Yoonji; Bu, Jiyoon; Cho, Young-Ho; Son, Il Tae; Kang, Sung-Bum

2017-02-01

Circulating tumor cells (CTCs) contain prognostic information of the tumor, since they shed from the primary tumor and invade into the bloodstream. Therefore, the viable isolation is necessary for a consequent analysis of CTCs. Here, we present a device for the viable isolation and efficient retrieval of CTCs using slanted slot filters, formed by a reversibly deformable membrane barrier. Conventional filters have difficulties in retrieving captured cells, since they easily clog the slots. Moreover, large stress concentration at the sharp edges of squared slots, causes cell lysis. In contrast, the present device shows over 94% of high retrieval efficiency, since the slots can be opened simply by relieving the pressure. Furthermore, the inflated membrane barrier naturally forms the slanted slots, thus reducing the cell damage. By using cancer cell lines, we verified that the present device successfully isolate targeted cells, even at an extremely low concentrations (~10 cells/0.1 ml). In the clinical study, 85.7% of patients initially showed CTC positive while the numbers generally decreased after the surgery. We have also proved that the number of CTCs were highly correlated with tumour invasiveness. Therefore, the present device has potential for use in cancer diagnosis, surgical validation, and invasiveness analysis.

Exploiting salient semantic analysis for information retrieval

NASA Astrophysics Data System (ADS)

Luo, Jing; Meng, Bo; Quan, Changqin; Tu, Xinhui

2016-11-01

Recently, many Wikipedia-based methods have been proposed to improve the performance of different natural language processing (NLP) tasks, such as semantic relatedness computation, text classification and information retrieval. Among these methods, salient semantic analysis (SSA) has been proven to be an effective way to generate conceptual representation for words or documents. However, its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use SSA to improve the information retrieval performance, and propose a SSA-based retrieval method under the language model framework. First, SSA model is adopted to build conceptual representations for documents and queries. Then, these conceptual representations and the bag-of-words (BOW) representations can be used in combination to estimate the language models of queries and documents. The proposed method is evaluated on several standard text retrieval conference (TREC) collections. Experiment results on standard TREC collections show the proposed models consistently outperform the existing Wikipedia-based retrieval methods.

Cluster-Based Query Expansion Using Language Modeling for Biomedical Literature Retrieval

ERIC Educational Resources Information Center

Xu, Xuheng

2011-01-01

The tremendously huge volume of biomedical literature, scientists' specific information needs, long terms of multiples words, and fundamental problems of synonym and polysemy have been challenging issues facing the biomedical information retrieval community researchers. Search engines have significantly improved the efficiency and effectiveness of…

JPL Developments in Retrieval Algorithms for Geostationary Observations - Applications to H2CO

NASA Technical Reports Server (NTRS)

Kurosu, Thomas P.; Kulawik, Susan; Natraj, Vijay

2012-01-01

JPL has strong expertise in atmospheric retrievals from UV and thermal IR, and a wide range of tools to apply to observations and instrument characterization. Radiative Transfer, AMF, Inversion, Fitting, Assimilation. Tools were applied for a preliminary study of H2CO sensitivities from GEO. Results show promise for moderate/strong H2CO lading but also that low background conditions will prove a challenge. H2CO DOF are not too strongly dependent on FWHM. GEMS (Geostationary Environmental Monitoring Spectrometer) choice of 0.6 nm FWHM (?) spectral resolution is adequate for H2CO retrievals. Case study can easily be adapted to GEMS observations/instrument model for more in-depth sensitivity characterization.

Highly-efficient quantum memory for polarization qubits in a spatially-multiplexed cold atomic ensemble.

PubMed

Vernaz-Gris, Pierre; Huang, Kun; Cao, Mingtao; Sheremet, Alexandra S; Laurat, Julien

2018-01-25

Quantum memory for flying optical qubits is a key enabler for a wide range of applications in quantum information. A critical figure of merit is the overall storage and retrieval efficiency. So far, despite the recent achievements of efficient memories for light pulses, the storage of qubits has suffered from limited efficiency. Here we report on a quantum memory for polarization qubits that combines an average conditional fidelity above 99% and efficiency around 68%, thereby demonstrating a reversible qubit mapping where more information is retrieved than lost. The qubits are encoded with weak coherent states at the single-photon level and the memory is based on electromagnetically-induced transparency in an elongated laser-cooled ensemble of cesium atoms, spatially multiplexed for dual-rail storage. This implementation preserves high optical depth on both rails, without compromise between multiplexing and storage efficiency. Our work provides an efficient node for future tests of quantum network functionalities and advanced photonic circuits.

FUEL-FLEXIBLE GASIFICATION-COMBUSTION TECHNOLOGY FOR PRODUCTION OF H2 AND SEQUESTRATION-READY CO2

DOE Office of Scientific and Technical Information (OSTI.GOV)

George Rizeq; Janice West; Arnaldo Frydman

Further development of a combustion Large Eddy Simulation (LES) code for the design of advanced gaseous combustion systems is described in this sixth quarterly report. CFD Research Corporation (CFDRC) is developing the LES module within the parallel, unstructured solver included in the commercial CFD-ACE+ software. In this quarter, in-situ adaptive tabulation (ISAT) for efficient chemical rate storage and retrieval was implemented and tested within the Linear Eddy Model (LEM). ISAT type 3 is being tested so that extrapolation can be performed and further improve the retrieval rate. Further testing of the LEM for subgrid chemistry was performed for parallel applicationsmore » and for multi-step chemistry. Validation of the software on backstep and bluff-body reacting cases were performed. Initial calculations of the SimVal experiment at Georgia Tech using their LES code were performed. Georgia Tech continues the effort to parameterize the LEM over composition space so that a neural net can be used efficiently in the combustion LES code. A new and improved Artificial Neural Network (ANN), with log-transformed output, for the 1-step chemistry was implemented in CFDRC's LES code and gave reasonable results. This quarter, the 2nd consortium meeting was held at CFDRC. Next quarter, LES software development and testing will continue. Alpha testing of the code will continue to be performed on cases of interest to the industrial consortium. Optimization of subgrid models will be pursued, particularly with the ISAT approach. Also next quarter, the demonstration of the neural net approach, for multi-step chemical kinetics speed-up in CFD-ACE+, will be accomplished.« less

Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load

PubMed Central

Burke, C. J.; Seifritz, E.; Tobler, P. N.

2017-01-01

Abstract Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain’s capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations. PMID:28462394

Poor readers' retrieval mechanism: efficient access is not dependent on reading skill

PubMed Central

Johns, Clinton L.; Matsuki, Kazunaga; Van Dyke, Julie A.

2015-01-01

A substantial body of evidence points to a cue-based direct-access retrieval mechanism as a crucial component of skilled adult reading. We report two experiments aimed at examining whether poor readers are able to make use of the same retrieval mechanism. This is significant in light of findings that poor readers have difficulty retrieving linguistic information (e.g., Perfetti, 1985). Our experiments are based on a previous demonstration of direct-access retrieval in language processing, presented in McElree et al. (2003). Experiment 1 replicates the original result using an auditory implementation of the Speed-Accuracy Tradeoff (SAT) method. This finding represents a significant methodological advance, as it opens up the possibility of exploring retrieval speeds in non-reading populations. Experiment 2 provides evidence that poor readers do use a direct-access retrieval mechanism during listening comprehension, despite overall poorer accuracy and slower retrieval speeds relative to skilled readers. The findings are discussed with respect to hypotheses about the source of poor reading comprehension. PMID:26528212

Using input feature information to improve ultraviolet retrieval in neural networks

NASA Astrophysics Data System (ADS)

Sun, Zhibin; Chang, Ni-Bin; Gao, Wei; Chen, Maosi; Zempila, Melina

2017-09-01

In neural networks, the training/predicting accuracy and algorithm efficiency can be improved significantly via accurate input feature extraction. In this study, some spatial features of several important factors in retrieving surface ultraviolet (UV) are extracted. An extreme learning machine (ELM) is used to retrieve the surface UV of 2014 in the continental United States, using the extracted features. The results conclude that more input weights can improve the learning capacities of neural networks.

Retrieving Liquid Water Path and Precipitable Water Vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, David D.; Clough, Shepard A.; Liljegren, James C.

2007-11-01

Ground-based two-channel microwave radiometers have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) – twp geophysical parameters critical for many areas of atmospheric research – are retrieved. An algorithm that utilizes two advanced retrieval techniques, a computationally expensive physical-iterative approach and an efficient statistical method, has been developed to retrieve these parameters. An important component of this Microwave Retrieval (MWRRET) algorithm is the determination of small (< 1K) offsets that are subtracted from the observed brightness temperaturesmore » before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm provides significantly more accurate retrievals than the original ARM statistical retrieval which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm provides significantly better retrievals of PWV and LWP from the ARM 2-channel microwave radiometers compared to the original ARM product.« less

INFORMATION RETRIEVAL EXPERIMENT. FINAL REPORT.

ERIC Educational Resources Information Center

SELYE, HANS

THIS REPORT IS A BRIEF REVIEW OF RESULTS OF AN EXPERIMENT TO DETERMINE THE INFORMATION RETRIEVAL EFFICIENCY OF A MANUAL SPECIALIZED INFORMATION SYSTEM BASED ON 700,000 DOCUMENTS IN THE FIELDS OF ENDOCRINOLOGY, STRESS, MAST CELLS, AND ANAPHYLACTOID REACTIONS. THE SYSTEM RECEIVES 30,000 PUBLICATIONS ANNUALLY. DETAILED INFORMATION IS REPRESENTED BY…

Improving real-time efficiency of case-based reasoning for medical diagnosis.

PubMed

Park, Yoon-Joo

2014-01-01

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. Some previous researches overcome this problem by clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new case-based reasoning method called the Clustering-Merging CBR (CM-CBR) which produces similar level of predictive performances than the conventional CBR with spending significantly less computational cost.

Generating Concise Rules for Human Motion Retrieval

NASA Astrophysics Data System (ADS)

Mukai, Tomohiko; Wakisaka, Ken-Ichi; Kuriyama, Shigeru

This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

Manifold Preserving: An Intrinsic Approach for Semisupervised Distance Metric Learning.

PubMed

Ying, Shihui; Wen, Zhijie; Shi, Jun; Peng, Yaxin; Peng, Jigen; Qiao, Hong

2017-05-18

In this paper, we address the semisupervised distance metric learning problem and its applications in classification and image retrieval. First, we formulate a semisupervised distance metric learning model by considering the metric information of inner classes and interclasses. In this model, an adaptive parameter is designed to balance the inner metrics and intermetrics by using data structure. Second, we convert the model to a minimization problem whose variable is symmetric positive-definite matrix. Third, in implementation, we deduce an intrinsic steepest descent method, which assures that the metric matrix is strictly symmetric positive-definite at each iteration, with the manifold structure of the symmetric positive-definite matrix manifold. Finally, we test the proposed algorithm on conventional data sets, and compare it with other four representative methods. The numerical results validate that the proposed method significantly improves the classification with the same computational efficiency.

Wide field fluorescence epi-microscopy behind a scattering medium enabled by speckle correlations

NASA Astrophysics Data System (ADS)

Hofer, Matthias; Soeller, Christian; Brasselet, Sophie; Bertolotti, Jacopo

2018-04-01

Fluorescence microscopy is widely used in biological imaging, however scattering from tissues strongly limits its applicability to a shallow depth. In this work we adapt a methodology inspired from stellar speckle interferometry, and exploit the optical memory effect to enable fluorescence microscopy through a turbid layer. We demonstrate efficient reconstruction of micrometer-size fluorescent objects behind a scattering medium in epi-microscopy, and study the specificities of this imaging modality (magnification, field of view, resolution) as compared to traditional microscopy. Using a modified phase retrieval algorithm to reconstruct fluorescent objects from speckle images, we demonstrate robust reconstructions even in relatively low signal to noise conditions. This modality is particularly appropriate for imaging in biological media, which are known to exhibit relatively large optical memory ranges compatible with tens of micrometers size field of views, and large spectral bandwidths compatible with emission fluorescence spectra of tens of nanometers widths.

Google matrix analysis of directed networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Complex amplitude reconstruction by iterative amplitude-phase retrieval algorithm with reference

NASA Astrophysics Data System (ADS)

Shen, Cheng; Guo, Cheng; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-06-01

Multi-image iterative phase retrieval methods have been successfully applied in plenty of research fields due to their simple but efficient implementation. However, there is a mismatch between the measurement of the first long imaging distance and the sequential interval. In this paper, an amplitude-phase retrieval algorithm with reference is put forward without additional measurements or priori knowledge. It gets rid of measuring the first imaging distance. With a designed update formula, it significantly raises the convergence speed and the reconstruction fidelity, especially in phase retrieval. Its superiority over the original amplitude-phase retrieval (APR) method is validated by numerical analysis and experiments. Furthermore, it provides a conceptual design of a compact holographic image sensor, which can achieve numerical refocusing easily.

High resolution satellite image indexing and retrieval using SURF features and bag of visual words

NASA Astrophysics Data System (ADS)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

Precipitation Retrievals in typhoon domain combining of FY3C MWHTS Observations and WRF Predicted Models

NASA Astrophysics Data System (ADS)

Jieying, HE; Shengwei, ZHANG; Na, LI

2017-02-01

A passive sub-millimeter precipitation retrievals algorithm is provided based on Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Feng Yun 3C (FY-3C) satellite. Using the validated global reference physical model NCEP/WRF/VDISORT), NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF, and derive the typical precipitation data from the whole world. The precipitation retrieval algorithm can operate either on land or on seawater for global. To simply the calculation procedure and save the training time, principle component analysis (PCA) was adapted to filter out the redundancy caused by scanning angle and surface effects, as well as system noise. According to the comparison and validation combing with other precipitation sources, it is demonstrated that the retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution.

Toward Studying Music Cognition with Information Retrieval Techniques: Lessons Learned from the OpenMIIR Initiative.

PubMed

Stober, Sebastian

2017-01-01

As an emerging sub-field of music information retrieval (MIR), music imagery information retrieval (MIIR) aims to retrieve information from brain activity recorded during music cognition-such as listening to or imagining music pieces. This is a highly inter-disciplinary endeavor that requires expertise in MIR as well as cognitive neuroscience and psychology. The OpenMIIR initiative strives to foster collaborations between these fields to advance the state of the art in MIIR. As a first step, electroencephalography (EEG) recordings of music perception and imagination have been made publicly available, enabling MIR researchers to easily test and adapt their existing approaches for music analysis like fingerprinting, beat tracking or tempo estimation on this new kind of data. This paper reports on first results of MIIR experiments using these OpenMIIR datasets and points out how these findings could drive new research in cognitive neuroscience.

Toward Studying Music Cognition with Information Retrieval Techniques: Lessons Learned from the OpenMIIR Initiative

PubMed Central

Stober, Sebastian

2017-01-01

As an emerging sub-field of music information retrieval (MIR), music imagery information retrieval (MIIR) aims to retrieve information from brain activity recorded during music cognition–such as listening to or imagining music pieces. This is a highly inter-disciplinary endeavor that requires expertise in MIR as well as cognitive neuroscience and psychology. The OpenMIIR initiative strives to foster collaborations between these fields to advance the state of the art in MIIR. As a first step, electroencephalography (EEG) recordings of music perception and imagination have been made publicly available, enabling MIR researchers to easily test and adapt their existing approaches for music analysis like fingerprinting, beat tracking or tempo estimation on this new kind of data. This paper reports on first results of MIIR experiments using these OpenMIIR datasets and points out how these findings could drive new research in cognitive neuroscience. PMID:28824478

Temperature and dust profiles in Martian dust storm conditions retrieved from Mars Climate Sounder measurements

NASA Astrophysics Data System (ADS)

Kleinboehl, A.; Kass, D. M.; Schofield, J. T.; McCleese, D. J.

2013-12-01

Mars Climate Sounder (MCS) is a mid- and far-infrared thermal emission radiometer on board the Mars Reconnaissance Orbiter. It measures radiances in limb and nadir/on-planet geometry from which vertical profiles of atmospheric temperature, water vapor, dust and condensates can be retrieved in an altitude range from 0 to 80 km and with a vertical resolution of ~5 km. Due to the limb geometry used as the MCS primary observation mode, retrievals in conditions with high aerosol loading are challenging. We have developed several modifications to the MCS retrieval algorithm that will facilitate profile retrievals in high-dust conditions. Key modifications include a retrieval option that uses a surface pressure climatology if a pressure retrieval is not possible in high dust conditions, an extension of aerosol retrievals to higher altitudes, and a correction to the surface temperature climatology. In conditions of a global dust storm, surface temperatures tend to be lower compared to standard conditions. Taking this into account using an adaptive value based on atmospheric opacity leads to improved fits to the radiances measured by MCS and improves the retrieval success rate. We present first results of these improved retrievals during the global dust storm in 2007. Based on the limb opacities observed during the storm, retrievals are typically possible above ~30 km altitude. Temperatures around 240 K are observed in the middle atmosphere at mid- and high southern latitudes after the onset of the storm. Dust appears to be nearly homogeneously mixed at lower altitudes. Significant dust opacities are detected at least up to 70 km altitude. During much of the storm, in particular at higher altitudes, the retrieved dust profiles closely resemble a Conrath-profile.

Science information systems: Archive, access, and retrieval

NASA Technical Reports Server (NTRS)

Campbell, William J.

1991-01-01

The objective of this research is to develop technology for the automated characterization and interactive retrieval and visualization of very large, complex scientific data sets. Technologies will be developed for the following specific areas: (1) rapidly archiving data sets; (2) automatically characterizing and labeling data in near real-time; (3) providing users with the ability to browse contents of databases efficiently and effectively; (4) providing users with the ability to access and retrieve system independent data sets electronically; and (5) automatically alerting scientists to anomalies detected in data.

Web-based multimedia information retrieval for clinical application research

NASA Astrophysics Data System (ADS)

Cao, Xinhua; Hoo, Kent S., Jr.; Zhang, Hong; Ching, Wan; Zhang, Ming; Wong, Stephen T. C.

2001-08-01

We described a web-based data warehousing method for retrieving and analyzing neurological multimedia information. The web-based method supports convenient access, effective search and retrieval of clinical textual and image data, and on-line analysis. To improve the flexibility and efficiency of multimedia information query and analysis, a three-tier, multimedia data warehouse for epilepsy research has been built. The data warehouse integrates clinical multimedia data related to epilepsy from disparate sources and archives them into a well-defined data model.

A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

The Effects of Probe Similarity on Retrieval and Comparison Processes in Associative Recognition.

PubMed

Zhang, Qiong; Walsh, Matthew M; Anderson, John R

2017-02-01

In this study, we investigated the information processing stages underlying associative recognition. We recorded EEG data while participants performed a task that involved deciding whether a probe word triple matched any previously studied triple. We varied the similarity between probes and studied triples. According to a model of associative recognition developed in the Adaptive Control of Thought-Rational cognitive architecture, probe similarity affects the duration of the retrieval stage: Retrieval is fastest when the probe is similar to a studied triple. This effect may be obscured, however, by the duration of the comparison stage, which is fastest when the probe is not similar to the retrieved triple. Owing to the opposing effects of probe similarity on retrieval and comparison, overall RTs provide little information about each stage's duration. As such, we evaluated the model using a novel approach that decomposes the EEG signal into a sequence of latent states and provides information about the durations of the underlying information processing stages. The approach uses a hidden semi-Markov model to identify brief sinusoidal peaks (called bumps) that mark the onsets of distinct cognitive stages. The analysis confirmed that probe type has opposite effects on retrieval and comparison stages.

Representation and alignment of sung queries for music information retrieval

NASA Astrophysics Data System (ADS)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

Sparse Contextual Activation for Efficient Visual Re-Ranking.

PubMed

Bai, Song; Bai, Xiang

2016-03-01

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA.

A vector-product information retrieval system adapted to heterogeneous, distributed computing environments

NASA Technical Reports Server (NTRS)

Rorvig, Mark E.

1991-01-01

Vector-product information retrieval (IR) systems produce retrieval results superior to all other searching methods but presently have no commercial implementations beyond the personal computer environment. The NASA Electronic Library Systems (NELS) provides a ranked list of the most likely relevant objects in collections in response to a natural language query. Additionally, the system is constructed using standards and tools (Unix, X-Windows, Notif, and TCP/IP) that permit its operation in organizations that possess many different hosts, workstations, and platforms. There are no known commercial equivalents to this product at this time. The product has applications in all corporate management environments, particularly those that are information intensive, such as finance, manufacturing, biotechnology, and research and development.

The Searching Effectiveness of Social Tagging in Museum Websites

ERIC Educational Resources Information Center

Cho, Chung-Wen; Yeh, Ting-Kuang; Cheng, Shu-Wen; Chang, Chun-Yen

2012-01-01

This paper explores the search effectiveness of social tagging which allows the public to freely tag resources, denoted as keywords, with any words as well as to share personal opinions on those resources. Social tagging potentially helps users to organize, manage, and retrieve resources. Efficient retrieval can help users put more of their focus…

Data retrieval system provides unlimited hardware design information

NASA Technical Reports Server (NTRS)

Rawson, R. D.; Swanson, R. L.

1967-01-01

Data is input to magnetic tape on a single format card that specifies the system, location, and component, the test point identification number, the operators initial, the date, a data code, and the data itself. This method is efficient for large volume data storage and retrieval, and permits output variations without continuous program modifications.

A Semantic Rule-Based Framework for Efficient Retrieval of Educational Materials

ERIC Educational Resources Information Center

Mahmoudi, Maryam Tayefeh; Taghiyareh, Fattaneh; Badie, Kambiz

2013-01-01

Retrieving resources in an appropriate manner has a promising role in increasing the performance of educational support systems. A variety of works have been done to organize materials for educational purposes using tagging techniques. Despite the effectiveness of these techniques within certain domains, organizing resources in a way being…

Test-Retest Stability of Word Retrieval in Aphasic Discourse

ERIC Educational Resources Information Center

Boyle, Mary

2014-01-01

Purpose: This study examined the test-retest stability of select word-retrieval measures in the discourses of people with aphasia who completed a 5-stimulus discourse task. Method: Discourse samples across 3 sessions from 12 individuals with aphasia were analyzed for the stability of measures of informativeness, efficiency, main concepts, noun and…

Using Taxonomic Indexing Trees to Efficiently Retrieve SCORM-Compliant Documents in e-Learning Grids

ERIC Educational Resources Information Center

Shih, Wen-Chung; Tseng, Shian-Shyong; Yang, Chao-Tung

2008-01-01

With the flourishing development of e-Learning, more and more SCORM-compliant teaching materials are developed by institutes and individuals in different sites. In addition, the e-Learning grid is emerging as an infrastructure to enhance traditional e-Learning systems. Therefore, information retrieval schemes supporting SCORM-compliant documents…

Systematically Retrieving Research: A Case Study Evaluating Seven Databases

ERIC Educational Resources Information Center

Taylor, Brian; Wylie, Emma; Dempster, Martin; Donnelly, Michael

2007-01-01

Objective: Developing the scientific underpinnings of social welfare requires effective and efficient methods of retrieving relevant items from the increasing volume of research. Method: We compared seven databases by running the nearest equivalent search on each. The search topic was chosen for relevance to social work practice with older people.…

Precise and Efficient Retrieval of Captioned Images: The MARIE Project.

ERIC Educational Resources Information Center

Rowe, Neil C.

1999-01-01

The MARIE project explores knowledge-based information retrieval of captioned images of the kind found in picture libraries and on the Internet. MARIE's five-part approach exploits the idea that images are easier to understand with context, especially descriptive text near them, but it also does image analysis. Experiments show MARIE prototypes…

Combined sphere-spheroid particle model for the retrieval of the microphysical aerosol parameters via regularized inversion of lidar data

NASA Astrophysics Data System (ADS)

Samaras, Stefanos; Böckmann, Christine; Nicolae, Doina

2016-06-01

In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results.

Compressed-domain video indexing techniques using DCT and motion vector information in MPEG video

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; Doermann, David S.; Lin, King-Ip; Faloutsos, Christos

1997-01-01

Development of various multimedia applications hinges on the availability of fast and efficient storage, browsing, indexing, and retrieval techniques. Given that video is typically stored efficiently in a compressed format, if we can analyze the compressed representation directly, we can avoid the costly overhead of decompressing and operating at the pixel level. Compressed domain parsing of video has been presented in earlier work where a video clip is divided into shots, subshots, and scenes. In this paper, we describe key frame selection, feature extraction, and indexing and retrieval techniques that are directly applicable to MPEG compressed video. We develop a frame-type independent representation of the various types of frames present in an MPEG video in which al frames can be considered equivalent. Features are derived from the available DCT, macroblock, and motion vector information and mapped to a low-dimensional space where they can be accessed with standard database techniques. The spatial information is used as primary index while the temporal information is used to enhance the robustness of the system during the retrieval process. The techniques presented enable fast archiving, indexing, and retrieval of video. Our operational prototype typically takes a fraction of a second to retrieve similar video scenes from our database, with over 95% success.

Physical Retrieval of Surface Emissivity Spectrum from Hyperspectral Infrared Radiances

NASA Technical Reports Server (NTRS)

Li, Jun; Weisz, Elisabeth; Zhou, Daniel K.

2007-01-01

Retrieval of temperature, moisture profiles and surface skin temperature from hyperspectral infrared (IR) radiances requires spectral information about the surface emissivity. Using constant or inaccurate surface emissivities typically results in large retrieval errors, particularly over semi-arid or arid areas where the variation in emissivity spectrum is large both spectrally and spatially. In this study, a physically based algorithm has been developed to retrieve a hyperspectral IR emissivity spectrum simultaneously with the temperature and moisture profiles, as well as the surface skin temperature. To make the solution stable and efficient, the hyperspectral emissivity spectrum is represented by eigenvectors, derived from the laboratory measured hyperspectral emissivity database, in the retrieval process. Experience with AIRS (Atmospheric InfraRed Sounder) radiances shows that a simultaneous retrieval of the emissivity spectrum and the sounding improves the surface skin temperature as well as temperature and moisture profiles, particularly in the near surface layer.

Interactive radiographic image retrieval system.

PubMed

Kundu, Malay Kumar; Chowdhury, Manish; Das, Sudeb

2017-02-01

Content based medical image retrieval (CBMIR) systems enable fast diagnosis through quantitative assessment of the visual information and is an active research topic over the past few decades. Most of the state-of-the-art CBMIR systems suffer from various problems: computationally expensive due to the usage of high dimensional feature vectors and complex classifier/clustering schemes. Inability to properly handle the "semantic gap" and the high intra-class versus inter-class variability problem of the medical image database (like radiographic image database). This yields an exigent demand for developing highly effective and computationally efficient retrieval system. We propose a novel interactive two-stage CBMIR system for diverse collection of medical radiographic images. Initially, Pulse Coupled Neural Network based shape features are used to find out the most probable (similar) image classes using a novel "similarity positional score" mechanism. This is followed by retrieval using Non-subsampled Contourlet Transform based texture features considering only the images of the pre-identified classes. Maximal information compression index is used for unsupervised feature selection to achieve better results. To reduce the semantic gap problem, the proposed system uses a novel fuzzy index based relevance feedback mechanism by incorporating subjectivity of human perception in an analytic manner. Extensive experiments were carried out to evaluate the effectiveness of the proposed CBMIR system on a subset of Image Retrieval in Medical Applications (IRMA)-2009 database consisting of 10,902 labeled radiographic images of 57 different modalities. We obtained overall average precision of around 98% after only 2-3 iterations of relevance feedback mechanism. We assessed the results by comparisons with some of the state-of-the-art CBMIR systems for radiographic images. Unlike most of the existing CBMIR systems, in the proposed two-stage hierarchical framework, main importance is given on constructing efficient and compact feature vector representation, search-space reduction and handling the "semantic gap" problem effectively, without compromising the retrieval performance. Experimental results and comparisons show that the proposed system performs efficiently in the radiographic medical image retrieval field. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

THEMIS Surface-Atmosphere Separation Strategy and Preliminary Results

NASA Technical Reports Server (NTRS)

Bandfield, J. L.; Smith, M. D.; Christensen, P. R.

2002-01-01

Methods refined and adapted from the TES investigation are used to develop a surface-atmosphere separation strategy for THEMIS image analysis and atmospheric temperature and opacity retrievals. Additional information is contained in the original extended abstract.

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

NASA Astrophysics Data System (ADS)

Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

2013-02-01

Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

Photopolarimetric Retrievals of Snow Properties

NASA Technical Reports Server (NTRS)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

Retrieval of the thickness of undeformed sea ice from C-band compact polarimetric SAR images

NASA Astrophysics Data System (ADS)

Zhang, X.; Dierking, W.; Zhang, J.; Meng, J. M.; Lang, H. T.

2015-10-01

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. The parameter is denoted as "CP-Ratio". In model simulations we investigated the sensitivity of CP-Ratio to the dielectric constant, thickness, surface roughness, and incidence angle. From the results of the simulations we deduced optimal conditions for the thickness retrieval. On the basis of C-band CTLR SAR data, which were generated from Radarsat-2 quad-polarization images acquired jointly with helicopter-borne sea ice thickness measurements in the region of the Sea of Labrador, we tested empirical equations for thickness retrieval. An exponential fit between CP-Ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.92 for the retrieval procedure when applying it on level ice of 0.9 m mean thickness.

CatSperζ regulates the structural continuity of sperm Ca2+ signaling domains and is required for normal fertility

PubMed Central

Chung, Jean-Ju; Miki, Kiyoshi; Kim, Doory; Shim, Sang-Hee; Shi, Huanan F; Hwang, Jae Yeon; Cai, Xinjiang; Iseri, Yusuf; Zhuang, Xiaowei; Clapham, David E

2017-01-01

We report that the Gm7068 (CatSpere) and Tex40 (CatSperz) genes encode novel subunits of a 9-subunit CatSper ion channel complex. Targeted disruption of CatSperz reduces CatSper current and sperm rheotactic efficiency in mice, resulting in severe male subfertility. Normally distributed in linear quadrilateral nanodomains along the flagellum, the complex lacking CatSperζ is disrupted at ~0.8 μm intervals along the flagellum. This disruption renders the proximal flagellum inflexible and alters the 3D flagellar envelope, thus preventing sperm from reorienting against fluid flow in vitro and efficiently migrating in vivo. Ejaculated CatSperz-null sperm cells retrieved from the mated female uterus partially rescue in vitro fertilization (IVF) that failed with epididymal spermatozoa alone. Human CatSperε is quadrilaterally arranged along the flagella, similar to the CatSper complex in mouse sperm. We speculate that the newly identified CatSperζ subunit is a late evolutionary adaptation to maximize fertilization inside the mammalian female reproductive tract. DOI: http://dx.doi.org/10.7554/eLife.23082.001 PMID:28226241

Brain-controlled applications using dynamic P300 speller matrices.

PubMed

Halder, Sebastian; Pinegger, Andreas; Käthner, Ivo; Wriessnegger, Selina C; Faller, Josef; Pires Antunes, João B; Müller-Putz, Gernot R; Kübler, Andrea

2015-01-01

Access to the world wide web and multimedia content is an important aspect of life. We present a web browser and a multimedia user interface adapted for control with a brain-computer interface (BCI) which can be used by severely motor impaired persons. The web browser dynamically determines the most efficient P300 BCI matrix size to select the links on the current website. This enables control of the web browser with fewer commands and smaller matrices. The multimedia player was based on an existing software. Both applications were evaluated with a sample of ten healthy participants and three end-users. All participants used a visual P300 BCI with face-stimuli for control. The healthy participants completed the multimedia player task with 90% accuracy and the web browsing task with 85% accuracy. The end-users completed the tasks with 62% and 58% accuracy. All healthy participants and two out of three end-users reported that they felt to be in control of the system. In this study we presented a multimedia application and an efficient web browser implemented for control with a BCI. Both applications provide access to important areas of modern information retrieval and entertainment. Copyright © 2014 Elsevier B.V. All rights reserved.

Classified and clustered data constellation: An efficient approach of 3D urban data management

NASA Astrophysics Data System (ADS)

Azri, Suhaibah; Ujang, Uznir; Castro, Francesc Antón; Rahman, Alias Abdul; Mioc, Darka

2016-03-01

The growth of urban areas has resulted in massive urban datasets and difficulties handling and managing issues related to urban areas. Huge and massive datasets can degrade data retrieval and information analysis performance. In addition, the urban environment is very difficult to manage because it involves various types of data, such as multiple types of zoning themes in the case of urban mixed-use development. Thus, a special technique for efficient handling and management of urban data is necessary. This paper proposes a structure called Classified and Clustered Data Constellation (CCDC) for urban data management. CCDC operates on the basis of two filters: classification and clustering. To boost up the performance of information retrieval, CCDC offers a minimal percentage of overlap among nodes and coverage area to avoid repetitive data entry and multipath query. The results of tests conducted on several urban mixed-use development datasets using CCDC verify that it efficiently retrieves their semantic and spatial information. Further, comparisons conducted between CCDC and existing clustering and data constellation techniques, from the aspect of preservation of minimal overlap and coverage, confirm that the proposed structure is capable of preserving the minimum overlap and coverage area among nodes. Our overall results indicate that CCDC is efficient in handling and managing urban data, especially urban mixed-use development applications.

Feed efficiency of tropically adapted cattle when fed in winter or spring in a temperate location

USDA-ARS?s Scientific Manuscript database

Earlier work has shown that young, tropically adapted cattle do not gain as rapidly as temperately adapted cattle during the winter in OK. The objective for this study was to determine if efficiency of gains was also impacted in tropically adapted cattle and if efficiency is consistent in different...

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Quantum storage of a photonic polarization qubit in a solid.

PubMed

Gündoğan, Mustafa; Ledingham, Patrick M; Almasi, Attaallah; Cristiani, Matteo; de Riedmatten, Hugues

2012-05-11

We report on the quantum storage and retrieval of photonic polarization quantum bits onto and out of a solid state storage device. The qubits are implemented with weak coherent states at the single photon level, and are stored for a predetermined time of 500 ns in a praseodymium doped crystal with a storage and retrieval efficiency of 10%, using the atomic frequency comb scheme. We characterize the storage by using quantum state tomography, and find that the average conditional fidelity of the retrieved qubits exceeds 95% for a mean photon number μ=0.4. This is significantly higher than a classical benchmark, taking into account the poissonian statistics and finite memory efficiency, which proves that our crystal functions as a quantum storage device for polarization qubits. These results extend the storage capabilities of solid state quantum light matter interfaces to polarization encoding, which is widely used in quantum information science.

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

Evaluation of dielectric mixing models for microwave soil moisture retrieval using data from the Combined Radar/Radiometer (ComRAD) ground-based SMAP simulator

USDA-ARS?s Scientific Manuscript database

Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...

Performance assessment of future thermal infrared geostationary instruments to monitor air quality

NASA Astrophysics Data System (ADS)

Sellitto, P.; Dauphin, P.; Dufour, G.; Eremenko, M.; Cuesta, J.; Coman, A.; Forêt, G.; Beekmann, M.; Gaubert, B.; Flaud, J.-M.

2012-04-01

Air quality (AQ) has a recognized onerous impact on human health and the environment, and then on society. It is more and more clear that constantly and efficiently monitoring AQ from space is a valuable step forward towards a more thorough comprehension of pollution processes that can have a relevant impact on the biosphere. In recent years, important progresses in this field have been made, e.g., reliable observations of several pollutants have been obtained, proving the feasibility of monitoring atmospheric composition from space. In this sense, low Earth orbit (LEO) thermal infrared (TIR) space-borne instruments are widely regarded as a useful tool to observe targeted AQ parameters like tropospheric ozone concentrations [1]. However, limitations remain with the current observation systems in particular to observe ozone in the lowermost troposphere (LmT) with a spatial and temporal resolution relevant for monitoring pollution processes at the regional scale. Indeed, LEO instruments are not well adapted to monitor small scale and short term phenomena, owing to their unsatisfactory revisit time. From this point of view, a more satisfactory concept might be based on geostationary (GEO) platforms. Current and planned GEO missions are mainly tailored on meteorological parameters retrieval and do not have sufficient spectral resolutions and signal to noise ratios (SNR) to infer information on trace gases in the LmT. New satellite missions are currently proposed that can partly overcome these limitations. Here we present a group of simulation exercises and sensitivity analyses to set-up future TIR GEO missions adapted to monitor and forecast AQ over Europe, and to evaluate their technical requirements. At this aim, we have developed a general simulator to produce pseudo-observations for different platform/instrument configurations. The core of this simulator is the KOPRA radiative transfer model, including the KOPRAfit inversion module [2]. Note that to assess the impact of the different instruments on the analyses and forecasts of AQ by means of models, our simulator can be coupled with the chemistry and transport model CHIMERE to conduct observing system simulation experiments (OSSEs). Using our simulator, we have produced pseudo-observations for targeted sensors including some potential and planned future GEO instruments like MTG-IRS and MAGEAQ. In order to achieve the best performances that can be obtained from TIR instruments, we applied an altitude-dependent Tikhonov-Philips retrieval algorithm optimized to maximize the information retrieved from the lower troposphere. This algorithm has already demonstrated powerful performances to retrieve lower tropospheric ozone and to detect pollution events [1]. Finally, a detailed analysis of the pseudo-observations has allowed quantifying the added-value brought by the MAGEAQ TIR instrument to resolve LmT geographical patterns and temporal trends of ozone. The results are critically discussed.

Three-dimensional propagation in near-field tomographic X-ray phase retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruhlandt, Aike, E-mail: aruhlan@gwdg.de; Salditt, Tim

An extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions is presented, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. This paper presents an extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. The approach is based on a novel three-dimensional propagator and is derived for the case of optically weak objects. It can be easily implemented in current phase retrieval architectures, is computationally efficient and reduces the need for restrictive prior assumptions, resultingmore » in superior reconstruction quality.« less

Quantum Private Queries

NASA Astrophysics Data System (ADS)

Giovannetti, Vittorio; Lloyd, Seth; Maccone, Lorenzo

2008-06-01

We propose a cheat sensitive quantum protocol to perform a private search on a classical database which is efficient in terms of communication complexity. It allows a user to retrieve an item from the database provider without revealing which item he or she retrieved: if the provider tries to obtain information on the query, the person querying the database can find it out. The protocol ensures also perfect data privacy of the database: the information that the user can retrieve in a single query is bounded and does not depend on the size of the database. With respect to the known (quantum and classical) strategies for private information retrieval, our protocol displays an exponential reduction in communication complexity and in running-time computational complexity.

Two-dimensional thermography image retrieval from zig-zag scanned data with TZ-SCAN

NASA Astrophysics Data System (ADS)

Okumura, Hiroshi; Yamasaki, Ryohei; Arai, Kohei

2008-10-01

TZ-SCAN is a simple and low cost thermal imaging device which consists of a single point radiation thermometer on a tripod with a pan-tilt rotator, a DC motor controller board with a USB interface, and a laptop computer for rotator control, data acquisition, and data processing. TZ-SCAN acquires a series of zig-zag scanned data and stores the data as CSV file. A 2-D thermal distribution image can be retrieved by using the second quefrency peak calculated from TZ-SCAN data. An experiment is conducted to confirm the validity of the thermal retrieval algorithm. The experimental result shows efficient accuracy for 2-D thermal distribution image retrieval.

A humming retrieval system based on music fingerprint

NASA Astrophysics Data System (ADS)

Han, Xingkai; Cao, Baiyu

2011-10-01

In this paper, we proposed an improved music information retrieval method utilizing the music fingerprint. The goal of this method is to represent the music with compressed musical information. Based on the selected MIDI files, which are generated automatically as our music target database, we evaluate the accuracy, effectiveness, and efficiency of this method. In this research we not only extract the feature sequence, which can represent the file effectively, from the query and melody database, but also make it possible for retrieving the results in an innovative way. We investigate on the influence of noise to the performance of our system. As experimental result shows, the retrieval accuracy arriving at up to91% without noise is pretty well

Adaptation of machine translation for multilingual information retrieval in the medical domain.

PubMed

Pecina, Pavel; Dušek, Ondřej; Goeuriot, Lorraine; Hajič, Jan; Hlaváčová, Jaroslava; Jones, Gareth J F; Kelly, Liadh; Leveling, Johannes; Mareček, David; Novák, Michal; Popel, Martin; Rosa, Rudolf; Tamchyna, Aleš; Urešová, Zdeňka

2014-07-01

We investigate machine translation (MT) of user search queries in the context of cross-lingual information retrieval (IR) in the medical domain. The main focus is on techniques to adapt MT to increase translation quality; however, we also explore MT adaptation to improve effectiveness of cross-lingual IR. Our MT system is Moses, a state-of-the-art phrase-based statistical machine translation system. The IR system is based on the BM25 retrieval model implemented in the Lucene search engine. The MT techniques employed in this work include in-domain training and tuning, intelligent training data selection, optimization of phrase table configuration, compound splitting, and exploiting synonyms as translation variants. The IR methods include morphological normalization and using multiple translation variants for query expansion. The experiments are performed and thoroughly evaluated on three language pairs: Czech-English, German-English, and French-English. MT quality is evaluated on data sets created within the Khresmoi project and IR effectiveness is tested on the CLEF eHealth 2013 data sets. The search query translation results achieved in our experiments are outstanding - our systems outperform not only our strong baselines, but also Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. The baseline BLEU scores increased from 26.59 to 41.45 for Czech-English, from 23.03 to 40.82 for German-English, and from 32.67 to 40.82 for French-English. This is a 55% improvement on average. In terms of the IR performance on this particular test collection, a significant improvement over the baseline is achieved only for French-English. For Czech-English and German-English, the increased MT quality does not lead to better IR results. Most of the MT techniques employed in our experiments improve MT of medical search queries. Especially the intelligent training data selection proves to be very successful for domain adaptation of MT. Certain improvements are also obtained from German compound splitting on the source language side. Translation quality, however, does not appear to correlate with the IR performance - better translation does not necessarily yield better retrieval. We discuss in detail the contribution of the individual techniques and state-of-the-art features and provide future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.

Unretrieved shooting loss of mourning doves in north-central South Carolina

USGS Publications Warehouse

Haas, G.H.

1977-01-01

Unretrieved loss for mourning doves (Zenaida macroura) in north-central South Carolina was between 27 and 41 percent of the retrieved kill for the 1973 through 1975 hunting seasons based on 1,396 doves shot by 281 hunters. Dove hunters hunted in groups, fired 8.6 shots per retrieved dove, and engaged in a substantial number of illegal activities. Increased dove populations and hunter bag resulted in increased unretrieved loss, numbers of shots per bagged bird, and illegal activities. Retriever dogs increased the efficiency of dove hunters.

Using PubMed search strings for efficient retrieval of manual therapy research literature.

PubMed

Pillastrini, Paolo; Vanti, Carla; Curti, Stefania; Mattioli, Stefano; Ferrari, Silvano; Violante, Francesco Saverio; Guccione, Andrew

2015-02-01

The aim of this study was to construct PubMed search strings that could efficiently retrieve studies on manual therapy (MT), especially for time-constrained clinicians. Our experts chose 11 Medical Subject Heading terms describing MT along with 84 additional potential terms. For each term that was able to retrieve more than 100 abstracts, we systematically extracted a sample of abstracts from which we estimated the proportion of studies potentially relevant to MT. We then constructed 2 search strings: 1 narrow (threshold of pertinent articles ≥40%) and 1 expanded (including all terms for which a proportion had been calculated). We tested these search strings against articles on 2 conditions relevant to MT (thoracic and temporomandibular pain). We calculated the number of abstracts needed to read (NNR) to identify 1 potentially pertinent article in the context of these conditions. Finally, we evaluated the efficiency of the proposed PubMed search strings to identify relevant articles included in a systematic review on spinal manipulative therapy for chronic low back pain. Fifty-five search terms were able to extract more than 100 citations. The NNR to find 1 potentially pertinent article using the narrow string was 1.2 for thoracic pain and 1.3 for temporomandibular pain, and the NNR for the expanded string was 1.9 and 1.6, respectively. The narrow search strategy retrieved all the randomized controlled trials included in the systematic review selected for comparison. The proposed PubMed search strings may help health care professionals locate potentially pertinent articles and review a large number of MT studies efficiently to better implement evidence-based practice. Copyright © 2015 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

The relationship between dominance, corticosterone, memory, and food caching in mountain chickadees (Poecile gambeli).

PubMed

Pravosudov, Vladimir V; Mendoza, Sally P; Clayton, Nicola S

2003-08-01

It has been hypothesized that in avian social groups subordinate individuals should maintain more energy reserves than dominants, as an insurance against increased perceived risk of starvation. Subordinates might also have elevated baseline corticosterone levels because corticosterone is known to facilitate fattening in birds. Recent experiments showed that moderately elevated corticosterone levels resulting from unpredictable food supply are correlated with enhanced cache retrieval efficiency and more accurate performance on a spatial memory task. Given the correlation between corticosterone and memory, a further prediction is that subordinates might be more efficient at cache retrieval and show more accurate performance on spatial memory tasks. We tested these predictions in dominant-subordinate pairs of mountain chickadees (Poecile gambeli). Each pair was housed in the same cage but caching behavior was tested individually in an adjacent aviary to avoid the confounding effects of small spaces in which birds could unnaturally and directly influence each other's behavior. In sharp contrast to our hypothesis, we found that subordinate chickadees cached less food, showed less efficient cache retrieval, and performed significantly worse on the spatial memory task than dominants. Although the behavioral differences could have resulted from social stress of subordination, and dominant birds reached significantly higher levels of corticosterone during their response to acute stress compared to subordinates, there were no significant differences between dominants and subordinates in baseline levels or in the pattern of adrenocortical stress response. We find no evidence, therefore, to support the hypothesis that subordinate mountain chickadees maintain elevated baseline corticosterone levels whereas lower caching rates and inferior cache retrieval efficiency might contribute to reduced survival of subordinates commonly found in food-caching parids.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Promotion of endocytosis efficiency through an ATP-independent mechanism at rat calyx of Held terminals.

PubMed

Yue, Hai-Yuan; Bieberich, Erhard; Xu, Jianhua

2017-08-01

At rat calyx of Held terminals, ATP was required not only for slow endocytosis, but also for rapid phase of compensatory endocytosis. An ATP-independent form of endocytosis was recruited to accelerate membrane retrieval at increased activity and temperature. ATP-independent endocytosis primarily involved retrieval of pre-existing membrane, which depended on Ca 2+ and the activity of neutral sphingomyelinase but not clathrin-coated pit maturation. ATP-independent endocytosis represents a non-canonical mechanism that can efficiently retrieve membrane at physiological conditions without competing for the limited ATP at elevated neuronal activity. Neurotransmission relies on membrane endocytosis to maintain vesicle supply and membrane stability. Endocytosis has been generally recognized as a major ATP-dependent function, which efficiently retrieves more membrane at elevated neuronal activity when ATP consumption within nerve terminals increases drastically. This paradox raises the interesting question of whether increased activity recruits ATP-independent mechanism(s) to accelerate endocytosis at the same time as preserving ATP availability for other tasks. To address this issue, we studied ATP requirement in three typical forms of endocytosis at rat calyx of Held terminals by whole-cell membrane capacitance measurements. At room temperature, blocking ATP hydrolysis effectively abolished slow endocytosis and rapid endocytosis but only partially inhibited excess endocytosis following intense stimulation. The ATP-independent endocytosis occurred at calyces from postnatal days 8-15, suggesting its existence before and after hearing onset. This endocytosis was not affected by a reduction of exocytosis using the light chain of botulinum toxin C, nor by block of clathrin-coat maturation. It was abolished by EGTA, which preferentially blocked endocytosis of retrievable membrane pre-existing at the surface, and was impaired by oxidation of cholesterol and inhibition of neutral sphingomyelinase. ATP-independent endocytosis became more significant at 34-35°C, and recovered membrane by an amount that, on average, was close to exocytosis. The results of the present study suggest that activity and temperature recruit ATP-independent endocytosis of pre-existing membrane (in addition to ATP-dependent endocytosis) to efficiently retrieve membrane at nerve terminals. This less understood endocytosis represents a non-canonical mechanism regulated by lipids such as cholesterol and sphingomyelinase. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation

NASA Technical Reports Server (NTRS)

Mandrake, Lukas

2013-01-01

Retrieval algorithms like that used by the Orbiting Carbon Observatory (OCO)-2 mission generate massive quantities of data of varying quality and reliability. A computationally efficient, simple method of labeling problematic datapoints or predicting soundings that will fail is required for basic operation, given that only 6% of the retrieved data may be operationally processed. This method automatically obtains a filter designed to reduce scatter based on a small number of input features. Most machine-learning filter construction algorithms attempt to predict error in the CO2 value. By using a surrogate goal of Mean Monthly STDEV, the goal is to reduce the retrieved CO2 scatter rather than solving the harder problem of reducing CO2 error. This lends itself to improved interpretability and performance. This software reduces the scatter of retrieved CO2 values globally based on a minimum number of input features. It can be used as a prefilter to reduce the number of soundings requested, or as a post-filter to label data quality. The use of the MMS (Mean Monthly Standard deviation) provides a much cleaner, clearer filter than the standard ABS(CO2-truth) metrics previously employed by competitor methods. The software's main strength lies in a clearer (i.e., fewer features required) filter that more efficiently reduces scatter in retrieved CO2 rather than focusing on the more complex (and easily removed) bias issues.

5-HT2a receptor in mPFC influences context-guided reconsolidation of object memory in perirhinal cortex.

PubMed

Morici, Juan Facundo; Miranda, Magdalena; Gallo, Francisco Tomás; Zanoni, Belén; Bekinschtein, Pedro; Weisstaub, Noelia V

2018-05-02

Context-dependent memories may guide adaptive behavior relaying in previous experience while updating stored information through reconsolidation. Retrieval can be triggered by partial and shared cues. When the cue is presented, the most relevant memory should be updated. In a contextual version of the object recognition task, we examined the effect of medial PFC (mPFC) serotonin 2a receptor (5-HT2aR) blockade during retrieval in reconsolidation of competing objects memories. We found that mPFC 5-HT2aR controls retrieval and reconsolidation of object memories in the perirhinal cortex (PRH), but not in the dorsal hippocampus in rats. Also, reconsolidation of objects memories in PRH required a functional interaction between the ventral hippocampus and the mPFC. Our results indicate that in the presence of conflicting information at retrieval, mPFC 5-HT2aR may facilitate top-down context-guided control over PRH to control the behavioral response and object memory reconsolidation. © 2018, Morici et al.

5-HT2a receptor in mPFC influences context-guided reconsolidation of object memory in perirhinal cortex

PubMed Central

Morici, Juan Facundo; Miranda, Magdalena; Gallo, Francisco Tomás; Zanoni, Belén; Bekinschtein, Pedro

2018-01-01

Context-dependent memories may guide adaptive behavior relaying in previous experience while updating stored information through reconsolidation. Retrieval can be triggered by partial and shared cues. When the cue is presented, the most relevant memory should be updated. In a contextual version of the object recognition task, we examined the effect of medial PFC (mPFC) serotonin 2a receptor (5-HT2aR) blockade during retrieval in reconsolidation of competing objects memories. We found that mPFC 5-HT2aR controls retrieval and reconsolidation of object memories in the perirhinal cortex (PRH), but not in the dorsal hippocampus in rats. Also, reconsolidation of objects memories in PRH required a functional interaction between the ventral hippocampus and the mPFC. Our results indicate that in the presence of conflicting information at retrieval, mPFC 5-HT2aR may facilitate top-down context-guided control over PRH to control the behavioral response and object memory reconsolidation. PMID:29717980

Lesser Neural Pattern Similarity across Repeated Tests Is Associated with Better Long-Term Memory Retention.

PubMed

Karlsson Wirebring, Linnea; Wiklund-Hörnqvist, Carola; Eriksson, Johan; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

2015-07-01

Encoding and retrieval processes enhance long-term memory performance. The efficiency of encoding processes has recently been linked to representational consistency: the reactivation of a representation that gets more specific each time an item is further studied. Here we examined the complementary hypothesis of whether the efficiency of retrieval processes also is linked to representational consistency. Alternatively, recurrent retrieval might foster representational variability--the altering or adding of underlying memory representations. Human participants studied 60 Swahili-Swedish word pairs before being scanned with fMRI the same day and 1 week later. On Day 1, participants were tested three times on each word pair, and on Day 7 each pair was tested once. A BOLD signal change in right superior parietal cortex was associated with subsequent memory on Day 1 and with successful long-term retention on Day 7. A representational similarity analysis in this parietal region revealed that beneficial recurrent retrieval was associated with representational variability, such that the pattern similarity on Day 1 was lower for retrieved words subsequently remembered compared with those subsequently forgotten. This was mirrored by a monotonically decreased BOLD signal change in dorsolateral prefrontal cortex on Day 1 as a function of repeated successful retrieval for words subsequently remembered, but not for words subsequently forgotten. This reduction in prefrontal response could reflect reduced demands on cognitive control. Collectively, the results offer novel insights into why memory retention benefits from repeated retrieval, and they suggest fundamental differences between repeated study and repeated testing. Repeated testing is known to produce superior long-term retention of the to-be-learned material compared with repeated encoding and other learning techniques, much because it fosters repeated memory retrieval. This study demonstrates that repeated memory retrieval might strengthen memory by inducing more differentiated or elaborated memory representations in the parietal cortex, and at the same time reducing demands on prefrontal-cortex-mediated cognitive control processes during retrieval. The findings contrast with recent demonstrations that repeated encoding induces less differentiated or elaborated memory representations. Together, this study suggests a potential neurocognitive explanation of why repeated retrieval is more beneficial for long-term retention than repeated encoding, a phenomenon known as the testing effect. Copyright © 2015 the authors 0270-6474/15/359595-08$15.00/0.

Development of an Autodiagnostic Adaptive Precision Trainer for Decision Making (ADAPT-DM)

DTIC Science & Technology

2010-06-01

limitation of behavioral measures is that they are limited in their ability to discriminate performance within the ‘‘good’’ or ‘‘ bad ’’ performance... Berka et al. 2007; Klein and Hoffman 1992). In rule-based control mode, rules are consciously retrieved from memory and applied to gathered...because studies have shown a trend for decreasing EEG engagement with increasing task proficiency ( Berka et al. 2007; Stevens, Galloway, and Berka 2007). N

SLUDGE RETRIEVAL FROM HANFORD K WEST BASIN SETTLER TANKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

ERPENBECK EG; LESHIKAR GA

In 2010, an innovative, remotely operated retrieval system was deployed to successfully retrieve over 99.7% of the radioactive sludge from ten submerged tanks in Hanford's K-West Basin. As part of K-West Basin cleanup, the accumulated sludge needed to be removed from the 0.5 meter diameter by 5 meter long settler tanks and transferred approximately 45 meters to an underwater container for sampling and waste treatment. The abrasive, dense, non-homogeneous sludge was the product of the washing process of corroded nuclear fuel. It consists of small (less than 600 micron) particles of uranium metal, uranium oxide, and various other constituents, potentiallymore » agglomerated or cohesive after 10 years of storage. The Settler Tank Retrieval System (STRS) was developed to access, mobilize and pump out the sludge from each tank using a standardized process of retrieval head insertion, periodic high pressure water spray, retraction, and continuous pumping of the sludge. Blind operations were guided by monitoring flow rate, radiation levels in the sludge stream, and solids concentration. The technology developed and employed in the STRS can potentially be adapted to similar problematic waste tanks or pipes that must be remotely accessed to achieve mobilization and retrieval of the sludge within.« less

Description and evaluation of the CASA dual-Doppler system

NASA Astrophysics Data System (ADS)

Martinez, Matthew

2011-12-01

Long range weather surveillance radars are designed for observing weather events for hundreds of kilometers from the radar and operate over a large coverage domain independently of weather conditions. As a result a loss in spatial resolution and limited temporal sampling of the weather phenomenon occurs. Due to the curvature of the Earth, long-range weather radars tend to make the majority of their precipitation and wind observations in the middle to upper troposphere, resulting in missed features associates with severe weather occurring in the lowest three kilometers of the troposphere. The spacing of long-range weather radars in the United States limits the feasibility of using dual-Doppler wind retrievals that would provide valuable information on the kinematics of weather events to end-users and researchers. The National Science Foundation Center for Collaborative Adapting Sensing of the Atmosphere (CASA) aims to change the current weather sensing model by increasing coverage of the lowest three kilometers of the troposphere by using densely spaced networked short-range weather radars. CASA has deployed a network of these radars in south-western Oklahoma, known as Integrated Project 1 (IP1). The individual radars are adaptively steered by an automated system known as the Meteorological Command and Control (MCC). The geometry of the IP1 network is such that the coverage domains of the individual radars are overlapping. A dual-Doppler system has been developed for the IP1 network which takes advantage of the overlapping coverage domains. The system is comprised of two subsystems, scan optimization and wind field retrieval. The scan strategy subsystem uses the DCAS model and the number of dual-Doppler pairs in the IP1 network to minimizes the normalized standard deviation in the wind field retrieval. The scan strategy subsystem also minimizes the synchronization error between two radars. The retrieval itself is comprised of two steps, data resampling and the retrieval process. The resampling step map data collected in radar coordinates to a common Cartesian grid. The retrieval process uses the radial velocity measurements to estimate the northward, eastward, and vertical component of the wind. The error in the retrieval is related to the beam crossing angle. The best retrievals occur at beam crossing angles greater than 30 degrees. During operations statistics on the scan strategy and wind field retrievals are collected in real-time. For the scan strategy subsystem statistics on the beam crossing angels, maximum elevation angle, number of elevation angles, maximum observable height, and synchronization time between radars in a pair are collected by the MCC. These statistics are used to evaluate the performance of the scan strategy subsystem. Observations of a strong wind event occurring on April 2, 2010 are used to evaluate the decision process associated with the scan strategy optimization. For the retrieval subsystem, the normalized standard deviation for the wind field retrieval is used to evaluate the quality of the retrieval. Wind fields from an EF2 tornado observed on May 14, 2009 are used to evaluate the quality of the wind field retrievals in hazardous wind events. Two techniques for visualizing vector fields are available, streamlines and arrows. Each visualization technique is evaluated based on the task of visualizing small and large scale phenomenon. Applications of the wind field retrievals include the computation of the vorticity and divergence fields. Vorticity and divergence for an EF2 tornado observed on May 14, 2009 are evaluated against vorticity and divergence for other observed tornadoes.

Development and testing of a text-mining approach to analyse patients' comments on their experiences of colorectal cancer care.

PubMed

Wagland, Richard; Recio-Saucedo, Alejandra; Simon, Michael; Bracher, Michael; Hunt, Katherine; Foster, Claire; Downing, Amy; Glaser, Adam; Corner, Jessica

2016-08-01

Quality of cancer care may greatly impact on patients' health-related quality of life (HRQoL). Free-text responses to patient-reported outcome measures (PROMs) provide rich data but analysis is time and resource-intensive. This study developed and tested a learning-based text-mining approach to facilitate analysis of patients' experiences of care and develop an explanatory model illustrating impact on HRQoL. Respondents to a population-based survey of colorectal cancer survivors provided free-text comments regarding their experience of living with and beyond cancer. An existing coding framework was tested and adapted, which informed learning-based text mining of the data. Machine-learning algorithms were trained to identify comments relating to patients' specific experiences of service quality, which were verified by manual qualitative analysis. Comparisons between coded retrieved comments and a HRQoL measure (EQ5D) were explored. The survey response rate was 63.3% (21 802/34 467), of which 25.8% (n=5634) participants provided free-text comments. Of retrieved comments on experiences of care (n=1688), over half (n=1045, 62%) described positive care experiences. Most negative experiences concerned a lack of post-treatment care (n=191, 11% of retrieved comments) and insufficient information concerning self-management strategies (n=135, 8%) or treatment side effects (n=160, 9%). Associations existed between HRQoL scores and coded algorithm-retrieved comments. Analysis indicated that the mechanism by which service quality impacted on HRQoL was the extent to which services prevented or alleviated challenges associated with disease and treatment burdens. Learning-based text mining techniques were found useful and practical tools to identify specific free-text comments within a large dataset, facilitating resource-efficient qualitative analysis. This method should be considered for future PROM analysis to inform policy and practice. Study findings indicated that perceived care quality directly impacts on HRQoL. 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/

Development and tuning of an original search engine for patent libraries in medicinal chemistry.

PubMed

Pasche, Emilie; Gobeill, Julien; Kreim, Olivier; Oezdemir-Zaech, Fatma; Vachon, Therese; Lovis, Christian; Ruch, Patrick

2014-01-01

The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to adapt to the various search tasks clearly increases the effectiveness of the system. We conclude that different search tasks demand different information retrieval engines' settings in order to yield optimal end-user retrieval.

Development and tuning of an original search engine for patent libraries in medicinal chemistry

PubMed Central

2014-01-01

Background The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. Methods We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. Results The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. Conclusions We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to adapt to the various search tasks clearly increases the effectiveness of the system. We conclude that different search tasks demand different information retrieval engines' settings in order to yield optimal end-user retrieval. PMID:24564220

Content Based Lecture Video Retrieval Using Speech and Video Text Information

ERIC Educational Resources Information Center

Yang, Haojin; Meinel, Christoph

2014-01-01

In the last decade e-lecturing has become more and more popular. The amount of lecture video data on the "World Wide Web" (WWW) is growing rapidly. Therefore, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. This paper presents an approach for automated video indexing and video…

A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

PubMed

Ma, Ling; Liu, Xiabi; Gao, Yan; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2017-02-01

This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Comparison of k-means related clustering methods for nuclear medicine images segmentation

NASA Astrophysics Data System (ADS)

Borys, Damian; Bzowski, Pawel; Danch-Wierzchowska, Marta; Psiuk-Maksymowicz, Krzysztof

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Human memory retrieval as Lévy foraging

NASA Astrophysics Data System (ADS)

Rhodes, Theo; Turvey, Michael T.

2007-11-01

When people attempt to recall as many words as possible from a specific category (e.g., animal names) their retrievals occur sporadically over an extended temporal period. Retrievals decline as recall progresses, but short retrieval bursts can occur even after tens of minutes of performing the task. To date, efforts to gain insight into the nature of retrieval from this fundamental phenomenon of semantic memory have focused primarily upon the exponential growth rate of cumulative recall. Here we focus upon the time intervals between retrievals. We expected and found that, for each participant in our experiment, these intervals conformed to a Lévy distribution suggesting that the Lévy flight dynamics that characterize foraging behavior may also characterize retrieval from semantic memory. The closer the exponent on the inverse square power-law distribution of retrieval intervals approximated the optimal foraging value of 2, the more efficient was the retrieval. At an abstract dynamical level, foraging for particular foods in one's niche and searching for particular words in one's memory must be similar processes if particular foods and particular words are randomly and sparsely located in their respective spaces at sites that are not known a priori. We discuss whether Lévy dynamics imply that memory processes, like foraging, are optimized in an ecological way.

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

TU-AB-303-08: GPU-Based Software Platform for Efficient Image-Guided Adaptive Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, S; Robinson, A; McNutt, T

2015-06-15

Purpose: In this study, we develop an integrated software platform for adaptive radiation therapy (ART) that combines fast and accurate image registration, segmentation, and dose computation/accumulation methods. Methods: The proposed system consists of three key components; 1) deformable image registration (DIR), 2) automatic segmentation, and 3) dose computation/accumulation. The computationally intensive modules including DIR and dose computation have been implemented on a graphics processing unit (GPU). All required patient-specific data including the planning CT (pCT) with contours, daily cone-beam CTs, and treatment plan are automatically queried and retrieved from their own databases. To improve the accuracy of DIR between pCTmore » and CBCTs, we use the double force demons DIR algorithm in combination with iterative CBCT intensity correction by local intensity histogram matching. Segmentation of daily CBCT is then obtained by propagating contours from the pCT. Daily dose delivered to the patient is computed on the registered pCT by a GPU-accelerated superposition/convolution algorithm. Finally, computed daily doses are accumulated to show the total delivered dose to date. Results: Since the accuracy of DIR critically affects the quality of the other processes, we first evaluated our DIR method on eight head-and-neck cancer cases and compared its performance. Normalized mutual-information (NMI) and normalized cross-correlation (NCC) computed as similarity measures, and our method produced overall NMI of 0.663 and NCC of 0.987, outperforming conventional methods by 3.8% and 1.9%, respectively. Experimental results show that our registration method is more consistent and roust than existing algorithms, and also computationally efficient. Computation time at each fraction took around one minute (30–50 seconds for registration and 15–25 seconds for dose computation). Conclusion: We developed an integrated GPU-accelerated software platform that enables accurate and efficient DIR, auto-segmentation, and dose computation, thus supporting an efficient ART workflow. This work was supported by NIH/NCI under grant R42CA137886.« less

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin

2014-03-01

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.

Content-aware network storage system supporting metadata retrieval

NASA Astrophysics Data System (ADS)

Liu, Ke; Qin, Leihua; Zhou, Jingli; Nie, Xuejun

2008-12-01

Nowadays, content-based network storage has become the hot research spot of academy and corporation[1]. In order to solve the problem of hit rate decline causing by migration and achieve the content-based query, we exploit a new content-aware storage system which supports metadata retrieval to improve the query performance. Firstly, we extend the SCSI command descriptor block to enable system understand those self-defined query requests. Secondly, the extracted metadata is encoded by extensible markup language to improve the universality. Thirdly, according to the demand of information lifecycle management (ILM), we store those data in different storage level and use corresponding query strategy to retrieval them. Fourthly, as the file content identifier plays an important role in locating data and calculating block correlation, we use it to fetch files and sort query results through friendly user interface. Finally, the experiments indicate that the retrieval strategy and sort algorithm have enhanced the retrieval efficiency and precision.

Retrieval of the thickness of undeformed sea ice from simulated C-band compact polarimetric SAR images

NASA Astrophysics Data System (ADS)

Zhang, Xi; Dierking, Wolfgang; Zhang, Jie; Meng, Junmin; Lang, Haitao

2016-07-01

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric (CP) synthetic aperture radar (SAR) images. The parameter is denoted as the "CP ratio". In model simulations we investigated the sensitivity of the CP ratio to the dielectric constant, ice thickness, ice surface roughness, and radar incidence angle. From the results of the simulations we deduced optimal sea ice conditions and radar incidence angles for the ice thickness retrieval. C-band SAR data acquired over the Labrador Sea in circular transmit and linear receive (CTLR) mode were generated from RADARSAT-2 quad-polarization images. In comparison with results from helicopter-borne measurements, we tested different empirical equations for the retrieval of ice thickness. An exponential fit between the CP ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region, we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.94 for the retrieval procedure when applying it to level ice between 0.1 and 0.8 m thick.

Combination of image descriptors for the exploration of cultural photographic collections

NASA Astrophysics Data System (ADS)

Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain

2017-01-01

The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

Ultra-high resolution coded wavefront sensor.

PubMed

Wang, Congli; Dun, Xiong; Fu, Qiang; Heidrich, Wolfgang

2017-06-12

Wavefront sensors and more general phase retrieval methods have recently attracted a lot of attention in a host of application domains, ranging from astronomy to scientific imaging and microscopy. In this paper, we introduce a new class of sensor, the Coded Wavefront Sensor, which provides high spatio-temporal resolution using a simple masked sensor under white light illumination. Specifically, we demonstrate megapixel spatial resolution and phase accuracy better than 0.1 wavelengths at reconstruction rates of 50 Hz or more, thus opening up many new applications from high-resolution adaptive optics to real-time phase retrieval in microscopy.

Research on keyword retrieval method of HBase database based on index structure

NASA Astrophysics Data System (ADS)

Gong, Pijin; Lv, Congmin; Gong, Yongsheng; Ma, Haozhi; Sun, Yang; Wang, Lu

2017-10-01

With the rapid development of manned spaceflight engineering, the scientific experimental data in space application system is increasing rapidly. How to efficiently query the specific data in the mass data volume has become a problem. In this paper, a method of retrieving the object data based on the object attribute as the keyword is proposed. The HBase database is used to store the object data and object attributes, and the secondary index is constructed. The research shows that this method is a good way to retrieve specified data based on object attributes.

Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search.

PubMed

Liu, Xianglong; Deng, Cheng; Lang, Bo; Tao, Dacheng; Li, Xuelong

2016-02-01

Recent years have witnessed the success of binary hashing techniques in approximate nearest neighbor search. In practice, multiple hash tables are usually built using hashing to cover more desired results in the hit buckets of each table. However, rare work studies the unified approach to constructing multiple informative hash tables using any type of hashing algorithms. Meanwhile, for multiple table search, it also lacks of a generic query-adaptive and fine-grained ranking scheme that can alleviate the binary quantization loss suffered in the standard hashing techniques. To solve the above problems, in this paper, we first regard the table construction as a selection problem over a set of candidate hash functions. With the graph representation of the function set, we propose an efficient solution that sequentially applies normalized dominant set to finding the most informative and independent hash functions for each table. To further reduce the redundancy between tables, we explore the reciprocal hash tables in a boosting manner, where the hash function graph is updated with high weights emphasized on the misclassified neighbor pairs of previous hash tables. To refine the ranking of the retrieved buckets within a certain Hamming radius from the query, we propose a query-adaptive bitwise weighting scheme to enable fine-grained bucket ranking in each hash table, exploiting the discriminative power of its hash functions and their complement for nearest neighbor search. Moreover, we integrate such scheme into the multiple table search using a fast, yet reciprocal table lookup algorithm within the adaptive weighted Hamming radius. In this paper, both the construction method and the query-adaptive search method are general and compatible with different types of hashing algorithms using different feature spaces and/or parameter settings. Our extensive experiments on several large-scale benchmarks demonstrate that the proposed techniques can significantly outperform both the naive construction methods and the state-of-the-art hashing algorithms.

An end to end secure CBIR over encrypted medical database.

PubMed

Bellafqira, Reda; Coatrieux, Gouenou; Bouslimi, Dalel; Quellec, Gwenole

2016-08-01

In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features extracted from the encrypted images are themselves encrypted. This is achieved by means of homomorphic encryption and two non-colluding servers, we however both consider as honest but curious. In that way an end to end secure CBIR process is ensured. Experimental results carried out on a diabetic retinopathy database encrypted with the Paillier cryptosystem indicate that our SCBIR achieves retrieval performance as good as if images were processed in their non-encrypted form.

Efficient Caption-Based Retrieval of Multimedia Information

DTIC Science & Technology

1993-10-09

in the design of transportable natural language interfaces. Artifcial Intelligence , 32 (1987), 173-243. - 13- (101 Jones, M. and Eisner, J. A...systems for multimedia data . They exploit captions on the data and perform natural-language processing of them and English retrieval requests. Some...content analysis of the data is also performed to obtain additional descriptive information. The key to getting this approach to work is sufficiently

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2012-09-01

the Gerchberg-Saxton algorithm in the Fresnel diffraction regime, and is much more robust against image noise than the TIE-based method. For details...developed efficient coding with the software modules for the image registration, flat-filed correction , and phase retrievals. In addition, we...X, Liu H. 2010. Performance analysis of the attenuation-partition based iterative phase retrieval algorithm for in-line phase-contrast imaging

Suitable Adaptation Mechanisms for Intelligent Tutoring Technologies

DTIC Science & Technology

2010-12-01

the Acoustic Society of America, 93(2), pp. 1097-1108. Neurofeedback equipment - Wireless Brainquiry PET EEG and ActivEEG. (n.d.). Retrieved from...27 5.2 Electroencephalogram ( EEG ...electroencephalogram ( EEG ), heart rate variability (HRV- a measure involving the electrocardiogram [ECG]), and galvanic skin response (GSR) either

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Flexible Retrieval: When True Inferences Produce False Memories

PubMed Central

Carpenter, Alexis C.; Schacter, Daniel L.

2016-01-01

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether a) false memories increased for successful versus unsuccessful inferences, and b) any such effects were specific to after as compared to before participants received the inference test. In each of four experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes. PMID:27918169

Text grouping in patent analysis using adaptive K-means clustering algorithm

NASA Astrophysics Data System (ADS)

Shanie, Tiara; Suprijadi, Jadi; Zulhanif

2017-03-01

Patents are one of the Intellectual Property. Analyzing patent is one requirement in knowing well the development of technology in each country and in the world now. This study uses the patent document coming from the Espacenet server about Green Tea. Patent documents related to the technology in the field of tea is still widespread, so it will be difficult for users to information retrieval (IR). Therefore, it is necessary efforts to categorize documents in a specific group of related terms contained therein. This study uses titles patent text data with the proposed Green Tea in Statistical Text Mining methods consists of two phases: data preparation and data analysis stage. The data preparation phase uses Text Mining methods and data analysis stage is done by statistics. Statistical analysis in this study using a cluster analysis algorithm, the Adaptive K-Means Clustering Algorithm. Results from this study showed that based on the maximum value Silhouette, generate 87 clusters associated fifteen terms therein that can be utilized in the process of information retrieval needs.

Neptune Clouds and Methane, from Ground-Based Visible and Near-Infrared Spectroscopy with Adaptive Optics

NASA Astrophysics Data System (ADS)

Tice, D. S.; Irwin, P. G. J.; Houghton, R. W. C.; Fletcher, L. N.; Clarke, F.; Hurley, J.; Thatte, N.; Tecza, M.

2013-09-01

Observations of Neptune were made in June/July 2012 with the SWIFT integral field spectrometer at the Palomar Observatory's 200-inch Hale Telescope. Spectral resolutions for observations between 0.65 μm and 1.0 μm were R ≥ 3250. Palomar's PALM-3000 adaptive optics system enabled images of the full Neptunian disc to be recorded at a spatial scale of 0.08"·pixel^-1 with a seeing of approximately 0.30" - 0.40". Retrievals of cloud properties and methane abundance in the highly dynamic atmosphere were obtained with the general-purpose retrieval tool, NEMESIS. The short wavelengths of the observations allowed for good characterisation of the scattering particles' optical properties in the many cloud and haze layers of the upper Neptunian atmosphere. A region of relatively low methane absorption and high collision-induced hydrogen quadrupole absorption at 825 nm further constrains spectral properties of clouds as distinguished from those of methane absorption.

Dynamic generation and coherent control of beating stationary light pulses by a microwave coupling field in five-level cold atoms

NASA Astrophysics Data System (ADS)

Bao, Qian-Qian; Zhang, Yan; Cui, Cui-Li; Meng, Shao-Ying; Fang, You-Wei; Tian, Xue-Dong

2018-04-01

We propose an efficient scheme for generating and controlling beating stationary light pulses in a five-level atomic sample driven into electromagnetically induced transparency condition. This scheme relies on an asymmetrical procedure of light storage and retrieval tuned by two counter-propagating control fields where an additional coupling field, such as the microwave field, is introduced in the retrieval stage. A quantum probe field, incident upon such an atomic sample, is first transformed into spin coherence excitation of the atoms and then retrieved as beating stationary light pulses exhibiting a series of maxima and minima in intensity due to the alternative constructive and destructive interference. It is convenient to control the beating stationary light pulses just by manipulating the intensity and detuning of the additional microwave field. This interesting phenomenon involves in fact the coherent manipulation of dark-state polaritons and could be explored to achieve the efficient temporal splitting of stationary light pulses and accurate measurement of the microwave intensity.

[Sex dimorphism in the functional organization of the cerebral hemispheres during the memorization of verbal information].

PubMed

Vol'f, N V

1998-01-01

Sexual differences in the hemispheric organization of verbal functions were shown in experiments with dichotic presentation of word lists, in Sternbeg's memory scanning task, in studies of EEG power and coherence while memorizing the lists of dichotically presented words. The efficiency of word retrieval and speed of memory scanning for stimuli presented to the right hemisphere were higher in women. EEG activation while memorizing words was more pronounced in men. There were negative correlations between left ear word retrieval and EEG activation in women. The author's findings showed sexual dimorphism in functional connections within the cortical regions of the brain while memorizing verbal information. The changes in coherence were in positive correlation with the efficiency of word retrieval in women and in inverse correlation in men, and this was evidence for the different physiological significance of changes in coherence in men and women. This suggests that the physiological significance of changes in coherence differs in men and women.

Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

PubMed

ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

2017-11-01

Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

Morphology and Efficiency of a Specialized Foraging Behavior, Sediment Sifting, in Neotropical Cichlid Fishes

PubMed Central

Willis, Stuart; Watkins, Crystal; Honeycutt, Rodney L.; Winemiller, Kirk O.

2014-01-01

Understanding of relationships between morphology and ecological performance can help to reveal how natural selection drives biological diversification. We investigate relationships between feeding behavior, foraging performance and morphology within a diverse group of teleost fishes, and examine the extent to which associations can be explained by evolutionary relatedness. Morphological adaptation associated with sediment sifting was examined using a phylogenetic linear discriminant analysis on a set of ecomorphological traits from 27 species of Neotropical cichlids. For most sifting taxa, feeding behavior could be effectively predicted by a linear discriminant function of ecomorphology across multiple clades of sediment sifters, and this pattern could not be explained by shared evolutionary history alone. Additionally, we tested foraging efficiency in seven Neotropical cichlid species, five of which are specialized benthic feeders with differing head morphology. Efficiency was evaluated based on the degree to which invertebrate prey could be retrieved at different depths of sediment. Feeding performance was compared both with respect to feeding mode and species using a phylogenetic ANCOVA, with substrate depth as a covariate. Benthic foraging performance was constant across sediment depths in non-sifters but declined with depth in sifters. The non-sifting Hypsophrys used sweeping motions of the body and fins to excavate large pits to uncover prey; this tactic was more efficient for consuming deeply buried invertebrates than observed among sediment sifters. Findings indicate that similar feeding performance among sediment-sifting cichlids extracting invertebrate prey from shallow sediment layers reflects constraints associated with functional morphology and, to a lesser extent, phylogeny. PMID:24603485

Morphology and efficiency of a specialized foraging behavior, sediment sifting, in neotropical cichlid fishes.

PubMed

López-Fernández, Hernán; Arbour, Jessica; Willis, Stuart; Watkins, Crystal; Honeycutt, Rodney L; Winemiller, Kirk O

2014-01-01

Understanding of relationships between morphology and ecological performance can help to reveal how natural selection drives biological diversification. We investigate relationships between feeding behavior, foraging performance and morphology within a diverse group of teleost fishes, and examine the extent to which associations can be explained by evolutionary relatedness. Morphological adaptation associated with sediment sifting was examined using a phylogenetic linear discriminant analysis on a set of ecomorphological traits from 27 species of Neotropical cichlids. For most sifting taxa, feeding behavior could be effectively predicted by a linear discriminant function of ecomorphology across multiple clades of sediment sifters, and this pattern could not be explained by shared evolutionary history alone. Additionally, we tested foraging efficiency in seven Neotropical cichlid species, five of which are specialized benthic feeders with differing head morphology. Efficiency was evaluated based on the degree to which invertebrate prey could be retrieved at different depths of sediment. Feeding performance was compared both with respect to feeding mode and species using a phylogenetic ANCOVA, with substrate depth as a covariate. Benthic foraging performance was constant across sediment depths in non-sifters but declined with depth in sifters. The non-sifting Hypsophrys used sweeping motions of the body and fins to excavate large pits to uncover prey; this tactic was more efficient for consuming deeply buried invertebrates than observed among sediment sifters. Findings indicate that similar feeding performance among sediment-sifting cichlids extracting invertebrate prey from shallow sediment layers reflects constraints associated with functional morphology and, to a lesser extent, phylogeny.

An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks

NASA Astrophysics Data System (ADS)

Tucker, Gregory E.; Lancaster, Stephen T.; Gasparini, Nicole M.; Bras, Rafael L.; Rybarczyk, Scott M.

2001-10-01

We describe a new set of data structures and algorithms for dynamic terrain modeling using a triangulated irregular network (TINs). The framework provides an efficient method for storing, accessing, and updating a Delaunay triangulation and its associated Voronoi diagram. The basic data structure consists of three interconnected data objects: triangles, nodes, and directed edges. Encapsulating each of these geometric elements within a data object makes it possible to essentially decouple the TIN representation from the modeling applications that make use of it. Both the triangulation and its corresponding Voronoi diagram can be rapidly retrieved or updated, making these methods well suited to adaptive remeshing schemes. We develop a set of algorithms for defining drainage networks and identifying closed depressions (e.g., lakes) for hydrologic and geomorphic modeling applications. We also outline simple numerical algorithms for solving network routing and 2D transport equations within the TIN framework. The methods are illustrated with two example applications, a landscape evolution model and a distributed rainfall-runoff model.

FJET Database Project: Extract, Transform, and Load

NASA Technical Reports Server (NTRS)

Samms, Kevin O.

2015-01-01

The Data Mining & Knowledge Management team at Kennedy Space Center is providing data management services to the Frangible Joint Empirical Test (FJET) project at Langley Research Center (LARC). FJET is a project under the NASA Engineering and Safety Center (NESC). The purpose of FJET is to conduct an assessment of mild detonating fuse (MDF) frangible joints (FJs) for human spacecraft separation tasks in support of the NASA Commercial Crew Program. The Data Mining & Knowledge Management team has been tasked with creating and managing a database for the efficient storage and retrieval of FJET test data. This paper details the Extract, Transform, and Load (ETL) process as it is related to gathering FJET test data into a Microsoft SQL relational database, and making that data available to the data users. Lessons learned, procedures implemented, and programming code samples are discussed to help detail the learning experienced as the Data Mining & Knowledge Management team adapted to changing requirements and new technology while maintaining flexibility of design in various aspects of the data management project.

Safeguards of Neurotransmission: Endocytic Adaptors as Regulators of Synaptic Vesicle Composition and Function

PubMed Central

Kaempf, Natalie; Maritzen, Tanja

2017-01-01

Communication between neurons relies on neurotransmitters which are released from synaptic vesicles (SVs) upon Ca2+ stimuli. To efficiently load neurotransmitters, sense the rise in intracellular Ca2+ and fuse with the presynaptic membrane, SVs need to be equipped with a stringently controlled set of transmembrane proteins. In fact, changes in SV protein composition quickly compromise neurotransmission and most prominently give rise to epileptic seizures. During exocytosis SVs fully collapse into the presynaptic membrane and consequently have to be replenished to sustain neurotransmission. Therefore, surface-stranded SV proteins have to be efficiently retrieved post-fusion to be used for the generation of a new set of fully functional SVs, a process in which dedicated endocytic sorting adaptors play a crucial role. The question of how the precise reformation of SVs is achieved is intimately linked to how SV membranes are retrieved. For a long time both processes were believed to be two sides of the same coin since Clathrin-mediated endocytosis (CME), the proposed predominant SV recycling mode, will jointly retrieve SV membranes and proteins. However, with the recent proposal of Clathrin-independent SV recycling pathways SV membrane retrieval and SV reformation turn into separable events. This review highlights the progress made in unraveling the molecular mechanisms mediating the high-fidelity retrieval of SV proteins and discusses how the gathered knowledge about SV protein recycling fits in with the new notions of SV membrane endocytosis. PMID:29085282

A privacy-preserving solution for compressed storage and selective retrieval of genomic data.

PubMed

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S; Molyneaux, Adam; Xu, Zhenyu; Fellay, Jacques; Steinmetz, Lars M; Hubaux, Jean-Pierre

2016-12-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. © 2016 Huang et al.; Published by Cold Spring Harbor Laboratory Press.

The influence of prior knowledge on the retrieval-directed function of note taking in prior knowledge activation.

PubMed

Wetzels, Sandra A J; Kester, Liesbeth; van Merriënboer, Jeroen J G; Broers, Nick J

2011-06-01

Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in supporting prior knowledge activation if available prior knowledge is limited. This study investigates the effects of the retrieval-directed function of note taking depending on learners' level of prior knowledge. It is hypothesized that the effectiveness of note taking is influenced by the amount of prior knowledge learners already possess. Sixty-one high school students participated in this study. A prior knowledge test was used to ascertain differences in level of prior knowledge and assign participants to a low or a high prior knowledge group. A 2×2 factorial design was used to investigate the effects of note taking during prior knowledge activation (yes, no) depending on learners' level of prior knowledge (low, high) on mental effort, performance, and mental efficiency. Note taking during prior knowledge activation lowered mental effort and increased mental efficiency for high prior knowledge learners. For low prior knowledge learners, note taking had the opposite effect on mental effort and mental efficiency. The effects of the retrieval-directed function of note taking are influenced by learners' level of prior knowledge. Learners with high prior knowledge benefit from taking notes while activating prior knowledge, whereas note taking has no beneficial effects for learners with limited prior knowledge. ©2010 The British Psychological Society.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data

PubMed Central

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S.; Molyneaux, Adam; Xu, Zhenyu; Hubaux, Jean-Pierre

2016-01-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients’ complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. PMID:27789525

Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

PubMed

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-10-01

A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

Learning Short Binary Codes for Large-scale Image Retrieval.

PubMed

Liu, Li; Yu, Mengyang; Shao, Ling

2017-03-01

Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.

FIR: An Effective Scheme for Extracting Useful Metadata from Social Media.

PubMed

Chen, Long-Sheng; Lin, Zue-Cheng; Chang, Jing-Rong

2015-11-01

Recently, the use of social media for health information exchange is expanding among patients, physicians, and other health care professionals. In medical areas, social media allows non-experts to access, interpret, and generate medical information for their own care and the care of others. Researchers paid much attention on social media in medical educations, patient-pharmacist communications, adverse drug reactions detection, impacts of social media on medicine and healthcare, and so on. However, relatively few papers discuss how to extract useful knowledge from a huge amount of textual comments in social media effectively. Therefore, this study aims to propose a Fuzzy adaptive resonance theory network based Information Retrieval (FIR) scheme by combining Fuzzy adaptive resonance theory (ART) network, Latent Semantic Indexing (LSI), and association rules (AR) discovery to extract knowledge from social media. In our FIR scheme, Fuzzy ART network firstly has been employed to segment comments. Next, for each customer segment, we use LSI technique to retrieve important keywords. Then, in order to make the extracted keywords understandable, association rules mining is presented to organize these extracted keywords to build metadata. These extracted useful voices of customers will be transformed into design needs by using Quality Function Deployment (QFD) for further decision making. Unlike conventional information retrieval techniques which acquire too many keywords to get key points, our FIR scheme can extract understandable metadata from social media.

Font adaptive word indexing of modern printed documents.

PubMed

Marinai, Simone; Marino, Emanuele; Soda, Giovanni

2006-08-01

We propose an approach for the word-level indexing of modern printed documents which are difficult to recognize using current OCR engines. By means of word-level indexing, it is possible to retrieve the position of words in a document, enabling queries involving proximity of terms. Web search engines implement this kind of indexing, allowing users to retrieve Web pages on the basis of their textual content. Nowadays, digital libraries hold collections of digitized documents that can be retrieved either by browsing the document images or relying on appropriate metadata assembled by domain experts. Word indexing tools would therefore increase the access to these collections. The proposed system is designed to index homogeneous document collections by automatically adapting to different languages and font styles without relying on OCR engines for character recognition. The approach is based on three main ideas: the use of Self Organizing Maps (SOM) to perform unsupervised character clustering, the definition of one suitable vector-based word representation whose size depends on the word aspect-ratio, and the run-time alignment of the query word with indexed words to deal with broken and touching characters. The most appropriate applications are for processing modern printed documents (17th to 19th centuries) where current OCR engines are less accurate. Our experimental analysis addresses six data sets containing documents ranging from books of the 17th century to contemporary journals.

Improved image retrieval based on fuzzy colour feature vector

NASA Astrophysics Data System (ADS)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Deeply learnt hashing forests for content based image retrieval in prostate MR images

NASA Astrophysics Data System (ADS)

Shah, Amit; Conjeti, Sailesh; Navab, Nassir; Katouzian, Amin

2016-03-01

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.

Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke.

PubMed

Hope, Thomas M H; Leff, Alex P; Prejawa, Susan; Bruce, Rachel; Haigh, Zula; Lim, Louise; Ramsden, Sue; Oberhuber, Marion; Ludersdorfer, Philipp; Crinion, Jenny; Seghier, Mohamed L; Price, Cathy J

2017-06-01

Stroke survivors with acquired language deficits are commonly thought to reach a 'plateau' within a year of stroke onset, after which their residual language skills will remain stable. Nevertheless, there have been reports of patients who appear to recover over years. Here, we analysed longitudinal change in 28 left-hemisphere stroke patients, each more than a year post-stroke when first assessed-testing each patient's spoken object naming skills and acquiring structural brain scans twice. Some of the patients appeared to improve over time while others declined; both directions of change were associated with, and predictable given, structural adaptation in the intact right hemisphere of the brain. Contrary to the prevailing view that these patients' language skills are stable, these results imply that real change continues over years. The strongest brain-behaviour associations (the 'peak clusters') were in the anterior temporal lobe and the precentral gyrus. Using functional magnetic resonance imaging, we confirmed that both regions are actively involved when neurologically normal control subjects name visually presented objects, but neither appeared to be involved when the same participants used a finger press to make semantic association decisions on the same stimuli. This suggests that these regions serve word-retrieval or articulatory functions in the undamaged brain. We teased these interpretations apart by reference to change in other tasks. Consistent with the claim that the real change is occurring here, change in spoken object naming was correlated with change in two other similar tasks, spoken action naming and written object naming, each of which was independently associated with structural adaptation in similar (overlapping) right hemisphere regions. Change in written object naming, which requires word-retrieval but not articulation, was also significantly more correlated with both (i) change in spoken object naming; and (ii) structural adaptation in the two peak clusters, than was change in another task-auditory word repetition-which requires articulation but not word retrieval. This suggests that the changes in spoken object naming reflected variation at the level of word-retrieval processes. Surprisingly, given their qualitatively similar activation profiles, hypertrophy in the anterior temporal region was associated with improving behaviour, while hypertrophy in the precentral gyrus was associated with declining behaviour. We predict that either or both of these regions might be fruitful targets for neural stimulation studies (suppressing the precentral region and/or enhancing the anterior temporal region), aiming to encourage recovery or arrest decline even years after stroke occurs. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke

PubMed Central

Leff, Alex P.; Prejawa, Susan; Bruce, Rachel; Haigh, Zula; Lim, Louise; Ramsden, Sue; Oberhuber, Marion; Ludersdorfer, Philipp; Crinion, Jenny; Seghier, Mohamed L.; Price, Cathy J.

2017-01-01

Abstract Stroke survivors with acquired language deficits are commonly thought to reach a ‘plateau’ within a year of stroke onset, after which their residual language skills will remain stable. Nevertheless, there have been reports of patients who appear to recover over years. Here, we analysed longitudinal change in 28 left-hemisphere stroke patients, each more than a year post-stroke when first assessed—testing each patient’s spoken object naming skills and acquiring structural brain scans twice. Some of the patients appeared to improve over time while others declined; both directions of change were associated with, and predictable given, structural adaptation in the intact right hemisphere of the brain. Contrary to the prevailing view that these patients’ language skills are stable, these results imply that real change continues over years. The strongest brain–behaviour associations (the ‘peak clusters’) were in the anterior temporal lobe and the precentral gyrus. Using functional magnetic resonance imaging, we confirmed that both regions are actively involved when neurologically normal control subjects name visually presented objects, but neither appeared to be involved when the same participants used a finger press to make semantic association decisions on the same stimuli. This suggests that these regions serve word-retrieval or articulatory functions in the undamaged brain. We teased these interpretations apart by reference to change in other tasks. Consistent with the claim that the real change is occurring here, change in spoken object naming was correlated with change in two other similar tasks, spoken action naming and written object naming, each of which was independently associated with structural adaptation in similar (overlapping) right hemisphere regions. Change in written object naming, which requires word-retrieval but not articulation, was also significantly more correlated with both (i) change in spoken object naming; and (ii) structural adaptation in the two peak clusters, than was change in another task—auditory word repetition—which requires articulation but not word retrieval. This suggests that the changes in spoken object naming reflected variation at the level of word-retrieval processes. Surprisingly, given their qualitatively similar activation profiles, hypertrophy in the anterior temporal region was associated with improving behaviour, while hypertrophy in the precentral gyrus was associated with declining behaviour. We predict that either or both of these regions might be fruitful targets for neural stimulation studies (suppressing the precentral region and/or enhancing the anterior temporal region), aiming to encourage recovery or arrest decline even years after stroke occurs. PMID:28444235

A Web Based Approach to Integrate Space Culture and Education

NASA Astrophysics Data System (ADS)

Gerla, F.

2002-01-01

Our intention is to dedicate a large section of our web site to space education. As the national User Support and Operation Center (USOC) for the International Space Station, MARS Center is also willing to provide material, such as videos and data, for educational purposes. In order to base our initiative on authoritative precedents, our first step has been a comparative analysis between different space agency education web sites, such as ESA and NASA. As is well known, Internet is a powerful reality, capable of connecting people all over the world and rendering public a huge amount of information. The first problem, then, is to organize this information, in order to use the web as an efficient education tool. That is why studies such as User Modeling (UM), Human Computer Interaction (HCI) and Semantic Web have become more important in Information Technology and Science. Traditional search engines are unable to provide an optimal retrieval of contents really searched for by users. Semantic Web is a valid alternative: according to its theories, web information should be represented using metadata language. Users should be able and enabled to successfully search, obtain and study new information from web. Forging knowledge in an intelligent manner, preventing users from making errors, and making this formidable quantity of information easily available have also been the starting points for HCI methodologies for defining Adaptable Interfaces. Here the information is divided into different sets, on the basis of the intended user profile, in order to prevent users from getting lost. Realized as an adaptable interface, an education web site can help users to effectively retrieve the information necessary for their scopes (teaching for a teacher and learning for a student). For students it's a great advantage to use interfaces designed on the basis of their age and scholastic level. Indeed, an adaptable interface is intended not just for students, but also for teachers, who can use it to prepare their lessons, retrieve information and organize the didactic material in order to support their lessons. We think it important to use a user centered "psychology" based on UM: we have to know the needs and expectations of the students. Our intent is to use usability tests not just to prove the site effectiveness and clearness, but also to investigate aesthetical preferences of children and young people. Physics, mathematics, chemistry are just some of the difficult learning fields connected with space technologies. Space culture is a potentially never-ending field, and our scope will be to lead students by hand in this universe of knowledge. This paper will present MARS activities in the framework of the above methodologies aimed at implementing a web based approach to integrate space culture and education. The activities are already in progress and some results will be presented in the final paper.

Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

PubMed Central

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-01-01

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. PMID:25225874

Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.

PubMed

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-09-15

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

Enhancing the Retrieval Effectiveness of Large Information Systems. Final Report for the Period 1 June 1975-31 December 1976.

ERIC Educational Resources Information Center

Becker, David S.; Pyrce, Sharon R.

The goal of this project was to find ways of enhancing the efficiency of searching machine readable data bases. Ways are sought to transfer to the computer some of the tasks that are normally performed by the user, i.e., to further automate information retrieval. Four experiments were conducted to test the feasibility of a sequential processing…

Intelligent distributed medical image management

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.

1995-05-01

The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

Use of magnetic polyaniline/maghemite nanocomposite for DNA retrieval from aqueous solutions.

PubMed

Medina-Llamas, Juan Carlos; Chávez-Guajardo, Alicia Elizabeth; Andrade, Cesar Augusto Souza; Alves, Kleber Gonçalves Bezerra; de Melo, Celso Pinto

2014-11-15

We demonstrated that the magnetic polyaniline/maghemite nanocomposite (Pani/γ-Fe2O3 MNC) is an efficient agent for retrieval of pure double stranded deoxyribonucleic acid (dsDNA) chains from aqueous solutions. The dsDNA chains used in the retrieval experiments were of sodium salt of Salmon Sperm DNA. Based on λ=260 nm absorption measurements, we have employed UV-Vis spectroscopy to estimate the concentration of DNA present in solutions, before and after the interaction with the MNC. The best results corresponded to a maximum amount of 75.2 mg of DNA absorbed per gram of MNC reached within only 10 min of joint exposure into the aqueous solution. After magnetic separation of the fully DNA-loaded Pani/γ-Fe2O3 MNC, we achieved essentially complete DNA desorption by appropriate changes in the pH of the solution. We have shown that it is possible to recycle the use of these MNC in several adsorption-desorption cycles. By comparing the present results to those of other DNA retrieval systems reported in the literature, we argued that the Pani/γ-Fe2O3 MNC here described represent a promising low-cost material for use as a fast, simple and efficient method of DNA separation and concentration. Copyright © 2014 Elsevier Inc. All rights reserved.

Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

NASA Astrophysics Data System (ADS)

Aggarwal, Preeti; Sardana, H. K.

2010-02-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

Memory as discrimination: a challenge to the encoding-retrieval match principle.

PubMed

Poirier, Marie; Nairne, James S; Morin, Caroline; Zimmermann, Friederike G S; Koutmeridou, Kyriaki; Fowler, James

2012-01-01

Four experiments contrasted the predictions of a general encoding-retrieval match hypothesis with those of a view claiming that the distinctiveness of the cue-target relationship is the causal factor in retrieval. In Experiments 1, 2, and 4 participants learned the relationships between 4 targets and trios of cues; in Experiment 3 there were 3 targets, each associated with a pair of cues. A learning phase was followed by a cued-recognition task where the correct target had to be identified based on 1 or more of the cues. The main performance measurement was response time. Learning was designed to lead to high accuracy so effects could be attributed to retrieval efficiency rather than to variations in encoding. The nature of the cues and targets was varied across experiments. The critical factor was whether each cue was uniquely associated with the to-be-recalled target. All experiments orthogonally manipulated (a) how discriminative-or uniquely associated with a target-each cue was and (b) the degree of overlap between the cues present during learning and those present at retrieval. The novel finding reported here is that increasing the encoding-retrieval match can hinder performance if the increase simultaneously reduces how well cues predict a target-that is, a cue's diagnostic value. Encoding-retrieval match was not the factor that determined the effectiveness of retrieval. Our findings suggest that increasing the encoding-retrieval match can lead to no change, an increase, or a decrease in retrieval performance.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

Searching and synthesising 'grey literature' and 'grey information' in public health: critical reflections on three case studies.

PubMed

Adams, Jean; Hillier-Brown, Frances C; Moore, Helen J; Lake, Amelia A; Araujo-Soares, Vera; White, Martin; Summerbell, Carolyn

2016-09-29

Grey literature includes a range of documents not controlled by commercial publishing organisations. This means that grey literature can be difficult to search and retrieve for evidence synthesis. Much knowledge and evidence in public health, and other fields, accumulates from innovation in practice. This knowledge may not even be of sufficient formality to meet the definition of grey literature. We term this knowledge 'grey information'. Grey information may be even harder to search for and retrieve than grey literature. On three previous occasions, we have attempted to systematically search for and synthesise public health grey literature and information-both to summarise the extent and nature of particular classes of interventions and to synthesise results of evaluations. Here, we briefly describe these three 'case studies' but focus on our post hoc critical reflections on searching for and synthesising grey literature and information garnered from our experiences of these case studies. We believe these reflections will be useful to future researchers working in this area. Issues discussed include search methods, searching efficiency, replicability of searches, data management, data extraction, assessing study 'quality', data synthesis, time and resources, and differentiating evidence synthesis from primary research. Information on applied public health research questions relating to the nature and range of public health interventions, as well as many evaluations of these interventions, may be predominantly, or only, held in grey literature and grey information. Evidence syntheses on these topics need, therefore, to embrace grey literature and information. Many typical systematic review methods for searching, appraising, managing, and synthesising the evidence base can be adapted for use with grey literature and information. Evidence synthesisers should carefully consider the opportunities and problems offered by including grey literature and information. Enhanced incentives for accurate recording and further methodological developments in retrieval will facilitate future syntheses of grey literature and information.

Enhancing navigation in biomedical databases by community voting and database-driven text classification

PubMed Central

Duchrow, Timo; Shtatland, Timur; Guettler, Daniel; Pivovarov, Misha; Kramer, Stefan; Weissleder, Ralph

2009-01-01

Background The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal. Here, we introduce and apply community voting, database-driven text classification, and visual aids as a means to incorporate distributed expert knowledge, to automatically classify database entries and to efficiently retrieve them. Results Using a previously developed peptide database as an example, we compared several machine learning algorithms in their ability to classify abstracts of published literature results into categories relevant to peptide research, such as related or not related to cancer, angiogenesis, molecular imaging, etc. Ensembles of bagged decision trees met the requirements of our application best. No other algorithm consistently performed better in comparative testing. Moreover, we show that the algorithm produces meaningful class probability estimates, which can be used to visualize the confidence of automatic classification during the retrieval process. To allow viewing long lists of search results enriched by automatic classifications, we added a dynamic heat map to the web interface. We take advantage of community knowledge by enabling users to cast votes in Web 2.0 style in order to correct automated classification errors, which triggers reclassification of all entries. We used a novel framework in which the database "drives" the entire vote aggregation and reclassification process to increase speed while conserving computational resources and keeping the method scalable. In our experiments, we simulate community voting by adding various levels of noise to nearly perfectly labelled instances, and show that, under such conditions, classification can be improved significantly. Conclusion Using PepBank as a model database, we show how to build a classification-aided retrieval system that gathers training data from the community, is completely controlled by the database, scales well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases. The system can be accessed at . PMID:19799796

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Experiments on sparsity assisted phase retrieval of phase objects

NASA Astrophysics Data System (ADS)

Gaur, Charu; Lochab, Priyanka; Khare, Kedar

2017-05-01

Iterative phase retrieval algorithms such as the Gerchberg-Saxton method and the Fienup hybrid input-output method are known to suffer from the twin image stagnation problem, particularly when the solution to be recovered is complex valued and has centrosymmetric support. Recently we showed that the twin image stagnation problem can be addressed using image sparsity ideas (Gaur et al 2015 J. Opt. Soc. Am. A 32 1922). In this work we test this sparsity assisted phase retrieval method with experimental single shot Fourier transform intensity data frames corresponding to phase objects displayed on a spatial light modulator. The standard iterative phase retrieval algorithms are combined with an image sparsity based penalty in an adaptive manner. Illustrations for both binary and continuous phase objects are provided. It is observed that image sparsity constraint has an important role to play in obtaining meaningful phase recovery without encountering the well-known stagnation problems. The results are valuable for enabling single shot coherent diffraction imaging of phase objects for applications involving illumination wavelengths over a wide range of electromagnetic spectrum.

Efficient packing of patterns in sparse distributed memory by selective weighting of input bits

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1991-01-01

When a set of patterns is stored in a distributed memory, any given storage location participates in the storage of many patterns. From the perspective of any one stored pattern, the other patterns act as noise, and such noise limits the memory's storage capacity. The more similar the retrieval cues for two patterns are, the more the patterns interfere with each other in memory, and the harder it is to separate them on retrieval. A method is described of weighting the retrieval cues to reduce such interference and thus to improve the separability of patterns that have similar cues.

Concept locator: a client-server application for retrieval of UMLS metathesaurus concepts through complex boolean query.

PubMed

Nadkarni, P M

1997-08-01

Concept Locator (CL) is a client-server application that accesses a Sybase relational database server containing a subset of the UMLS Metathesaurus for the purpose of retrieval of concepts corresponding to one or more query expressions supplied to it. CL's query grammar permits complex Boolean expressions, wildcard patterns, and parenthesized (nested) subexpressions. CL translates the query expressions supplied to it into one or more SQL statements that actually perform the retrieval. The generated SQL is optimized by the client to take advantage of the strengths of the server's query optimizer, and sidesteps its weaknesses, so that execution is reasonably efficient.

A novel composite adaptive flap controller design by a high-efficient modified differential evolution identification approach.

PubMed

Li, Nailu; Mu, Anle; Yang, Xiyun; Magar, Kaman T; Liu, Chao

2018-05-01

The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A passage retrieval method based on probabilistic information retrieval model and UMLS concepts in biomedical question answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-04-01

Passage retrieval, the identification of top-ranked passages that may contain the answer for a given biomedical question, is a crucial component for any biomedical question answering (QA) system. Passage retrieval in open-domain QA is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in biomedical QA. In this paper, we present a new biomedical passage retrieval method based on Stanford CoreNLP sentence/passage length, probabilistic information retrieval (IR) model and UMLS concepts. In the proposed method, we first use our document retrieval system based on PubMed search engine and UMLS similarity to retrieve relevant documents to a given biomedical question. We then take the abstracts from the retrieved documents and use Stanford CoreNLP for sentence splitter to make a set of sentences, i.e., candidate passages. Using stemmed words and UMLS concepts as features for the BM25 model, we finally compute the similarity scores between the biomedical question and each of the candidate passages and keep the N top-ranked ones. Experimental evaluations performed on large standard datasets, provided by the BioASQ challenge, show that the proposed method achieves good performances compared with the current state-of-the-art methods. The proposed method significantly outperforms the current state-of-the-art methods by an average of 6.84% in terms of mean average precision (MAP). We have proposed an efficient passage retrieval method which can be used to retrieve relevant passages in biomedical QA systems with high mean average precision. Copyright © 2017 Elsevier Inc. All rights reserved.

Retrieval and management of medical information from heterogeneous sources, for its integration in a medical record visualisation tool.

PubMed

Cabarcos, Alba; Sanchez, Tamara; Seoane, Jose A; Aguiar-Pulido, Vanessa; Freire, Ana; Dorado, Julian; Pazos, Alejandro

2010-01-01

Nowadays, medical practice needs, at the patient Point-of-Care (POC), personalised knowledge adjustable in each moment to the clinical needs of each patient, in order to provide support to decision-making processes, taking into account personalised information. To achieve this, adapting the hospital information systems is necessary. Thus, there is a need of computational developments capable of retrieving and integrating the large amount of biomedical information available today, managing the complexity and diversity of these systems. Hence, this paper describes a prototype which retrieves biomedical information from different sources, manages it to improve the results obtained and to reduce response time and, finally, integrates it so that it is useful for the clinician, providing all the information available about the patient at the POC. Moreover, it also uses tools which allow medical staff to communicate and share knowledge.

Tagging motor memories with transcranial direct current stimulation allows later artificially-controlled retrieval

PubMed Central

Nozaki, Daichi; Yokoi, Atsushi; Kimura, Takahiro; Hirashima, Masaya; Orban de Xivry, Jean-Jacques

2016-01-01

We demonstrate that human motor memories can be artificially tagged and later retrieved by noninvasive transcranial direct current stimulation (tDCS). Participants learned to adapt reaching movements to two conflicting dynamical environments that were each associated with a different tDCS polarity (anodal or cathodal tDCS) on the sensorimotor cortex. That is, we sought to determine whether divergent background activity levels within the sensorimotor cortex (anodal: higher activity; cathodal: lower activity) give rise to distinct motor memories. After a training session, application of each tDCS polarity automatically resulted in the retrieval of the motor memory corresponding to that polarity. These results reveal that artificial modulation of neural activity in the sensorimotor cortex through tDCS can act as a context for the formation and recollection of motor memories. DOI: http://dx.doi.org/10.7554/eLife.15378.001 PMID:27472899

Adaptive Visualization for Focused Personalized Information Retrieval

ERIC Educational Resources Information Center

Ahn, Jae-wook

2010-01-01

The new trend on the Web has totally changed today's information access environment. The traditional information overload problem has evolved into the qualitative level beyond the quantitative growth. The mode of producing and consuming information is changing and we need a new paradigm for accessing information. Personalized search is one of…

Trait-Treatment Interactions (TTI), Cognitive Processes and Research on Communication Media.

ERIC Educational Resources Information Center

Di Vesta, Francis J.

The Trait Treatment Interaction (TTI) Process approach is particularly adapted to the study of information-processing by receivers of information presented in the media. Differences in people's experiences do lead to different cognitive structures. Different people use the same machinery of perceiving, coding, storing, and retrieving. Neverthless,…

Nonbibliographic Applications of Z39.50.

ERIC Educational Resources Information Center

Kunze, John A.

1992-01-01

Describes the use of the Z39.50 information retrieval protocol as the basis for Infocal, a read-only, client/server-based campus information system. Technical considerations in adapting the protocol to nonbibliographic data, including semantic modules, dynamic attribute sets, and dynamic record syntax, are described in detail. (Contains 11…

Improvement of OMI Ozone Profile Retrievals in the Troposphere and Lower Troposphere by the Use of the Tropopause-Based Ozone Profile Climatology

NASA Technical Reports Server (NTRS)

Bak, Juseon; Liu, X.; Wei, J.; Kim, J. H.; Chance, K.; Barnet, C.

2011-01-01

An advance algorithm based on the optimal estimation technique has beeen developed to derive ozone profile from GOME UV radiances and have adapted it to OMI UV radiances. OMI vertical resolution : 7-11 km in the troposphere and 10-14 km in the stratosphere. Satellite ultraviolet measurements (GOME, OMI) contain little vertical information for the small scale of ozone, especially in the upper troposphere (UT) and lower stratosphere (LS) where the sharp O3 gradient across the tropopause and large ozone variability are observed. Therefore, retrievals depend greatly on the a-priori knowledge in the UTLS

Coastal and Marine Bird Data Base

USGS Publications Warehouse

Anderson, S.H.; Geissler, P.H.; Dawson, D.K.

1980-01-01

Summary: This report discusses the development of a coastal and marine bird data base at the Migratory Bird and Habitat Research Laboratory. The system is compared with other data bases, and suggestions for future development, such as possible adaptations for other taxonomic groups, are included. The data base is based on the Statistical Analysis System but includes extensions programmed in PL/I. The Appendix shows how the system evolved. Output examples are given for heron data and pelagic bird data which indicate the types of analyses that can be conducted and output figures. The Appendixes include a retrieval language user's guide and description of the retrieval process and listing of translator program.

Post-weaning feed efficiency of tropically adapted purebred and crossbred calves when fed in either winter or spring

USDA-ARS?s Scientific Manuscript database

Earlier work has shown that young, tropically adapted (Brahman and Romosinuano) cattle do not gain as rapidly as temperately adapted (Angus) cattle during the winter in OK. The objective for this study was as to compare efficiency of gains between tropically- and temperately-adapted cattle breeds. O...

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Fast, axis-agnostic, dynamically summarized storage and retrieval for mass spectrometry data.

PubMed

Handy, Kyle; Rosen, Jebediah; Gillan, André; Smith, Rob

2017-01-01

Mass spectrometry, a popular technique for elucidating the molecular contents of experimental samples, creates data sets comprised of millions of three-dimensional (m/z, retention time, intensity) data points that correspond to the types and quantities of analyzed molecules. Open and commercial MS data formats are arranged by retention time, creating latency when accessing data across multiple m/z. Existing MS storage and retrieval methods have been developed to overcome the limitations of retention time-based data formats, but do not provide certain features such as dynamic summarization and storage and retrieval of point meta-data (such as signal cluster membership), precluding efficient viewing applications and certain data-processing approaches. This manuscript describes MzTree, a spatial database designed to provide real-time storage and retrieval of dynamically summarized standard and augmented MS data with fast performance in both m/z and RT directions. Performance is reported on real data with comparisons against related published retrieval systems.

Flexible retrieval: When true inferences produce false memories.

PubMed

Carpenter, Alexis C; Schacter, Daniel L

2017-03-01

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether (a) false memories increased for successful versus unsuccessful inferences, and (b) any such effects were specific to after compared with before participants received the inference test. In each of 4 experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Characterizing region of interest in image using MPEG-7 visual descriptors

NASA Astrophysics Data System (ADS)

Ryu, Min-Sung; Park, Soo-Jun; Won, Chee Sun

2005-08-01

In this paper, we propose a region-based image retrieval system using EHD (Edge Histogram Descriptor) and CLD (Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., 4x4) non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between EHD and CLD, we need to take an 8x8 inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists

PubMed Central

Wiley, Laura K.; Sivley, R. Michael; Bush, William S.

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist PMID:23894185

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

PubMed

Wiley, Laura K; Sivley, R Michael; Bush, William S

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

Semantic Segmentation of Forest Stands of Pure Species as a Global Optimization Problem

NASA Astrophysics Data System (ADS)

Dechesne, C.; Mallet, C.; Le Bris, A.; Gouet-Brunet, V.

2017-05-01

Forest stand delineation is a fundamental task for forest management purposes, that is still mainly manually performed through visual inspection of geospatial (very) high spatial resolution images. Stand detection has been barely addressed in the literature which has mainly focused, in forested environments, on individual tree extraction and tree species classification. From a methodological point of view, stand detection can be considered as a semantic segmentation problem. It offers two advantages. First, one can retrieve the dominant tree species per segment. Secondly, one can benefit from existing low-level tree species label maps from the literature as a basis for high-level object extraction. Thus, the semantic segmentation issue becomes a regularization issue in a weakly structured environment and can be formulated in an energetical framework. This papers aims at investigating which regularization strategies of the literature are the most adapted to delineate and classify forest stands of pure species. Both airborne lidar point clouds and multispectral very high spatial resolution images are integrated for that purpose. The local methods (such as filtering and probabilistic relaxation) are not adapted for such problem since the increase of the classification accuracy is below 5%. The global methods, based on an energy model, tend to be more efficient with an accuracy gain up to 15%. The segmentation results using such models have an accuracy ranging from 96% to 99%.

Spatial Query for Planetary Data

NASA Technical Reports Server (NTRS)

Shams, Khawaja S.; Crockett, Thomas M.; Powell, Mark W.; Joswig, Joseph C.; Fox, Jason M.

2011-01-01

Science investigators need to quickly and effectively assess past observations of specific locations on a planetary surface. This innovation involves a location-based search technology that was adapted and applied to planetary science data to support a spatial query capability for mission operations software. High-performance location-based searching requires the use of spatial data structures for database organization. Spatial data structures are designed to organize datasets based on their coordinates in a way that is optimized for location-based retrieval. The particular spatial data structure that was adapted for planetary data search is the R+ tree.

Information retrieval for systematic reviews in food and feed topics: A narrative review.

PubMed

Wood, Hannah; O'Connor, Annette; Sargeant, Jan; Glanville, Julie

2018-01-09

Systematic review methods are now being used for reviews of food production, food safety and security, plant health, and animal health and welfare. Information retrieval methods in this context have been informed by human health-care approaches and ideally should be based on relevant research and experience. This narrative review seeks to identify and summarize current research-based evidence and experience on information retrieval for systematic reviews in food and feed topics. MEDLINE (Ovid), Science Citation Index (Web of Science), and ScienceDirect (http://www.sciencedirect.com/) were searched in 2012 and 2016. We also contacted topic experts and undertook citation searches. We selected and summarized studies reporting research on information retrieval, as well as published guidance and experience. There is little published evidence on the most efficient way to conduct searches for food and feed topics. There are few available study design search filters, and their use may be problematic given poor or inconsistent reporting of study methods. Food and feed research makes use of a wide range of study designs so it might be best to focus strategy development on capturing study populations, although this also has challenges. There is limited guidance on which resources should be searched and whether publication bias in disciplines relevant to food and feed necessitates extensive searching of the gray literature. There is some limited evidence on information retrieval approaches, but more research is required to inform effective and efficient approaches to searching to populate food and feed reviews. Copyright © 2018 John Wiley & Sons, Ltd.

The effects of aging on ERP correlates of source memory retrieval for self-referential information.

PubMed

Dulas, Michael R; Newsome, Rachel N; Duarte, Audrey

2011-03-04

Numerous behavioral studies have suggested that normal aging negatively affects source memory accuracy for various kinds of associations. Neuroimaging evidence suggests that less efficient retrieval processing (temporally delayed and attenuated) may contribute to these impairments. Previous aging studies have not compared source memory accuracy and corresponding neural activity for different kinds of source details; namely, those that have been encoded via a more or less effective strategy. Thus, it is not yet known whether encoding source details in a self-referential manner, a strategy suggested to promote successful memory in the young and old, may enhance source memory accuracy and reduce the commonly observed age-related changes in neural activity associated with source memory retrieval. Here, we investigated these issues by using event-related potentials (ERPs) to measure the effects of aging on the neural correlates of successful source memory retrieval ("old-new effects") for objects encoded either self-referentially or self-externally. Behavioral results showed that both young and older adults demonstrated better source memory accuracy for objects encoded self-referentially. ERP results showed that old-new effects onsetted earlier for self-referentially encoded items in both groups and that age-related differences in the onset latency of these effects were reduced for self-referentially, compared to self-externally, encoded items. These results suggest that the implementation of an effective encoding strategy, like self-referential processing, may lead to more efficient retrieval, which in turn may improve source memory accuracy in both young and older adults. Published by Elsevier B.V.

Traffic-Adaptive, Flow-Specific Medium Access for Wireless Networks

DTIC Science & Technology

2009-09-01

hybrid, contention and non-contention schemes are shown to be special cases. This work also compares the energy efficiency of centralized and distributed...solutions and proposes an energy efficient version of traffic-adaptive CWS-MAC that includes an adaptive sleep cycle coordinated through the use of...preamble sampling. A preamble sampling probability parameter is introduced to manage the trade-off between energy efficiency and throughput and delay

Optimal Embedding for Shape Indexing in Medical Image Databases

PubMed Central

Qian, Xiaoning; Tagare, Hemant D.; Fulbright, Robert K.; Long, Rodney; Antani, Sameer

2010-01-01

This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine x-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape-similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. PMID:20163981

Optimal embedding for shape indexing in medical image databases.

PubMed

Qian, Xiaoning; Tagare, Hemant D; Fulbright, Robert K; Long, Rodney; Antani, Sameer

2010-06-01

This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine X-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A Graph Theoretical Approach to Study the Organization of the Cortical Networks during Different Mathematical Tasks

PubMed Central

Klados, Manousos A.; Kanatsouli, Kassia; Antoniou, Ioannis; Babiloni, Fabio; Tsirka, Vassiliki; Bamidis, Panagiotis D.; Micheloyannis, Sifis

2013-01-01

The two core systems of mathematical processing (subitizing and retrieval) as well as their functionality are already known and published. In this study we have used graph theory to compare the brain network organization of these two core systems in the cortical layer during difficult calculations. We have examined separately all the EEG frequency bands in healthy young individuals and we found that the network organization at rest, as well as during mathematical tasks has the characteristics of Small World Networks for all the bands, which is the optimum organization required for efficient information processing. The different mathematical stimuli provoked changes in the graph parameters of different frequency bands, especially the low frequency bands. More specific, in Delta band the induced network increases it’s local and global efficiency during the transition from subitizing to retrieval system, while results suggest that difficult mathematics provoke networks with higher cliquish organization due to more specific demands. The network of the Theta band follows the same pattern as before, having high nodal and remote organization during difficult mathematics. Also the spatial distribution of the network’s weights revealed more prominent connections in frontoparietal regions, revealing the working memory load due to the engagement of the retrieval system. The cortical networks of the alpha brainwaves were also more efficient, both locally and globally, during difficult mathematics, while the fact that alpha’s network was more dense on the frontparietal regions as well, reveals the engagement of the retrieval system again. Concluding, this study gives more evidences regarding the interaction of the two core systems, exploiting the produced functional networks of the cerebral cortex, especially for the difficult mathematics. PMID:23990992

Impact of PubMed search filters on the retrieval of evidence by physicians.

PubMed

Shariff, Salimah Z; Sontrop, Jessica M; Haynes, R Brian; Iansavichus, Arthur V; McKibbon, K Ann; Wilczynski, Nancy L; Weir, Matthew A; Speechley, Mark R; Thind, Amardeep; Garg, Amit X

2012-02-21

Physicians face challenges when searching PubMed for research evidence, and they may miss relevant articles while retrieving too many nonrelevant articles. We investigated whether the use of search filters in PubMed improves searching by physicians. We asked a random sample of Canadian nephrologists to answer unique clinical questions derived from 100 systematic reviews of renal therapy. Physicians provided the search terms that they would type into PubMed to locate articles to answer these questions. We entered the physician-provided search terms into PubMed and applied two types of search filters alone or in combination: a methods-based filter designed to identify high-quality studies about treatment (clinical queries "therapy") and a topic-based filter designed to identify studies with renal content. We evaluated the comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to nonrelevant articles) of the filtered and nonfiltered searches. Primary studies included in the systematic reviews served as the reference standard for relevant articles. The average physician-provided search terms retrieved 46% of the relevant articles, while 6% of the retrieved articles were relevant (corrected) (the ratio of relevant to nonrelevant articles was 1:16). The use of both filters together produced a marked improvement in efficiency, resulting in a ratio of relevant to nonrelevant articles of 1:5 (16 percentage point improvement; 99% confidence interval 9% to 22%; p < 0.003) with no substantive change in comprehensiveness (44% of relevant articles found; p = 0.55). The use of PubMed search filters improves the efficiency of physician searches. Improved search performance may enhance the transfer of research into practice and improve patient care.

A Graph theoretical approach to study the organization of the cortical networks during different mathematical tasks.

PubMed

Klados, Manousos A; Kanatsouli, Kassia; Antoniou, Ioannis; Babiloni, Fabio; Tsirka, Vassiliki; Bamidis, Panagiotis D; Micheloyannis, Sifis

2013-01-01

The two core systems of mathematical processing (subitizing and retrieval) as well as their functionality are already known and published. In this study we have used graph theory to compare the brain network organization of these two core systems in the cortical layer during difficult calculations. We have examined separately all the EEG frequency bands in healthy young individuals and we found that the network organization at rest, as well as during mathematical tasks has the characteristics of Small World Networks for all the bands, which is the optimum organization required for efficient information processing. The different mathematical stimuli provoked changes in the graph parameters of different frequency bands, especially the low frequency bands. More specific, in Delta band the induced network increases it's local and global efficiency during the transition from subitizing to retrieval system, while results suggest that difficult mathematics provoke networks with higher cliquish organization due to more specific demands. The network of the Theta band follows the same pattern as before, having high nodal and remote organization during difficult mathematics. Also the spatial distribution of the network's weights revealed more prominent connections in frontoparietal regions, revealing the working memory load due to the engagement of the retrieval system. The cortical networks of the alpha brainwaves were also more efficient, both locally and globally, during difficult mathematics, while the fact that alpha's network was more dense on the frontparietal regions as well, reveals the engagement of the retrieval system again. Concluding, this study gives more evidences regarding the interaction of the two core systems, exploiting the produced functional networks of the cerebral cortex, especially for the difficult mathematics.

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

Phase retrieval with the reverse projection method in the presence of object's scattering

NASA Astrophysics Data System (ADS)

Wang, Zhili; Gao, Kun; Wang, Dajiang

2017-08-01

X-ray grating interferometry can provide substantially increased contrast over traditional attenuation-based techniques in biomedical applications, and therefore novel and complementary information. Recently, special attention has been paid to quantitative phase retrieval in X-ray grating interferometry, which is mandatory to perform phase tomography, to achieve material identification, etc. An innovative approach, dubbed ;Reverse Projection; (RP), has been developed for quantitative phase retrieval. The RP method abandons grating scanning completely, and is thus advantageous in terms of higher efficiency and reduced radiation damage. Therefore, it is expected that this novel method would find its potential in preclinical and clinical implementations. Strictly speaking, the reverse projection method is applicable for objects exhibiting only absorption and refraction. In this contribution, we discuss the phase retrieval with the reverse projection method for general objects with absorption, refraction and scattering simultaneously. Especially, we investigate the influence of the object's scattering on the retrieved refraction signal. Both theoretical analysis and numerical experiments are performed. The results show that the retrieved refraction signal is the product of object's refraction and scattering signals for small values. In the case of a strong scattering, the reverse projection method cannot provide reliable phase retrieval. Those presented results will guide the use of the reverse projection method for future practical applications, and help to explain some possible artifacts in the retrieved images and/or reconstructed slices.

Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses

PubMed Central

Baddeley, Michelle; Tobler, Philippe N.; Schultz, Wolfram

2016-01-01

Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. SIGNIFICANCE STATEMENT Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise representation (e.g., when the avoidance of a loss in a loss-context is coded the same as receipt of a gain in a gain-context). We investigated an intermediate form of adaptation that is efficient while maintaining information about received gains and avoided losses. We found that frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Importantly, adaptation was intermediate, in line with influential models of reference dependence in behavioral economics. PMID:27683899

How I do it: a practical database management system to assist clinical research teams with data collection, organization, and reporting.

PubMed

Lee, Howard; Chapiro, Julius; Schernthaner, Rüdiger; Duran, Rafael; Wang, Zhijun; Gorodetski, Boris; Geschwind, Jean-François; Lin, MingDe

2015-04-01

The objective of this study was to demonstrate that an intra-arterial liver therapy clinical research database system is a more workflow efficient and robust tool for clinical research than a spreadsheet storage system. The database system could be used to generate clinical research study populations easily with custom search and retrieval criteria. A questionnaire was designed and distributed to 21 board-certified radiologists to assess current data storage problems and clinician reception to a database management system. Based on the questionnaire findings, a customized database and user interface system were created to perform automatic calculations of clinical scores including staging systems such as the Child-Pugh and Barcelona Clinic Liver Cancer, and facilitates data input and output. Questionnaire participants were favorable to a database system. The interface retrieved study-relevant data accurately and effectively. The database effectively produced easy-to-read study-specific patient populations with custom-defined inclusion/exclusion criteria. The database management system is workflow efficient and robust in retrieving, storing, and analyzing data. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2017-08-01

Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3-5%.

Emotional memory retrieval. rTMS stimulation on left DLPFC increases the positive memories.

PubMed

Balconi, Michela; Ferrari, Chiara

2012-09-01

A suggestive hypothesis proposed that the lateral prefrontal cortex (LPFC) may be identified as the site of emotion-memory integration, since it was shown to be sensitive to the encoding and retrieval of emotional content. In the present research we explored the role of the dorsolateral prefrontal cortex (DLPFC) in memory retrieval of positive vs. negative emotional stimuli. This effect was analyzed by using an rTMS paradigm that induced a cortical activation of the left DLPFC. Subjects were required to perform a task consisting of two experimental phases: an encoding phase, where some lists composed by positive and negative emotional words were presented to the subjects; a retrieval phase, where the old stimuli and the new stimuli were presented for a recognition performance. The rTMS stimulation was provided during the retrieval phase over the left DLPFC. We found that the rTMS stimulation over this area affects the memory retrieval of positive emotional material, with higher memory efficiency (reduced RTs). This result suggested that left DLPFC activation promotes the memory retrieval of emotional information. Secondly, the valence model of emotional cue processing may explain decreasing of RTs, by pointing out the distinct role the left hemisphere has in positive emotional cue processing.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Phase structure rewrite systems in information retrieval

NASA Technical Reports Server (NTRS)

Klingbiel, P. H.

1985-01-01

Operational level automatic indexing requires an efficient means of normalizing natural language phrases. Subject switching requires an efficient means of translating one set of authorized terms to another. A phrase structure rewrite system called a Lexical Dictionary is explained that performs these functions. Background, operational use, other applications and ongoing research are explained.

Going "Netless"

ERIC Educational Resources Information Center

Taylor, Elien

2005-01-01

The reliability on technology through the use of electricity is discussed. However, one should be cautious to regain information if the electricity goes off, and must have efficient methods of information retrieval.

On Seeing Black Literature through Brown and Blue Eyes: Teaching African American Literature in Racially Mixed Classes.

ERIC Educational Resources Information Center

McLaughlin, Margaret A.

Educators at Georgia Southern University began using a whole language approach to developmental literacy instruction by adapting the model David Bartholomae and Anthony Petrosky provide in "Facts, Artifacts, and Counterfacts." Rather than a focus on information retrieval and transfer, whole language curricula encourage students to engage…

Using multi-satellite data fusion to estimate daily high spatial resolution evapotranspiration over a forested site in North Carolina

USDA-ARS?s Scientific Manuscript database

Atmosphere-Land Exchange Inverse model and associated disaggregation scheme (ALEXI/DisALEXI). Satellite-based ET retrievals from both the Moderate Resolution Imaging Spectoradiometer (MODIS; 1km, daily) and Landsat (30m, bi-weekly) are fused with The Spatial and Temporal Adaptive Reflective Fusion ...

Memory recall and spike-frequency adaptation

NASA Astrophysics Data System (ADS)

Roach, James P.; Sander, Leonard M.; Zochowski, Michal R.

2016-05-01

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored patterns that contain the memory. However, it is unclear how the behavior is controlled by the brain so that after convergence to one configuration, it can proceed with recognition of another one. In the Hopfield model, this happens only through unrealistic changes of an effective global temperature that destabilizes all stored configurations. Here we show that spike-frequency adaptation (SFA), a common mechanism affecting neuron activation in the brain, can provide state-dependent control of pattern retrieval. We demonstrate this in a Hopfield network modified to include SFA, and also in a model network of biophysical neurons. In both cases, SFA allows for selective stabilization of attractors with different basins of attraction, and also for temporal dynamics of attractor switching that is not possible in standard autoassociative schemes. The dynamics of our models give a plausible account of different sorts of memory retrieval.

A novel stone retrieval basket for more efficient lithotripsy procedures.

PubMed

Salimi, N; Mahajan, A; Don, J; Schwartz, B

2009-01-01

This paper presents the development of an improved stone retrieval device that uses a newly designed cage of Nitinol wires encompassing a mesh basket made of a material that is laser resistant. Current methods to extract large stones involve imaging, using a laser to fragment the stones and then using existing cage-like baskets to trap the fragments individually and extracting them one at a time. These procedures are tedious, and may result in leaving some fragments behind that can reform causing the need for another procedure. The device presented in this paper will have a mesh-like sack which will consist of a laser resistant material of polytetrafluoroethylene (PTFE) enclosed within a newly designed Nitinol cage. Two alternate designs are provided for the cage in this paper. The handle of the device is revised to allow for a 3 Fr (1 mm) opening such that a laser's fiber optic cable can enter the device. Using this device a laser can be used to fragment the stone, and all the fragments are retained in the basket in both the design options. The basket can then be retracted allowing for the retrieval of all the fragments in one shot. The stone retrieval basket presented in this paper will significantly improve the efficiency and effectiveness of lithotripsy procedures for removal of large kidney and biliary tract stones.

Serum hCG Levels following the Ovulatory Injection: Associations with Patient Weight and Implantation Time

PubMed Central

Noorhasan, Dorette J.; McGovern, Peter G.; Cho, Michael; Seungdamrong, Aimee; Ahmad, Khaliq; McCulloh, David H.

2015-01-01

Objective. To test if serum hCG levels the morning after the ovulatory hCG injection correlate with (1) retrieval efficiency, (2) oocyte maturity, (3) embryo quality, (4) pregnancy, and/or (5) time to implantation in patients undergoing in vitro fertilization (IVF) with intracytoplasmic sperm injection (ICSI). Design. Retrospective cohort analysis. Setting. University-based IVF clinic. Patient(s). All IVF/ICSI cycles from April 2005 to February 2008 whose hCG administration was confirmed (n = 472 patients). Intervention(s). Serum hCG was measured the morning following the ovulatory injection, on the 16th day following retrieval, and repeated on day 18 for those with positive results. Main Outcome Measure(s). Number of follicles on the day of hCG injection, number of oocytes retrieved, maturity of oocytes, embryo quality, pregnancy outcome, and time to implantation. Result(s). hCG levels did not correlate with retrieval efficiency, oocyte maturity, embryo quality, or pregnancy. Postinjection hCG levels were inversely associated with patient weight and time to implantation. Conclusion(s). No correlation was found between hCG level and any parameter of embryo quality. Patient weight affected hCG levels following hCG injection and during the early period of pregnancy following implantation. No association between postinjection hCG level and time of implantation (adjusted for patient weight) was apparent. PMID:26587025

Measuring and Predicting Tag Importance for Image Retrieval.

PubMed

Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

2017-12-01

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

Multi-clues image retrieval based on improved color invariants

NASA Astrophysics Data System (ADS)

Liu, Liu; Li, Jian-Xun

2012-05-01

At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

PubMed

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.

PubMed

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.

Evolution of Self-Organized Task Specialization in Robot Swarms

PubMed Central

Ferrante, Eliseo; Turgut, Ali Emre; Duéñez-Guzmán, Edgar; Dorigo, Marco; Wenseleers, Tom

2015-01-01

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization. PMID:26247819

Evolution of Self-Organized Task Specialization in Robot Swarms.

PubMed

Ferrante, Eliseo; Turgut, Ali Emre; Duéñez-Guzmán, Edgar; Dorigo, Marco; Wenseleers, Tom

2015-08-01

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as "task partitioning", whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.

Central Satellite Data Repository Supporting Research and Development

NASA Astrophysics Data System (ADS)

Han, W.; Brust, J.

2015-12-01

Near real-time satellite data is critical to many research and development activities of atmosphere, land, and ocean processes. Acquiring and managing huge volumes of satellite data without (or with less) latency in an organization is always a challenge in the big data age. An organization level data repository is a practical solution to meeting this challenge. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a scalable, stable, and reliable repository to acquire, manipulate, and disseminate various types of satellite data in an effective and efficient manner. SCDR collects more than 200 data products, which are commonly used by multiple groups in STAR, from NOAA, GOES, Metop, Suomi NPP, Sentinel, Himawari, and other satellites. The processes of acquisition, recording, retrieval, organization, and dissemination are performed in parallel. Multiple data access interfaces, like FTP, FTPS, HTTP, HTTPS, and RESTful, are supported in the SCDR to obtain satellite data from their providers through high speed internet. The original satellite data in various raster formats can be parsed in the respective adapter to retrieve data information. The data information is ingested to the corresponding partitioned tables in the central database. All files are distributed equally on the Network File System (NFS) disks to balance the disk load. SCDR provides consistent interfaces (including Perl utility, portal, and RESTful Web service) to locate files of interest easily and quickly and access them directly by over 200 compute servers via NFS. SCDR greatly improves collection and integration of near real-time satellite data, addresses satellite data requirements of scientists and researchers, and facilitates their primary research and development activities.

Remote sensing estimation of colored dissolved organic matter (CDOM) in optically shallow waters

NASA Astrophysics Data System (ADS)

Li, Jiwei; Yu, Qian; Tian, Yong Q.; Becker, Brian L.

2017-06-01

It is not well understood how bottom reflectance of optically shallow waters affects the algorithm performance of colored dissolved organic matters (CDOM) retrieval. This study proposes a new algorithm that considers bottom reflectance in estimating CDOM absorption from optically shallow inland or coastal waters. The field sampling was conducted during four research cruises within the Saginaw River, Kawkawlin River and Saginaw Bay of Lake Huron. A stratified field sampling campaign collected water samples, determined the depth at each sampling location and measured optical properties. The sampled CDOM absorption at 440 nm broadly ranged from 0.12 to 8.46 m-1. Field sample analysis revealed that bottom reflectance does significantly change water apparent optical properties. We developed a CDOM retrieval algorithm (Shallow water Bio-Optical Properties algorithm, SBOP) that effectively reduces uncertainty by considering bottom reflectance in shallow waters. By incorporating the bottom contribution in upwelling radiances, the SBOP algorithm was able to explain 74% of the variance of CDOM values (RMSE = 0.22 and R2 = 0.74). The bottom effect index (BEI) was introduced to efficiently separate optically shallow and optically deep waters. Based on the BEI, an adaptive approach was proposed that references the amount of bottom effect in order to identify the most suitable algorithm (optically shallow water algorithm [SBOP] or optically deep water algorithm [QAA-CDOM]) to improve CDOM estimation (RMSE = 0.22 and R2 = 0.81). Our results potentially help to advance the capability of remote sensing in monitoring carbon pools at the land-water interface.

Phase retrieval based wavefront sensing experimental implementation and wavefront sensing accuracy calibration

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2009-05-01

As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.

Simple method based on intensity measurements for characterization of aberrations from micro-optical components.

PubMed

Perrin, Stephane; Baranski, Maciej; Froehly, Luc; Albero, Jorge; Passilly, Nicolas; Gorecki, Christophe

2015-11-01

We report a simple method, based on intensity measurements, for the characterization of the wavefront and aberrations produced by micro-optical focusing elements. This method employs the setup presented earlier in [Opt. Express 22, 13202 (2014)] for measurements of the 3D point spread function, on which a basic phase-retrieval algorithm is applied. This combination allows for retrieval of the wavefront generated by the micro-optical element and, in addition, quantification of the optical aberrations through the wavefront decomposition with Zernike polynomials. The optical setup requires only an in-motion imaging system. The technique, adapted for the optimization of micro-optical component fabrication, is demonstrated by characterizing a planoconvex microlens.

Modulating influences of memory strength and sensitivity of the retrieval test on the detectability of the sleep consolidation effect.

PubMed

Schoch, Sarah F; Cordi, Maren J; Rasch, Björn

2017-11-01

Emotionality can increase recall probability of memories as emotional information is highly relevant for future adaptive behavior. It has been proposed that memory processes acting during sleep selectively promote the consolidation of emotional memories, so that neutral memories no longer profit from sleep consolidation after learning. This appears as a selective effect of sleep for emotional memories. However, other factors contribute to the appearance of a consolidation benefit and influence this interpretation. Here we show that the strength of the memory trace before sleep and the sensitivity of the retrieval test after sleep are critical factors contributing to the detection of the benefit of sleep on memory for emotional and neutral stimuli. 228 subjects learned emotional and neutral pictures and completed a free recall after a 12-h retention interval of either sleep or wakefulness. We manipulated memory strength by including an immediate retrieval test before the retention interval in half of the participants. In addition, we varied the sensitivity of the retrieval test by including an interference learning task before retrieval testing in half of the participants. We show that a "selective" benefit of sleep for emotional memories only occurs in the condition with high memory strength. Furthermore, this "selective" benefit disappeared when we controlled for the memory strength before the retention interval and used a highly sensitive retrieval test. Our results indicate that although sleep benefits are more robust for emotional memories, neutral memories similarly profit from sleep after learning when more sensitive indicators are used. We conclude that whether sleep benefits on memory appear depends on several factors, including emotion, memory strength and sensitivity of the retrieval test. Copyright © 2017 Elsevier Inc. All rights reserved.

An Intelligent Pictorial Information System

NASA Astrophysics Data System (ADS)

Lee, Edward T.; Chang, B.

1987-05-01

In examining the history of computer application, we discover that early computer systems were developed primarily for applications related to scientific computation, as in weather prediction, aerospace applications, and nuclear physics applications. At this stage, the computer system served as a big calculator to perform, in the main, manipulation of numbers. Then it was found that computer systems could also be used for business applications, information storage and retrieval, word processing, and report generation. The history of computer application is summarized in Table I. The complexity of pictures makes picture processing much more difficult than number and alphanumerical processing. Therefore, new techniques, new algorithms, and above all, new pictorial knowledge, [1] are needed to overcome the limitatins of existing computer systems. New frontiers in designing computer systems are the ways to handle the representation,[2,3] classification, manipulation, processing, storage, and retrieval of pictures. Especially, the ways to deal with similarity measures and the meaning of the word "approximate" and the phrase "approximate reasoning" are an important and an indispensable part of an intelligent pictorial information system. [4,5] The main objective of this paper is to investigate the mathematical foundation for the effective organization and efficient retrieval of pictures in similarity-directed pictorial databases, [6] based on similarity retrieval techniques [7] and fuzzy languages [8]. The main advantage of this approach is that similar pictures are stored logically close to each other by using quantitative similarity measures. Thus, for answering queries, the amount of picture data needed to be searched can be reduced and the retrieval time can be improved. In addition, in a pictorial database, very often it is desired to find pictures (or feature vectors, histograms, etc.) that are most similar to or most dissimilar [9] to a test picture (or feature vector). Using similarity measures, one can not only store similar pictures logically or physically close to each other in order to improve retrieval or updating efficiency, one can also use such similarity measures to answer fuzzy queries involving nonexact retrieval conditions. In this paper, similarity directed pictorial databases involving geometric figures, chromosome images, [10] leukocyte images, cardiomyopathy images, and satellite images [11] are presented as illustrative examples.

Factors Associated with Advanced Inferior Vena Cava Filter Removals: A Single-Center Retrospective Study of 203 Patients Over 7 Years

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowell, Joshua D., E-mail: Joshua.Dowell@osumc.edu; Wagner, Daniel, E-mail: Daniel.Wagner@osumc.edu; Elliott, Eric, E-mail: Eric.Elliott@osumc.edu

PurposeTo identify factors associated with advanced inferior vena cava filter (IVCF) retrieval to raise awareness on technical considerations, retrieval efficiency, and patient safety.Materials and MethodsA single-center retrospective review was performed of 203 consecutive retrievable IVC filters placed between 2007 and 2014. Attempted retrievals were classified as advanced if the routine “snare and sheath” technique was initially unsuccessful after multiple attempts, or an alternate endovascular maneuver or access site was utilized. Patient and filter characteristics were recorded.Results203 attempted retrievals were reviewed (48.7 % male, 51.2 % female, mean age 52.7 years, mean dwell time 109 days). Advanced retrievals were observed in 20 patients (9.8 %) (15more » females, 5 males). Fluoroscopy time (p ≤ 0.01, 34.3 ± 21.1 and 5.3 ± 4.5 min for advanced retrievals and routine retrievals respectively, same below), gender (p = 0.031), and retrieval tilt angle (p ≤ 0.01, 5.7 ± 5.10° vs. 11.9 ± 11.03°) were associated with advanced retrievals. Females were 3.16 times more likely to have an advanced retrieval performed than males with a significantly higher tilt angle in those with advanced retrieval. History of cancer (p = 0.502), dwell time (p = 0.916), retrieval caval diameter (p = 0.053), placement caval diameter (p = 0.365), filter type (p = 0.710), strut perforation (p = 0.506), placement tilt angle (p = 0.311), and age (p = 0.558) were not found significantly associated with advanced retrievals.ConclusionsWomen are at increased risk for advanced filter retrieval secondary to a significant change in filter tilt over time compared to men, independent of filter type or competing demographic or filter risks, likely placing them at increased risk for higher procedural fluoroscopy times.« less

C-A1-03: Considerations in the Design and Use of an Oracle-based Virtual Data Warehouse

PubMed Central

Bredfeldt, Christine; McFarland, Lela

2011-01-01

Background/Aims The amount of clinical data available for research is growing exponentially. As it grows, increasing the efficiency of both data storage and data access becomes critical. Relational database management systems (rDBMS) such as Oracle are ideal solutions for managing longitudinal clinical data because they support large-scale data storage and highly efficient data retrieval. In addition, they can greatly simplify the management of large data warehouses, including security management and regular data refreshes. However, the HMORN Virtual Data Warehouse (VDW) was originally designed based on SAS datasets, and this design choice has a number of implications for both the design and use of an Oracle-based VDW. From a design standpoint, VDW tables are designed as flat SAS datasets, which do not take full advantage of Oracle indexing capabilities. From a data retrieval standpoint, standard VDW SAS scripts do not take advantage of SAS pass-through SQL capabilities to enable Oracle to perform the processing required to narrow datasets to the population of interest. Methods Beginning in 2009, the research department at Kaiser Permanente in the Mid-Atlantic States (KPMA) has developed an Oracle-based VDW according to the HMORN v3 specifications. In order to take advantage of the strengths of relational databases, KPMA introduced an interface layer to the VDW data, using views to provide access to standardized VDW variables. In addition, KPMA has developed SAS programs that provide access to SQL pass-through processing for first-pass data extraction into SAS VDW datasets for processing by standard VDW scripts. Results We discuss both the design and performance considerations specific to the KPMA Oracle-based VDW. We benchmarked performance of the Oracle-based VDW using both standard VDW scripts and an initial pre-processing layer to evaluate speed and accuracy of data return. Conclusions Adapting the VDW for deployment in an Oracle environment required minor changes to the underlying structure of the data. Further modifications of the underlying data structure would lead to performance enhancements. Maximally efficient data access for standard VDW scripts requires an extra step that involves restricting the data to the population of interest at the data server level prior to standard processing.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

A retrieval algorithm of hydrometer profile for submillimeter-wave radiometer

NASA Astrophysics Data System (ADS)

Liu, Yuli; Buehler, Stefan; Liu, Heguang

2017-04-01

Vertical profiles of particle microphysics perform vital functions for the estimation of climatic feedback. This paper proposes a new algorithm to retrieve the profile of the parameters of the hydrometeor(i.e., ice, snow, rain, liquid cloud, graupel) based on passive submillimeter-wave measurements. These parameters include water content and particle size. The first part of the algorithm builds the database and retrieves the integrated quantities. Database is built up by Atmospheric Radiative Transfer Simulator(ARTS), which uses atmosphere data to simulate the corresponding brightness temperature. Neural network, trained by the precalculated database, is developed to retrieve the water path for each type of particles. The second part of the algorithm analyses the statistical relationship between water path and vertical parameters profiles. Based on the strong dependence existing between vertical layers in the profiles, Principal Component Analysis(PCA) technique is applied. The third part of the algorithm uses the forward model explicitly to retrieve the hydrometeor profiles. Cost function is calculated in each iteration, and Differential Evolution(DE) algorithm is used to adjust the parameter values during the evolutionary process. The performance of this algorithm is planning to be verified for both simulation database and measurement data, by retrieving profiles in comparison with the initial one. Results show that this algorithm has the ability to retrieve the hydrometeor profiles efficiently. The combination of ARTS and optimization algorithm can get much better results than the commonly used database approach. Meanwhile, the concept that ARTS can be used explicitly in the retrieval process shows great potential in providing solution to other retrieval problems.

The impact of threat of shock-induced anxiety on memory encoding and retrieval

PubMed Central

Bolton, Sorcha

2017-01-01

Anxiety disorders are the most common mental health disorders, and daily transient feelings of anxiety (or “stress”) are ubiquitous. However, the precise impact of both transient and pathological anxiety on higher-order cognitive functions, including short- and long-term memory, is poorly understood. A clearer understanding of the anxiety–memory relationship is important as one of the core symptoms of anxiety, most prominently in post-traumatic stress disorder (PTSD), is intrusive reexperiencing of traumatic events in the form of vivid memories. This study therefore aimed to examine the impact of induced anxiety (threat of shock) on memory encoding and retrieval. Eighty-six healthy participants completed tasks assessing: visuospatial working memory, verbal recognition, face recognition, and associative memory. Critically, anxiety was manipulated within-subjects: information was both encoded and retrieved under threat of shock and safe (no shock) conditions. Results revealed that visuospatial working memory was enhanced when information was encoded and subsequently retrieved under threat, and that threat impaired the encoding of faces regardless of the condition in which it was retrieved. Episodic memory and verbal short-term recognition were, however, unimpaired. These findings indicate that transient anxiety in healthy individuals has domain-specific, rather than domain-general, impacts on memory. Future studies would benefit from expanding these findings into anxiety disorder patients to delineate the differences between adaptive and maladaptive responding. PMID:28916628

Optimizing Schedules of Retrieval Practice for Durable and Efficient Learning: How Much Is Enough?

ERIC Educational Resources Information Center

Rawson, Katherine A.; Dunlosky, John

2011-01-01

The literature on testing effects is vast but supports surprisingly few prescriptive conclusions for how to schedule practice to achieve both durable and efficient learning. Key limitations are that few studies have examined the effects of initial learning criterion or the effects of relearning, and no prior research has examined the combined…

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei

2016-03-01

Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, W.; Qin, J.; Yang, K.; Liu, S.; Lu, N.; Niu, X.

2015-12-01

Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Precision estimate for Odin-OSIRIS limb scatter retrievals

NASA Astrophysics Data System (ADS)

Bourassa, A. E.; McLinden, C. A.; Bathgate, A. F.; Elash, B. J.; Degenstein, D. A.

2012-02-01

The limb scatter measurements made by the Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on the Odin spacecraft are used to routinely produce vertically resolved trace gas and aerosol extinction profiles. Version 5 of the ozone and stratospheric aerosol extinction retrievals, which are available for download, are performed using a multiplicative algebraic reconstruction technique (MART). The MART inversion is a type of relaxation method, and as such the covariance of the retrieved state is estimated numerically, which, if done directly, is a computationally heavy task. Here we provide a methodology for the derivation of a numerical estimate of the covariance matrix for the retrieved state using the MART inversion that is sufficiently efficient to perform for each OSIRIS measurement. The resulting precision is compared with the variability in a large set of pairs of OSIRIS measurements that are close in time and space in the tropical stratosphere where the natural atmospheric variability is weak. These results are found to be highly consistent and thus provide confidence in the numerical estimate of the precision in the retrieved profiles.

Active learning methods for interactive image retrieval.

PubMed

Gosselin, Philippe Henri; Cord, Matthieu

2008-07-01

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

A mathematical model of neuro-fuzzy approximation in image classification

NASA Astrophysics Data System (ADS)

Gopalan, Sasi; Pinto, Linu; Sheela, C.; Arun Kumar M., N.

2016-06-01

Image digitization and explosion of World Wide Web has made traditional search for image, an inefficient method for retrieval of required grassland image data from large database. For a given input query image Content-Based Image Retrieval (CBIR) system retrieves the similar images from a large database. Advances in technology has increased the use of grassland image data in diverse areas such has agriculture, art galleries, education, industry etc. In all the above mentioned diverse areas it is necessary to retrieve grassland image data efficiently from a large database to perform an assigned task and to make a suitable decision. A CBIR system based on grassland image properties and it uses the aid of a feed-forward back propagation neural network for an effective image retrieval is proposed in this paper. Fuzzy Memberships plays an important role in the input space of the proposed system which leads to a combined neural fuzzy approximation in image classification. The CBIR system with mathematical model in the proposed work gives more clarity about fuzzy-neuro approximation and the convergence of the image features in a grassland image.

Storage and retrieval of quantum information with a hybrid optomechanics-spin system

NASA Astrophysics Data System (ADS)

Feng, Zhi-Bo; Zhang, Jian-Qi; Yang, Wan-Li; Feng, Mang

2016-08-01

We explore an efficient scheme for transferring the quantum state between an optomechanical cavity and an electron spin of diamond nitrogen-vacancy center. Assisted by a mechanical resonator, quantum information can be controllably stored (retrieved) into (from) the electron spin by adjusting the external field-induced detuning or coupling. Our scheme connects effectively the cavity photon and the electron spin and transfers quantum states between two regimes with large frequency difference. The experimental feasibility of our protocol is justified with accessible laboratory parameters.

TRECVID: the utility of a content-based video retrieval evaluation

NASA Astrophysics Data System (ADS)

Hauptmann, Alexander G.

2006-01-01

TRECVID, an annual retrieval evaluation benchmark organized by NIST, encourages research in information retrieval from digital video. TRECVID benchmarking covers both interactive and manual searching by end users, as well as the benchmarking of some supporting technologies including shot boundary detection, extraction of semantic features, and the automatic segmentation of TV news broadcasts. Evaluations done in the context of the TRECVID benchmarks show that generally, speech transcripts and annotations provide the single most important clue for successful retrieval. However, automatically finding the individual images is still a tremendous and unsolved challenge. The evaluations repeatedly found that none of the multimedia analysis and retrieval techniques provide a significant benefit over retrieval using only textual information such as from automatic speech recognition transcripts or closed captions. In interactive systems, we do find significant differences among the top systems, indicating that interfaces can make a huge difference for effective video/image search. For interactive tasks efficient interfaces require few key clicks, but display large numbers of images for visual inspection by the user. The text search finds the right context region in the video in general, but to select specific relevant images we need good interfaces to easily browse the storyboard pictures. In general, TRECVID has motivated the video retrieval community to be honest about what we don't know how to do well (sometimes through painful failures), and has focused us to work on the actual task of video retrieval, as opposed to flashy demos based on technological capabilities.

The Potential of Clear Sky Carbon Dioxide Satellite Retrievals

NASA Astrophysics Data System (ADS)

Nelson, R.; O'Dell, C.

2013-12-01

It has been shown that neglecting scattering and absorption by aerosols and thin clouds can lead to significant errors in retrievals of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. These clear sky retrievals, which assume no aerosol effects, are desirable because of their high computational efficiency relative to common full physics retrievals. Further, clear sky retrievals may be able to make higher quality measurements relative to the full physics approach because they may introduce fewer potential biases under certain circumstances. These biases can appear when we try to retrieve clouds and aerosols in the full physics methods when there are none actually present. Recent work has shown that intelligent pre-screening can remove soundings with large light-path modifications over ocean surfaces. In this work, we test the hypothesis that intelligent pre-screening of soundings may be successfully used over land surfaces as well as oceans, which would allow clear sky retrievals to be applicable over all surfaces. We also test the hypothesis that major light path modification effects associated with aerosols can be identified based on spectral tests at 0.76, 1.6, and 2 microns. This presentation summarizes our study of both simulated data and satellite observations from the GOSAT instrument in order to assess the effectiveness of using a clear sky retrieval algorithm coupled with intelligent pre-screening to accurately measure carbon dioxide from space-borne instruments.

Wavelet-based associative memory

NASA Astrophysics Data System (ADS)

Jones, Katharine J.

2004-04-01

Faces provide important characteristics of a person"s identification. In security checks, face recognition still remains the method in continuous use despite other approaches (i.e. fingerprints, voice recognition, pupil contraction, DNA scanners). With an associative memory, the output data is recalled directly using the input data. This can be achieved with a Nonlinear Holographic Associative Memory (NHAM). This approach can also distinguish between strongly correlated images and images that are partially or totally enclosed by others. Adaptive wavelet lifting has been used for Content-Based Image Retrieval. In this paper, adaptive wavelet lifting will be applied to face recognition to achieve an associative memory.

Research of image retrieval technology based on color feature

NASA Astrophysics Data System (ADS)

Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

2009-10-01

Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram make rotating and translation does not change. The HSV color space is used to show color characteristic of image, which is suitable to the visual characteristic of human. Taking advance of human's feeling to color, it quantifies color sector with unequal interval, and get characteristic vector. Finally, it matches the similarity of image with the algorithm of the histogram intersection and the partition-overall histogram. Users can choose a demonstration image to show inquired vision require, and also can adjust several right value through the relevance-feedback method to obtain the best result of search.An image retrieval system based on these approaches is presented. The result of the experiments shows that the image retrieval based on partition-overall histogram can keep the space distribution information while abstracting color feature efficiently, and it is superior to the normal color histograms in precision rate while researching. The query precision rate is more than 95%. In addition, the efficient block expression will lower the complicate degree of the images to be searched, and thus the searching efficiency will be increased. The image retrieval algorithms based on the partition-overall histogram proposed in the paper is efficient and effective.

Documentation of a spatial data-base management system for monitoring pesticide application in Washington

USGS Publications Warehouse

Schurr, K.M.; Cox, S.E.

1994-01-01

The Pesticide-Application Data-Base Management System was created as a demonstration project and was tested with data submitted to the Washington State Department of Agriculture by pesticide applicators from a small geographic area. These data were entered into the Department's relational data-base system and uploaded into the system's ARC/INFO files. Locations for pesticide applica- tions are assigned within the Public Land Survey System grids, and ARC/INFO programs in the Pesticide-Application Data-Base Management System can subdivide each survey section into sixteen idealized quarter-quarter sections for display map grids. The system provides data retrieval and geographic information system plotting capabilities from a menu of seven basic retrieval options. Additionally, ARC/INFO coverages can be created from the retrieved data when required for particular applications. The Pesticide-Application Data-Base Management System, or the general principles used in the system, could be adapted to other applica- tions or to other states.

Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

NASA Technical Reports Server (NTRS)

Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome

2011-01-01

The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

Turning back the hands of time: autobiographical memories in dementia cued by a museum setting.

PubMed

Miles, Amanda N; Fischer-Mogensen, Lise; Nielsen, Nadia H; Hermansen, Stine; Berntsen, Dorthe

2013-09-01

The current study examined the effects of cuing autobiographical memory retrieval in 12 older participants with dementia through immersion into a historically authentic environment that recreated the material and cultural context of the participants' youth. Participants conversed in either an everyday setting (control condition) or a museum setting furnished in early twentieth century style (experimental condition) while being presented with condition matched cues. Conversations were coded for memory content based on an adapted version of Levine, Svoboda, Hay, Winocur, and Moscovitch (2002) coding scheme. More autobiographical memories were recalled in the museum setting, and these memories were more elaborated, more spontaneous and included especially more internal (episodic) details compared to memories in the control condition. The findings have theoretical and practical implications by showing that the memories retrieved in the museum setting were both quantitatively and qualitatively different from memories retrieved during a control condition. Copyright © 2013 Elsevier Inc. All rights reserved.

Unipolar Terminal-Attractor Based Neural Associative Memory with Adaptive Threshold

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Barhen, Jacob (Inventor); Farhat, Nabil H. (Inventor); Wu, Chwan-Hwa (Inventor)

1996-01-01

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner-product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Unipolar terminal-attractor based neural associative memory with adaptive threshold

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Barhen, Jacob (Inventor); Farhat, Nabil H. (Inventor); Wu, Chwan-Hwa (Inventor)

1993-01-01

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Motor learning and consolidation: the case of visuomotor rotation.

PubMed

Krakauer, John W

2009-01-01

Adaptation to visuomotor rotation is a particular form of motor learning distinct from force-field adaptation, sequence learning, and skill learning. Nevertheless, study of adaptation to visuomotor rotation has yielded a number of findings and principles that are likely of general importance to procedural learning and memory. First, rotation learning is implicit and appears to proceed through reduction in a visual prediction error generated by a forward model, such implicit adaptation occurs even when it is in conflict with an explicit task goal. Second, rotation learning is subject to different forms of interference: retrograde, anterograde through aftereffects, and contextual blocking of retrieval. Third, opposite rotations can be recalled within a short time interval without interference if implicit contextual cues (effector change) rather than explicit cues (color change) are used. Fourth, rotation learning consolidates both over time and with increased initial training (saturation learning).

Memory Dynamics and Decision Making in Younger and Older Adults

ERIC Educational Resources Information Center

Lechuga, M. Teresa; Gomez-Ariza, Carlos J.; Iglesias-Parro, Sergio; Pelegrina, Santiago

2012-01-01

The main aim of this research was to study whether memory dynamics influence older people's choices to the same extent as younger's ones. To do so, we adapted the retrieval-practice paradigm to produce variations in memory accessibility of information on which decisions were made later. Based on previous results, we expected to observe…

Documentation and User's Guide to the Computer Management System for the Clinical Teacher Curriculum.

ERIC Educational Resources Information Center

Dia, Ahmed

The guide to the computer management system for individualized instructional strategy associated with the clinical teacher curriculum at Florida State University is presented. The system is described in terms of 27 Cobol programs and the Multiple Access and Retrieval System (MARS VI), which were adapted to requirements of the clinical teacher…

Improvements to GPS Airborne Radio Occultation in the Lower Troposphere Through Implementation of the Phase Matching Method

NASA Astrophysics Data System (ADS)

Wang, K.-N.; Garrison, J. L.; Haase, J. S.; Murphy, B. J.

2017-10-01

Airborne radio occultation (ARO) is a remote sensing technique for atmospheric sounding using Global Positioning System signals received by an airborne instrument. The atmospheric refractivity profile, which depends on pressure, temperature, and water vapor, can be retrieved by measuring the signal delay due to the refractive medium through which the signal traverses. The ARO system was developed to make repeated observations within an individual meteorological event such as a tropical storm, regardless of the presence of clouds and precipitation, and complements existing observation techniques such as dropsondes and satellite remote sensing. RO systems can suffer multipath ray propagation in the lower troposphere if there are strong refractivity gradients, for example, due to a highly variable moisture distribution or a sharp boundary layer, interfering with continuous carrier phase tracking as well as complicating retrievals. The phase matching method has now been adapted for ARO and is shown to reduce negative biases in the refractivity retrieval by providing robust retrievals of bending angle in the presence of multipath. The retrieval results are presented for a flight campaign in September 2010 for Hurricane Karl in the Caribbean Sea. The accuracy is assessed through comparison with the European Centre for Medium Range Weather Forecasts Interim Reanalysis. The fractional difference in refractivity can be maintained at a standard deviation of 2% from flight level down to a height of 2 km. The phase matching method decreases the negative refractivity bias by as much as 4% over the classical geometrical optics retrieval method.

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the "Deep Blue" Aerosol Project

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Lee, J.; Bettenhausen, C.; Kim, W. V.; Smirnov, A.

2018-01-01

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine-mode AOD fraction are also well correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

A Major Controversy in Codon-Anticodon Adaptation Resolved by a New Codon Usage Index

PubMed Central

Xia, Xuhua

2015-01-01

Two alternative hypotheses attribute different benefits to codon-anticodon adaptation. The first assumes that protein production is rate limited by both initiation and elongation and that codon-anticodon adaptation would result in higher elongation efficiency and more efficient and accurate protein production, especially for highly expressed genes. The second claims that protein production is rate limited only by initiation efficiency but that improved codon adaptation and, consequently, increased elongation efficiency have the benefit of increasing ribosomal availability for global translation. To test these hypotheses, a recent study engineered a synthetic library of 154 genes, all encoding the same protein but differing in degrees of codon adaptation, to quantify the effect of differential codon adaptation on protein production in Escherichia coli. The surprising conclusion that “codon bias did not correlate with gene expression” and that “translation initiation, not elongation, is rate-limiting for gene expression” contradicts the conclusion reached by many other empirical studies. In this paper, I resolve the contradiction by reanalyzing the data from the 154 sequences. I demonstrate that translation elongation accounts for about 17% of total variation in protein production and that the previous conclusion is due to the use of a codon adaptation index (CAI) that does not account for the mutation bias in characterizing codon adaptation. The effect of translation elongation becomes undetectable only when translation initiation is unrealistically slow. A new index of translation elongation ITE is formulated to facilitate studies on the efficiency and evolution of the translation machinery. PMID:25480780

[Extinction and Reconsolidation of Memory].

PubMed

Zuzina, A B; Balaban, P M

2015-01-01

Retrieval of memory followed by reconsolidation can strengthen a memory, while retrieval followed by extinction results in a decrease of memory performance due to weakening of existing memory or formation of a competing memory. In our study we analyzed the behavior and responses of identified neurons involved in the network underlying aversive learning in terrestrial snail Helix, and made an attempt to describe the conditions in which the retrieval of memory leads either to extinction or reconsolidation. In the network underlying the withdrawal behavior, sensory neurons, premotor interneurons, motor neurons, and modulatory for this network serotonergic neurons are identified and recordings from representatives of these groups were made before and after aversive learning. In the network underlying feeding behavior, the premotor modulatory serotonergic interneurons and motor neurons involved in motor program of feeding are identified. Analysis of changes in neural activity after aversive learning showed that modulatory neurons of feeding behavior do not demonstrate any changes (sometimes a decrease of responses to food was observed), while responses to food in withdrawal behavior premotor interneurons changed qualitatively, from under threshold EPSPs to spike discharges. Using a specific for serotonergic neurons neurotoxin 5,7-DiHT it was shown previously that the serotonergic system is necessary for the aversive learning, but is not necessary for maintenance and retrieval of this memory. These results suggest that the serotonergic neurons that are necessary as part of a reinforcement for developing the associative changes in the network may be not necessary for the retrieval of memory. The hypothesis presented in this review concerns the activity of the "reinforcement" serotonergic neurons that is suggested to be the gate condition for the choice between extinction/reconsolidation triggered by memory retrieval: if these serotonergic neurons do not respond during the retrieval due to adaptation, habituation, changes in environment, etc., then we will observe the extinction; while if these neurons respond to the CS during memory retrieval, we will observe the reconsolidation phenomenon.

Ancient genomics

PubMed Central

Der Sarkissian, Clio; Allentoft, Morten E.; Ávila-Arcos, María C.; Barnett, Ross; Campos, Paula F.; Cappellini, Enrico; Ermini, Luca; Fernández, Ruth; da Fonseca, Rute; Ginolhac, Aurélien; Hansen, Anders J.; Jónsson, Hákon; Korneliussen, Thorfinn; Margaryan, Ashot; Martin, Michael D.; Moreno-Mayar, J. Víctor; Raghavan, Maanasa; Rasmussen, Morten; Velasco, Marcela Sandoval; Schroeder, Hannes; Schubert, Mikkel; Seguin-Orlando, Andaine; Wales, Nathan; Gilbert, M. Thomas P.; Willerslev, Eske; Orlando, Ludovic

2015-01-01

The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence throughput of next generation sequencing platforms and the ability to target short and degraded DNA molecules. Many ancient specimens previously unsuitable for DNA analyses because of extensive degradation can now successfully be used as source materials. Additionally, the analytical power obtained by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when testing specific hypotheses related to the past. PMID:25487338

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

Iterative-Transform Phase Retrieval Using Adaptive Diversity

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

[Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

PubMed

Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

2012-12-01

This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

Is retrieval the key? Metamemory judgment and testing as learning strategies.

PubMed

Akdoğan, Elçin; Izaute, Marie; Danion, Jean-Marie; Vidailhet, Pierre; Bacon, Elisabeth

2016-11-01

Re-reading is the most common learning strategy, albeit not a very efficient one. Testing is highly efficient, but not perceived by students as a learning strategy. Prospective judgment-of-learning (JOL) reflect the learner's impression of subsequently being able to retrieve the ongoing learning in a cued-recall task. Estimating JOL involves attempting to retrieve the information, as in testing. The few studies that have explored the potential mnemonic benefit of JOL have yielded contradictory results. Our aim was to compare JOL and testing with re-study and to examine the impact of these strategies according to the relative difficulty of the material (cue-target association strength) in two experiments. After a first encoding phase, participants re-studied, provided JOL, or took a test. Forty-eight hours later, they participated in a final cued-recall test, during which their confidence level judgments were collected. The main result was that delayed JOL behaved in the same way as testing, and both yielded better performances than re-study when material was of moderate difficulty. The easy or very difficult material revealed no differences between these strategies. JOL is proposed as an alternative to testing when faced with difficult material.

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

PubMed

Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

2007-01-01

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

A hierarchical SVG image abstraction layer for medical imaging

NASA Astrophysics Data System (ADS)

Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

2010-03-01

As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

Analysis and design of a high power laser adaptive phased array transmitter

NASA Technical Reports Server (NTRS)

Mevers, G. E.; Soohoo, J. F.; Winocur, J.; Massie, N. A.; Southwell, W. H.; Brandewie, R. A.; Hayes, C. L.

1977-01-01

The feasibility of delivering substantial quantities of optical power to a satellite in low earth orbit from a ground based high energy laser (HEL) coupled to an adaptive antenna was investigated. Diffraction effects, atmospheric transmission efficiency, adaptive compensation for atmospheric turbulence effects, including the servo bandwidth requirements for this correction, and the adaptive compensation for thermal blooming were examined. To evaluate possible HEL sources, atmospheric investigations were performed for the CO2, (C-12)(O-18)2 isotope, CO and DF wavelengths using output antenna locations of both sea level and mountain top. Results indicate that both excellent atmospheric and adaption efficiency can be obtained for mountain top operation with a micron isotope laser operating at 9.1 um, or a CO laser operating single line (P10) at about 5.0 (C-12)(O-18)2um, which was a close second in the evaluation. Four adaptive power transmitter system concepts were generated and evaluated, based on overall system efficiency, reliability, size and weight, advanced technology requirements and potential cost. A multiple source phased array was selected for detailed conceptual design. The system uses a unique adaption technique of phase locking independent laser oscillators which allows it to be both relatively inexpensive and most reliable with a predicted overall power transfer efficiency of 53%.

DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.

PubMed

Clima, Lilia; Peptanariu, Dragos; Pinteala, Mariana; Salic, Adrian; Barboiu, Mihail

2015-12-25

Dynamic constitutional frameworks, based on squalene, PEG and PEI components, reversibly connected to core centers, allow the efficient identification of adaptive vectors for good DNA transfection efficiency and are well tolerated by mammalian cells.

NATO IST 124 Experimentation Instructions

DTIC Science & Technology

2016-11-10

more reliable and predictable network performance through adaptive and efficient control schemes . This report provides guidance and instructions for...tactical heterogeneous networks for more reliable and predictable network performance through adaptive and efficient control schemes . This report

Joint aerosol and water-leaving radiance retrieval from Airborne Multi-angle SpectroPolarimeter Imager

NASA Astrophysics Data System (ADS)

Xu, F.; Dubovik, O.; Zhai, P.; Kalashnikova, O. V.; Diner, D. J.

2015-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI typically acquires observations of a target area at 9 view angles between ±67° off the nadir. Its spectral channels are centered at 355, 380, 445, 470*, 555, 660*, and 865* nm, where the asterisk denotes the polarimetric bands. In order to retrieve information from the AirMSPI observations, we developed a efficient and flexible retrieval code that can jointly retrieve aerosol and water leaving radiance simultaneously. The forward model employs a coupled Markov Chain (MC) [2] and adding/doubling [3] radiative transfer method which is fully linearized and integrated with a multi-patch retrieval algorithm to obtain aerosol and water leaving radiance/Chl-a information. Various constraints are imposed to improve convergence and retrieval stability. We tested the aerosol and water leaving radiance retrievals using the AirMSPI radiance and polarization measurements by comparing to the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration to the values reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California. In addition, the MC-based retrievals of aerosol properties were compared with GRASP ([4-5]) retrievals for selected cases. The MC-based retrieval approach was then used to systematically explore the benefits of AirMSPI's ultraviolet and polarimetric channels, the use of multiple view angles, and constraints provided by inclusion of bio-optical models of the water-leaving radiance. References [1]. D. J. Diner, et al. Atmos. Meas. Tech. 6, 1717 (2013). [2]. F. Xu et al. Opt. Lett. 36, 2083 (2011). [3]. J. E. Hansen and L.D. Travis. Space Sci. Rev. 16, 527 (1974). [4]. O. Dubovik et al. Atmos. Meas. Tech., 4, 975 (2011). [5]. O. Dubovik et al. SPIE: Newsroom, DOI:10.1117/2.1201408.005558 (2014).

Electromagnetic information transfer through aqueous system.

PubMed

Foletti, Alberto; Ledda, Mario; Lolli, Maria Grazia; Grimaldi, Settimio; Lisi, Antonella

2017-01-01

Several beneficial effects of the electromagnetic information transfer through aqueous system (EMITTAS) procedure have previously been reported in vitro. The clinical potential of this procedure has also started to be evaluated. Information flow in biological systems can be investigated through chemical and molecular approaches or by a biophysical approach focused on endogenous electrodynamic activities. Electromagnetic signals are endogenously generated at different levels of the biological organization and, likely, play an active role in synchronizing internal cell function or local/systemic adaptive response. Consequently, each adaptive response can be described by its specific electromagnetic pattern and, therefore, correlates with a unique and specific electromagnetic signature. A biophysical procedure synchronously integrating the EMITTAS procedure has already been applied for the treatment of articular pain, low-back pain, neck pain and mobility, fluctuating asymmetry, early-stage chronic kidney disease, refractory gynecological infections, minor anxiety and depression disorders. This clinical strategy involves a single treatment, since the EMITTAS procedure allows the patient to continue his/her own personal treatment at home by means of self-administration of the recorded aqueous system. A significant and long-lasting improvement has been reported, showing a potential beneficial use of this biophysical procedure in the management of common illnesses in an efficient, effective and personalized way. Data from recent studies suggest that aqueous systems may play a key role in providing the basis for recording, storing, transferring and retrieving clinically effective quanta of biological information. These features likely enable to trigger local and systemic self-regulation and self-regeneration potential of the organism.

1975 Automotive Characteristics Data Base

DOT National Transportation Integrated Search

1976-10-01

A study of automobile characteristics as a supportive tool for auto energy consumption, fuel economy monitoring, and fleet analysis studies is presented. This report emphasizes the utility of efficient data retrieval methods in fuel economy analysis,...

Post-Flight Data Analysis Tool

NASA Technical Reports Server (NTRS)

George, Marina

2018-01-01

A software tool that facilitates the retrieval and analysis of post-flight data. This allows our team and other teams to effectively and efficiently analyze and evaluate post-flight data in order to certify commercial providers.

FastBit Reference Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Kesheng

2007-08-02

An index in a database system is a data structure that utilizes redundant information about the base data to speed up common searching and retrieval operations. Most commonly used indexes are variants of B-trees, such as B+-tree and B*-tree. FastBit implements a set of alternative indexes call compressed bitmap indexes. Compared with B-tree variants, these indexes provide very efficient searching and retrieval operations by sacrificing the efficiency of updating the indexes after the modification of an individual record. In addition to the well-known strengths of bitmap indexes, FastBit has a special strength stemming from the bitmap compression scheme used. Themore » compression method is called the Word-Aligned Hybrid (WAH) code. It reduces the bitmap indexes to reasonable sizes and at the same time allows very efficient bitwise logical operations directly on the compressed bitmaps. Compared with the well-known compression methods such as LZ77 and Byte-aligned Bitmap code (BBC), WAH sacrifices some space efficiency for a significant improvement in operational efficiency. Since the bitwise logical operations are the most important operations needed to answer queries, using WAH compression has been shown to answer queries significantly faster than using other compression schemes. Theoretical analyses showed that WAH compressed bitmap indexes are optimal for one-dimensional range queries. Only the most efficient indexing schemes such as B+-tree and B*-tree have this optimality property. However, bitmap indexes are superior because they can efficiently answer multi-dimensional range queries by combining the answers to one-dimensional queries.« less

EM-31 RETRIEVAL KNOWLEDGE CENTER MEETING REPORT: MOBILIZE AND DISLODGE TANK WASTE HEELS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fellinger, A.

2010-02-16

The Retrieval Knowledge Center sponsored a meeting in June 2009 to review challenges and gaps to retrieval of tank waste heels. The facilitated meeting was held at the Savannah River Research Campus with personnel broadly representing tank waste retrieval knowledge at Hanford, Savannah River, Idaho, and Oak Ridge. This document captures the results of this meeting. In summary, it was agreed that the challenges to retrieval of tank waste heels fell into two broad categories: (1) mechanical heel waste retrieval methodologies and equipment and (2) understanding and manipulating the heel waste (physical, radiological, and chemical characteristics) to support retrieval optionsmore » and subsequent processing. Recent successes and lessons from deployments of the Sand and Salt Mantis vehicles as well as retrieval of C-Area tanks at Hanford were reviewed. Suggestions to address existing retrieval approaches that utilize a limited set of tools and techniques are included in this report. The meeting found that there had been very little effort to improve or integrate the multiple proven or new techniques and tools available into a menu of available methods for rapid insertion into baselines. It is recommended that focused developmental efforts continue in the two areas underway (low-level mixing evaluation and pumping slurries with large solid materials) and that projects to demonstrate new/improved tools be launched to outfit tank farm operators with the needed tools to complete tank heel retrievals effectively and efficiently. This document describes the results of a meeting held on June 3, 2009 at the Savannah River Site in South Carolina to identify technology gaps and potential technology solutions to retrieving high-level waste (HLW) heels from waste tanks within the complex of sites run by the U. S. Department of Energy (DOE). The meeting brought together personnel with extensive tank waste retrieval knowledge from DOE's four major waste sites - Hanford, Savannah River, Idaho, and Oak Ridge. The meeting was arranged by the Retrieval Knowledge Center (RKC), which is a technology development project sponsored by the Office of Technology Innovation & Development - formerly the Office of Engineering and Technology - within the DOE Office of Environmental Management (EM).« less

[Ecological adaptability evaluation of peanut cultivars based on biomass and nutrient accumulation].

PubMed

Wang, Xue; Cui, Shao-xiong; Sun, Zhi-mei; Mu, Guo-jun; Cui, Shun-li; Wang, Peng-chao; Liu, Li-feng

2015-07-01

To identify the good peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability, 19 selected peanut cultivars were planted in the low champaign area and piedmont plain area of Hebei Province. By using principal component analysis, the adaptability of these 19 cultivars was evaluated for different ecological regions through comparing their 16 main traits including biomass and nutrient parameters. According to the critical value of principal component (>1.0), the 16 biomass and nutrient characteristics were integrated into 4 principal components which accounted for 85% of the original information. The results indicated that there were obvious differences in yield and nutrient use efficiency for the peanut cultivars in different ecological regions. The 19 peanut cultivars were classified into 2 groups according to their ecological adaptability, and the cultivars from the group with wide adaptability could further be divided into 3 categories according to their yield and nutrient use efficiency. Among these cultivars, Yuhua 9719, Jihua 0212-4, Weihua 10, Yuhua 15, Puhua 28 and Jihua 10 were selected as the better peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability.

Altered selection during language processing in individuals at high risk for psychosis.

PubMed

Vargas, T; Snyder, H; Banich, M; Newberry, R; Shankman, Stewart A; Strauss, Gregory P; Mittal, V A

2018-06-19

Performance in the executive function (EF) domain has been linked to symptoms and functional outcomes in psychosis. Studies have found that UHR populations have difficulty with verbal fluency, which involves multiple facets of EF. Two potentially implicated EF facets were examined to explore whether these could be dissociated in UHR populations: selection among alternatives (measured by selection costs) and retrieval from semantic memory retrieval (measured by retrieval costs). A total of 45 UHR individuals and 46 healthy controls (HVs) were assessed with a verb generation task. Differences in selection cost (RT difference between high and low selection demand conditions) and retrieval cost (RT difference between high and low retrieval demand conditions) were examined and participants were also assessed for clinical symptoms. The UHR group showed greater selection costs relative to HVs, F (1, 91) = 4.39, p = 0.039. However, there were no group differences on retrieval cost, F (1, 91) = 0.63, p = 0.43. A positive association (r = 0.41) was found between disorganized and negative symptoms and selection costs (but not retrieval costs) in the UHR group. There was no significant association between selection costs and positive symptoms. Increased selection costs may reflect impaired performance in the neural inhibition domain of EF in the UHR population, potentially underlying a mechanistically distinct EF subdomain that affects the group's ability to efficiently select between competing options. Findings suggest that UHR individuals may exhibit impairment in selecting among alternatives, but not in retrieval from semantic memory. Copyright © 2018 Elsevier B.V. All rights reserved.

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

PubMed

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Challenges and methodology for indexing the computerized patient record.

PubMed

Ehrler, Frédéric; Ruch, Patrick; Geissbuhler, Antoine; Lovis, Christian

2007-01-01

Patient records contain most crucial documents for managing the treatments and healthcare of patients in the hospital. Retrieving information from these records in an easy, quick and safe way helps care providers to save time and find important facts about their patient's health. This paper presents the scalability issues induced by the indexing and the retrieval of the information contained in the patient records. For this study, EasyIR, an information retrieval tool performing full text queries and retrieving the related documents has been used. An evaluation of the performance reveals that the indexing process suffers from overhead consequence of the particular structure of the patient records. Most IR tools are designed to manage very large numbers of documents in a single index whereas in our hypothesis, one index per record, which usually implies few documents, has been imposed. As the number of modifications and creations of patient records are significant in a day, using a specialized and efficient indexation tool is required.

A memory learning framework for effective image retrieval.

PubMed

Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang

2005-04-01

Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.

How teachers can help learners build storage and retrieval strength.

PubMed

Desy, Janeve; Busche, Kevin; Cusano, Ronald; Veale, Pamela; Coderre, Sylvain; McLaughlin, Kevin

2018-04-01

To be an effective teacher, content expertise is necessary but alone does not guarantee optimal learning outcomes for students. In this article, the authors discuss ways in which medical teachers can shape the learning of their students and enable them to become more efficient and effective learners. Using Bjork and Bjork's new theory of disuse as their framework, the authors discuss strategies to improve storage strength of to-be-learned information and strategies to improve retrieval strength of learned information. Strategies to improve storage strength include optimizing cognitive load, providing causal explanations, and giving effective feedback. Strategies to improve retrieval strength include situated cognition and various types of retrieval practice. Adopting these teaching strategies should hopefully help teachers improve the learning outcomes of their students, but there is still a need for further research into the science of learning and the science of instruction, including comparative effectiveness of different teaching strategies and how best to translate findings from the psychology literature into medical education.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

PubMed

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

Adaptive top-down suppression of hippocampal activity and the purging of intrusive memories from consciousness.

PubMed

Benoit, Roland G; Hulbert, Justin C; Huddleston, Ean; Anderson, Michael C

2015-01-01

When reminded of unwanted memories, people often attempt to suppress these experiences from awareness. Prior work indicates that control processes mediated by the dorsolateral prefrontal cortex (DLPFC) modulate hippocampal activity during such retrieval suppression. It remains unknown whether this modulation plays a role in purging an intrusive memory from consciousness. Here, we combined fMRI and effective connectivity analyses with phenomenological reports to scrutinize a role for adaptive top-down suppression of hippocampal retrieval processes in terminating mnemonic awareness of intrusive memories. Participants either suppressed or recalled memories of pictures depicting faces or places. After each trial, they reported their success at regulating awareness of the memory. DLPFC activation was greatest when unwanted memories intruded into consciousness and needed to be purged, and this increased engagement predicted superior control of intrusive memories over time. However, hippocampal activity was decreased during the suppression of place memories only. Importantly, the inhibitory influence of the DLPFC on the hippocampus was linked to the ensuing reduction in intrusions of the suppressed memories. Individuals who exhibited negative top-down coupling during early suppression attempts experienced fewer involuntary memory intrusions later on. Over repeated suppressions, the DLPFC-hippocampus connectivity grew less negative with the degree that they no longer had to purge unwanted memories from awareness. These findings support a role of DLPFC in countermanding the unfolding recollection of an unwanted memory via the suppression of hippocampal processing, a mechanism that may contribute to adaptation in the aftermath of traumatic experiences.

Inhibitory Voluntary Control of Memory: Effect of Stimulus Onset Asynchrony on Reaction Time to Suppressed Memories

ERIC Educational Resources Information Center

Algarabel, Salvador; Luciano, Juan V.; Martinez, Jose L.

2006-01-01

Anderson & Green (2001) have recently shown that using an adaptation of the go-no go task, participants can voluntarily inhibit the retrieval of specific memories. We present three experiments in which we try to determine the degree of automaticity involved, and the role of the previous prime-target relation on the development of this inhibitory…

Oblivious image watermarking combined with JPEG compression

NASA Astrophysics Data System (ADS)

Chen, Qing; Maitre, Henri; Pesquet-Popescu, Beatrice

2003-06-01

For most data hiding applications, the main source of concern is the effect of lossy compression on hidden information. The objective of watermarking is fundamentally in conflict with lossy compression. The latter attempts to remove all irrelevant and redundant information from a signal, while the former uses the irrelevant information to mask the presence of hidden data. Compression on a watermarked image can significantly affect the retrieval of the watermark. Past investigations of this problem have heavily relied on simulation. It is desirable not only to measure the effect of compression on embedded watermark, but also to control the embedding process to survive lossy compression. In this paper, we focus on oblivious watermarking by assuming that the watermarked image inevitably undergoes JPEG compression prior to watermark extraction. We propose an image-adaptive watermarking scheme where the watermarking algorithm and the JPEG compression standard are jointly considered. Watermark embedding takes into consideration the JPEG compression quality factor and exploits an HVS model to adaptively attain a proper trade-off among transparency, hiding data rate, and robustness to JPEG compression. The scheme estimates the image-dependent payload under JPEG compression to achieve the watermarking bit allocation in a determinate way, while maintaining consistent watermark retrieval performance.

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

Interferogram conditioning for improved Fourier analysis and application to X-ray phase imaging by grating interferometry.

PubMed

Montaux-Lambert, Antoine; Mercère, Pascal; Primot, Jérôme

2015-11-02

An interferogram conditioning procedure, for subsequent phase retrieval by Fourier demodulation, is presented here as a fast iterative approach aiming at fulfilling the classical boundary conditions imposed by Fourier transform techniques. Interference fringe patterns with typical edge discontinuities were simulated in order to reveal the edge artifacts that classically appear in traditional Fourier analysis, and were consecutively used to demonstrate the correction efficiency of the proposed conditioning technique. Optimization of the algorithm parameters is also presented and discussed. Finally, the procedure was applied to grating-based interferometric measurements performed in the hard X-ray regime. The proposed algorithm enables nearly edge-artifact-free retrieval of the phase derivatives. A similar enhancement of the retrieved absorption and fringe visibility images is also achieved.

All-optical switch and transistor gated by one stored photon.

PubMed

Chen, Wenlan; Beck, Kristin M; Bücker, Robert; Gullans, Michael; Lukin, Mikhail D; Tanji-Suzuki, Haruka; Vuletić, Vladan

2013-08-16

The realization of an all-optical transistor, in which one "gate" photon controls a "source" light beam, is a long-standing goal in optics. By stopping a light pulse in an atomic ensemble contained inside an optical resonator, we realized a device in which one stored gate photon controls the resonator transmission of subsequently applied source photons. A weak gate pulse induces bimodal transmission distribution, corresponding to zero and one gate photons. One stored gate photon produces fivefold source attenuation and can be retrieved from the atomic ensemble after switching more than one source photon. Without retrieval, one stored gate photon can switch several hundred source photons. With improved storage and retrieval efficiency, our work may enable various new applications, including photonic quantum gates and deterministic multiphoton entanglement.

Computerized adaptive measurement of depression: A simulation study

PubMed Central

Gardner, William; Shear, Katherine; Kelleher, Kelly J; Pajer, Kathleen A; Mammen, Oommen; Buysse, Daniel; Frank, Ellen

2004-01-01

Background Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity. Methods Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale. Results The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated r = .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r = .74) than the BDI total score did (r = .70). Conclusions Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity. PMID:15132755

Alpha Oscillations during Incidental Encoding Predict Subsequent Memory for New "Foil" Information.

PubMed

Vogelsang, David A; Gruber, Matthias; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

2018-05-01

People can employ adaptive strategies to increase the likelihood that previously encoded information will be successfully retrieved. One such strategy is to constrain retrieval toward relevant information by reimplementing the neurocognitive processes that were engaged during encoding. Using EEG, we examined the temporal dynamics with which constraining retrieval toward semantic versus nonsemantic information affects the processing of new "foil" information encountered during a memory test. Time-frequency analysis of EEG data acquired during an initial study phase revealed that semantic compared with nonsemantic processing was associated with alpha decreases in a left frontal electrode cluster from around 600 msec after stimulus onset. Successful encoding of semantic versus nonsemantic foils during a subsequent memory test was related to decreases in alpha oscillatory activity in the same left frontal electrode cluster, which emerged relatively late in the trial at around 1000-1600 msec after stimulus onset. Across participants, left frontal alpha power elicited by semantic processing during the study phase correlated significantly with left frontal alpha power associated with semantic foil encoding during the memory test. Furthermore, larger left frontal alpha power decreases elicited by semantic foil encoding during the memory test predicted better subsequent semantic foil recognition in an additional surprise foil memory test, although this effect did not reach significance. These findings indicate that constraining retrieval toward semantic information involves reimplementing semantic encoding operations that are mediated by alpha oscillations and that such reimplementation occurs at a late stage of memory retrieval, perhaps reflecting additional monitoring processes.

Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci

NASA Astrophysics Data System (ADS)

Kosmale, Miriam; Popp, Thomas

2016-04-01

Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.

GeoGIS : phase III.

DOT National Transportation Integrated Search

2011-08-01

GeoGIS is a web-based geotechnical database management system that is being developed for the Alabama : Department of Transportation (ALDOT). The purpose of GeoGIS is to facilitate the efficient storage and retrieval of : geotechnical documents for A...

49 CFR 565.10 - Purpose and scope.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.10 - Purpose and scope.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.10 - Purpose and scope.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.10 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.10 - Purpose and scope.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

Kalman filters for assimilating near-surface observations in the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2012-12-01

We present a dual Kalman Filter (KF) approach for retrieving states and parameters controlling soil water dynamics in a homogenous soil column by using near-surface state observations. The dual Kalman filter couples a standard KF algorithm for retrieving the states and an unscented KF algorithm for retrieving the parameters. We examine the performance of the dual Kalman Filter applied to two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil matric pressure head (h). We use a synthetic time-series series of true states and noise corrupted observations and a synthetic time-series of meteorological forcing. The performance analyses account for the effect of the input parameters, the observation depth and the assimilation frequency as well as the relationship between the retrieved states and the assimilated variables. We show that the identifiability of the parameters is strongly conditioned by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. State identifiability is instead efficient even with a relatively coarse time-resolution of the assimilated observation. The accuracy of the retrieved states exhibits limited sensitivity to the observation depth and the assimilation frequency.

Content-based image retrieval on mobile devices

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Abdullah, Shafaq; Kiranyaz, Serkan; Gabbouj, Moncef

2005-03-01

Content-based image retrieval area possesses a tremendous potential for exploration and utilization equally for researchers and people in industry due to its promising results. Expeditious retrieval of desired images requires indexing of the content in large-scale databases along with extraction of low-level features based on the content of these images. With the recent advances in wireless communication technology and availability of multimedia capable phones it has become vital to enable query operation in image databases and retrieve results based on the image content. In this paper we present a content-based image retrieval system for mobile platforms, providing the capability of content-based query to any mobile device that supports Java platform. The system consists of light-weight client application running on a Java enabled device and a server containing a servlet running inside a Java enabled web server. The server responds to image query using efficient native code from selected image database. The client application, running on a mobile phone, is able to initiate a query request, which is handled by a servlet in the server for finding closest match to the queried image. The retrieved results are transmitted over mobile network and images are displayed on the mobile phone. We conclude that such system serves as a basis of content-based information retrieval on wireless devices and needs to cope up with factors such as constraints on hand-held devices and reduced network bandwidth available in mobile environments.

Characterization of human-dog social interaction using owner report.

PubMed

Lit, Lisa; Schweitzer, Julie B; Oberbauer, Anita M

2010-07-01

Dog owners were surveyed for observations of social behaviors in their dogs, using questions adapted from the human Autism Diagnostic Observation Schedule (ADOS) pre-verbal module. Using 939 responses for purebred and mixed-breed dogs, three factors were identified: initiation of reciprocal social behaviors (INIT), response to social interactions (RSPNS), and communication (COMM). There were small or no effects of sex, age, breed group or training. For six breeds with more than 35 responses (Border Collie, Rough Collie, German Shepherd, Golden Retriever, Labrador Retriever, Standard Poodle), the behaviors eye contact with humans, enjoyment in interactions with human interaction, and name recognition demonstrated little variability across breeds, while asking for objects, giving/showing objects to humans, and attempts to direct humans' attention showed higher variability across these breeds. Breeds with genetically similar backgrounds had similar response distributions for owner reports of dog response to pointing. When considering these breeds according to the broad categories of "herders" and "retrievers," owners reported that the "herders" used more eye contact and vocalization, while the "retrievers" used more body contact. Information regarding social cognitive abilities in dogs provided by owner report suggest that there is variability across many social cognitive abilities in dogs and offers direction for further experimental investigations. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A method for retrieving endodontic or atypical nonendodontic separated instruments from the root canal: a report of two cases.

PubMed

Monteiro, Jardel Camilo do Carmo; Kuga, Milton Carlos; Dantas, Andrea Abi Rached; Jordão-Basso, Keren Cristina Fagundes; Keine, Katia Cristina; Ruchaya, Prashant Jay; Faria, Gisele; Leonardo, Renato de Toledo

2014-11-01

This clinical report presents a new method for retrieving separated instruments from the root canal with minimally invasive procedures. The presence of separated instrument in root canal may interfere in the endodontic treatment prognosis. There are several recommended methods to retrieve separated instruments, but some are difficult in clinically practice. This study describes two cases of separated instrument removal from the root canal using a stainless-steel prepared needle associated with a K-file. Case 1 presented a fractured gutta-percha condenser within the mandibular second premolar, it was separated during incorrect intracanal medication calcium hydroxide placement. Case 2 had a fractured sewing needle within the upper central incisor that the patient used to remove food debris from the root canal. After cervical preparation, the fractured instruments were fitted inside a prepared needle and then an endodontic instrument (#25 K-file) was adapted with clockwise turning motion between the needle inner wall and the fragment. The endodontic or atypical nonendodontic separated instrument may be easily pull on of the root canal using a single and low cost device. The methods for retrieving separated instruments from root canal are difficult and destructive procedures. The present case describes a simple method to solve this problem.

An iterative correction approach used to retrieve the refractive index of squid pigment aerosols

NASA Astrophysics Data System (ADS)

Dinneen, Sean R.; Deravi, Leila F.; Greenslade, Margaret E.

2018-03-01

Pigments localized within cephalopod chromatophores are important for dermal coloration. When isolated and used as materials outside of the animal, the pigments can be processed as aerosols, illustrating a potential application for spray-on-coatings. The optical features of the pigment aerosols are difficult to analyze and require a method to correct for the particle charging and solvent effects accumulated during the aerosolizing process. We describe a method to account for these effects using an innovative iterative approach tied to retrieved refractive index (RI) values. RI retrievals were obtained via the best fit between the corrected, experimentally observed extinction efficiencies compared to those calculated by Mie theory for a specific RI at selected sizes. In addition to these retrievals, the impact of solvent on the particles’ optical properties was also examined via the Maxwell-Garnett mixing rule. Ultimately, we obtained a pigment RI with a real portion (n) of 1.66 (±0.05) representing a lower limit and an imaginary portion (k) of 0.13 (±0.08)i representing an upper limit for the generated aerosols. Combined, this approach advances techniques used to retrieve RI values that benefits both atmospheric chemistry and bio-inspired materials.

Storage and retrieval properties of dual codes for pictures and words in recognition memory.

PubMed

Snodgrass, J G; McClure, P

1975-09-01

Storage and retrieval properties of pictures and words were studied within a recognition memory paradigm. Storage was manipulated by instructing subjects either to image or to verbalize to both picture and word stimuli during the study sequence. Retrieval was manipulated by representing a proportion of the old picture and word items in their opposite form during the recognition test (i.e., some old pictures were tested with their corresponding words and vice versa). Recognition performance for pictures was identical under the two instructional conditions, whereas recognition performance for words was markedly superior under the imagery instruction condition. It was suggested that subjects may engage in dual coding of simple pictures naturally, regardless of instructions, whereas dual coding of words may occur only under imagery instructions. The form of the test item had no effect on recognition performance for either type of stimulus and under either instructional condition. However, change of form of the test item markedly reduced item-by-item correlations between the two instructional conditions. It is tentatively proposed that retrieval is required in recognition, but that the effect of a form change is simply to make the retrieval process less consistent, not less efficient.

Assessment of urban pluvial flood risk and efficiency of adaptation options through simulations - A new generation of urban planning tools

NASA Astrophysics Data System (ADS)

Löwe, Roland; Urich, Christian; Sto. Domingo, Nina; Mark, Ole; Deletic, Ana; Arnbjerg-Nielsen, Karsten

2017-07-01

We present a new framework for flexible testing of flood risk adaptation strategies in a variety of urban development and climate scenarios. This framework couples the 1D-2D hydrodynamic simulation package MIKE FLOOD with the agent-based urban development model DAnCE4Water and provides the possibility to systematically test various flood risk adaptation measures ranging from large infrastructure changes over decentralised water management to urban planning policies. We have tested the framework in a case study in Melbourne, Australia considering 9 scenarios for urban development and climate and 32 potential combinations of flood adaptation measures. We found that the performance of adaptation measures strongly depended on the considered climate and urban development scenario and the other implementation measures implemented, suggesting that adaptive strategies are preferable over one-off investments. Urban planning policies proved to be an efficient means for the reduction of flood risk, while implementing property buyback and pipe increases in a guideline-oriented manner was too costly. Random variations in location and time point of urban development could have significant impact on flood risk and would in some cases outweigh the benefits of less efficient adaptation strategies. The results of our setup can serve as an input for robust decision making frameworks and thus support the identification of flood risk adaptation measures that are economically efficient and robust to variations of climate and urban layout.

Remote sensing applications to Missouri environmental resources information system

NASA Technical Reports Server (NTRS)

Myers, R. E.

1977-01-01

An efficient system for retrieval of remotely sensed data to be used by natural resources oriented agencies, and a natural resources data system that can meet the needs of state agencies were studied. To accomplish these objectives, natural resources data sources were identified, and study of systems already in operation which address themselves to the more efficient utilization of natural resources oriented data was prepared.

Rain Rate and DSD Retrievals at Kwajalein Atoll

NASA Astrophysics Data System (ADS)

Wolff, David; Marks, David; Tokay, Ali

2010-05-01

The dual-polarization weather radar on Kwajalein Atoll in the Republic of the Marshall Islands (KPOL) is one of the only full-time (24/7) operational S-band dual-polarimetric (DP) radars in the tropics. Using the DP data from KPOL, as well as data from a Joss-Waldvogel disdrometer on Kwajalein Island, algorithms for quality control, as well as calibration of reflectivity and differential reflectivity have been developed and adapted for application in a near real-time operational environment. Observations during light rain and drizzle show that KPOL measurements (since 2006) meet or exceed quality thresholds for these applications (as determined by consensus of the radar community). While the methodology for development of such applications is well documented, tuning of specific algorithms to a particular regime and observed raindrop size distributions requires a comprehensive testing and adjustment period to ensure high quality products. Upon application of these data quality techniques to the KPOL data, we have tested and compared several different rain retrieval algorithms. These include conventional Z-R, DP hybrid techniques, as well as polarimetrically-tuned Z-R described by Bringi et al. 2004. One of the major benefits of the polarimetrically tuned Z-R technique, is its ability to use the DP observations to retrieve key parameters of the drop size distribution (DSD), such as the median drop diameter, and the intercept and shape parameter of the assumed gammaDSD. We will show several such retrievals for different rain systems, as well as their distribution with height below the melting layer. From a physical validation perspective, such DSD parameter retrievals provide an important means to cross-validate microphysical parameterizations in GPM Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) retrieval algorithms.

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

NASA Technical Reports Server (NTRS)

Rokke, L.; Joiner, J.

1999-01-01

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Petaminer: Using ROOT for efficient data storage in MySQL database

NASA Astrophysics Data System (ADS)

Cranshaw, J.; Malon, D.; Vaniachine, A.; Fine, V.; Lauret, J.; Hamill, P.

2010-04-01

High Energy and Nuclear Physics (HENP) experiments store Petabytes of event data and Terabytes of calibration data in ROOT files. The Petaminer project is developing a custom MySQL storage engine to enable the MySQL query processor to directly access experimental data stored in ROOT files. Our project is addressing the problem of efficient navigation to PetaBytes of HENP experimental data described with event-level TAG metadata, which is required by data intensive physics communities such as the LHC and RHIC experiments. Physicists need to be able to compose a metadata query and rapidly retrieve the set of matching events, where improved efficiency will facilitate the discovery process by permitting rapid iterations of data evaluation and retrieval. Our custom MySQL storage engine enables the MySQL query processor to directly access TAG data stored in ROOT TTrees. As ROOT TTrees are column-oriented, reading them directly provides improved performance over traditional row-oriented TAG databases. Leveraging the flexible and powerful SQL query language to access data stored in ROOT TTrees, the Petaminer approach enables rich MySQL index-building capabilities for further performance optimization.

Evaluation of relational and NoSQL database architectures to manage genomic annotations.

PubMed

Schulz, Wade L; Nelson, Brent G; Felker, Donn K; Durant, Thomas J S; Torres, Richard

2016-12-01

While the adoption of next generation sequencing has rapidly expanded, the informatics infrastructure used to manage the data generated by this technology has not kept pace. Historically, relational databases have provided much of the framework for data storage and retrieval. Newer technologies based on NoSQL architectures may provide significant advantages in storage and query efficiency, thereby reducing the cost of data management. But their relative advantage when applied to biomedical data sets, such as genetic data, has not been characterized. To this end, we compared the storage, indexing, and query efficiency of a common relational database (MySQL), a document-oriented NoSQL database (MongoDB), and a relational database with NoSQL support (PostgreSQL). When used to store genomic annotations from the dbSNP database, we found the NoSQL architectures to outperform traditional, relational models for speed of data storage, indexing, and query retrieval in nearly every operation. These findings strongly support the use of novel database technologies to improve the efficiency of data management within the biological sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

The Hitchhiker's Guide to the Outer Solar System

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Quadrelli, Marco; Lantoine, Gregory; Backes, Paul; Lopez Ortega, Alejandro; Grip, Havard; Yen, Chen-Wan; Jewitt, David

2015-01-01

We propose a novel deep space propulsion method called the Comet Hitchhiker. The concept is to perform momentum exchange with small bodies (i.e., asteroid and comet) using an extendable/retrievable tether and a harpoon. Unlike previously proposed tethered fly-by, the use of extendable tether enables to change the relative speed with a target. Hence Hitchhiker would be a prospective means of providing orbit insertion deltaV, particularly for rendezvous missions to small bodies in the outer Solar System such as Kuiper belt objects and Centaurs, which are not easily manageable with chemical propulsion or solar electric propulsion. Furthermore, by applying regenerative brake during a hitchhike maneuver, a Hitchhiker can harvest energy. The stored energy can be used to make a departure from the target by quickly retrieving the tether, which we call a inverse hitchhike maneuver. By repeating hitchhike and inverse Hitchhike maneuvers, a Hitchhiker could perform a mission to rendezvous with multiple targets efficiently, which we call a multi-hitchhike mission. We derive the basic equation of Hitchhiker, namely the Space Hitchhike Equation, which relates the specific strength and mass fraction of tether to achievable ?V. We then perform detailed feasibility analysis through finite element simulations of tether as well as hypervelocity impact simulations of the harpoon using the Adaptive Mesh Refinement Objected-oriented C++ (AMROC) algorithm. The analysis results suggest that a hitchhike maneuver with deltaV = approximately 1.5km/s is feasible with flight proven materials such as Kevlar/Zylon tether and tungsten harpoon. A carbon nanotube tether, combined with diamond harpoon, would enable approximately 10 km/s hitchhike maneuver. Finally, we present two particular mission scenarios for Hitchhiker: Pluto rendezvous and a multi-hitchhike mission to the Themis family asteroids in the main belt.

Vegetation Monitoring with Gaussian Processes and Latent Force Models

NASA Astrophysics Data System (ADS)

Camps-Valls, Gustau; Svendsen, Daniel; Martino, Luca; Campos, Manuel; Luengo, David

2017-04-01

Monitoring vegetation by biophysical parameter retrieval from Earth observation data is a challenging problem, where machine learning is currently a key player. Neural networks, kernel methods, and Gaussian Process (GP) regression have excelled in parameter retrieval tasks at both local and global scales. GP regression is based on solid Bayesian statistics, yield efficient and accurate parameter estimates, and provides interesting advantages over competing machine learning approaches such as confidence intervals. However, GP models are hampered by lack of interpretability, that prevented the widespread adoption by a larger community. In this presentation we will summarize some of our latest developments to address this issue. We will review the main characteristics of GPs and their advantages in vegetation monitoring standard applications. Then, three advanced GP models will be introduced. First, we will derive sensitivity maps for the GP predictive function that allows us to obtain feature ranking from the model and to assess the influence of examples in the solution. Second, we will introduce a Joint GP (JGP) model that combines in situ measurements and simulated radiative transfer data in a single GP model. The JGP regression provides more sensible confidence intervals for the predictions, respects the physics of the underlying processes, and allows for transferability across time and space. Finally, a latent force model (LFM) for GP modeling that encodes ordinary differential equations to blend data-driven modeling and physical models of the system is presented. The LFM performs multi-output regression, adapts to the signal characteristics, is able to cope with missing data in the time series, and provides explicit latent functions that allow system analysis and evaluation. Empirical evidence of the performance of these models will be presented through illustrative examples.

Retrieving both phase and amplitude information of Green's functions by ambient seismic wave field cross-correlation: A case study with a limestone mine induced seismic event

NASA Astrophysics Data System (ADS)

Kwak, S.; Song, S. G.; Kim, G.; Shin, J. S.

2015-12-01

Recently many seismologists have paid attention to ambient seismic field, which is no more referred as noise and called as Earth's hum, but as useful signal to understand subsurface seismic velocity structure. It has also been demonstrated that empirical Green's functions can be constructed by retrieving both phase and amplitude information from ambient seismic field (Prieto and Beroza 2008). The constructed empirical Green's functions can be used to predict strong ground motions after focal depth and double-couple mechanism corrections (Denolle et al. 2013). They do not require detailed subsurface velocity model and intensive computation for ground motion simulation. In this study, we investigate the capability of predicting long period surface waves by the ambient seismic wave field with a seismic event of Mw 4.0, which occurred with a limestone mine collapse in South Korea on January 31, 2015. This limestone-mine event provides an excellent opportunity to test the efficiency of the ambient seismic wave field in retrieving both phase and amplitude information of Green's functions due to the single force mechanism of the collapse event. In other words, both focal depth and double-couple mechanism corrections are not required for this event. A broadband seismic station, which is about 5.4 km away from the mine event, is selected as a source station. Then surface waves retrieved from the ambient seismic wave field cross-correlation are compared with those generated by the event. Our preliminary results show some potential of the ambient seismic wave field in retrieving both phase and amplitude of Green's functions from a single force impulse source at the Earth's surface. More comprehensive analysis by increasing the time length of stacking may improve the results in further studies. We also aim to investigate the efficiency of retrieving the full empirical Green's functions with the 2007 Mw 4.6 Odaesan earthquake, which is one of the strongest earthquakes occurred in South Korea in the last decade.

Diffused holographic information storage and retrieval using photorefractive optical materials

NASA Astrophysics Data System (ADS)

McMillen, Deanna Kay

Holography offers a tremendous opportunity for dense information storage, theoretically one bit per cubic wavelength of material volume, with rapid retrieval, of up to thousands of pages of information simultaneously. However, many factors prevent the theoretical storage limit from being reached, including dynamic range problems and imperfections in recording materials. This research explores new ways of moving closer to practical holographic information storage and retrieval by altering the recording materials, in this case, photorefractive crystals, and by increasing the current storage capacity while improving the information retrieved. As an experimental example of the techniques developed, the information retrieved is the correlation peak from an optical recognition architecture, but the materials and methods developed are applicable to many other holographic information storage systems. Optical correlators can potentially solve any signal or image recognition problem. Military surveillance, fingerprint identification for law enforcement or employee identification, and video games are but a few examples of applications. A major obstacle keeping optical correlators from being universally accepted is the lack of a high quality, thick (high capacity) holographic recording material that operates with red or infrared wavelengths which are available from inexpensive diode lasers. This research addresses the problems from two positions: find a better material for use with diode lasers, and reduce the requirements placed on the material while maintaining an efficient and effective system. This research found that the solutions are new dopants introduced into photorefractive lithium niobate to improve wavelength sensitivities and the use of a novel inexpensive diffuser that reduces the dynamic range and optical element quality requirements (which reduces the cost) while improving performance. A uniquely doped set of 12 lithium niobate crystals was specified and procured for this research. Transmission spectra and diffraction efficiencies were measured for each of the crystals using wavelengths in the visible spectrum. The diffraction efficiency was increased by as much as two orders of magnitude by using a new dopant combination. A new optical diffuser was designed, modeled, fabricated, and tested as a means of improving storage capacity for angularly multiplexed holograms in photorefractive crystals. The diffuser reduced the dynamic range requirement by over three orders of magnitude, increased the storage capacity by more than 400%, and dramatically improved the correlation signals.

49 CFR 565.20 - Purpose and scope.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN... and physical requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of...

49 CFR 565.1 - Purpose and scope.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS General... requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.1 - Purpose and scope.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS General... requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.20 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN... and physical requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of...

49 CFR 565.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS General... requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.20 - Purpose and scope.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN... and physical requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of...

49 CFR 565.20 - Purpose and scope.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN... and physical requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of...

49 CFR 565.1 - Purpose and scope.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS General... requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

49 CFR 565.20 - Purpose and scope.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN... and physical requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of...

49 CFR 565.1 - Purpose and scope.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS General... requirements for a vehicle identification number (VIN) system and its installation to simplify vehicle identification information retrieval and to increase the accuracy and efficiency of vehicle recall campaigns. ...

A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

PubMed Central

Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah

2015-01-01

A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974

STAR adaptation of QR algorithm. [program for solving over-determined systems of linear equations

NASA Technical Reports Server (NTRS)

Shah, S. N.

1981-01-01

The QR algorithm used on a serial computer and executed on the Control Data Corporation 6000 Computer was adapted to execute efficiently on the Control Data STAR-100 computer. How the scalar program was adapted for the STAR-100 and why these adaptations yielded an efficient STAR program is described. Program listings of the old scalar version and the vectorized SL/1 version are presented in the appendices. Execution times for the two versions applied to the same system of linear equations, are compared.

A Knowledge-based System for Intelligent Support in Pharmacogenomics Evidence Assessment: Ontology-driven Evidence Representation and Retrieval.

PubMed

Lee, Chia-Ju; Devine, Beth; Tarczy-Hornoch, Peter

2017-01-01

Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care. To illustrate functionality, the system was piloted in the context of clopidogrel and warfarin pharmacogenomics. In contrast to existing pharmacogenomics knowledge bases, the developed system is the first to exploit the expressivity and reasoning power of logic-based representation formalism to enable unambiguous expression and automatic retrieval of pharmacogenomics evidence to support systematic review with meta-analysis.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

Impacts of Mass-dimension and Area-dimension relationships on retrieval ice particle effective radius from radar and lidar measurements

NASA Astrophysics Data System (ADS)

Ham, S. H.; Kato, S.; Rose, F. G.

2016-12-01

In the retrieval of ice clouds from Radar and Lidar Measurements, mass-Dimension (m-D) and Area-Dimension (A-D) relationships are often used to describe nonspherical ice particle shapes. This study analytically investigates how the assumption of m-D and A-D relationships affects retrieval of ice effective radius. We use gamma and lognormal particle distributions and integrate optical parameters over the size distribution. The effective radius is expressed as a function of radar reflectivity factor, visible extinction coefficient, and parameters describing m-D and A-D relationships. The analytic expressions are used for converting effective radius retrieved from one set of m-D and A-D relationships into that with another set of m-D and A-D, including plates, solid columns, bullets, and mixture of different habits. The conversion method can be used for consistent radiative transfer simulation with cloud retrieval algorithms. In addition, when we want to merge cloud effective radii retrieved from different m-D and A-D, the conversion method can be efficiently used to remove undesired biases caused by m-D and A-D assumptions. Furthermore, the sensitivity of the effective radius to m-D and A-D relationships can be quantified by taking the first derivative of the effective radius with respect to parameters expressing the m-D and A-D relationships.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation.

PubMed

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus F X

2007-08-30

Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from ftp://ftpmips.gsf.de/plants/apollo_webservice.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation

PubMed Central

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus FX

2007-01-01

Background Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. Results To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. Conclusion This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from . PMID:17760972

Star adaptation for two-algorithms used on serial computers

NASA Technical Reports Server (NTRS)

Howser, L. M.; Lambiotte, J. J., Jr.

1974-01-01

Two representative algorithms used on a serial computer and presently executed on the Control Data Corporation 6000 computer were adapted to execute efficiently on the Control Data STAR-100 computer. Gaussian elimination for the solution of simultaneous linear equations and the Gauss-Legendre quadrature formula for the approximation of an integral are the two algorithms discussed. A description is given of how the programs were adapted for STAR and why these adaptations were necessary to obtain an efficient STAR program. Some points to consider when adapting an algorithm for STAR are discussed. Program listings of the 6000 version coded in 6000 FORTRAN, the adapted STAR version coded in 6000 FORTRAN, and the STAR version coded in STAR FORTRAN are presented in the appendices.

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1997-01-01

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

The medial prefrontal cortex is involved in spatial memory retrieval under partial-cue conditions.

PubMed

Jo, Yong Sang; Park, Eun Hye; Kim, Il Hwan; Park, Soon Kwon; Kim, Hyun; Kim, Hyun Taek; Choi, June-Seek

2007-12-05

Brain circuits involved in pattern completion, or retrieval of memory from fragmented cues, were investigated. Using different versions of the Morris water maze, we explored the roles of the CA3 subregion of the hippocampus and the medial prefrontal cortex (mPFC) in spatial memory retrieval under various conditions. In a hidden platform task, both CA3 and mPFC lesions disrupted memory retrieval under partial-cue, but not under full-cue, conditions. For a delayed matching-to-place task, CA3 lesions produced a deficit in both forming and recalling spatial working memory regardless of extramaze cue conditions. In contrast, damage to mPFC impaired memory retrieval only when a fraction of cues was available. To corroborate the lesion study, we examined the expression of the immediate early gene c-fos in mPFC and the hippocampus. After training of spatial reference memory in full-cue conditions for 6 d, the same training procedure in the absence of all cues except one increased the number of Fos-immunoreactive cells in mPFC and CA3. Furthermore, mPFC inactivation with muscimol, a GABA agonist, blocked memory retrieval in the degraded-cue environment. However, mPFC-lesioned animals initially trained in a single-cue environment had no difficulty in retrieving spatial memory when the number of cues was increased, demonstrating that contextual change per se did not impair the behavioral performance of the mPFC-lesioned animals. Together, these findings strongly suggest that pattern completion requires interactions between mPFC and the hippocampus, in which mPFC plays significant roles in retrieving spatial information maintained in the hippocampus for efficient navigation.

Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Bruegge, Carol J.; Dubovik, Oleg

2017-07-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high-altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from nine viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov-chain/adding-doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI data sets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI preengineering test flight. The retrieval results including aerosol optical depth, single-scattering albedo, aerosol size and refractive index are compared with Aerosol Robotic Network reference data. We identify the best angular combinations for 2, 3, 5, and 7 angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements and target revisits in constraining aerosol property and surface reflection retrieval.

Potentiating mGluR5 function with a positive allosteric modulator enhances adaptive learning.

PubMed

Xu, Jian; Zhu, Yongling; Kraniotis, Stephen; He, Qionger; Marshall, John J; Nomura, Toshihiro; Stauffer, Shaun R; Lindsley, Craig W; Conn, P Jeffrey; Contractor, Anis

2013-07-18

Metabotropic glutamate receptor 5 (mGluR5) plays important roles in modulating neural activity and plasticity and has been associated with several neuropathological disorders. Previous work has shown that genetic ablation or pharmacological inhibition of mGluR5 disrupts fear extinction and spatial reversal learning, suggesting that mGluR5 signaling is required for different forms of adaptive learning. Here, we tested whether ADX47273, a selective positive allosteric modulator (PAM) of mGluR5, can enhance adaptive learning in mice. We found that systemic administration of the ADX47273 enhanced reversal learning in the Morris Water Maze, an adaptive task. In addition, we found that ADX47273 had no effect on single-session and multi-session extinction, but administration of ADX47273 after a single retrieval trial enhanced subsequent fear extinction learning. Together these results demonstrate a role for mGluR5 signaling in adaptive learning, and suggest that mGluR5 PAMs represent a viable strategy for treatment of maladaptive learning and for improving behavioral flexibility.

Potentiating mGluR5 function with a positive allosteric modulator enhances adaptive learning

PubMed Central

Xu, Jian; Zhu, Yongling; Kraniotis, Stephen; He, Qionger; Marshall, John J.; Nomura, Toshihiro; Stauffer, Shaun R.; Lindsley, Craig W.; Conn, P. Jeffrey; Contractor, Anis

2013-01-01

Metabotropic glutamate receptor 5 (mGluR5) plays important roles in modulating neural activity and plasticity and has been associated with several neuropathological disorders. Previous work has shown that genetic ablation or pharmacological inhibition of mGluR5 disrupts fear extinction and spatial reversal learning, suggesting that mGluR5 signaling is required for different forms of adaptive learning. Here, we tested whether ADX47273, a selective positive allosteric modulator (PAM) of mGluR5, can enhance adaptive learning in mice. We found that systemic administration of the ADX47273 enhanced reversal learning in the Morris Water Maze, an adaptive task. In addition, we found that ADX47273 had no effect on single-session and multi-session extinction, but administration of ADX47273 after a single retrieval trial enhanced subsequent fear extinction learning. Together these results demonstrate a role for mGluR5 signaling in adaptive learning, and suggest that mGluR5 PAMs represent a viable strategy for treatment of maladaptive learning and for improving behavioral flexibility. PMID:23869026

Study of Navy Recruiting Simulation Tool

DTIC Science & Technology

2010-03-01

thinking” (p. 205). E. ROLE-PLAY Role-play “is a technology for intensifying and accelerating learning” (Blatner, 2009, p. 18). Adapted from psychodrama ...American Society of Group Psychotherapy and Psychodrama . (n.d.). Psychodrama . Retrieved March 5, 2010, from National Coalition of Creative Arts Therapies...nl.edu: http://www.nl.edu/academics/cas/ace/facultypapers/StephenBrookfield_AdultLear ning.cfm 106 Casey, A. M. (2001). Psychodrama : Applied role

Affordability Tradeoffs Under Uncertainty Using Epoch-Era Analysis

DTIC Science & Technology

2013-09-30

Procedia Computer Science , Retrieved from: http://www.elsevier.com Bobinis, J., Haimowitz, J., Tuttle, P., & Garrison, C. (2012, October). Affordability...commercial products. Dr. Rhodes received her PhD in Systems Science from the T.J. Watson School of Engineering at Binghamton University. She serves on...components, evaluate feedback, and be adaptive to evolving system behaviors . As affordability is a concept evaluated over time, such a method can

MATRIS Indexing and Retrieval Thesaurus (MIRT): Hierarchical List of Indexing Terms

DTIC Science & Technology

1994-08-01

Adaptability i Fiqcg Dissatisfaction Fiqci Personal goals / objectives Fiqck Health I Fiqcm Religious values Fiqco Socialization Fiqcq Self esteem Fiqcs...Military-civilian mix Bmi Officer-enlisted mix Bink Volunteer force Bmm Aging workforce I Bmo Grade distribution Bmq Occupational / career mix Bms...Ehd Peer instruction Ehe Tutoring Ehg Individualized instruction Ehga *UF Learner-centered instruction Ehga *UF Self -paced instruction Ehh Programmed

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

Experimental determination of pore shapes using phase retrieval from q -space NMR diffraction

NASA Astrophysics Data System (ADS)

Demberg, Kerstin; Laun, Frederik Bernd; Bertleff, Marco; Bachert, Peter; Kuder, Tristan Anselm

2018-05-01

This paper presents an approach to solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method that allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for investigation of the microstructure of biological tissue and porous materials. Classical q -space imaging composed of two short diffusion-encoding gradient pulses yields, analogously to diffraction experiments, the modulus squared of the Fourier transform of the pore image which entails an inversion problem: An unambiguous reconstruction of the pore image requires both magnitude and phase. Here the phase information is recovered from the Fourier modulus by applying a phase retrieval algorithm. This allows omitting experimentally challenging phase measurements using specialized temporal gradient profiles. A combination of the hybrid input-output algorithm and the error reduction algorithm was used with dynamically adapting support (shrinkwrap extension). No a priori knowledge on the pore shape was fed to the algorithm except for a finite pore extent. The phase retrieval approach proved successful for simulated data with and without noise and was validated in phantom experiments with well-defined pores using hyperpolarized xenon gas.

The remains of the day in dissociative amnesia.

PubMed

Staniloiu, Angelica; Markowitsch, Hans J

2012-04-10

Memory is not a unity, but is divided along a content axis and a time axis, respectively. Along the content dimension, five long-term memory systems are described, according to their hierarchical ontogenetic and phylogenetic organization. These memory systems are assumed to be accompanied by different levels of consciousness. While encoding is based on a hierarchical arrangement of memory systems from procedural to episodic-autobiographical memory, retrieval allows independence in the sense that no matter how information is encoded, it can be retrieved in any memory system. Thus, we illustrate the relations between various long-term memory systems by reviewing the spectrum of abnormalities in mnemonic processing that may arise in the dissociative amnesia-a condition that is usually characterized by a retrieval blockade of episodic-autobiographical memories and occurs in the context of psychological trauma, without evidence of brain damage on conventional structural imaging. Furthermore, we comment on the functions of implicit memories in guiding and even adaptively molding the behavior of patients with dissociative amnesia and preserving, in the absence of autonoetic consciousness, the so-called "internal coherence of life".

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2009-01-01

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

Experimental determination of pore shapes using phase retrieval from q-space NMR diffraction.

PubMed

Demberg, Kerstin; Laun, Frederik Bernd; Bertleff, Marco; Bachert, Peter; Kuder, Tristan Anselm

2018-05-01

This paper presents an approach to solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method that allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for investigation of the microstructure of biological tissue and porous materials. Classical q-space imaging composed of two short diffusion-encoding gradient pulses yields, analogously to diffraction experiments, the modulus squared of the Fourier transform of the pore image which entails an inversion problem: An unambiguous reconstruction of the pore image requires both magnitude and phase. Here the phase information is recovered from the Fourier modulus by applying a phase retrieval algorithm. This allows omitting experimentally challenging phase measurements using specialized temporal gradient profiles. A combination of the hybrid input-output algorithm and the error reduction algorithm was used with dynamically adapting support (shrinkwrap extension). No a priori knowledge on the pore shape was fed to the algorithm except for a finite pore extent. The phase retrieval approach proved successful for simulated data with and without noise and was validated in phantom experiments with well-defined pores using hyperpolarized xenon gas.

The Remains of the Day in Dissociative Amnesia

PubMed Central

Staniloiu, Angelica; Markowitsch, Hans J.

2012-01-01

Memory is not a unity, but is divided along a content axis and a time axis, respectively. Along the content dimension, five long-term memory systems are described, according to their hierarchical ontogenetic and phylogenetic organization. These memory systems are assumed to be accompanied by different levels of consciousness. While encoding is based on a hierarchical arrangement of memory systems from procedural to episodic-autobiographical memory, retrieval allows independence in the sense that no matter how information is encoded, it can be retrieved in any memory system. Thus, we illustrate the relations between various long-term memory systems by reviewing the spectrum of abnormalities in mnemonic processing that may arise in the dissociative amnesia—a condition that is usually characterized by a retrieval blockade of episodic-autobiographical memories and occurs in the context of psychological trauma, without evidence of brain damage on conventional structural imaging. Furthermore, we comment on the functions of implicit memories in guiding and even adaptively molding the behavior of patients with dissociative amnesia and preserving, in the absence of autonoetic consciousness, the so-called “internal coherence of life”. PMID:24962768

Two biomechanical strategies for locomotor adaptation to split-belt treadmill walking in subjects with and without transtibial amputation.

PubMed

Selgrade, Brian P; Toney, Megan E; Chang, Young-Hui

2017-02-28

Locomotor adaptation is commonly studied using split-belt treadmill walking, in which each foot is placed on a belt moving at a different speed. As subjects adapt to split-belt walking, they reduce metabolic power, but the biomechanical mechanism behind this improved efficiency is unknown. Analyzing mechanical work performed by the legs and joints during split-belt adaptation could reveal this mechanism. Because ankle work in the step-to-step transition is more efficient than hip work, we hypothesized that control subjects would reduce hip work on the fast belt and increase ankle work during the step-to-step transition as they adapted. We further hypothesized that subjects with unilateral, trans-tibial amputation would instead increase propulsive work from their intact leg on the slow belt. Control subjects reduced hip work and shifted more ankle work to the step-to-step transition, supporting our hypothesis. Contrary to our second hypothesis, intact leg work, ankle work and hip work in amputees were unchanged during adaptation. Furthermore, all subjects increased collisional energy loss on the fast belt, but did not increase propulsive work. This was possible because subjects moved further backward during fast leg single support in late adaptation than in early adaptation, compensating by reducing backward movement in slow leg single support. In summary, subjects used two strategies to improve mechanical efficiency in split-belt walking adaptation: a CoM displacement strategy that allows for less forward propulsion on the fast belt; and, an ankle timing strategy that allows efficient ankle work in the step-to-step transition to increase while reducing inefficient hip work. Copyright © 2017 Elsevier Ltd. All rights reserved.

Melody Alignment and Similarity Metric for Content-Based Music Retrieval

NASA Astrophysics Data System (ADS)

Zhu, Yongwei; Kankanhalli, Mohan S.

2003-01-01

Music query-by-humming has attracted much research interest recently. It is a challenging problem since the hummed query inevitably contains much variation and inaccuracy. Furthermore, the similarity computation between the query tune and the reference melody is not easy due to the difficulty in ensuring proper alignment. This is because the query tune can be rendered at an unknown speed and it is usually an arbitrary subsequence of the target reference melody. Many of the previous methods, which adopt note segmentation and string matching, suffer drastically from the errors in the note segmentation, which affects retrieval accuracy and efficiency. Some methods solve the alignment issue by controlling the speed of the articulation of queries, which is inconvenient because it forces users to hum along a metronome. Some other techniques introduce arbitrary rescaling in time but this is computationally very inefficient. In this paper, we introduce a melody alignment technique, which addresses the robustness and efficiency issues. We also present a new melody similarity metric, which is performed directly on melody contours of the query data. This approach cleanly separates the alignment and similarity measurement in the search process. We show how to robustly and efficiently align the query melody with the reference melodies and how to measure the similarity subsequently. We have carried out extensive experiments. Our melody alignment method can reduce the matching candidate to 1.7% with 95% correct alignment rate. The overall retrieval system achieved 80% recall in the top 10 rank list. The results demonstrate the robustness and effectiveness the proposed methods.

Smart Polyacrylonitrile (PAN) Nanofibers with Thermal Energy Storage and Retrieval Functionality

NASA Astrophysics Data System (ADS)

Cherry, De'Andre James

Phase change materials (PCMs) are generally substances with a high heat of fusion in the process of solid to liquid phase change. The nature of PCMs make them efficient materials to store and retrieve large amounts of thermal energy. Presently, high efficiency thermal energy storage/retrieval in applications where flexibility and space saving are required, such as smart textiles, still remains as a challenge. In this study, lauric acid (LA) and myristic acid (MA) were combined to prepare a specific binary fatty acid eutectic (LA-MA) with a melting point near the operating body temperature of a human being and then encapsulated in polyacrylonitrile (PAN) nanofibers through the electrospinning technique. Functionalized PCM-enhanced PAN nanofibers containing LA-MA at 30%, 50%, 70% and 100% of the weight of the PAN were successfully synthesized. The morphological structures and thermal energy storage capacity of the PCM-enhanced PAN nanofibers were characterized by electron microscopy (EM) and differential scanning calorimetry (DSC). The novel PCM-enhanced PAN nanofibers maintained their cylindrical fiber morphology after multiple heating-cooling cycles and retained their latent heat storage functionality. Thus, it is envisioned that the prepared PCM-enhanced PAN nanofibers will find use in applications such as smart textiles where temperature regulation functionality is required.

Occam's razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2005-01-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

A new pattern associative memory model for image recognition based on Hebb rules and dot product

NASA Astrophysics Data System (ADS)

Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

2018-04-01

A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

Occam"s razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2004-12-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

Integrated Power Adapter: Isolated Converter with Integrated Passives and Low Material Stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2010-09-01

ADEPT Project: CPES at Virginia Tech is developing an extremely efficient power converter that could be used in power adapters for small, lightweight laptops and other types of mobile electronic devices. Power adapters convert electrical energy into useable power for an electronic device, and they currently waste a lot of energy when they are plugged into an outlet to power up. CPES at Virginia Tech is integrating high-density capacitors, new magnetic materials, high-frequency integrated circuits, and a constant-flux transformer to create its efficient power converter. The high-density capacitors enable the power adapter to store more energy. The new magnetic materialsmore » also increase energy storage, and they can be precisely dispensed using a low-cost ink-jet printer which keeps costs down. The high-frequency integrated circuits can handle more power, and they can handle it more efficiently. And, the constant-flux transformer processes a consistent flow of electrical current, which makes the converter more efficient.« less

Learning semantic and visual similarity for endomicroscopy video retrieval.

PubMed

Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them. In our resulting retrieval system, we decide to use visual signatures for perceived similarity learning and retrieval, and semantic signatures for the output of an additional information, expressed in the endoscopist own language, which provides a relevant semantic translation of the visual retrieval outputs.