Cover times of random searches
NASA Astrophysics Data System (ADS)
Chupeau, Marie; Bénichou, Olivier; Voituriez, Raphaël
2015-10-01
How long must one undertake a random search to visit all sites of a given domain? This time, known as the cover time, is a key observable to quantify the efficiency of exhaustive searches, which require a complete exploration of an area and not only the discovery of a single target. Examples range from immune-system cells chasing pathogens to animals harvesting resources, from robotic exploration for cleaning or demining to the task of improving search algorithms. Despite its broad relevance, the cover time has remained elusive and so far explicit results have been scarce and mostly limited to regular random walks. Here we determine the full distribution of the cover time for a broad range of random search processes, including Lévy strategies, intermittent strategies, persistent random walks and random walks on complex networks, and reveal its universal features. We show that for all these examples the mean cover time can be minimized, and that the corresponding optimal strategies also minimize the mean search time for a single target, unambiguously pointing towards their robustness.
A parallel algorithm for random searches
NASA Astrophysics Data System (ADS)
Wosniack, M. E.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2015-11-01
We discuss a parallelization procedure for a two-dimensional random search of a single individual, a typical sequential process. To assure the same features of the sequential random search in the parallel version, we analyze the former spatial patterns of the encountered targets for different search strategies and densities of homogeneously distributed targets. We identify a lognormal tendency for the distribution of distances between consecutively detected targets. Then, by assigning the distinct mean and standard deviation of this distribution for each corresponding configuration in the parallel simulations (constituted by parallel random walkers), we are able to recover important statistical properties, e.g., the target detection efficiency, of the original problem. The proposed parallel approach presents a speedup of nearly one order of magnitude compared with the sequential implementation. This algorithm can be easily adapted to different instances, as searches in three dimensions. Its possible range of applicability covers problems in areas as diverse as automated computer searchers in high-capacity databases and animal foraging.
Adaptation and visual search in mammographic images.
Kompaniez-Dunigan, Elysse; Abbey, Craig K; Boone, John M; Webster, Michael A
2015-05-01
Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the images. The stimuli were randomly selected sections from normal mammograms previously classified with BIRADS Density scores of "fatty" versus "dense," corresponding to differences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in visual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corresponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was randomly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background texture. Our results are consistent with the hypothesis that adaptation allows observers to more effectively suppress the specific structure of the background, thereby heightening visual salience and search efficiency.
Robust local search for spacecraft operations using adaptive noise
NASA Technical Reports Server (NTRS)
Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve
2004-01-01
Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.
NASA Technical Reports Server (NTRS)
Kester, DO; Bontekoe, Tj. Romke
1994-01-01
In order to make the best high resolution images of IRAS data it is necessary to incorporate any knowledge about the instrument into a model: the IRAS model. This is necessary since every remaining systematic effect will be amplified by any high resolution technique into spurious artifacts in the images. The search for random noise is in fact the never-ending quest for better quality results, and can only be obtained by better models. The Dutch high-resolution effort has resulted in HIRAS which drives the MEMSYS5 algorithm. It is specifically designed for IRAS image construction. A detailed description of HIRAS with many results is in preparation. In this paper we emphasize many of the instrumental effects incorporated in the IRAS model, including our improved 100 micron IRAS response functions.
Searching for nodes in random graphs.
Lancaster, David
2011-11-01
We consider the problem of searching for a node on a labeled random graph according to a greedy algorithm that selects a route to the desired node using metric information on the graph. Motivated by peer-to-peer networks two types of random graph are proposed with properties particularly amenable to this kind of algorithm. We derive equations for the probability that the search is successful and also study the number of hops required, finding both numerical and analytic evidence of a transition as the number of links is varied.
Chasing information to search in random environments
NASA Astrophysics Data System (ADS)
Masson, J.-B.; Bailly Bechet, M.; Vergassola, M.
2009-10-01
We discuss search strategies for finding sources of particles transported in a random environment and detected by the searcher(s). The mixing of the particles in the environment is supposed to be strong, so that strategies based on concentration-gradient ascent are not viable. These dilute conditions are common in natural environments typical of searches performed by insects and birds. The sparseness of the detections constitutes the major stumbling block in developing efficient olfactory robots to detect mines, chemical leaks, etc. We first discuss a search strategy, 'infotaxis', recently introduced for the search of a single source by a single robot. Decisions are made by locally maximizing the rate of acquisition of information on the location of the source and they balance exploration and exploitation. We present numerical simulations demonstrating the efficiency of the method and, most importantly, its robustness to lack of detailed modeling of the transport of particles in the random environment. We then introduce a novel formulation of infotaxis for collective searches where a swarm of robots is available and must be coordinated. Gains in the search time are impressive and the method can be further generalized to deal with conflicts arising in the identification of multiple sources.
Parameter adaptive estimation of random processes
NASA Technical Reports Server (NTRS)
Caglayan, A. K.; Vanlandingham, H. F.
1975-01-01
This paper is concerned with the parameter adaptive least squares estimation of random processes. The main result is a general representation theorem for the conditional expectation of a random variable on a product probability space. Using this theorem along with the general likelihood ratio expression, the least squares estimate of the process is found in terms of the parameter conditioned estimates. The stochastic differential for the a posteriori probability and the stochastic differential equation for the a posteriori density are found by using simple stochastic calculus on the representations obtained. The results are specialized to the case when the parameter has a discrete distribution. The results can be used to construct an implementable recursive estimator for certain types of nonlinear filtering problems. This is illustrated by some simple examples.
NASA Astrophysics Data System (ADS)
da Luz, Marcos G. E.; Grosberg, Alexander; Raposo, Ernesto P.; Viswanathan, Gandhi M.
2009-10-01
`I can't find my keys!' Who hasn't gone through this experience when leaving, in a hurry, to attend to some urgent matter? The keys could be in many different places. Unless one remembers where he or she has left the keys, the only solution is to look around, more or less randomly. Random searches are common because in many cases the locations of the specific targets are not known a priori. Indeed, such problems have been discussed in diverse contexts, attracting the interest of scientists from many fields, for example: the dynamical or stochastic search for a stable minimum in a complex energy landscape, relevant to systems such as glasses, protein (folding), and others; oil recovery from mature reservoirs; proteins searching for their specific target sites on DNA; animal foraging; survival at the edge of extinction due to low availability of energetic resources; automated searches of registers in high-capacity databases, search engine (e.g., `crawlers') that explore the internet; and even pizza delivery in a jammed traffic system of a medium-size town. In this way, the subject is interesting, challenging and has recently become an important scientific area of investigation. Although the applications are diverse, the underlying physical mechanisms are the same which will become clear in this special issue. Moreover, the inherent complexity of the problem, the abundance of ideas and methods found in this growing interdisciplinary field of research is studied in many areas of physics. In particular, the concepts and methods of statistical mechanics are particularly useful to the study of random searches. On one hand, it centres on how to find the global or local maxima of search efficiency functions with incomplete information. This is, of course, related to the long tradition in physics of using different conceptual and mathematical tools, such as variational methods, to extremize relevant quantities, e.g., energy, entropy and action. Such ideas and approaches are
Adaptive Random Testing with Combinatorial Input Domain
Lu, Yansheng
2014-01-01
Random testing (RT) is a fundamental testing technique to assess software reliability, by simply selecting test cases in a random manner from the whole input domain. As an enhancement of RT, adaptive random testing (ART) has better failure-detection capability and has been widely applied in different scenarios, such as numerical programs, some object-oriented programs, and mobile applications. However, not much work has been done on the effectiveness of ART for the programs with combinatorial input domain (i.e., the set of categorical data). To extend the ideas to the testing for combinatorial input domain, we have adopted different similarity measures that are widely used for categorical data in data mining and have proposed two similarity measures based on interaction coverage. Then, we propose a new version named ART-CID as an extension of ART in combinatorial input domain, which selects an element from categorical data as the next test case such that it has the lowest similarity against already generated test cases. Experimental results show that ART-CID generally performs better than RT, with respect to different evaluation metrics. PMID:24772036
Adaptive cuckoo search algorithm for unconstrained optimization.
Ong, Pauline
2014-01-01
Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases. PMID:25298971
Adaptive cuckoo search algorithm for unconstrained optimization.
Ong, Pauline
2014-01-01
Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases.
Bayesian response adaptive randomization using longitudinal outcomes.
Hatayama, Tomoyoshi; Morita, Satoshi; Sakamaki, Kentaro
2015-01-01
The response adaptive randomization (RAR) method is used to increase the number of patients assigned to more efficacious treatment arms in clinical trials. In many trials evaluating longitudinal patient outcomes, RAR methods based only on the final measurement may not benefit significantly from RAR because of its delayed initiation. We propose a Bayesian RAR method to improve RAR performance by accounting for longitudinal patient outcomes (longitudinal RAR). We use a Bayesian linear mixed effects model to analyze longitudinal continuous patient outcomes for calculating a patient allocation probability. In addition, we aim to mitigate the loss of statistical power because of large patient allocation imbalances by embedding adjusters into the patient allocation probability calculation. Using extensive simulation we compared the operating characteristics of our proposed longitudinal RAR method with those of the RAR method based only on the final measurement and with an equal randomization method. Simulation results showed that our proposed longitudinal RAR method assigned more patients to the presumably superior treatment arm compared with the other two methods. In addition, the embedded adjuster effectively worked to prevent extreme patient allocation imbalances. However, our proposed method may not function adequately when the treatment effect difference is moderate or less, and still needs to be modified to deal with unexpectedly large departures from the presumed longitudinal data model.
WORTH ADAPTING? REVISITING THE USEFULNESS OF OUTCOME-ADAPTIVE RANDOMIZATION
Lee, J. Jack; Chen, Nan; Yin, Guosheng
2012-01-01
Outcome-adaptive randomization (AR) allocates more patients to the better treatments as the information accumulates in the trial. Is it worth to apply outcome-AR in clinical trials? Different views permeate the medical and statistical communities. We provide additional insights to the question by conducting extensive simulation studies. Trials are designed to maintain the type I error rate, achieve a specified power, and provide better treatment to patients. Generally speaking, equal randomization (ER) requires a smaller sample size and yields a smaller number of non-responders than AR by controlling type I and type II errors. Conversely, AR produces a higher overall response rate than ER with or without expanding the trial to the same maximum sample size. When there exist substantial treatment differences, AR can yield a higher overall response rate as well as a lower average sample size and a smaller number of non-responders. Similar results are found for the survival endpoint. The differences between AR and ER quickly diminish with early stopping of a trial due to efficacy or futility. In summary, ER maintains balanced allocation throughout the trial and reaches the specified statistical power with a smaller number of patients in the trial. If the trial’s result is positive, ER may lead to early approval of the treatment. AR focuses on treating patients best in the trial. AR may be preferred when the difference in efficacy between treatments is large or when limited patients are available. PMID:22753588
NASA Astrophysics Data System (ADS)
da Luz, Marcos G. E.; Grosberg, Alexander; Raposo, Ernesto P.; Viswanathan, Gandhi M.
2009-10-01
`I can't find my keys!' Who hasn't gone through this experience when leaving, in a hurry, to attend to some urgent matter? The keys could be in many different places. Unless one remembers where he or she has left the keys, the only solution is to look around, more or less randomly. Random searches are common because in many cases the locations of the specific targets are not known a priori. Indeed, such problems have been discussed in diverse contexts, attracting the interest of scientists from many fields, for example: the dynamical or stochastic search for a stable minimum in a complex energy landscape, relevant to systems such as glasses, protein (folding), and others; oil recovery from mature reservoirs; proteins searching for their specific target sites on DNA; animal foraging; survival at the edge of extinction due to low availability of energetic resources; automated searches of registers in high-capacity databases, search engine (e.g., `crawlers') that explore the internet; and even pizza delivery in a jammed traffic system of a medium-size town. In this way, the subject is interesting, challenging and has recently become an important scientific area of investigation. Although the applications are diverse, the underlying physical mechanisms are the same which will become clear in this special issue. Moreover, the inherent complexity of the problem, the abundance of ideas and methods found in this growing interdisciplinary field of research is studied in many areas of physics. In particular, the concepts and methods of statistical mechanics are particularly useful to the study of random searches. On one hand, it centres on how to find the global or local maxima of search efficiency functions with incomplete information. This is, of course, related to the long tradition in physics of using different conceptual and mathematical tools, such as variational methods, to extremize relevant quantities, e.g., energy, entropy and action. Such ideas and approaches are
Randomized discrepancy bounded local search for transmission expansion planning
Bent, Russell W; Daniel, William B
2010-11-23
In recent years the transmission network expansion planning problem (TNEP) has become increasingly complex. As the TNEP is a non-linear and non-convex optimization problem, researchers have traditionally focused on approximate models of power flows to solve the TNEP. Existing approaches are often tightly coupled to the approximation choice. Until recently these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (e.g. large amounts of limited control, renewable generation) and necessitates new approaches. Recent work on deterministic Discrepancy Bounded Local Search (DBLS) has shown it to be quite effective in addressing this question. DBLS encapsulates the complexity of power flow modeling in a black box that may be queried for information about the quality of proposed expansions. In this paper, we propose a randomization strategy that builds on DBLS and dramatically increases the computational efficiency of the algorithm.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Decoherence in optimized quantum random-walk search algorithm
NASA Astrophysics Data System (ADS)
Zhang, Yu-Chao; Bao, Wan-Su; Wang, Xiang; Fu, Xiang-Qun
2015-08-01
This paper investigates the effects of decoherence generated by broken-link-type noise in the hypercube on an optimized quantum random-walk search algorithm. When the hypercube occurs with random broken links, the optimized quantum random-walk search algorithm with decoherence is depicted through defining the shift operator which includes the possibility of broken links. For a given database size, we obtain the maximum success rate of the algorithm and the required number of iterations through numerical simulations and analysis when the algorithm is in the presence of decoherence. Then the computational complexity of the algorithm with decoherence is obtained. The results show that the ultimate effect of broken-link-type decoherence on the optimized quantum random-walk search algorithm is negative. Project supported by the National Basic Research Program of China (Grant No. 2013CB338002).
Particle Swarm Based Collective Searching Model for Adaptive Environment
Cui, Xiaohui; Patton, Robert M; Potok, Thomas E; Treadwell, Jim N
2008-01-01
This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.
Particle Swarm Based Collective Searching Model for Adaptive Environment
Cui, Xiaohui; Patton, Robert M; Potok, Thomas E; Treadwell, Jim N
2007-01-01
This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.
Parameter identification using a creeping-random-search algorithm
NASA Technical Reports Server (NTRS)
Parrish, R. V.
1971-01-01
A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.
The Search for the Adaptable ICT Student
ERIC Educational Resources Information Center
Van Der Vyver, Glen
2009-01-01
The "new" ICT professional should be an articulate problem-solver who understands business and technology, in particular how technology can solve business problems. Furthermore, the ideal ICT student should be adaptable. The adaptable student embraces change, learns quickly, understands the job market, thrives on variety, is autonomous, predicts…
Guided Text Search Using Adaptive Visual Analytics
Steed, Chad A; Symons, Christopher T; Senter, James K; DeNap, Frank A
2012-10-01
This research demonstrates the promise of augmenting interactive visualizations with semi- supervised machine learning techniques to improve the discovery of significant associations and insights in the search and analysis of textual information. More specifically, we have developed a system called Gryffin that hosts a unique collection of techniques that facilitate individualized investigative search pertaining to an ever-changing set of analytical questions over an indexed collection of open-source documents related to critical national infrastructure. The Gryffin client hosts dynamic displays of the search results via focus+context record listings, temporal timelines, term-frequency views, and multiple coordinate views. Furthermore, as the analyst interacts with the display, the interactions are recorded and used to label the search records. These labeled records are then used to drive semi-supervised machine learning algorithms that re-rank the unlabeled search records such that potentially relevant records are moved to the top of the record listing. Gryffin is described in the context of the daily tasks encountered at the US Department of Homeland Security s Fusion Center, with whom we are collaborating in its development. The resulting system is capable of addressing the analysts information overload that can be directly attributed to the deluge of information that must be addressed in the search and investigative analysis of textual information.
Adaptive importance sampling of random walks on continuous state spaces
Baggerly, K.; Cox, D.; Picard, R.
1998-11-01
The authors consider adaptive importance sampling for a random walk with scoring in a general state space. Conditions under which exponential convergence occurs to the zero-variance solution are reviewed. These results generalize previous work for finite, discrete state spaces in Kollman (1993) and in Kollman, Baggerly, Cox, and Picard (1996). This paper is intended for nonstatisticians and includes considerable explanatory material.
Adaptive Designs for Randomized Trials in Public Health
Brown, C. Hendricks; Have, Thomas R. Ten; Jo, Booil; Dagne, Getachew; Wyman, Peter A.; Muthén, Bengt; Gibbons, Robert D.
2009-01-01
In this article, we present a discussion of two general ways in which the traditional randomized trial can be modified or adapted in response to the data being collected. We use the term adaptive design to refer to a trial in which characteristics of the study itself, such as the proportion assigned to active intervention versus control, change during the trial in response to data being collected. The term adaptive sequence of trials refers to a decision-making process that fundamentally informs the conceptualization and conduct of each new trial with the results of previous trials. Our discussion below investigates the utility of these two types of adaptations for public health evaluations. Examples are provided to illustrate how adaptation can be used in practice. From these case studies, we discuss whether such evaluations can or should be analyzed as if they were formal randomized trials, and we discuss practical as well as ethical issues arising in the conduct of these new-generation trials. PMID:19296774
Dementia alters standing postural adaptation during a visual search task in older adult men.
Jor'dan, Azizah J; McCarten, J Riley; Rottunda, Susan; Stoffregen, Thomas A; Manor, Brad; Wade, Michael G
2015-04-23
This study investigated the effects of dementia on standing postural adaptation during performance of a visual search task. We recruited 16 older adults with dementia and 15 without dementia. Postural sway was assessed by recording medial-lateral (ML) and anterior-posterior (AP) center-of-pressure when standing with and without a visual search task; i.e., counting target letter frequency within a block of displayed randomized letters. ML sway variability was significantly higher in those with dementia during visual search as compared to those without dementia and compared to both groups during the control condition. AP sway variability was significantly greater in those with dementia as compared to those without dementia, irrespective of task condition. In the ML direction, the absolute and percent change in sway variability between the control condition and visual search (i.e., postural adaptation) was greater in those with dementia as compared to those without. In contrast, postural adaptation to visual search was similar between groups in the AP direction. As compared to those without dementia, those with dementia identified fewer letters on the visual task. In the non-dementia group only, greater increases in postural adaptation in both the ML and AP direction, correlated with lower performance on the visual task. The observed relationship between postural adaptation during the visual search task and visual search task performance--in the non-dementia group only--suggests a critical link between perception and action. Dementia reduces the capacity to perform a visual-based task while standing and thus, appears to disrupt this perception-action synergy.
Hierarchical random walks in trace fossils and the origin of optimal search behavior
Sims, David W.; Reynolds, Andrew M.; Humphries, Nicolas E.; Southall, Emily J.; Wearmouth, Victoria J.; Metcalfe, Brett; Twitchett, Richard J.
2014-01-01
Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa. PMID:25024221
NASA Astrophysics Data System (ADS)
Ramazani, Saba; Jackson, Delvin L.; Selmic, Rastko R.
2013-05-01
In search and surveillance operations, deploying a team of mobile agents provides a robust solution that has multiple advantages over using a single agent in efficiency and minimizing exploration time. This paper addresses the challenge of identifying a target in a given environment when using a team of mobile agents by proposing a novel method of mapping and movement of agent teams in a cooperative manner. The approach consists of two parts. First, the region is partitioned into a hexagonal beehive structure in order to provide equidistant movements in every direction and to allow for more natural and flexible environment mapping. Additionally, in search environments that are partitioned into hexagons, mobile agents have an efficient travel path while performing searches due to this partitioning approach. Second, we use a team of mobile agents that move in a cooperative manner and utilize the Tabu Random algorithm to search for the target. Due to the ever-increasing use of robotics and Unmanned Aerial Vehicle (UAV) platforms, the field of cooperative multi-agent search has developed many applications recently that would benefit from the use of the approach presented in this work, including: search and rescue operations, surveillance, data collection, and border patrol. In this paper, the increased efficiency of the Tabu Random Search algorithm method in combination with hexagonal partitioning is simulated, analyzed, and advantages of this approach are presented and discussed.
Searching for adaptive traits in genetic resources - phenology based approach
NASA Astrophysics Data System (ADS)
Bari, Abdallah
2015-04-01
Searching for adaptive traits in genetic resources - phenology based approach Abdallah Bari, Kenneth Street, Eddy De Pauw, Jalal Eddin Omari, and Chandra M. Biradar International Center for Agricultural Research in the Dry Areas, Rabat Institutes, Rabat, Morocco Phenology is an important plant trait not only for assessing and forecasting food production but also for searching in genebanks for adaptive traits. Among the phenological parameters we have been considering to search for such adaptive and rare traits are the onset (sowing period) and the seasonality (growing period). Currently an application is being developed as part of the focused identification of germplasm strategy (FIGS) approach to use climatic data in order to identify crop growing seasons and characterize them in terms of onset and duration. These approximations of growing period characteristics can then be used to estimate flowering and maturity dates for dryland crops, such as wheat, barley, faba bean, lentils and chickpea, and assess, among others, phenology-related traits such as days to heading [dhe] and grain filling period [gfp]. The approach followed here is based on first calculating long term average daily temperatures by fitting a curve to the monthly data over days from beginning of the year. Prior to the identification of these phenological stages the onset is extracted first from onset integer raster GIS layers developed based on a model of the growing period that considers both moisture and temperature limitations. The paper presents some examples of real applications of the approach to search for rare and adaptive traits.
Stochastic Leader Gravitational Search Algorithm for Enhanced Adaptive Beamforming Technique
Darzi, Soodabeh; Islam, Mohammad Tariqul; Tiong, Sieh Kiong; Kibria, Salehin; Singh, Mandeep
2015-01-01
In this paper, stochastic leader gravitational search algorithm (SL-GSA) based on randomized k is proposed. Standard GSA (SGSA) utilizes the best agents without any randomization, thus it is more prone to converge at suboptimal results. Initially, the new approach randomly choses k agents from the set of all agents to improve the global search ability. Gradually, the set of agents is reduced by eliminating the agents with the poorest performances to allow rapid convergence. The performance of the SL-GSA was analyzed for six well-known benchmark functions, and the results are compared with SGSA and some of its variants. Furthermore, the SL-GSA is applied to minimum variance distortionless response (MVDR) beamforming technique to ensure compatibility with real world optimization problems. The proposed algorithm demonstrates superior convergence rate and quality of solution for both real world problems and benchmark functions compared to original algorithm and other recent variants of SGSA. PMID:26552032
Self-Adaptive Stepsize Search Applied to Optimal Structural Design
NASA Astrophysics Data System (ADS)
Nolle, L.; Bland, J. A.
Structural engineering often involves the design of space frames that are required to resist predefined external forces without exhibiting plastic deformation. The weight of the structure and hence the weight of its constituent members has to be as low as possible for economical reasons without violating any of the load constraints. Design spaces are usually vast and the computational costs for analyzing a single design are usually high. Therefore, not every possible design can be evaluated for real-world problems. In this work, a standard structural design problem, the 25-bar problem, has been solved using self-adaptive stepsize search (SASS), a relatively new search heuristic. This algorithm has only one control parameter and therefore overcomes the drawback of modern search heuristics, i.e. the need to first find a set of optimum control parameter settings for the problem at hand. In this work, SASS outperforms simulated-annealing, genetic algorithms, tabu search and ant colony optimization.
Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search.
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
NASA Astrophysics Data System (ADS)
Reynolds, A. M.
2008-04-01
A random Lévy-looping model of searching is devised and optimal random Lévy-looping searching strategies are identified for the location of a single target whose position is uncertain. An inverse-square power law distribution of loop lengths is shown to be optimal when the distance between the centre of the search and the target is much shorter than the size of the longest possible loop in the searching pattern. Optimal random Lévy-looping searching patterns have recently been observed in the flight patterns of honeybees (Apis mellifera) when attempting to locate their hive and when searching after a known food source becomes depleted. It is suggested that the searching patterns of desert ants (Cataglyphis) are consistent with the adoption of an optimal Lévy-looping searching strategy.
Vrugt, Jasper A; Hyman, James M; Robinson, Bruce A; Higdon, Dave; Ter Braak, Cajo J F; Diks, Cees G H
2008-01-01
Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.
δ-exceedance records and random adaptive walks
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2016-08-01
We study a modified record process where the kth record in a series of independent and identically distributed random variables is defined recursively through the condition {Y}k\\gt {Y}k-1-{δ }k-1 with a deterministic sequence {δ }k\\gt 0 called the handicap. For constant {δ }k\\equiv δ and exponentially distributed random variables it has been shown in previous work that the process displays a phase transition as a function of δ between a normal phase where the mean record value increases indefinitely and a stationary phase where the mean record value remains bounded and a finite fraction of all entries are records (Park et al 2015 Phys. Rev. E 91 042707). Here we explore the behavior for general probability distributions and decreasing and increasing sequences {δ }k, focusing in particular on the case when {δ }k matches the typical spacing between subsequent records in the underlying simple record process without handicap. We find that a continuous phase transition occurs only in the exponential case, but a novel kind of first order transition emerges when {δ }k is increasing. The problem is partly motivated by the dynamics of evolutionary adaptation in biological fitness landscapes, where {δ }k corresponds to the change of the deterministic fitness component after k mutational steps. The results for the record process are used to compute the mean number of steps that a population performs in such a landscape before being trapped at a local fitness maximum.
Adaptive random renormalization group classification of multiscale dispersive processes
NASA Astrophysics Data System (ADS)
Cushman, John; O'Malley, Dan
2013-04-01
Renormalization group operators provide a detailed classification tool for dispersive processes. We begin by reviewing a two-scale renormalization group classification scheme. Repeated application of one operator is associated with long time behavior of the process while repeated application of the other is associated with short time behavior. This approach is shown to be robust even in the presence of non-stationary increments and/or infinite second moments. Fixed points of the operators can be used for further sub classification of the processes when appropriate limits exist. As an example we look at advective dispersion in an ergodic velocity field. Let X(t) be a fixed point of the long-time renormalization group operator (RGO) RX(t)=X(rt)/r^p. Scaling laws for the probability density, mean first passage times, and finite-size Lyapunov exponents of such fixed points are reviewed in anticipation of more general results. A generalized RGO, Rp, where the exponent in R above is now a random variable is introduced. Scaling laws associated with these random RGOs (RRGOs) are demonstrated numerically and applied to a process modeling the transition from sub-dispersion to Fickian dispersion. The scaling laws for the RRGO are not simple power laws, but instead are a weighted average of power laws. The weighting in the scaling laws can be determined adaptively via Bayes' theorem.
Lévy flight random searches in biological phenomena
NASA Astrophysics Data System (ADS)
Viswanathan, G. M.; Bartumeus, F.; V. Buldyrev, Sergey; Catalan, J.; Fulco, U. L.; Havlin, Shlomo; da Luz, M. G. E.; Lyra, M. L.; Raposo, E. P.; Eugene Stanley, H.
2002-11-01
There has been growing interest in the study of Lévy flights observed in the movements of biological organisms performing random walks while searching for other organisms. Here, we approach the problem of what is the best statistical strategy for optimizing the encounter rate between “searcher” and “target” organisms-either of the same or of different species-in terms of a limiting generalized searcher-target model (e.g., predator-prey, mating partner, pollinator-flower). In this context, we discuss known results showing that for fixed targets an inverse square density distribution of step lengths can optimize the encounter rate. For moving targets, we review how the encounter rate depends on whether organisms move in Lévy or Brownian random walks. We discuss recent findings indicating that Lévy walks confer a significant advantage for increasing encounter rates only when the searcher is larger or moves rapidly relative to the target, and when the target density is low.
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search.
Fricke, G Matthew; Letendre, Kenneth A; Moses, Melanie E; Cannon, Judy L
2016-03-01
Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call "hotspots" within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search.
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search
Fricke, G. Matthew; Letendre, Kenneth A.; Moses, Melanie E.; Cannon, Judy L.
2016-01-01
Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call “hotspots” within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search. PMID:26990103
Generalized pattern search algorithms with adaptive precision function evaluations
Polak, Elijah; Wetter, Michael
2003-05-14
In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to a form that uses adaptive precision approximations to the cost function. These numerical approximations need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. Such an approach leads to substantial time savings in minimizing computationally expensive functions.
A novel adaptive Cuckoo search for optimal query plan generation.
Gomathi, Ramalingam; Sharmila, Dhandapani
2014-01-01
The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330
A novel adaptive Cuckoo search for optimal query plan generation.
Gomathi, Ramalingam; Sharmila, Dhandapani
2014-01-01
The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.
A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation
Gomathi, Ramalingam; Sharmila, Dhandapani
2014-01-01
The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330
Accelerated search for materials with targeted properties by adaptive design
Xue, Dezhen; Balachandran, Prasanna V.; Hogden, John; Theiler, James; Xue, Deqing; Lookman, Turab
2016-01-01
Finding new materials with targeted properties has traditionally been guided by intuition, and trial and error. With increasing chemical complexity, the combinatorial possibilities are too large for an Edisonian approach to be practical. Here we show how an adaptive design strategy, tightly coupled with experiments, can accelerate the discovery process by sequentially identifying the next experiments or calculations, to effectively navigate the complex search space. Our strategy uses inference and global optimization to balance the trade-off between exploitation and exploration of the search space. We demonstrate this by finding very low thermal hysteresis (ΔT) NiTi-based shape memory alloys, with Ti50.0Ni46.7Cu0.8Fe2.3Pd0.2 possessing the smallest ΔT (1.84 K). We synthesize and characterize 36 predicted compositions (9 feedback loops) from a potential space of ∼800,000 compositions. Of these, 14 had smaller ΔT than any of the 22 in the original data set. PMID:27079901
Accelerated search for materials with targeted properties by adaptive design
NASA Astrophysics Data System (ADS)
Xue, Dezhen; Balachandran, Prasanna V.; Hogden, John; Theiler, James; Xue, Deqing; Lookman, Turab
2016-04-01
Finding new materials with targeted properties has traditionally been guided by intuition, and trial and error. With increasing chemical complexity, the combinatorial possibilities are too large for an Edisonian approach to be practical. Here we show how an adaptive design strategy, tightly coupled with experiments, can accelerate the discovery process by sequentially identifying the next experiments or calculations, to effectively navigate the complex search space. Our strategy uses inference and global optimization to balance the trade-off between exploitation and exploration of the search space. We demonstrate this by finding very low thermal hysteresis (ΔT) NiTi-based shape memory alloys, with Ti50.0Ni46.7Cu0.8Fe2.3Pd0.2 possessing the smallest ΔT (1.84 K). We synthesize and characterize 36 predicted compositions (9 feedback loops) from a potential space of ~800,000 compositions. Of these, 14 had smaller ΔT than any of the 22 in the original data set.
Accelerated search for materials with targeted properties by adaptive design.
Xue, Dezhen; Balachandran, Prasanna V; Hogden, John; Theiler, James; Xue, Deqing; Lookman, Turab
2016-01-01
Finding new materials with targeted properties has traditionally been guided by intuition, and trial and error. With increasing chemical complexity, the combinatorial possibilities are too large for an Edisonian approach to be practical. Here we show how an adaptive design strategy, tightly coupled with experiments, can accelerate the discovery process by sequentially identifying the next experiments or calculations, to effectively navigate the complex search space. Our strategy uses inference and global optimization to balance the trade-off between exploitation and exploration of the search space. We demonstrate this by finding very low thermal hysteresis (ΔT) NiTi-based shape memory alloys, with Ti50.0Ni46.7Cu0.8Fe2.3Pd0.2 possessing the smallest ΔT (1.84 K). We synthesize and characterize 36 predicted compositions (9 feedback loops) from a potential space of ∼800,000 compositions. Of these, 14 had smaller ΔT than any of the 22 in the original data set. PMID:27079901
Accelerated search for materials with targeted properties by adaptive design.
Xue, Dezhen; Balachandran, Prasanna V; Hogden, John; Theiler, James; Xue, Deqing; Lookman, Turab
2016-04-15
Finding new materials with targeted properties has traditionally been guided by intuition, and trial and error. With increasing chemical complexity, the combinatorial possibilities are too large for an Edisonian approach to be practical. Here we show how an adaptive design strategy, tightly coupled with experiments, can accelerate the discovery process by sequentially identifying the next experiments or calculations, to effectively navigate the complex search space. Our strategy uses inference and global optimization to balance the trade-off between exploitation and exploration of the search space. We demonstrate this by finding very low thermal hysteresis (ΔT) NiTi-based shape memory alloys, with Ti50.0Ni46.7Cu0.8Fe2.3Pd0.2 possessing the smallest ΔT (1.84 K). We synthesize and characterize 36 predicted compositions (9 feedback loops) from a potential space of ∼800,000 compositions. Of these, 14 had smaller ΔT than any of the 22 in the original data set.
Adaptive pumping for spectral control of random lasers
NASA Astrophysics Data System (ADS)
Bachelard, Nicolas; Gigan, Sylvain; Noblin, Xavier; Sebbah, Patrick
2014-06-01
A laser is not necessarily a sophisticated device: pumping an amplifying medium randomly filled with scatterers makes a perfectly viable `random laser'. The absence of mirrors greatly simplifies laser design, but control over the emission wavelength and directionality is lost, seriously hindering prospects for this otherwise simple laser. Recently, we proposed an approach to tame random lasers, inspired by coherent light control in complex media. Here, we implement this method in an optofluidic random laser where modes are spatially extended and overlap, making individual mode selection impossible, a priori. We show experimentally that control over laser emission can be regained even in this extreme case. By actively shaping the optical pump within the random laser, single-mode operation at any selected wavelength is achieved with spectral selectivity down to 0.06 nm and more than 10 dB side-lobe rejection. This method paves the way towards versatile tunable and controlled random lasers as well as the taming of other laser sources.
Adaptive nowcasting of influenza outbreaks using Google searches
Preis, Tobias; Moat, Helen Susannah
2014-01-01
Seasonal influenza outbreaks and pandemics of new strains of the influenza virus affect humans around the globe. However, traditional systems for measuring the spread of flu infections deliver results with one or two weeks delay. Recent research suggests that data on queries made to the search engine Google can be used to address this problem, providing real-time estimates of levels of influenza-like illness in a population. Others have however argued that equally good estimates of current flu levels can be forecast using historic flu measurements. Here, we build dynamic ‘nowcasting’ models; in other words, forecasting models that estimate current levels of influenza, before the release of official data one week later. We find that when using Google Flu Trends data in combination with historic flu levels, the mean absolute error (MAE) of in-sample ‘nowcasts’ can be significantly reduced by 14.4%, compared with a baseline model that uses historic data on flu levels only. We further demonstrate that the MAE of out-of-sample nowcasts can also be significantly reduced by between 16.0% and 52.7%, depending on the length of the sliding training interval. We conclude that, using adaptive models, Google Flu Trends data can indeed be used to improve real-time influenza monitoring, even when official reports of flu infections are available with only one week's delay. PMID:26064532
ADAPTIVE MATCHING IN RANDOMIZED TRIALS AND OBSERVATIONAL STUDIES
van der Laan, Mark J.; Balzer, Laura B.; Petersen, Maya L.
2014-01-01
SUMMARY In many randomized and observational studies the allocation of treatment among a sample of n independent and identically distributed units is a function of the covariates of all sampled units. As a result, the treatment labels among the units are possibly dependent, complicating estimation and posing challenges for statistical inference. For example, cluster randomized trials frequently sample communities from some target population, construct matched pairs of communities from those included in the sample based on some metric of similarity in baseline community characteristics, and then randomly allocate a treatment and a control intervention within each matched pair. In this case, the observed data can neither be represented as the realization of n independent random variables, nor, contrary to current practice, as the realization of n/2 independent random variables (treating the matched pair as the independent sampling unit). In this paper we study estimation of the average causal effect of a treatment under experimental designs in which treatment allocation potentially depends on the pre-intervention covariates of all units included in the sample. We define efficient targeted minimum loss based estimators for this general design, present a theorem that establishes the desired asymptotic normality of these estimators and allows for asymptotically valid statistical inference, and discuss implementation of these estimators. We further investigate the relative asymptotic efficiency of this design compared with a design in which unit-specific treatment assignment depends only on the units’ covariates. Our findings have practical implications for the optimal design and analysis of pair matched cluster randomized trials, as well as for observational studies in which treatment decisions may depend on characteristics of the entire sample. PMID:25097298
Adapting GNU random forest program for Unix and Windows
NASA Astrophysics Data System (ADS)
Jirina, Marcel; Krayem, M. Said; Jirina, Marcel, Jr.
2013-10-01
The Random Forest is a well-known method and also a program for data clustering and classification. Unfortunately, the original Random Forest program is rather difficult to use. Here we describe a new version of this program originally written in Fortran 77. The modified program in Fortran 95 needs to be compiled only once and information for different tasks is passed with help of arguments. The program was tested with 24 data sets from UCI MLR and results are available on the net.
Adaptive search in mobile peer-to-peer databases
NASA Technical Reports Server (NTRS)
Wolfson, Ouri (Inventor); Xu, Bo (Inventor)
2010-01-01
Information is stored in a plurality of mobile peers. The peers communicate in a peer to peer fashion, using a short-range wireless network. Occasionally, a peer initiates a search for information in the peer to peer network by issuing a query. Queries and pieces of information, called reports, are transmitted among peers that are within a transmission range. For each search additional peers are utilized, wherein these additional peers search and relay information on behalf of the originator of the search.
Post and a random-walk search mode
NASA Technical Reports Server (NTRS)
Martin, J. A.
1984-01-01
Multidisciplinary analysis often requires optimization of nonlinear systems that are subject to constraints. Trajectory optimization is one example of this situation. The Program to Optimize Simulated Trajectories (POST) was used successfully for a number of problems. The purpose is to describe POST and a new optimization approach that has been incorporated into it. Typical uses of POST will also be illustrated. The projected-gradient approach to optimization is the preferred option in POST and is discussed. A new approach to optimization, the random-walk approach, is described, and results with the random-walk approach are presented.
Validity of tests under covariate-adaptive biased coin randomization and generalized linear models.
Shao, Jun; Yu, Xinxin
2013-12-01
Some covariate-adaptive randomization methods have been used in clinical trials for a long time, but little theoretical work has been done about testing hypotheses under covariate-adaptive randomization until Shao et al. (2010) who provided a theory with detailed discussion for responses under linear models. In this article, we establish some asymptotic results for covariate-adaptive biased coin randomization under generalized linear models with possibly unknown link functions. We show that the simple t-test without using any covariate is conservative under covariate-adaptive biased coin randomization in terms of its Type I error rate, and that a valid test using the bootstrap can be constructed. This bootstrap test, utilizing covariates in the randomization scheme, is shown to be asymptotically as efficient as Wald's test correctly using covariates in the analysis. Thus, the efficiency loss due to not using covariates in the analysis can be recovered by utilizing covariates in covariate-adaptive biased coin randomization. Our theory is illustrated with two most popular types of discrete outcomes, binary responses and event counts under the Poisson model, and exponentially distributed continuous responses. We also show that an alternative simple test without using any covariate under the Poisson model has an inflated Type I error rate under simple randomization, but is valid under covariate-adaptive biased coin randomization. Effects on the validity of tests due to model misspecification is also discussed. Simulation studies about the Type I errors and powers of several tests are presented for both discrete and continuous responses. PMID:23848580
The influence of the environment on Lévy random search efficiency: Fractality and memory effects
NASA Astrophysics Data System (ADS)
Ferreira, A. S.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2012-06-01
An open problem in the field of random searches relates to optimizing the search efficiency in fractal environments. Here we address this issue through a systematic study of Lévy searches in landscapes encompassing several degrees of target aggregation and fractality. For scarce resources, non-destructive searches with unrestricted revisits to targets are shown to present universal optimal behavior irrespective of the general scaling properties of the spatial distribution of targets. In contrast, no such universal behavior occurs in the destructive case with forbidden revisits, in which the optimal strategy strongly depends on the degree of target aggregation. We also investigate how the presence of memory and learning skills of the searcher affect the search efficiency. By considering a limiting model in which the searcher learns through recent experience to recognize food-rich areas, we find that a statistical memory of previous encounters does not necessarily increase the rate of target findings in random searches. Instead, there is an optimal extent of memory, dependent on specific details of the search space and stochastic dynamics, which maximizes the search efficiency. This finding suggests a more general result, namely that in some instances there are actual advantages to ignoring certain pieces of partial information while searching for objects.
Lévy flights do not always optimize random blind search for sparse targets
Palyulin, Vladimir V.; Chechkin, Aleksei V.; Metzler, Ralf
2014-01-01
It is generally believed that random search processes based on scale-free, Lévy stable jump length distributions (Lévy flights) optimize the search for sparse targets. Here we show that this popular search advantage is less universal than commonly assumed. We study the efficiency of a minimalist search model based on Lévy flights in the absence and presence of an external drift (underwater current, atmospheric wind, a preference of the walker owing to prior experience, or a general bias in an abstract search space) based on two different optimization criteria with respect to minimal search time and search reliability (cumulative arrival probability). Although Lévy flights turn out to be efficient search processes when the target is far from the starting point, or when relative to the starting point the target is upstream, we show that for close targets and for downstream target positioning regular Brownian motion turns out to be the advantageous search strategy. Contrary to claims that Lévy flights with a critical exponent α = 1 are optimal for the search of sparse targets in different settings, based on our optimization parameters the optimal α may range in the entire interval (1, 2) and especially include Brownian motion as the overall most efficient search strategy. PMID:24516153
NASA Astrophysics Data System (ADS)
Chen, Xinjia
2015-05-01
We consider the general problem of analysis and design of control systems in the presence of uncertainties. We treat uncertainties that affect a control system as random variables. The performance of the system is measured by the expectation of some derived random variables, which are typically bounded. We develop adaptive sequential randomized algorithms for estimating and optimizing the expectation of such bounded random variables with guaranteed accuracy and confidence level. These algorithms can be applied to overcome the conservatism and computational complexity in the analysis and design of controllers to be used in uncertain environments. We develop methods for investigating the optimality and computational complexity of such algorithms.
Moran, Robert F; McKay, David; Pickard, Chris J; Berry, Andrew J; Griffin, John M; Ashbrook, Sharon E
2016-04-21
The structural chemistry of materials containing low levels of nonstoichiometric hydrogen is difficult to determine, and producing structural models is challenging where hydrogen has no fixed crystallographic site. Here we demonstrate a computational approach employing ab initio random structure searching (AIRSS) to generate a series of candidate structures for hydrous wadsleyite (β-Mg2SiO4 with 1.6 wt% H2O), a high-pressure mineral proposed as a repository for water in the Earth's transition zone. Aligning with previous experimental work, we solely consider models with Mg3 (over Mg1, Mg2 or Si) vacancies. We adapt the AIRSS method by starting with anhydrous wadsleyite, removing a single Mg(2+) and randomly placing two H(+) in a unit cell model, generating 819 candidate structures. 103 geometries were then subjected to more accurate optimisation under periodic DFT. Using this approach, we find the most favourable hydration mechanism involves protonation of two O1 sites around the Mg3 vacancy. The formation of silanol groups on O3 or O4 sites (with loss of stable O1-H hydroxyls) coincides with an increase in total enthalpy. Importantly, the approach we employ allows observables such as NMR parameters to be computed for each structure. We consider hydrous wadsleyite (∼1.6 wt%) to be dominated by protonated O1 sites, with O3/O4-H silanol groups present as defects, a model that maps well onto experimental studies at higher levels of hydration (J. M. Griffin et al., Chem. Sci., 2013, 4, 1523). The AIRSS approach adopted herein provides the crucial link between atomic-scale structure and experimental studies. PMID:27020937
Moran, Robert F; McKay, David; Pickard, Chris J; Berry, Andrew J; Griffin, John M; Ashbrook, Sharon E
2016-04-21
The structural chemistry of materials containing low levels of nonstoichiometric hydrogen is difficult to determine, and producing structural models is challenging where hydrogen has no fixed crystallographic site. Here we demonstrate a computational approach employing ab initio random structure searching (AIRSS) to generate a series of candidate structures for hydrous wadsleyite (β-Mg2SiO4 with 1.6 wt% H2O), a high-pressure mineral proposed as a repository for water in the Earth's transition zone. Aligning with previous experimental work, we solely consider models with Mg3 (over Mg1, Mg2 or Si) vacancies. We adapt the AIRSS method by starting with anhydrous wadsleyite, removing a single Mg(2+) and randomly placing two H(+) in a unit cell model, generating 819 candidate structures. 103 geometries were then subjected to more accurate optimisation under periodic DFT. Using this approach, we find the most favourable hydration mechanism involves protonation of two O1 sites around the Mg3 vacancy. The formation of silanol groups on O3 or O4 sites (with loss of stable O1-H hydroxyls) coincides with an increase in total enthalpy. Importantly, the approach we employ allows observables such as NMR parameters to be computed for each structure. We consider hydrous wadsleyite (∼1.6 wt%) to be dominated by protonated O1 sites, with O3/O4-H silanol groups present as defects, a model that maps well onto experimental studies at higher levels of hydration (J. M. Griffin et al., Chem. Sci., 2013, 4, 1523). The AIRSS approach adopted herein provides the crucial link between atomic-scale structure and experimental studies.
Adaptation to a simulated central scotoma during visual search training.
Walsh, David V; Liu, Lei
2014-03-01
Patients with a central scotoma usually use a preferred retinal locus (PRL) consistently in daily activities. The selection process and time course of the PRL development are not well understood. We used a gaze-contingent display to simulate an isotropic central scotoma in normal subjects while they were practicing a difficult visual search task. As compared to foveal search, initial exposure to the simulated scotoma resulted in prolonged search reaction time, many more fixations and unorganized eye movements during search. By the end of a 1782-trial training with the simulated scotoma, the search performance improved to within 25% of normal foveal search. Accompanying the performance improvement, there were also fewer fixations, fewer repeated fixations in the same area of the search stimulus and a clear tendency of using one area near the border of the scotoma to identify the search target. The results were discussed in relation to natural development of PRL in central scotoma patients and potential visual training protocols to facilitate PRL development. PMID:24456805
NASA Astrophysics Data System (ADS)
Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua
2014-03-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua
2014-03-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua
2014-03-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm. PMID:24697395
Sheng, Zheng; Wang, Jun; Zhou, Bihua; Zhou, Shudao
2014-03-15
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Adaptation response of Arabidopsis thaliana to random positioning
NASA Astrophysics Data System (ADS)
Kittang, A.-I.; Winge, P.; van Loon, J. J. W. A.; Bones, A. M.; Iversen, T.-H.
2013-10-01
Arabidopsis thaliana seedlings were exposed on a Random Positioning Machine (RPM) under light conditions for 16 h and the samples were analysed using microarray techniques as part of a preparation for a space experiment on the International Space Station (ISS). The results demonstrated a moderate to low regulation of 55 genes (<0.2% of the analysed genes). Genes encoding proteins associated with the chaperone system (e.g. heat shock proteins, HSPs) and enzymes in the flavonoid biosynthesis were induced. Most of the repressed genes were associated with light and sugar responses. Significant up-regulation of selected HSP genes was found by quantitative Real-Time PCR in 1 week old plants after the RPM exposure both in light and darkness. Higher quantity of DPBA (diphenylboric acid 2-amino-ethyl ester) staining was observed in the whole root and in the root elongation zone of the seedlings exposed on the RPM by use of fluorescent microscopy, indicating higher flavonoid content. The regulated genes and an increase of flavonoids are related to several stresses, but increased occurrence of HSPs and flavonoids are also representative for normal growth (e.g. gravitropism). The response could be a direct stress response or an integrated response of the two signal pathways of light and gravity resulting in an overall light response.
Cooperative random Lévy flight searches and the flight patterns of honeybees
NASA Astrophysics Data System (ADS)
Reynolds, A. M.
2006-06-01
The most efficient Lévy flight (scale-free) searching strategy for N independent searchers to adopt when target sites are randomly and sparsely distributed is identified. For N=1, it is well known that the optimal searching strategy is attained when μ=2, where the exponent μ characterizes the Lévy distribution, P(l)=l, of flight-lengths. For N>1, the optimal searching strategy is attained as μ→1. It is suggested that the orientation flights of honeybees can be understood within the context of such an optimal cooperative random Lévy flight searching strategy. Upon returning to their hive after surveying a landscape honeybees can exchange information about the locations of target sites through the waggle dance. In accordance with observations it is predicted that the waggle dance can be disrupted without noticeable influence on a hive's ability to maintain weight when forage is plentiful.
Features: Real-Time Adaptive Feature and Document Learning for Web Search.
ERIC Educational Resources Information Center
Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai
2001-01-01
Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…
Bayesian Analysis for Exponential Random Graph Models Using the Adaptive Exchange Sampler*
Jin, Ick Hoon; Yuan, Ying; Liang, Faming
2014-01-01
Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the intractable normalizing constant and model degeneracy. In this paper, we consider a fully Bayesian analysis for exponential random graph models using the adaptive exchange sampler, which solves the intractable normalizing constant and model degeneracy issues encountered in Markov chain Monte Carlo (MCMC) simulations. The adaptive exchange sampler can be viewed as a MCMC extension of the exchange algorithm, and it generates auxiliary networks via an importance sampling procedure from an auxiliary Markov chain running in parallel. The convergence of this algorithm is established under mild conditions. The adaptive exchange sampler is illustrated using a few social networks, including the Florentine business network, molecule synthetic network, and dolphins network. The results indicate that the adaptive exchange algorithm can produce more accurate estimates than approximate exchange algorithms, while maintaining the same computational efficiency. PMID:24653788
Roberts, William M; Augustine, Steven B; Lawton, Kristy J; Lindsay, Theodore H; Thiele, Tod R; Izquierdo, Eduardo J; Faumont, Serge; Lindsay, Rebecca A; Britton, Matthew Cale; Pokala, Navin; Bargmann, Cornelia I; Lockery, Shawn R
2016-01-01
Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms. DOI: http://dx.doi.org/10.7554/eLife.12572.001 PMID:26824391
Adaptive box filters for removal of random noise from digital images
Eliason, E.M.; McEwen, A.S.
1990-01-01
We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors
Lu Dawei; Peng Xinhua; Du Jiangfeng; Zhu Jing; Zou Ping; Yu Yihua; Zhang Shanmin; Chen Qun
2010-02-15
An important quantum search algorithm based on the quantum random walk performs an oracle search on a database of N items with O({radical}(phN)) calls, yielding a speedup similar to the Grover quantum search algorithm. The algorithm was implemented on a quantum information processor of three-qubit liquid-crystal nuclear magnetic resonance (NMR) in the case of finding 1 out of 4, and the diagonal elements' tomography of all the final density matrices was completed with comprehensible one-dimensional NMR spectra. The experimental results agree well with the theoretical predictions.
Conditions under which a superdiffusive random-search strategy is necessary
NASA Astrophysics Data System (ADS)
Sotelo-López, S. A.; Santos, M. C.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2012-09-01
Intuitively, lower target densities and lower detection capabilities should demand more sophisticated search strategies for a random search reasonable outcome. In contrast, when targets are easily found, a simple Brownian random walk strategy is enough. But where is the threshold between these two scenarios and when is optimization really necessary? We address this considering the interplay between two essential scales in random search, the average distance between neighbor targets l0 and the detection capability rv. In the limit cases the ratio β=rv/l0 suffices to characterize the problem. For low (high) β a superdiffusive behavior is (is not) crucial for the process optimization. However, there is a crossover range, which is a nontrivial function of rv and l0, separating the two regimes. We analyze this intermediate region, common in nature, and discuss the often overlooked important trade between resources availability and the searcher location power. Our results highlight contexts where efficient random search is a key factor for survival, such as in animal foraging.
Error compensation in random vector double step saccades with and without global adaptation.
Zerr, Paul; Thakkar, Katharine N; Uzunbajakau, Siarhei; Van der Stigchel, Stefan
2016-10-01
In saccade sequences without visual feedback endpoint errors pose a problem for subsequent saccades. Accurate error compensation has previously been demonstrated in double step saccades (DSS) and is thought to rely on a copy of the saccade motor vector. However, these studies typically use fixed target vectors on each trial, calling into question the generalizability of the findings due to the high stimulus predictability. We present a random walk DSS paradigm (random target vector amplitudes and directions) to provide a more complete, realistic and generalizable description of error compensation in saccade sequences. We regressed the vector between the endpoint of the second saccade and the endpoint of a hypothetical second saccade that does not take first saccade error into account on the ideal compensation vector. This provides a direct and complete estimation of error compensation in DSS. We observed error compensation with varying stimulus displays that was comparable to previous findings. We also employed this paradigm to extend experiments that showed accurate compensation for systematic undershoots after specific-vector saccade adaptation. Utilizing the random walk paradigm for saccade adaptation by Rolfs et al. (2010) together with our random walk DSS paradigm we now also demonstrate transfer of adaptation from reactive to memory guided saccades for global saccade adaptation. We developed a new, generalizable DSS paradigm with unpredictable stimuli and successfully employed it to verify, replicate and extend previous findings, demonstrating that endpoint errors are compensated for saccades in all directions and variable amplitudes.
Error compensation in random vector double step saccades with and without global adaptation.
Zerr, Paul; Thakkar, Katharine N; Uzunbajakau, Siarhei; Van der Stigchel, Stefan
2016-10-01
In saccade sequences without visual feedback endpoint errors pose a problem for subsequent saccades. Accurate error compensation has previously been demonstrated in double step saccades (DSS) and is thought to rely on a copy of the saccade motor vector. However, these studies typically use fixed target vectors on each trial, calling into question the generalizability of the findings due to the high stimulus predictability. We present a random walk DSS paradigm (random target vector amplitudes and directions) to provide a more complete, realistic and generalizable description of error compensation in saccade sequences. We regressed the vector between the endpoint of the second saccade and the endpoint of a hypothetical second saccade that does not take first saccade error into account on the ideal compensation vector. This provides a direct and complete estimation of error compensation in DSS. We observed error compensation with varying stimulus displays that was comparable to previous findings. We also employed this paradigm to extend experiments that showed accurate compensation for systematic undershoots after specific-vector saccade adaptation. Utilizing the random walk paradigm for saccade adaptation by Rolfs et al. (2010) together with our random walk DSS paradigm we now also demonstrate transfer of adaptation from reactive to memory guided saccades for global saccade adaptation. We developed a new, generalizable DSS paradigm with unpredictable stimuli and successfully employed it to verify, replicate and extend previous findings, demonstrating that endpoint errors are compensated for saccades in all directions and variable amplitudes. PMID:27543803
Local search methods based on variable focusing for random K-satisfiability.
Lemoy, Rémi; Alava, Mikko; Aurell, Erik
2015-01-01
We introduce variable focused local search algorithms for satisfiabiliity problems. Usual approaches focus uniformly on unsatisfied clauses. The methods described here work by focusing on random variables in unsatisfied clauses. Variants are considered where variables are selected uniformly and randomly or by introducing a bias towards picking variables participating in several unsatistified clauses. These are studied in the case of the random 3-SAT problem, together with an alternative energy definition, the number of variables in unsatisfied constraints. The variable-based focused Metropolis search (V-FMS) is found to be quite close in performance to the standard clause-based FMS at optimal noise. At infinite noise, instead, the threshold for the linearity of solution times with instance size is improved by picking preferably variables in several UNSAT clauses. Consequences for algorithmic design are discussed. PMID:25679737
Local search methods based on variable focusing for random K -satisfiability
NASA Astrophysics Data System (ADS)
Lemoy, Rémi; Alava, Mikko; Aurell, Erik
2015-01-01
We introduce variable focused local search algorithms for satisfiabiliity problems. Usual approaches focus uniformly on unsatisfied clauses. The methods described here work by focusing on random variables in unsatisfied clauses. Variants are considered where variables are selected uniformly and randomly or by introducing a bias towards picking variables participating in several unsatistified clauses. These are studied in the case of the random 3-SAT problem, together with an alternative energy definition, the number of variables in unsatisfied constraints. The variable-based focused Metropolis search (V-FMS) is found to be quite close in performance to the standard clause-based FMS at optimal noise. At infinite noise, instead, the threshold for the linearity of solution times with instance size is improved by picking preferably variables in several UNSAT clauses. Consequences for algorithmic design are discussed.
NASA Astrophysics Data System (ADS)
Differt, Dominik; Hensen, Matthias; Pfeiffer, Walter
2016-05-01
Spatiotemporal nanolocalization of ultrashort pulses in a random scattering nanostructure via time reversal and adaptive optimization employing a genetic algorithm and a suitably defined fitness function is studied for two embedded nanoparticles that are separated by only a tenth of the free space wavelength. The nanostructure is composed of resonant core-shell nanoparticles (TiO2 core and Ag shell) placed randomly surrounding these two nanoparticles acting as targets. The time reversal scheme achieves selective nanolocalization only by chance if the incident radiation can couple efficiently to dipolar local modes interacting with the target/emitter particle. Even embedding the structure in a reverberation chamber fails improving the nanolocalization. In contrast, the adaptive optimization strategy reliably yields nanolocalization of the radiation and allows a highly selective excitation of either target position. This demonstrates that random scattering structures are interesting multi-purpose optical nanoantennas to realize highly flexible spatiotemporal optical near-field control.
Face adaptation does not improve performance on search or discrimination tasks.
Ng, Minna; Boynton, Geoffrey M; Fine, Ione
2008-01-04
The face adaptation effect, as described by M. A. Webster and O. H. MacLin (1999), is a robust perceptual shift in the appearance of faces after a brief adaptation period. For example, prolonged exposure to Asian faces causes a Eurasian face to appear distinctly Caucasian. This adaptation effect has been documented for general configural effects, as well as for the facial properties of gender, ethnicity, expression, and identity. We began by replicating the finding that adaptation to ethnicity, gender, and a combination of both features induces selective shifts in category appearance. We then investigated whether this adaptation has perceptual consequences beyond a shift in the perceived category boundary by measuring the effects of adaptation on RSVP, spatial search, and discrimination tasks. Adaptation had no discernable effect on performance for any of these tasks.
Machner, Björn; Sprenger, Andreas; Sander, Thurid; Heide, Wolfgang; Kimmig, Hubert; Helmchen, Christoph; Kömpf, Detlef
2009-05-01
Patients with homonymous hemianopia due to occipital brain lesions show disorders of visual search. In everyday life this leads to difficulties in reading and spatial orientation. It is a matter of debate whether these disorders are due to the brain lesion or rather reflect compensatory eye movement strategies developing over time. For the first time, eye movements of acute hemianopic patients (n= 9) were recorded during the first days following stroke while they performed an exploratory visual-search task. Compared to age-matched control subjects their search duration was prolonged due to increased fixations and refixations, that is, repeated scanning of previously searched locations. Saccadic amplitudes were smaller in patients. Right hemianopic patients were more impaired than left hemianopic patients. The number of fixations and refixations did not differ significantly between both hemifields in the patients. Follow-up of one patient revealed changes of visual search over 18 months. By using more structured scanpaths with fewer saccades his search duration decreased. Furthermore, he developed a more efficient eye-movement strategy by making larger but less frequent saccades toward his blind side. In summary, visual-search behavior of acute hemianopic patients differs from healthy control subjects and from chronic hemianopic patients. We conclude that abnormal visual search in acute hemianopic patients is related to the brain lesion. We provide some evidence for adaptive eye-movement strategies developed over time. These adaptive strategies make the visual search more efficient and may help to compensate for the persisting visual-field loss.
Campos, Daniel; Méndez, Vicenç
2015-12-01
Recent works have explored the properties of Lévy flights with resetting in one-dimensional domains and have reported the existence of phase transitions in the phase space of parameters which minimizes the mean first passage time (MFPT) through the origin [L. Kusmierz et al., Phys. Rev. Lett. 113, 220602 (2014)]. Here, we show how actually an interesting dynamics, including also phase transitions for the minimization of the MFPT, can also be obtained without invoking the use of Lévy statistics but for the simpler case of random walks with exponentially distributed flights of constant speed. We explore this dynamics both in the case of finite and infinite domains, and for different implementations of the resetting mechanism to show that different ways to introduce resetting consistently lead to a quite similar dynamics. The use of exponential flights has the strong advantage that exact solutions can be obtained easily for the MFPT through the origin, so a complete analytical characterization of the system dynamics can be provided. Furthermore, we discuss in detail how the phase transitions observed in random walks with resetting are closely related to several ideas recurrently used in the field of random search theory, in particular, to other mechanisms proposed to understand random search in space as mortal random walks or multiscale random walks. As a whole, we corroborate that one of the essential ingredients behind MFPT minimization lies in the combination of multiple movement scales (regardless of their specific origin). PMID:26764640
Ahirwal, M K; Kumar, Anil; Singh, G K
2013-01-01
This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.
An autonomous adaptive scheduling agent for period searching
NASA Astrophysics Data System (ADS)
Saunders, E. S.; Naylor, T.; Allan, A.
2008-03-01
We describe the design and implementation of an autonomous adaptive software agent that addresses the practical problem of observing undersampled, periodic, time-varying phenomena using a network of HTN-compliant robotic telescopes. The algorithm governing the behaviour of the agent uses an optimal geometric sampling technique to cover the period range of interest, but additionally implements proactive behaviour that maximises the optimality of the dataset in the face of an uncertain and changing operating environment.
Through the interaction of neutral and adaptive mutations, evolutionary search finds a way.
Yu, Tina; Miller, Julian Francis
2006-01-01
An evolutionary system that supports the interaction of neutral and adaptive mutations is investigated. Experimental results on a Boolean function and needle-in-haystack problems show that this system enables evolutionary search to find better solutions faster. Through a novel analysis based on the ratio of neutral to adaptive mutations, we identify this interaction as an engine that automatically adjusts the relative amounts of exploration and exploitation to achieve effective search (i.e., it is self-adaptive). Moreover, a hypothesis to describe the search process in this system is proposed and investigated. Our findings lead us to counter the arguments of those who dismiss the usefulness of neutrality. We argue that the benefits of neutrality are intimately related to its implementation, so that one must be cautious about making general claims about its merits or demerits.
Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
Bartumeus, Frederic; Raposo, Ernesto P; Viswanathan, Gandhimohan M; da Luz, Marcos G E
2014-01-01
Recent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high search efficiencies. Based on a one-dimensional comparative analysis we show a mechanism by which, at random, a searcher can optimize the encounter with close and distant targets. The mechanism consists of combining an optimal diffusivity (optimally enhanced diffusion) with a minimal diffusion constant. In such a way the search dynamics adequately balances the tension between finding close and distant targets, while, at the same time, shifts the optimal balance towards relatively larger close-to-distant target encounter ratios. We find that introducing a multiscale set of reorientations ensures both a thorough local space exploration without oversampling and a fast spreading dynamics at the large scale. Lévy reorientation patterns account for these properties but other reorientation strategies providing similar statistical signatures can mimic or achieve comparable efficiencies. Hence, the present work unveils general mechanisms underlying efficient random search, beyond the Lévy model. Our results suggest that animals could tune key statistical movement properties (e.g. enhanced diffusivity, minimal diffusion constant) to cope with the very general problem of balancing out intensive and extensive random searching. We believe that theoretical developments to mechanistically understand stochastic search strategies, such as the one here proposed, are crucial to develop an empirically verifiable and comprehensive animal foraging theory. PMID:25216191
Optimum search strategy for randomly distributed CW transmitters. [for project SETI
NASA Technical Reports Server (NTRS)
Gulkis, S.
1985-01-01
The relative probability of detecting randomly distributed CW transmitters as a function of the fraction of the sky which is searched (in a fixed time interval) is given. It is shown that the probability of detecting such a class of transmitters with a given receiving system is a maximum if the entire sky is searched, provided that the receiving system is sufficiently sensitive to detect the nearest transmitter in the allocated time and that the integration time - bandwidth product in a specified direction is greater than 8.
Holliday, Jason A; Wang, Tongli; Aitken, Sally
2012-09-01
Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.
NASA Astrophysics Data System (ADS)
Keller, Brenton; Cunefare, David; Grewal, Dilraj S.; Mahmoud, Tamer H.; Izatt, Joseph A.; Farsiu, Sina
2016-07-01
We introduce a metric in graph search and demonstrate its application for segmenting retinal optical coherence tomography (OCT) images of macular pathology. Our proposed "adjusted mean arc length" (AMAL) metric is an adaptation of the lowest mean arc length search technique for automated OCT segmentation. We compare this method to Dijkstra's shortest path algorithm, which we utilized previously in our popular graph theory and dynamic programming segmentation technique. As an illustrative example, we show that AMAL-based length-adaptive segmentation outperforms the shortest path in delineating the retina/vitreous boundary of patients with full-thickness macular holes when compared with expert manual grading.
2013-01-01
Objectives The Alzheimer's Disease Anti-inflammatory Prevention Trial Follow-up Study (ADAPT-FS) was designed to evaluate the efficacy of naproxen and celecoxib for the primary prevention of Alzheimer's disease (AD) several years after cessation of treatment in ADAPT. Methods ADAPT was a randomized, double-masked, multicenter clinical trial of naproxen or celecoxib vs placebo (1:1:1.5 assignment ratio) at six U.S.-based clinics. The trial enrolled 2528 people between 2001 and 2004. Treatments were discontinued in December 2004 and participants were monitored regularly until 2007. In 2010 and 2011, ADAPT-FS screened 1537 participants by telephone and, if indicated, examined them in person using standardized clinical assessments. The primary outcome was time to diagnosis of AD. Death index searches were performed for participants not located. Results Eighty-nine additional AD events were identified (24 celecoxib, 25 naproxen, and 40 placebo) yielding a total of 161 events (48 [6.6% of randomized participants] celecoxib, 43 [6.0%] naproxen, and 70 [6.5%] placebo) across ADAPT and ADAPT-FS. Adjusted hazard ratios (HRs) comparing each treatment with placebo showed no overall reduction in risk of AD: HR celecoxib vs placebo, 1.03 (95% confidence interval [CI], 0.72–1.50; P = .86); HR naproxen vs placebo, 0.92 (95% CI, 0.62– 1.35; P = .66). There were 349 deaths (110 [15.2%] celecoxib, 96 [13.4%] naproxen, and 143 [13.2%] placebo). Risk of death was similar for the naproxen- and placebo-assigned groups (HR, 0.99; 95% CI, 0.76−1.28; P = .93) and slightly higher for celecoxib compared with the placebo-assigned group (HR, 1.15; 95% CI, 0.90−1.48; P = .27). Conclusions These results acquired during a follow-up of approximately 7 years (which included a median of less than 1.5 years of treatment) do not support the hypothesis that celecoxib or naproxen prevent AD in adults with a family history of dementia. PMID:23562431
Cooper, R.J.; Mordecai, Rua S.; Mattsson, B.G.; Conroy, M.J.; Pacifici, K.; Peterson, J.T.; Moore, C.T.
2008-01-01
We describe a survey design and field protocol for the Ivory-billed Woodpecker (Campephilus principalis) search effort that will: (1) allow estimation of occupancy, use, and detection probability for habitats at two spatial scales within the bird?s former range, (2) assess relationships between occupancy, use, and habitat characteristics at those scales, (3) eventually allow the development of a population viability model that depends on patch occupancy instead of difficult-to-measure demographic parameters, and (4) be adaptive, allowing newly collected information to update the above models and search locations. The approach features random selection of patches to be searched from a sampling frame stratified and weighted by patch quality, and requires multiple visits per patch. It is adaptive within a season in that increased search activity is allowed in and around locations of strong visual and/or aural evidence, and adaptive among seasons in that habitat associations allow modification of stratum weights. This statistically rigorous approach is an improvement over simply visiting the ?best? habitat in an ad hoc fashion because we can learn from prior effort and modify the search accordingly. Results from the 2006-07 search season indicate weak relationships between occupancy and habitat (although we suggest modifications of habitat measurement protocols), and a very low detection probability, suggesting more visits per patch are required. Sample size requirements will be discussed.
Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array.
Li, Chuantao; Chen, Fuming; Qi, Fugui; Liu, Miao; Li, Zhao; Liang, Fulai; Jing, Xijing; Lu, Guohua; Wang, Jianqi
2016-01-01
It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor's respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person's head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors. PMID:27073860
Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array.
Li, Chuantao; Chen, Fuming; Qi, Fugui; Liu, Miao; Li, Zhao; Liang, Fulai; Jing, Xijing; Lu, Guohua; Wang, Jianqi
2016-01-01
It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor's respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person's head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors.
Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array
Liu, Miao; Li, Zhao; Liang, Fulai; Jing, Xijing; Lu, Guohua; Wang, Jianqi
2016-01-01
It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor’s respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person’s head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors. PMID:27073860
NASA Astrophysics Data System (ADS)
Baker, Paul T.; Caudill, Sarah; Hodge, Kari A.; Talukder, Dipongkar; Capano, Collin; Cornish, Neil J.
2015-03-01
Searches for gravitational waves produced by coalescing black hole binaries with total masses ≳25 M⊙ use matched filtering with templates of short duration. Non-Gaussian noise bursts in gravitational wave detector data can mimic short signals and limit the sensitivity of these searches. Previous searches have relied on empirically designed statistics incorporating signal-to-noise ratio and signal-based vetoes to separate gravitational wave candidates from noise candidates. We report on sensitivity improvements achieved using a multivariate candidate ranking statistic derived from a supervised machine learning algorithm. We apply the random forest of bagged decision trees technique to two separate searches in the high mass (≳25 M⊙ ) parameter space. For a search which is sensitive to gravitational waves from the inspiral, merger, and ringdown of binary black holes with total mass between 25 M⊙ and 100 M⊙ , we find sensitive volume improvements as high as 70±13%-109±11% when compared to the previously used ranking statistic. For a ringdown-only search which is sensitive to gravitational waves from the resultant perturbed intermediate mass black hole with mass roughly between 10 M⊙ and 600 M⊙ , we find sensitive volume improvements as high as 61±4%-241±12% when compared to the previously used ranking statistic. We also report how sensitivity improvements can differ depending on mass regime, mass ratio, and available data quality information. Finally, we describe the techniques used to tune and train the random forest classifier that can be generalized to its use in other searches for gravitational waves.
Reciprocity breaking during nonlinear propagation of adapted beams through random media
NASA Astrophysics Data System (ADS)
Palastro, J. P.; Peñano, J.; Nelson, W.; DiComo, G.; Helle, M.; Johnson, L. A.; Hafizi, B.
2016-08-01
Adaptive optics (AO) systems rely on the principle of reciprocity, or symmetry with respect to the interchange of point sources and receivers. These systems use the light received from a low power emitter on or near a target to compensate profile aberrations acquired by a laser beam during linear propagation through random media. If, however, the laser beam propagates nonlinearly, reciprocity is broken, potentially undermining AO correction. Here we examine the consequences of this breakdown. While discussed for general random and nonlinear media, we consider specific examples of Kerr-nonlinear, turbulent atmosphere.
Reciprocity breaking during nonlinear propagation of adapted beams through random media.
Palastro, J P; Peñano, J; Nelson, W; DiComo, G; Helle, M; Johnson, L A; Hafizi, B
2016-08-22
Adaptive optics (AO) systems rely on the principle of reciprocity, or symmetry with respect to the interchange of point sources and receivers. These systems use the light received from a low power emitter on or near a target to compensate phase aberrations acquired by a laser beam during linear propagation through random media. If, however, the laser beam propagates nonlinearly, reciprocity is broken, potentially undermining AO correction. Here we examine the consequences of this breakdown, providing the first analysis of AO applied to high peak power laser beams. While discussed for general random and nonlinear media, we consider specific examples of Kerr-nonlinear, turbulent atmosphere.
Reciprocity breaking during nonlinear propagation of adapted beams through random media.
Palastro, J P; Peñano, J; Nelson, W; DiComo, G; Helle, M; Johnson, L A; Hafizi, B
2016-08-22
Adaptive optics (AO) systems rely on the principle of reciprocity, or symmetry with respect to the interchange of point sources and receivers. These systems use the light received from a low power emitter on or near a target to compensate phase aberrations acquired by a laser beam during linear propagation through random media. If, however, the laser beam propagates nonlinearly, reciprocity is broken, potentially undermining AO correction. Here we examine the consequences of this breakdown, providing the first analysis of AO applied to high peak power laser beams. While discussed for general random and nonlinear media, we consider specific examples of Kerr-nonlinear, turbulent atmosphere. PMID:27557166
Yu, Xiaonan; Stewart, Sunita M; Chui, Jolian P L; Ho, Joy L Y; Li, Anthony C H; Lam, Tai Hing
2014-01-01
Immigration occurs globally, and immigrants are vulnerable to the development of adaptation difficulties. Little evidence is available for effective programs to enhance immigrant adaptation outside of the West. This pilot randomized controlled trial tested the effectiveness of two interventions used to decrease adaptation difficulties by (a) providing knowledge of resources that are relevant to the Hong Kong context or (b) enhancing personal resilience in immigrants to Hong Kong from Mainland China. A total of 220 participants were randomly assigned to three conditions: information, resilience, or control arms. They completed measures on adaptation difficulties, knowledge, and personal resilience at baseline, immediately after the intervention (postintervention), and at a 3-month follow-up. The information intervention resulted in higher increases postintervention in knowledge than did the other two arms. The resilience intervention reported greater increases in personal resilience than did the control arm at both postintervention and 3 months later; it also reported greater increases than the information arm did at the 3-month follow-up. Although both interventions reported greater decreases in adaptation difficulties than the control arm did at postintervention and 3 months later, no significant differences were found when they were compared with each other at both time points. Both programs had high acceptability and were feasible to implement in the community. Change in knowledge had no significant mediation effect on adaption difficulties, but change in personal resilience from baseline to postintervention mediated the effect of the intervention on the outcome of adaptation difficulties at the 3-month follow-up. These findings indicate evidence for benefits of the information and resilience interventions, and they inform further development of our programs. PMID:24411121
Effects of systematic phase errors on optimized quantum random-walk search algorithm
NASA Astrophysics Data System (ADS)
Zhang, Yu-Chao; Bao, Wan-Su; Wang, Xiang; Fu, Xiang-Qun
2015-06-01
This study investigates the effects of systematic errors in phase inversions on the success rate and number of iterations in the optimized quantum random-walk search algorithm. Using the geometric description of this algorithm, a model of the algorithm with phase errors is established, and the relationship between the success rate of the algorithm, the database size, the number of iterations, and the phase error is determined. For a given database size, we obtain both the maximum success rate of the algorithm and the required number of iterations when phase errors are present in the algorithm. Analyses and numerical simulations show that the optimized quantum random-walk search algorithm is more robust against phase errors than Grover’s algorithm. Project supported by the National Basic Research Program of China (Grant No. 2013CB338002).
Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.
Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng
2016-10-01
Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods. PMID:27448359
Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.
Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng
2016-10-01
Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods.
Van Es, Simone L; Kumar, Rakesh K; Pryor, Wendy M; Salisbury, Elizabeth L; Velan, Gary M
2015-09-01
To determine whether cytopathology whole slide images and virtual microscopy adaptive tutorials aid learning by postgraduate trainees, we designed a randomized crossover trial to evaluate the quantitative and qualitative impact of whole slide images and virtual microscopy adaptive tutorials compared with traditional glass slide and textbook methods of learning cytopathology. Forty-three anatomical pathology registrars were recruited from Australia, New Zealand, and Malaysia. Online assessments were used to determine efficacy, whereas user experience and perceptions of efficiency were evaluated using online Likert scales and open-ended questions. Outcomes of online assessments indicated that, with respect to performance, learning with whole slide images and virtual microscopy adaptive tutorials was equivalent to using traditional methods. High-impact learning, efficiency, and equity of learning from virtual microscopy adaptive tutorials were strong themes identified in open-ended responses. Participants raised concern about the lack of z-axis capability in the cytopathology whole slide images, suggesting that delivery of z-stacked whole slide images online may be important for future educational development. In this trial, learning cytopathology with whole slide images and virtual microscopy adaptive tutorials was found to be as effective as and perceived as more efficient than learning from glass slides and textbooks. The use of whole slide images and virtual microscopy adaptive tutorials has the potential to provide equitable access to effective learning from teaching material of consistently high quality. It also has broader implications for continuing professional development and maintenance of competence and quality assurance in specialist practice.
The adaptive dynamic community detection algorithm based on the non-homogeneous random walking
NASA Astrophysics Data System (ADS)
Xin, Yu; Xie, Zhi-Qiang; Yang, Jing
2016-05-01
With the changing of the habit and custom, people's social activity tends to be changeable. It is required to have a community evolution analyzing method to mine the dynamic information in social network. For that, we design the random walking possibility function and the topology gain function to calculate the global influence matrix of the nodes. By the analysis of the global influence matrix, the clustering directions of the nodes can be obtained, thus the NRW (Non-Homogeneous Random Walk) method for detecting the static overlapping communities can be established. We design the ANRW (Adaptive Non-Homogeneous Random Walk) method via adapting the nodes impacted by the dynamic events based on the NRW. The ANRW combines the local community detection with dynamic adaptive adjustment to decrease the computational cost for ANRW. Furthermore, the ANRW treats the node as the calculating unity, thus the running manner of the ANRW is suitable to the parallel computing, which could meet the requirement of large dataset mining. Finally, by the experiment analysis, the efficiency of ANRW on dynamic community detection is verified.
Lost in Search: (Mal-)Adaptation to Probabilistic Decision Environments in Children and Adults
ERIC Educational Resources Information Center
Betsch, Tilmann; Lehmann, Anne; Lindow, Stefanie; Lang, Anna; Schoemann, Martin
2016-01-01
Adaptive decision making in probabilistic environments requires individuals to use probabilities as weights in predecisional information searches and/or when making subsequent choices. Within a child-friendly computerized environment (Mousekids), we tracked 205 children's (105 children 5-6 years of age and 100 children 9-10 years of age) and 103…
A Need for an Adaptive Search Tool for Teachers: Case Study
ERIC Educational Resources Information Center
Seyedarabi, Faezeh; Seyedarabi, Arefeh
2005-01-01
Whether intentionally or not, teachers are excluded from having the full benefit of the new technologies developed and adapted by the search engine developers, while all the current and proposed research and developments are focused mainly on the end users (students/learners, businesses and/the government) and not specifically on teachers who act…
Evaluating random search strategies in three mammals from distinct feeding guilds.
Auger-Méthé, Marie; Derocher, Andrew E; DeMars, Craig A; Plank, Michael J; Codling, Edward A; Lewis, Mark A
2016-09-01
Searching allows animals to find food, mates, shelter and other resources essential for survival and reproduction and is thus among the most important activities performed by animals. Theory predicts that animals will use random search strategies in highly variable and unpredictable environments. Two prominent models have been suggested for animals searching in sparse and heterogeneous environments: (i) the Lévy walk and (ii) the composite correlated random walk (CCRW) and its associated area-restricted search behaviour. Until recently, it was difficult to differentiate between the movement patterns of these two strategies. Using a new method that assesses whether movement patterns are consistent with these two strategies and two other common random search strategies, we investigated the movement behaviour of three species inhabiting sparse northern environments: woodland caribou (Rangifer tarandus caribou), barren-ground grizzly bear (Ursus arctos) and polar bear (Ursus maritimus). These three species vary widely in their diets and thus allow us to contrast the movement patterns of animals from different feeding guilds. Our results showed that although more traditional methods would have found evidence for the Lévy walk for some individuals, a comparison of the Lévy walk to CCRWs showed stronger support for the latter. While a CCRW was the best model for most individuals, there was a range of support for its absolute fit. A CCRW was sufficient to explain the movement of nearly half of herbivorous caribou and a quarter of omnivorous grizzly bears, but was insufficient to explain the movement of all carnivorous polar bears. Strong evidence for CCRW movement patterns suggests that many individuals may use a multiphasic movement strategy rather than one-behaviour strategies such as the Lévy walk. The fact that the best model was insufficient to describe the movement paths of many individuals suggests that some animals living in sparse environments may use
ERIC Educational Resources Information Center
Waffenschmidt, Siw; Guddat, Charlotte
2015-01-01
Background: It is unclear which terms should be included in bibliographic searches for randomized controlled trials (RCTs) of drugs, and identifying relevant drug terms can be extremely laborious. The aim of our analysis was to determine whether a bibliographic search using only the generic drug name produces sufficient results for the generation…
Machner, Björn; Sprenger, Andreas; Sander, Thurid; Heide, Wolfgang; Kimmig, Hubert; Helmchen, Christoph; Kömpf, Detlef
2009-05-01
Patients with homonymous hemianopia due to occipital brain lesions show disorders of visual search. In everyday life this leads to difficulties in reading and spatial orientation. It is a matter of debate whether these disorders are due to the brain lesion or rather reflect compensatory eye movement strategies developing over time. For the first time, eye movements of acute hemianopic patients (n= 9) were recorded during the first days following stroke while they performed an exploratory visual-search task. Compared to age-matched control subjects their search duration was prolonged due to increased fixations and refixations, that is, repeated scanning of previously searched locations. Saccadic amplitudes were smaller in patients. Right hemianopic patients were more impaired than left hemianopic patients. The number of fixations and refixations did not differ significantly between both hemifields in the patients. Follow-up of one patient revealed changes of visual search over 18 months. By using more structured scanpaths with fewer saccades his search duration decreased. Furthermore, he developed a more efficient eye-movement strategy by making larger but less frequent saccades toward his blind side. In summary, visual-search behavior of acute hemianopic patients differs from healthy control subjects and from chronic hemianopic patients. We conclude that abnormal visual search in acute hemianopic patients is related to the brain lesion. We provide some evidence for adaptive eye-movement strategies developed over time. These adaptive strategies make the visual search more efficient and may help to compensate for the persisting visual-field loss. PMID:19645941
Ryeznik, Yevgen; Sverdlov, Oleksandr; Wong, Weng Kee
2016-01-01
Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool, a user interface software developed in MATLAB for designing response-adaptive randomized comparative clinical trials with censored time-to-event outcomes. The RARtool software can compute different types of optimal treatment allocation designs, and it can simulate response-adaptive randomization procedures targeting selected optimal allocations. Through simulations, an investigator can assess design characteristics under a variety of experimental scenarios and select the best procedure for practical implementation. We illustrate the utility of our RARtool software by redesigning a survival trial from the literature. PMID:26997924
Black-Box System Testing of Real-Time Embedded Systems Using Random and Search-Based Testing
NASA Astrophysics Data System (ADS)
Arcuri, Andrea; Iqbal, Muhammad Zohaib; Briand, Lionel
Testing real-time embedded systems (RTES) is in many ways challenging. Thousands of test cases can be potentially executed on an industrial RTES. Given the magnitude of testing at the system level, only a fully automated approach can really scale up to test industrial RTES. In this paper we take a black-box approach and model the RTES environment using the UML/MARTE international standard. Our main motivation is to provide a more practical approach to the model-based testing of RTES by allowing system testers, who are often not familiar with the system design but know the application domain well-enough, to model the environment to enable test automation. Environment models can support the automation of three tasks: the code generation of an environment simulator, the selection of test cases, and the evaluation of their expected results (oracles). In this paper, we focus on the second task (test case selection) and investigate three test automation strategies using inputs from UML/MARTE environment models: Random Testing (baseline), Adaptive Random Testing, and Search-Based Testing (using Genetic Algorithms). Based on one industrial case study and three artificial systems, we show how, in general, no technique is better than the others. Which test selection technique to use is determined by the failure rate (testing stage) and the execution time of test cases. Finally, we propose a practical process to combine the use of all three test strategies.
How to adapt broad-band gravitational-wave searches for r-modes
Owen, Benjamin J.
2010-11-15
Up to now there has been no search for gravitational waves from the r-modes of neutron stars in spite of the theoretical interest in the subject. Several oddities of r-modes must be addressed to obtain an observational result: The gravitational radiation field is dominated by the mass current (gravitomagnetic) quadrupole rather than the usual mass quadrupole, and the consequent difference in polarization affects detection statistics and parameter estimation. To astrophysically interpret a detection or upper limit it is necessary to convert the gravitational-wave amplitude to an r-mode amplitude. Also, it is helpful to know indirect limits on gravitational-wave emission to gauge the interest of various searches. Here I address these issues, thereby providing the ingredients to adapt broad-band searches for continuous gravitational waves to obtain r-mode results. I also show that searches of existing data can already have interesting sensitivities to r-modes.
CALL FOR PAPERS: Special issue on the random search problem: trends and perspectives
NASA Astrophysics Data System (ADS)
da Luz, Marcos G. E.; Grosberg, Alexander Y.; Raposo, Ernesto P.; Viswanathan, Gandhi M.
2008-11-01
This is a call for contributions to a special issue of Journal of Physics A: Mathematical and Theoretical dedicated to the subject of the random search problem. The motivation behind this special issue is to summarize in a single comprehensive publication, the main aspects (past and present), latest developments, different viewpoints and the directions being followed in this multidisciplinary field. We hope that such a special issue could become a particularly valuable reference for the broad scientific community working with the general random search problem. The Editorial Board has invited Marcos G E da Luz, Alexander Y Grosberg, Ernesto P Raposo and Gandhi M Viswanathan to serve as Guest Editors for the special issue. The general question of how to optimize the search for specific target objects in either continuous or discrete environments when the information available is limited is of significant importance in a broad range of fields. Representative examples include ecology (animal foraging, dispersion of populations), geology (oil recovery from mature reservoirs), information theory (automated researchers of registers in high-capacity database), molecular biology (proteins searching for their sites, e.g., on DNA ), etc. One reason underlying the richness of the random search problem relates to the `ignorance' of the locations of the randomly located `targets'. A statistical approach to the search problem can deal adequately with incomplete information and so stochastic strategies become advantageous. The general problem of how to search efficiently for randomly located target sites can thus be quantitatively described using the concepts and methods of statistical physics and stochastic processes. Scope Thus far, to the best of our knowledge, no recent textbook or review article in a physics journal has appeared on this topic. This makes a special issue with review and research articles attractive to those interested in acquiring a general introduction to the
Coevolution of information processing and topology in hierarchical adaptive random Boolean networks
NASA Astrophysics Data System (ADS)
Górski, Piotr J.; Czaplicka, Agnieszka; Hołyst, Janusz A.
2016-02-01
Random Boolean Networks (RBNs) are frequently used for modeling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive random Boolean Network (HARBN) as a system consisting of distinct adaptive RBNs (ARBNs) - subnetworks - connected by a set of permanent interlinks. We investigate mean node information, mean edge information as well as mean node degree. Information measures and internal subnetworks topology of HARBN coevolve and reach steady-states that are specific for a given network structure. The main natural feature of ARBNs, i.e. their adaptability, is preserved in HARBNs and they evolve towards critical configurations which is documented by power law distributions of network attractor lengths. The mean information processed by a single node or a single link increases with the number of interlinks added to the system. The mean length of network attractors and the mean steady-state connectivity possess minima for certain specific values of the quotient between the density of interlinks and the density of all links in networks. It means that the modular network displays extremal values of its observables when subnetworks are connected with a density a few times lower than a mean density of all links.
Controlled random search technique for estimation of convective heat transfer coefficient
NASA Astrophysics Data System (ADS)
Mehta, R. C.; Tiwari, S. B.
2007-09-01
This paper is concerned with a method for solving inverse heat conduction problem. The method is based on the controlled random search (CRS) technique in conjunction with modified Newton-Raphson method. The random search procedure does not need the computation of derivative of the function to be evaluated. Therefore, it is independent of the calculation of the sensitivity coefficient for nonlinear parameter estimation. The algorithm does not depend on the future-temperature information and can predict convective heat transfer coefficient with random errors in the input temperature data. The technique is first validated against an analytical solution of heat conduction equation for a typical rocket nozzle. Comparison with an earlier analysis of inverse heat conduction problem of a similar experiment shows that the present method provides solutions, which are fully consistent with the earlier results. Once validated, the technique is used to investigate another estimation of heat transfer coefficient for an experiment of short duration, high heating rate, and employing indepth temperature measurement. The CRS procedure, in conjunction with modified Newton-Raphson method, is quite useful in estimating the value of the convective heat-transfer coefficient from the measured transient temperature data on the outer surface or imbedded thermocouple inside the rocket nozzle. Some practical examples are illustrated, which demonstrate the stability and accuracy of the method to predict the surface heat flux.
An Adaptive Physical Activity Intervention for Overweight Adults: A Randomized Controlled Trial
Adams, Marc A.; Sallis, James F.; Norman, Gregory J.; Hovell, Melbourne F.; Hekler, Eric B.; Perata, Elyse
2013-01-01
Background Physical activity (PA) interventions typically include components or doses that are static across participants. Adaptive interventions are dynamic; components or doses change in response to short-term variations in participant's performance. Emerging theory and technologies make adaptive goal setting and feedback interventions feasible. Objective To test an adaptive intervention for PA based on Operant and Behavior Economic principles and a percentile-based algorithm. The adaptive intervention was hypothesized to result in greater increases in steps per day than the static intervention. Methods Participants (N = 20) were randomized to one of two 6-month treatments: 1) static intervention (SI) or 2) adaptive intervention (AI). Inactive overweight adults (85% women, M = 36.9±9.2 years, 35% non-white) in both groups received a pedometer, email and text message communication, brief health information, and biweekly motivational prompts. The AI group received daily step goals that adjusted up and down based on the percentile-rank algorithm and micro-incentives for goal attainment. This algorithm adjusted goals based on a moving window; an approach that responded to each individual's performance and ensured goals were always challenging but within participants' abilities. The SI group received a static 10,000 steps/day goal with incentives linked to uploading the pedometer's data. Results A random-effects repeated-measures model accounted for 180 repeated measures and autocorrelation. After adjusting for covariates, the treatment phase showed greater steps/day relative to the baseline phase (p<.001) and a group by study phase interaction was observed (p = .017). The SI group increased by 1,598 steps/day on average between baseline and treatment while the AI group increased by 2,728 steps/day on average between baseline and treatment; a significant between-group difference of 1,130 steps/day (Cohen's d = .74). Conclusions The adaptive
Hwang, Wei-Chin; Myers, Hector; Chiu, Eddie; Mak, Elsie; Butner, Jonathan; Fujimoto, Ken; Wood, Jeff; Miranda, Jeanne
2015-01-01
Objective No randomized controlled trials (RCTs) for adults have tested the effectiveness of a well-specified psychotherapy compared with a culturally adapted version of the same treatment. This study evaluates the effectiveness of cognitive behavioral therapy (CBT) and culturally adapted CBT (CA-CBT) in treating depressed Chinese American adults. Methods This was a RCT that treated 50 Chinese Americans who met criteria for major depression and sought treatment at community mental health clinics. Participants were screened beginning September 2008, with the last assessment conducted in March 2011. Participants were randomly assigned to 12 sessions of CBT or CA-CBT. Stratified randomization was used for patients who were on and not on antidepressants when they first came to the clinic, and the study did not influence regular prescription practices. The primary outcomes were dropout rates and the Hamilton Depression Rating Scale measured at baseline, session 4, session 8, and session 12. Results Participants in CA-CBT evidenced a greater overall decrease in depressive symptoms than those in CBT, but depression rates remained similarly high at week 12. Differences in dropout rates approached, but did not meet statistical significance (7% CA-CBT and 26% CBT). Conclusions Chinese Americans entered this study with very severe depression. Participants in both CBT and CA-CBT evidenced significant decreases in depressive symptoms, but the majority did not reach remission. Results suggest that these short-term treatments were not sufficient to address such severe depression and that more intensive and longer treatments may be needed. Results also indicate that cultural adaptations may confer additional treatment benefits. PMID:26129996
Adaptive consensus of scale-free multi-agent system by randomly selecting links
NASA Astrophysics Data System (ADS)
Mou, Jinping; Ge, Huafeng
2016-06-01
This paper investigates an adaptive consensus problem for distributed scale-free multi-agent systems (SFMASs) by randomly selecting links, where the degree of each node follows a power-law distribution. The randomly selecting links are based on the assumption that every agent decides to select links among its neighbours according to the received data with a certain probability. Accordingly, a novel consensus protocol with the range of the received data is developed, and each node updates its state according to the protocol. By the iterative method and Cauchy inequality, the theoretical analysis shows that all errors among agents converge to zero, and in the meanwhile, several criteria of consensus are obtained. One numerical example shows the reliability of the proposed methods.
Adaptive box filters for removal of random noise from digital images
NASA Technical Reports Server (NTRS)
Eliason, Eric M.; Mcewen, Alfred S.
1990-01-01
Adaptive box-filtering algorithms to remove random bit errors and to smooth noisy data have been developed. For both procedures, the standard deviation of those pixels within a local box surrounding each pixel is used. A series of two or three filters with decreasing box sizes can be run to clean up extremely noisy images and to remove bit errors near sharp edges. The second filter, for noise smoothing, is similar to the 'sigma filter' of Lee (1983). The technique effectively reduces speckle in radar images without eliminating fine details.
Search on a hypercubic lattice using a quantum random walk. I. d>2
Patel, Apoorva; Rahaman, Md. Aminoor
2010-09-15
Random walks describe diffusion processes, where movement at every time step is restricted to only the neighboring locations. We construct a quantum random walk algorithm, based on discretization of the Dirac evolution operator inspired by staggered lattice fermions. We use it to investigate the spatial search problem, that is, to find a marked vertex on a d-dimensional hypercubic lattice. The restriction on movement hardly matters for d>2, and scaling behavior close to Grover's optimal algorithm (which has no restriction on movement) can be achieved. Using numerical simulations, we optimize the proportionality constants of the scaling behavior, and demonstrate the approach to that for Grover's algorithm (equivalent to the mean-field theory or the d{yields}{infinity} limit). In particular, the scaling behavior for d=3 is only about 25% higher than the optimal d{yields}{infinity} value.
NASA Astrophysics Data System (ADS)
Vannini, Marco; Cannicci, Stefano; Mrabu, Elisha; Rorandelli, Rocco; Fratini, Sara
2008-12-01
Terebralia palustris is a common mud-whelk present at a particularly high density in all Indo-West Pacific mangroves. Young snails feed on nothing but mud while larger specimens are able to feed on fallen leaves too. In Kenya (Mida Creek) under the canopy, competition for mangrove leaves can be very high due to the high density of Sesarmidae crabs. On open exposed muddy platforms, no Sesarmidae occur but the leaf density is very low because the leaves are only randomly present as they are deposited and removed twice a day by the tide. However, the snail density is always very high, raising the question as to whether the snails use a special searching strategy to optimize their resource finding rather than a purely random movement. By analyzing the snails' movements on a uniform area at different levels and comparing them with simulated random paths, we could show that the snails' movements are not purely random. The distribution of different size classes of T. palustris in Mida Creek was known to be quite odd: the same simulation approach suggests that the zonation asymmetry could reasonably be due to the stochastic recruitment of juveniles in space and time and maintained by a substantial long-lasting spatial inertia.
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938
Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei
2015-01-01
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928
Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei
2015-01-01
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.
Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei
2015-01-01
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928
Patel, Manesh R.; Schardt, Connie M.; Sanders, Linda L.; Keitz, Sheri A.
2006-01-01
Objective: The paper compares the speed, validity, and applicability of two different protocols for searching the primary medical literature. Design: A randomized trial involving medicine residents was performed. Setting: An inpatient general medicine rotation was used. Participants: Thirty-two internal medicine residents were block randomized into four groups of eight. Main Outcome Measures: Success rate of each search protocol was measured by perceived search time, number of questions answered, and proportion of articles that were applicable and valid. Results: Residents randomized to the MEDLINE-first (protocol A) group searched 120 questions, and residents randomized to the MEDLINE-last (protocol B) searched 133 questions. In protocol A, 104 answers (86.7%) and, in protocol B, 117 answers (88%) were found to clinical questions. In protocol A, residents reported that 26 (25.2%) of the answers were obtained quickly or rated as “fast” (<5 minutes) as opposed to 55 (51.9%) in protocol B, (P = 0.0004). A subset of questions and articles (n = 79) were reviewed by faculty who found that both protocols identified similar numbers of answer articles that addressed the questions and were felt to be valid using critical appraisal criteria. Conclusion: For resident-generated clinical questions, both protocols produced a similarly high percentage of applicable and valid articles. The MEDLINE-last search protocol was perceived to be faster. However, in the MEDLINE-last protocol, a significant portion of questions (23%) still required searching MEDLINE to find an answer. PMID:17082828
2014-01-01
In the current practice, to determine the safety factor of a slope with two-dimensional circular potential failure surface, one of the searching methods for the critical slip surface is Genetic Algorithm (GA), while the method to calculate the slope safety factor is Fellenius' slices method. However GA needs to be validated with more numeric tests, while Fellenius' slices method is just an approximate method like finite element method. This paper proposed a new method to determine the minimum slope safety factor which is the determination of slope safety factor with analytical solution and searching critical slip surface with Genetic-Traversal Random Method. The analytical solution is more accurate than Fellenius' slices method. The Genetic-Traversal Random Method uses random pick to utilize mutation. A computer automatic search program is developed for the Genetic-Traversal Random Method. After comparison with other methods like slope/w software, results indicate that the Genetic-Traversal Random Search Method can give very low safety factor which is about half of the other methods. However the obtained minimum safety factor with Genetic-Traversal Random Search Method is very close to the lower bound solutions of slope safety factor given by the Ansys software. PMID:24782679
Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.
Mei, Gang; Xu, Nengxiong; Xu, Liangliang
2016-01-01
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm. PMID:27610308
NASA Astrophysics Data System (ADS)
Chen, Xianshun; Feng, Liang; Ong, Yew Soon
2012-07-01
In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.
Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.
Mei, Gang; Xu, Nengxiong; Xu, Liangliang
2016-01-01
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm.
Adaptive control of the propagation of ultrafast light through random and nonlinear media
NASA Astrophysics Data System (ADS)
Moores, Mark David
2001-12-01
Ultrafast light sources generate coherent pulses with durations of less than one picosecond, and represent the next generation of illuminators for medical imaging and optical communications applications. Such sources are already widely used experimentally. Correction of temporal widths or pulse envelopes after traversal of optically non-ideal materials is critical for the delivery of optimal ultrashort pulses. It is important to investigate the physical mechanisms that distort pulses and to develop and implement methods for minimizing these effects. In this work, we investigate methods for characterizing and manipulating pulse propagation dynamics in random (scattering) and nonlinear optical media. In particular, we use pulse shaping to manipulate the light field of ultrashort infrared pulses. Application of spectral phase by a liquid crystal spatial light modulator is used to control the temporal pulse shape. The applied phase is controlled by a genetic algorithm that adaptively responds to the feedback from previous phase profiles. Experiments are detailed that address related aspects of the character of ultrafast pulses-the short timescales and necessarily wide frequency bandwidths. Material dispersion is by definition frequency dependent. Passage through an inhomogeneous system of randomly situated boundaries (scatterers) causes additional distortion of ballistic pulses due to multiple reflections. The reflected rays accumulate phase shifts that depend on the separation of the reflecting boundaries and the photon frequency. Ultrafast bandwidths present a wide range of frequencies for dispersion and interaction with macroscopic dielectric structure. The shaper and adaptive learning algorithm are used to reduce these effects, lessening the impact of the scattering medium on propagating pulses. The timescale of ultrashort pulses results in peak intensities that interact with the electronic structure of optical materials to induce polarization that is no longer
First-passage times in multiscale random walks: The impact of movement scales on search efficiency
NASA Astrophysics Data System (ADS)
Campos, Daniel; Bartumeus, Frederic; Raposo, E. P.; Méndez, Vicenç
2015-11-01
An efficient searcher needs to balance properly the trade-off between the exploration of new spatial areas and the exploitation of nearby resources, an idea which is at the core of scale-free Lévy search strategies. Here we study multiscale random walks as an approximation to the scale-free case and derive the exact expressions for their mean-first-passage times in a one-dimensional finite domain. This allows us to provide a complete analytical description of the dynamics driving the situation in which both nearby and faraway targets are available to the searcher, so the exploration-exploitation trade-off does not have a trivial solution. For this situation, we prove that the combination of only two movement scales is able to outperform both ballistic and Lévy strategies. This two-scale strategy involves an optimal discrimination between the nearby and faraway targets which is only possible by adjusting the range of values of the two movement scales to the typical distances between encounters. So, this optimization necessarily requires some prior information (albeit crude) about target distances or distributions. Furthermore, we found that the incorporation of additional (three, four, …) movement scales and its adjustment to target distances does not improve further the search efficiency. This allows us to claim that optimal random search strategies arise through the informed combination of only two walk scales (related to the exploitative and the explorative scales, respectively), expanding on the well-known result that optimal strategies in strictly uninformed scenarios are achieved through Lévy paths (or, equivalently, through a hierarchical combination of multiple scales).
NASA Astrophysics Data System (ADS)
Land, Phillip; Majumdar, Arun K.
2016-05-01
This paper describes a new concept of mitigating signal distortions caused by random air-water interface using an adaptive optics (AO) system. This is the first time the concept of using an AO for mitigating the effects of distortions caused mainly by a random air-water interface is presented. We have demonstrated the feasibility of correcting the distortions using AO in a laboratory water tank for investigating the propagation effects of a laser beam through an airwater interface. The AO system consisting of a fast steering mirror, deformable mirror, and a Shack-Hartmann Wavefront Sensor for mitigating surface water distortions has a unique way of stabilizing and aiming a laser onto an object underneath the water. Essentially the AO system mathematically takes the complex conjugate of the random phase caused by air-water interface allowing the laser beam to penetrate through the water by cancelling with the complex conjugates. The results show the improvement of a number of metrics including Strehl ratio, a measure of the quality of optical image formation for diffraction limited optical system. These are the first results demonstrating the feasibility of developing a new sensor system such as Laser Doppler Vibrometer (LDV) utilizing AO for mitigating surface water distortions.
Lack of adaptation to random conflicting force fields of variable magnitude.
Gupta, Rahul; Ashe, James
2007-01-01
The concept of internal models has been used to explain how the brain learns and stores a variety of motor behaviors. A large body of work has shown that conflicting internal models could not be learned simultaneously; this suggests either a limited capacity or the unstable nature of short-term motor memories. However, it has been recently shown that multiple conflicting internal models of motor behavior could be acquired simultaneously if associated with appropriate contextual cues and random presentations. We re-examined this issue in a more complex environment in which the magnitude of the conflicting fields could vary randomly. Human subjects failed to show any evidence of learning the force fields themselves or the magnitude of the forces experienced, even with extended practice. Subjects did adapt to the applied perturbation when the field strength was kept constant but still did not form internal models. Our results show that neither random presentation nor specific contextual cues are sufficient for learning conflicting internal models when the magnitude of the forces is also unpredictable. The data suggest that multiple conflicting internal models cannot be learned in all environments, and provide support for the unstable nature or limited capacity of motor memories.
Shack-Hartmann wavefront sensor with large dynamic range by adaptive spot search method.
Shinto, Hironobu; Saita, Yusuke; Nomura, Takanori
2016-07-10
A Shack-Hartmann wavefront sensor (SHWFS) that consists of a microlens array and an image sensor has been used to measure the wavefront aberrations of human eyes. However, a conventional SHWFS has finite dynamic range depending on the diameter of the each microlens. The dynamic range cannot be easily expanded without a decrease of the spatial resolution. In this study, an adaptive spot search method to expand the dynamic range of an SHWFS is proposed. In the proposed method, spots are searched with the help of their approximate displacements measured with low spatial resolution and large dynamic range. By the proposed method, a wavefront can be correctly measured even if the spot is beyond the detection area. The adaptive spot search method is realized by using the special microlens array that generates both spots and discriminable patterns. The proposed method enables expanding the dynamic range of an SHWFS with a single shot and short processing time. The performance of the proposed method is compared with that of a conventional SHWFS by optical experiments. Furthermore, the dynamic range of the proposed method is quantitatively evaluated by numerical simulations.
NASA Astrophysics Data System (ADS)
Shi, Junfei; Li, Lingling; Liu, Fang; Jiao, Licheng; Liu, Hongying; Yang, Shuyuan; Liu, Lu; Hao, Hongxia
2016-04-01
Markov random field (MRF) model is an effective tool for polarimetric synthetic aperture radar (PolSAR) image classification. However, due to the lack of suitable contextual information in conventional MRF methods, there is usually a contradiction between edge preservation and region homogeneity in the classification result. To preserve edge details and obtain homogeneous regions simultaneously, an adaptive MRF framework is proposed based on a polarimetric sketch map. The polarimetric sketch map can provide the edge positions and edge directions in detail, which can guide the selection of neighborhood structures. Specifically, the polarimetric sketch map is extracted to partition a PolSAR image into structural and nonstructural parts, and then adaptive neighborhoods are learned for two parts. For structural areas, geometric weighted neighborhood structures are constructed to preserve image details. For nonstructural areas, the maximum homogeneous regions are obtained to improve the region homogeneity. Experiments are taken on both the simulated and real PolSAR data, and the experimental results illustrate that the proposed method can obtain better performance on both region homogeneity and edge preservation than the state-of-the-art methods.
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Ab initio random structure search for 13-atom clusters of fcc elements.
Chou, J P; Hsing, C R; Wei, C M; Cheng, C; Chang, C M
2013-03-27
The 13-atom metal clusters of fcc elements (Al, Rh, Ir, Ni, Pd, Pt, Cu, Ag, Au) were studied by density functional theory calculations. The global minima were searched for by the ab initio random structure searching method. In addition to some new lowest-energy structures for Pd13 and Au13, we found that the effective coordination numbers of the lowest-energy clusters would increase with the ratio of the dimer-to-bulk bond length. This correlation, together with the electronic structures of the lowest-energy clusters, divides the 13-atom clusters of these fcc elements into two groups (except for Au13, which prefers a two-dimensional structure due to the relativistic effect). Compact-like clusters that are composed exclusively of triangular motifs are preferred for elements without d-electrons (Al) or with (nearly) filled d-band electrons (Ni, Pd, Cu, Ag). Non-compact clusters composed mainly of square motifs connected by some triangular motifs (Rh, Ir, Pt) are favored for elements with unfilled d-band electrons.
Seeking mathematics success for college students: a randomized field trial of an adapted approach
NASA Astrophysics Data System (ADS)
Gula, Taras; Hoessler, Carolyn; Maciejewski, Wes
2015-11-01
Many students enter the Canadian college system with insufficient mathematical ability and leave the system with little improvement. Those students who enter with poor mathematics ability typically take a developmental mathematics course as their first and possibly only mathematics course. The educational experiences that comprise a developmental mathematics course vary widely and are, too often, ineffective at improving students' ability. This trend is concerning, since low mathematics ability is known to be related to lower rates of success in subsequent courses. To date, little attention has been paid to the selection of an instructional approach to consistently apply across developmental mathematics courses. Prior research suggests that an appropriate instructional method would involve explicit instruction and practising mathematical procedures linked to a mathematical concept. This study reports on a randomized field trial of a developmental mathematics approach at a college in Ontario, Canada. The new approach is an adaptation of the JUMP Math program, an explicit instruction method designed for primary and secondary school curriculae, to the college learning environment. In this study, a subset of courses was assigned to JUMP Math and the remainder was taught in the same style as in the previous years. We found consistent, modest improvement in the JUMP Math sections compared to the non-JUMP sections, after accounting for potential covariates. The findings from this randomized field trial, along with prior research on effective education for developmental mathematics students, suggest that JUMP Math is a promising way to improve college student outcomes.
CR-Calculus and adaptive array theory applied to MIMO random vibration control tests
NASA Astrophysics Data System (ADS)
Musella, U.; Manzato, S.; Peeters, B.; Guillaume, P.
2016-09-01
Performing Multiple-Input Multiple-Output (MIMO) tests to reproduce the vibration environment in a user-defined number of control points of a unit under test is necessary in applications where a realistic environment replication has to be achieved. MIMO tests require vibration control strategies to calculate the required drive signal vector that gives an acceptable replication of the target. This target is a (complex) vector with magnitude and phase information at the control points for MIMO Sine Control tests while in MIMO Random Control tests, in the most general case, the target is a complete spectral density matrix. The idea behind this work is to tailor a MIMO random vibration control approach that can be generalized to other MIMO tests, e.g. MIMO Sine and MIMO Time Waveform Replication. In this work the approach is to use gradient-based procedures over the complex space, applying the so called CR-Calculus and the adaptive array theory. With this approach it is possible to better control the process performances allowing the step-by-step Jacobian Matrix update. The theoretical bases behind the work are followed by an application of the developed method to a two-exciter two-axis system and by performance comparisons with standard methods.
Seismic random noise attenuation based on adaptive time-frequency peak filtering
NASA Astrophysics Data System (ADS)
Deng, Xinhuan; Ma, Haitao; Li, Yue; Zeng, Qian
2015-02-01
Time-frequency peak filtering (TFPF) method uses a specific window with fixed length to recover band-limited signal in stationary random noise. However, the derivatives of signal such as seismic wavelets may change rapidly in some short time intervals. In this case, TFPF equipped with fixed window length will not provide an optimal solution. In this letter, we present an adaptive version of TFPF for seismic random noise attenuation. In our version, the improved intersection of confidence intervals combined with short-time energy criterion is used to preprocess the noisy signal. And then, we choose an appropriate threshold to divide the noisy signal into signal, buffer and noise. Different optimal window lengths are used in each type of segments. We test the proposed method on both synthetic and field seismic data. The experimental results illustrate that the proposed method makes the degree of amplitude preservation raise more than 10% and signal-to-noise (SNR) improve 2-4 dB compared with the original algorithm.
A simple heuristic for Internet-based evidence search in primary care: a randomized controlled trial
Eberbach, Andreas; Becker, Annette; Rochon, Justine; Finkemeler, Holger; Wagner, Achim; Donner-Banzhoff, Norbert
2016-01-01
Background General practitioners (GPs) are confronted with a wide variety of clinical questions, many of which remain unanswered. Methods In order to assist GPs in finding quick, evidence-based answers, we developed a learning program (LP) with a short interactive workshop based on a simple three-step-heuristic to improve their search and appraisal competence (SAC). We evaluated the LP effectiveness with a randomized controlled trial (RCT). Participants (intervention group [IG] n=20; control group [CG] n=31) rated acceptance and satisfaction and also answered 39 knowledge questions to assess their SAC. We controlled for previous knowledge in content areas covered by the test. Results Main outcome – SAC: within both groups, the pre–post test shows significant (P=0.00) improvements in correctness (IG 15% vs CG 11%) and confidence (32% vs 26%) to find evidence-based answers. However, the SAC difference was not significant in the RCT. Other measures Most workshop participants rated “learning atmosphere” (90%), “skills acquired” (90%), and “relevancy to my practice” (86%) as good or very good. The LP-recommendations were implemented by 67% of the IG, whereas 15% of the CG already conformed to LP recommendations spontaneously (odds ratio 9.6, P=0.00). After literature search, the IG showed a (not significantly) higher satisfaction regarding “time spent” (IG 80% vs CG 65%), “quality of information” (65% vs 54%), and “amount of information” (53% vs 47%). Conclusion Long-standing established GPs have a good SAC. Despite high acceptance, strong learning effects, positive search experience, and significant increase of SAC in the pre–post test, the RCT of our LP showed no significant difference in SAC between IG and CG. However, we suggest that our simple decision heuristic merits further investigation. PMID:27563264
Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
NASA Astrophysics Data System (ADS)
Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin
2016-08-01
This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.
NASA Astrophysics Data System (ADS)
Wu, Xia; Wu, Genhua
2014-08-01
Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.
On random search: Collection kinetics of Paramecia into a trap embedded in a closed domain
NASA Astrophysics Data System (ADS)
Deforet, Maxime; Duplat, Jérôme; Vandenberghe, Nicolas; Villermaux, Emmanuel
2010-06-01
We study the kinetics of a large number of organisms initially spread uniformly in a circular two-dimensional medium, at the center of which a smaller circular trap has been introduced. We take advantage of the acidophily of Paramecium caudatum, which, coming from a neutral medium, penetrates a region of moderate acidity but moves back in the opposite situation when it meets a sharp negative acidity gradient to quantify its rate of irreversible aggregation into a spot of acidified medium in water. Two regimes are distinguished: A ballistic regime characteristic of "fresh" paramecia where the organisms swim in a straight path with a well defined velocity and a Brownian regime characteristic of older paramecia where the mean free path of the organisms is smaller than the system size. Both regimes are characterized by distinct aggregation laws. They both result from a pure random trapping process that appears to have no adaptive strategy.
NASA Astrophysics Data System (ADS)
Tsoulos, Ioannis G.; Lagaris, Isaac E.
2006-01-01
A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use of the procedure known as grammatical evolution. The method can be considered as a "genetic" modification of the Controlled Random Search procedure due to Price. The user may code the objective function either in C++ or in Fortran 77. We offer a comparison of the new method with others of similar structure, by presenting results of computational experiments on a set of test functions. Program summaryTitle of program: GenPrice Catalogue identifier:ADWP Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWP Program available from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: the tool is designed to be portable in all systems running the GNU C++ compiler Installation: University of Ioannina, Greece Programming language used: GNU-C++, GNU-C, GNU Fortran-77 Memory required to execute with typical data: 200 KB No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: no No. of lines in distributed program, including test data, etc.:13 135 No. of bytes in distributed program, including test data, etc.: 78 512 Distribution format: tar. gz Nature of physical problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques are frequently trapped in local minima. Global optimization is hence the appropriate tool. For example, solving a nonlinear system of equations via optimization, employing a "least squares" type of objective, one may encounter many local minima that do not correspond to solutions, i.e. minima with values
Optimal search strategies of space-time coupled random walkers with finite lifetimes.
Campos, D; Abad, E; Méndez, V; Yuste, S B; Lindenberg, K
2015-05-01
We present a simple paradigm for detection of an immobile target by a space-time coupled random walker with a finite lifetime. The motion of the walker is characterized by linear displacements at a fixed speed and exponentially distributed duration, interrupted by random changes in the direction of motion and resumption of motion in the new direction with the same speed. We call these walkers "mortal creepers." A mortal creeper may die at any time during its motion according to an exponential decay law characterized by a finite mean death rate ω(m). While still alive, the creeper has a finite mean frequency ω of change of the direction of motion. In particular, we consider the efficiency of the target search process, characterized by the probability that the creeper will eventually detect the target. Analytic results confirmed by numerical results show that there is an ω(m)-dependent optimal frequency ω=ω(opt) that maximizes the probability of eventual target detection. We work primarily in one-dimensional (d=1) domains and examine the role of initial conditions and of finite domain sizes. Numerical results in d=2 domains confirm the existence of an optimal frequency of change of direction, thereby suggesting that the observed effects are robust to changes in dimensionality. In the d=1 case, explicit expressions for the probability of target detection in the long time limit are given. In the case of an infinite domain, we compute the detection probability for arbitrary times and study its early- and late-time behavior. We further consider the survival probability of the target in the presence of many independent creepers beginning their motion at the same location and at the same time. We also consider a version of the standard "target problem" in which many creepers start at random locations at the same time. PMID:26066127
Optimal search strategies of space-time coupled random walkers with finite lifetimes.
Campos, D; Abad, E; Méndez, V; Yuste, S B; Lindenberg, K
2015-05-01
We present a simple paradigm for detection of an immobile target by a space-time coupled random walker with a finite lifetime. The motion of the walker is characterized by linear displacements at a fixed speed and exponentially distributed duration, interrupted by random changes in the direction of motion and resumption of motion in the new direction with the same speed. We call these walkers "mortal creepers." A mortal creeper may die at any time during its motion according to an exponential decay law characterized by a finite mean death rate ω(m). While still alive, the creeper has a finite mean frequency ω of change of the direction of motion. In particular, we consider the efficiency of the target search process, characterized by the probability that the creeper will eventually detect the target. Analytic results confirmed by numerical results show that there is an ω(m)-dependent optimal frequency ω=ω(opt) that maximizes the probability of eventual target detection. We work primarily in one-dimensional (d=1) domains and examine the role of initial conditions and of finite domain sizes. Numerical results in d=2 domains confirm the existence of an optimal frequency of change of direction, thereby suggesting that the observed effects are robust to changes in dimensionality. In the d=1 case, explicit expressions for the probability of target detection in the long time limit are given. In the case of an infinite domain, we compute the detection probability for arbitrary times and study its early- and late-time behavior. We further consider the survival probability of the target in the presence of many independent creepers beginning their motion at the same location and at the same time. We also consider a version of the standard "target problem" in which many creepers start at random locations at the same time.
NASA Astrophysics Data System (ADS)
Maeda, Shimon; Nosato, Hirokazu; Matsunawa, Tetsuaki; Miyairi, Masahiro; Nojima, Shigeki; Tanaka, Satoshi; Sakanashi, Hidenori; Murakawa, Masahiro; Saito, Tamaki; Higuchi, Tetsuya; Inoue, Soichi
2010-04-01
SRAF (Sub Resolution Assist Feature) technique has been widely used for DOF enhancement. Below 40nm design node, even in the case of using the SRAF technique, the resolution limit is approached due to the use of hyper NA imaging or low k1 lithography conditions especially for the contact layer. As a result, complex layout patterns or random patterns like logic data or intermediate pitch patterns become increasingly sensitive to photo-resist pattern fidelity. This means that the need for more accurate resolution technique is increasing in order to cope with lithographic patterning fidelity issues in low k1 lithography conditions. To face with these issues, new SRAF technique like model based SRAF using an interference map or inverse lithography technique has been proposed. But these approaches don't have enough assurance for accuracy or performance, because the ideal mask generated by these techniques is lost when switching to a manufacturable mask with Manhattan structures. As a result it might be very hard to put these things into practice and production flow. In this paper, we propose the novel method for extremely accurate SRAF placement using an adaptive search algorithm. In this method, the initial position of SRAF is generated by the traditional SRAF placement such as rule based SRAF, and it is adjusted by adaptive algorithm using the evaluation of lithography simulation. This method has three advantages which are preciseness, efficiency and industrial applicability. That is, firstly, the lithography simulation uses actual computational model considering process window, thus our proposed method can precisely adjust the SRAF positions, and consequently we can acquire the best SRAF positions. Secondly, because our adaptive algorithm is based on optimal gradient method, which is very simple algorithm and rectilinear search, the SRAF positions can be adjusted with high efficiency. Thirdly, our proposed method, which utilizes the traditional SRAF placement, is
NASA Astrophysics Data System (ADS)
Tao, Yimo; Zhou, Xiang Sean; Bi, Jinbo; Jerebkoa, Anna; Wolf, Matthias; Salganicoff, Marcos; Krishnana, Arun
2009-02-01
Characterization and quantification of the severity of diffuse parenchymal lung diseases (DPLDs) using Computed Tomography (CT) is an important issue in clinical research. Recently, several classification-based computer-aided diagnosis (CAD) systems [1-3] for DPLD have been proposed. For some of those systems, a degradation of performance [2] was reported on unseen data because of considerable inter-patient variances of parenchymal tissue patterns. We believe that a CAD system of real clinical value should be robust to inter-patient variances and be able to classify unseen cases online more effectively. In this work, we have developed a novel adaptive knowledge-driven CT image search engine that combines offline learning aspects of classification-based CAD systems with online learning aspects of content-based image retrieval (CBIR) systems. Our system can seamlessly and adaptively fuse offline accumulated knowledge with online feedback, leading to an improved online performance in detecting DPLD in both accuracy and speed aspects. Our contribution lies in: (1) newly developed 3D texture-based and morphology-based features; (2) a multi-class offline feature selection method; and, (3) a novel image search engine framework for detecting DPLD. Very promising results have been obtained on a small test set.
Adaptive Lévy Processes and Area-Restricted Search in Human Foraging
Hills, Thomas T.; Kalff, Christopher; Wiener, Jan M.
2013-01-01
A considerable amount of research has claimed that animals’ foraging behaviors display movement lengths with power-law distributed tails, characteristic of Lévy flights and Lévy walks. Though these claims have recently come into question, the proposal that many animals forage using Lévy processes nonetheless remains. A Lévy process does not consider when or where resources are encountered, and samples movement lengths independently of past experience. However, Lévy processes too have come into question based on the observation that in patchy resource environments resource-sensitive foraging strategies, like area-restricted search, perform better than Lévy flights yet can still generate heavy-tailed distributions of movement lengths. To investigate these questions further, we tracked humans as they searched for hidden resources in an open-field virtual environment, with either patchy or dispersed resource distributions. Supporting previous research, for both conditions logarithmic binning methods were consistent with Lévy flights and rank-frequency methods–comparing alternative distributions using maximum likelihood methods–showed the strongest support for bounded power-law distributions (truncated Lévy flights). However, goodness-of-fit tests found that even bounded power-law distributions only accurately characterized movement behavior for 4 (out of 32) participants. Moreover, paths in the patchy environment (but not the dispersed environment) showed a transition to intensive search following resource encounters, characteristic of area-restricted search. Transferring paths between environments revealed that paths generated in the patchy environment were adapted to that environment. Our results suggest that though power-law distributions do not accurately reflect human search, Lévy processes may still describe movement in dispersed environments, but not in patchy environments–where search was area-restricted. Furthermore, our results indicate that
ERIC Educational Resources Information Center
Poslawsky, Irina E; Naber, Fabiënne BA; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H
2015-01-01
In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child…
Adaptive Algebraic Multigrid for Finite Element Elliptic Equations with Random Coefficients
Kalchev, D
2012-04-02
This thesis presents a two-grid algorithm based on Smoothed Aggregation Spectral Element Agglomeration Algebraic Multigrid (SA-{rho}AMGe) combined with adaptation. The aim is to build an efficient solver for the linear systems arising from discretization of second-order elliptic partial differential equations (PDEs) with stochastic coefficients. Examples include PDEs that model subsurface flow with random permeability field. During a Markov Chain Monte Carlo (MCMC) simulation process, that draws PDE coefficient samples from a certain distribution, the PDE coefficients change, hence the resulting linear systems to be solved change. At every such step the system (discretized PDE) needs to be solved and the computed solution used to evaluate some functional(s) of interest that then determine if the coefficient sample is acceptable or not. The MCMC process is hence computationally intensive and requires the solvers used to be efficient and fast. This fact that at every step of MCMC the resulting linear system changes, makes an already existing solver built for the old problem perhaps not as efficient for the problem corresponding to the new sampled coefficient. This motivates the main goal of our study, namely, to adapt an already existing solver to handle the problem (with changed coefficient) with the objective to achieve this goal to be faster and more efficient than building a completely new solver from scratch. Our approach utilizes the local element matrices (for the problem with changed coefficients) to build local problems associated with constructed by the method agglomerated elements (a set of subdomains that cover the given computational domain). We solve a generalized eigenproblem for each set in a subspace spanned by the previous local coarse space (used for the old solver) and a vector, component of the error, that the old solver cannot handle. A portion of the spectrum of these local eigen-problems (corresponding to eigenvalues close to zero) form the
Polynomial order selection in random regression models via penalizing adaptively the likelihood.
Corrales, J D; Munilla, S; Cantet, R J C
2015-08-01
Orthogonal Legendre polynomials (LP) are used to model the shape of additive genetic and permanent environmental effects in random regression models (RRM). Frequently, the Akaike (AIC) and the Bayesian (BIC) information criteria are employed to select LP order. However, it has been theoretically shown that neither AIC nor BIC is simultaneously optimal in terms of consistency and efficiency. Thus, the goal was to introduce a method, 'penalizing adaptively the likelihood' (PAL), as a criterion to select LP order in RRM. Four simulated data sets and real data (60,513 records, 6675 Colombian Holstein cows) were employed. Nested models were fitted to the data, and AIC, BIC and PAL were calculated for all of them. Results showed that PAL and BIC identified with probability of one the true LP order for the additive genetic and permanent environmental effects, but AIC tended to favour over parameterized models. Conversely, when the true model was unknown, PAL selected the best model with higher probability than AIC. In the latter case, BIC never favoured the best model. To summarize, PAL selected a correct model order regardless of whether the 'true' model was within the set of candidates.
Rosenblum, Michael
2014-01-01
It is a challenge to design randomized trials when it is suspected that a treatment may benefit only certain subsets of the target population. In such situations, trial designs have been proposed that modify the population enrolled based on an interim analysis, in a preplanned manner. For example, if there is early evidence during the trial that the treatment only benefits a certain subset of the population, enrollment may then be restricted to this subset. At the end of such a trial, it is desirable to draw inferences about the selected population. We focus on constructing confidence intervals for the average treatment effect in the selected population. Confidence interval methods that fail to account for the adaptive nature of the design may fail to have the desired coverage probability. We provide a new procedure for constructing confidence intervals having at least 95% coverage probability, uniformly over a large class Q of possible data generating distributions. Our method involves computing the minimum factor c by which a standard confidence interval must be expanded in order to have, asymptotically, at least 95% coverage probability, uniformly over Q. Computing the expansion factor c is not trivial, since it is not a priori clear, for a given decision rule, which data generating distribution leads to the worst-case coverage probability. We give an algorithm that computes c, and prove an optimality property for the resulting confidence interval procedure. PMID:23553577
NASA Astrophysics Data System (ADS)
Zhang, Yongsheng; Xiong, Hongkai; He, Zhihai; Yu, Songyu
2010-07-01
An important issue in Wyner-Ziv video coding is the reconstruction of Wyner-Ziv frames with decoded bit-planes. So far, there are two major approaches: the Maximum a Posteriori (MAP) reconstruction and the Minimum Mean Square Error (MMSE) reconstruction algorithms. However, these approaches do not exploit smoothness constraints in natural images. In this paper, we model a Wyner-Ziv frame by Markov random fields (MRFs), and produce reconstruction results by finding an MAP estimation of the MRF model. In the MRF model, the energy function consists of two terms: a data term, MSE distortion metric in this paper, measuring the statistical correlation between side-information and the source, and a smoothness term enforcing spatial coherence. In order to better describe the spatial constraints of images, we propose a context-adaptive smoothness term by analyzing the correspondence between the output of Slepian-Wolf decoding and successive frames available at decoders. The significance of the smoothness term varies in accordance with the spatial variation within different regions. To some extent, the proposed approach is an extension to the MAP and MMSE approaches by exploiting the intrinsic smoothness characteristic of natural images. Experimental results demonstrate a considerable performance gain compared with the MAP and MMSE approaches.
Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field
Luo, Gang; Min, Wanli
2007-01-01
Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884
VES/TEM 1D joint inversion by using Controlled Random Search (CRS) algorithm
NASA Astrophysics Data System (ADS)
Bortolozo, Cassiano Antonio; Porsani, Jorge Luís; Santos, Fernando Acácio Monteiro dos; Almeida, Emerson Rodrigo
2015-01-01
Electrical (DC) and Transient Electromagnetic (TEM) soundings are used in a great number of environmental, hydrological, and mining exploration studies. Usually, data interpretation is accomplished by individual 1D models resulting often in ambiguous models. This fact can be explained by the way as the two different methodologies sample the medium beneath surface. Vertical Electrical Sounding (VES) is good in marking resistive structures, while Transient Electromagnetic sounding (TEM) is very sensitive to conductive structures. Another difference is VES is better to detect shallow structures, while TEM soundings can reach deeper layers. A Matlab program for 1D joint inversion of VES and TEM soundings was developed aiming at exploring the best of both methods. The program uses CRS - Controlled Random Search - algorithm for both single and 1D joint inversions. Usually inversion programs use Marquadt type algorithms but for electrical and electromagnetic methods, these algorithms may find a local minimum or not converge. Initially, the algorithm was tested with synthetic data, and then it was used to invert experimental data from two places in Paraná sedimentary basin (Bebedouro and Pirassununga cities), both located in São Paulo State, Brazil. Geoelectric model obtained from VES and TEM data 1D joint inversion is similar to the real geological condition, and ambiguities were minimized. Results with synthetic and real data show that 1D VES/TEM joint inversion better recovers simulated models and shows a great potential in geological studies, especially in hydrogeological studies.
Kalchev, D.; Ketelsen, C.; Vassilevski, P. S.
2013-11-07
Our paper proposes an adaptive strategy for reusing a previously constructed coarse space by algebraic multigrid to construct a two-level solver for a problem with nearby characteristics. Furthermore, a main target application is the solution of the linear problems that appear throughout a sequence of Markov chain Monte Carlo simulations of subsurface flow with uncertain permeability field. We demonstrate the efficacy of the method with extensive set of numerical experiments.
Sadjadi, Firooz A
2006-08-01
An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.
Benchmark tests and spin adaptation for the particle-particle random phase approximation
Yang, Yang; Steinmann, Stephan N.; Peng, Degao; Aggelen, Helen van; Yang, Weitao
2013-11-07
The particle-particle random phase approximation (pp-RPA) provides an approximation to the correlation energy in density functional theory via the adiabatic connection [H. van Aggelen, Y. Yang, and W. Yang, Phys. Rev. A 88, 030501 (2013)]. It has virtually no delocalization error nor static correlation error for single-bond systems. However, with its formal O(N{sup 6}) scaling, the pp-RPA is computationally expensive. In this paper, we implement a spin-separated and spin-adapted pp-RPA algorithm, which reduces the computational cost by a substantial factor. We then perform benchmark tests on the G2/97 enthalpies of formation database, DBH24 reaction barrier database, and four test sets for non-bonded interactions (HB6/04, CT7/04, DI6/04, and WI9/04). For the G2/97 database, the pp-RPA gives a significantly smaller mean absolute error (8.3 kcal/mol) than the direct particle-hole RPA (ph-RPA) (22.7 kcal/mol). Furthermore, the error in the pp-RPA is nearly constant with the number of atoms in a molecule, while the error in the ph-RPA increases. For chemical reactions involving typical organic closed-shell molecules, pp- and ph-RPA both give accurate reaction energies. Similarly, both RPAs perform well for reaction barriers and nonbonded interactions. These results suggest that the pp-RPA gives reliable energies in chemical applications. The adiabatic connection formalism based on pairing matrix fluctuation is therefore expected to lead to widely applicable and accurate density functionals.
NASA Astrophysics Data System (ADS)
Kasprzyk, J. R.; Watson, A. A.
2014-12-01
Deep uncertainty refers to situations in which decision makers or stakeholders do not know, or cannot fully agree upon, the full suite of risk factors within a planning problem. This phenomenon is especially important when considering scenarios of future environmental change, since there exist multiple trajectories of environmental forcings (e.g., streamflow timing and magnitude) and socioeconomic factors (e.g., population growth). This presentation first briefly reviews robust optimization and scenario approaches that have been proposed to plan for systems under deep uncertainty. One recently introduced framework is Many Objective Robust Decision Making (MORDM). MORDM combines two techniques: evolutionary algorithm search is used to generate planning alternatives, and robust decision making methods are used to sample performance over a large range of plausible factors and, subsequently, choose a robust solution. Within MORDM, Pareto approximate tradeoff sets of solutions are used to balance objectives and examine alternatives. However, MORDM does not currently incorporate the deeply uncertain scenario information into the search process itself. In this presentation, we suggest several avenues for doing so, that are focused on modifying the suite of uncertain data that is selected within the search process. Visualizations that compare tradeoff sets across different sets of assumptions can be used to guide decision makers' learning and, ultimately, their selection of several candidate solutions for further planning. For example, the baseline assumptions about probability distributions can be compared to optimization results under severe events to determine adaptive management strategies. A case study of water planning in the Lower Rio Grande Valley (LRGV) in Texas is used to demonstrate the approach. Our LRGV results compare baseline optimization with new solution sets that examine optimal management strategies under scenarios characterized by lower than average
Li, Borui; Mu, Chundi; Han, Shuli; Bai, Tianming
2014-01-01
Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects. Bayesian extended object tracking (EOT) using a random symmetrical positive definite (SPD) matrix is a very effective method to jointly estimate the kinematic state and physical extension of the target. The key issue in the application of this random matrix-based EOT approach is to model the physical extension and measurement noise accurately. Model parameter adaptive approaches for both extension dynamic and measurement noise are proposed in this study based on the properties of the SPD matrix to improve the performance of extension estimation. An interacting multi-model algorithm based on model parameter adaptive filter using random matrix is also presented. Simulation results demonstrate the effectiveness of the proposed adaptive approaches and multi-model algorithm. The estimation performance of physical extension is better than the other algorithms, especially when the target maneuvers. The kinematic state estimation error is lower than the others as well. PMID:24763252
Li, Borui; Mu, Chundi; Han, Shuli; Bai, Tianming
2014-04-24
Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects. Bayesian extended object tracking (EOT) using a random symmetrical positive definite (SPD) matrix is a very effective method to jointly estimate the kinematic state and physical extension of the target. The key issue in the application of this random matrix-based EOT approach is to model the physical extension and measurement noise accurately. Model parameter adaptive approaches for both extension dynamic and measurement noise are proposed in this study based on the properties of the SPD matrix to improve the performance of extension estimation. An interacting multi-model algorithm based on model parameter adaptive filter using random matrix is also presented. Simulation results demonstrate the effectiveness of the proposed adaptive approaches and multi-model algorithm. The estimation performance of physical extension is better than the other algorithms, especially when the target maneuvers. The kinematic state estimation error is lower than the others as well.
ERIC Educational Resources Information Center
Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien
2013-01-01
The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…
Job-Search Strategies and Reemployment Quality: The Impact of Career Adaptability
ERIC Educational Resources Information Center
Koen, Jessie; Klehe, Ute-Christine; Van Vianen, Annelies E. M.; Zikic, Jelena; Nauta, Aukje
2010-01-01
Past job-search research has focused on how hard unemployed people search for a job, but we still know little about the strategies that people use during their search and how we can predict the quality of the reemployment found. The first aim of this study was to predict the use of different job-search strategies via job-seekers' career…
Putungan, Darwin Barayang; Lin, Shi-Hsin; Kuo, Jer-Lai
2016-07-27
We systematically investigated the potential of single-layer VS2 polytypes as Na-battery anode materials via density functional theory calculations. We found that sodiation tends to inhibit the 1H-to-1T structural phase transition, in contrast to lithiation-induced transition on monolayer MoS2. Thus, VS2 can have better structural stability in the cycles of charging and discharging. Diffussion of Na atom was found to be very fast on both polytypes, with very small diffusion barriers of 0.085 eV (1H) and 0.088 eV (1T). Ab initio random structure searching was performed in order to explore stable configurations of Na on VS2. Our search found that both the V top and the hexagonal center sites are preferred adsorption sites for Na, with the 1H phase showing a relatively stronger binding. Notably, our random structures search revealed that Na clusters can form as a stacked second layer at full Na concentration, which is not reported in earlier works wherein uniform, single-layer Na adsorption phases were assumed. With reasonably high specific energy capacity (232.91 and 116.45 mAh/g for 1H and 1T phases, respectively) and open-circuit voltage (1.30 and 1.42 V for 1H and 1T phases, respectively), VS2 is a promising alternative material for Na-ion battery anodes with great structural sturdiness. Finally, we have shown the capability of the ab initio random structure searching in the assessment of potential materials for energy storage applications. PMID:27373121
Putungan, Darwin Barayang; Lin, Shi-Hsin; Kuo, Jer-Lai
2016-07-27
We systematically investigated the potential of single-layer VS2 polytypes as Na-battery anode materials via density functional theory calculations. We found that sodiation tends to inhibit the 1H-to-1T structural phase transition, in contrast to lithiation-induced transition on monolayer MoS2. Thus, VS2 can have better structural stability in the cycles of charging and discharging. Diffussion of Na atom was found to be very fast on both polytypes, with very small diffusion barriers of 0.085 eV (1H) and 0.088 eV (1T). Ab initio random structure searching was performed in order to explore stable configurations of Na on VS2. Our search found that both the V top and the hexagonal center sites are preferred adsorption sites for Na, with the 1H phase showing a relatively stronger binding. Notably, our random structures search revealed that Na clusters can form as a stacked second layer at full Na concentration, which is not reported in earlier works wherein uniform, single-layer Na adsorption phases were assumed. With reasonably high specific energy capacity (232.91 and 116.45 mAh/g for 1H and 1T phases, respectively) and open-circuit voltage (1.30 and 1.42 V for 1H and 1T phases, respectively), VS2 is a promising alternative material for Na-ion battery anodes with great structural sturdiness. Finally, we have shown the capability of the ab initio random structure searching in the assessment of potential materials for energy storage applications.
NASA Astrophysics Data System (ADS)
Lang, Jun; Hao, Zhengchao
2014-01-01
In this paper, we first propose the discrete multi-parameter fractional random transform (DMPFRNT), which can make the spectrum distributed randomly and uniformly. Then we introduce this new spectrum transform into the image fusion field and present a new approach for the remote sensing image fusion, which utilizes both adaptive pulse coupled neural network (PCNN) and the discrete multi-parameter fractional random transform in order to meet the requirements of both high spatial resolution and low spectral distortion. In the proposed scheme, the multi-spectral (MS) and panchromatic (Pan) images are converted into the discrete multi-parameter fractional random transform domains, respectively. In DMPFRNT spectrum domain, high amplitude spectrum (HAS) and low amplitude spectrum (LAS) components carry different informations of original images. We take full advantage of the synchronization pulse issuance characteristics of PCNN to extract the HAS and LAS components properly, and give us the PCNN ignition mapping images which can be used to determine the fusion parameters. In the fusion process, local standard deviation of the amplitude spectrum is chosen as the link strength of pulse coupled neural network. Numerical simulations are performed to demonstrate that the proposed method is more reliable and superior than several existing methods based on Hue Saturation Intensity representation, Principal Component Analysis, the discrete fractional random transform etc.
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-01-01
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved. PMID:27420062
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-01-01
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved. PMID:27420062
Villar, Sofía S.; Wason, James; Bowden, Jack
2016-01-01
SUMMARY The Gittins index provides a well established, computationally attractive, optimal solution to a class of resource allocation problems known collectively as the multi-arm bandit problem. Its development was originally motivated by the problem of optimal patient allocation in multi-arm clinical trials. However, it has never been used in practice, possibly for the following reasons: (1) it is fully sequential, i.e., the endpoint must be observable soon after treating a patient, reducing the medical settings to which it is applicable; (2) it is completely deterministic and thus removes randomization from the trial, which would naturally protect against various sources of bias. We propose a novel implementation of the Gittins index rule that overcomes these difficulties, trading off a small deviation from optimality for a fully randomized, adaptive group allocation procedure which offers substantial improvements in terms of patient benefit, especially relevant for small populations. We report the operating characteristics of our approach compared to existing methods of adaptive randomization using a recently published trial as motivation. PMID:26098023
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-07-12
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.
Searching for control: priming randomness increases the evaluation of ritual efficacy.
Legare, Cristine H; Souza, André L
2014-01-01
Reestablishing feelings of control after experiencing uncertainty has long been considered a fundamental motive for human behavior. We propose that rituals (i.e., socially stipulated, causally opaque practices) provide a means for coping with the aversive feelings associated with randomness due to the perception of a connection between ritual action and a desired outcome. Two experiments were conducted (one in Brazil [n = 40] and another in the United States [n = 94]) to evaluate how the perceived efficacy of rituals is affected by feelings of randomness. In a between-subjects design, the Scramble Sentence Task was used as a priming procedure in three conditions (i.e., randomness, negativity, and neutral) and participants were then asked to rate the efficacy of rituals used for problem-solving purposes. The results demonstrate that priming randomness increased participants' perception of ritual efficacy relative to negativity and neutral conditions. Implications for increasing our understanding of the relationship between perceived control and ritualistic behavior are discussed.
Xu, Hancong; Liu, Jinfeng; Li, Yang; Yin, Yan; Zhu, Chenxu; Lu, Hua
2014-07-10
Autofocus is an important technique for high-speed image acquisition in the second-generation DNA sequencing system, and this paper studies the passive focus algorithm for the system, which consists of two parts: focus measurement (FM) and focus search (FS). Based on the properties of DNA chips' images, we choose the normalized variance as the FM algorithm and develop a new robust FS named adaptive prediction approximation combined search (APACS). APACS utilizes golden section search (GSS) to approximate the focus position and engages the curve-fitting search (CFS) to predict the position simultaneously in every step of GSS. When the difference between consecutive predictions meets the set precision, the search finishes. Otherwise, it ends as GSS. In APACS, we also propose an estimation method, named the combination of centroid estimation and overdetermined equations estimation by least squares solution, to calculate the initial vector for the nonlinear equations in APACS prediction, which reduces the iterations and accelerates the search. The simulation and measured results demonstrate that APACS not only maintains the stability but also reduces the focus time compared with GSS and CFS, which indicates APACS is a robust and fast FS for the fluorescence microscope in a sequencing system.
Seismic random noise elimination according to the adaptive fractal conservation law
NASA Astrophysics Data System (ADS)
Meng, Fanlei; Li, Yue; Zeng, Qian
2016-05-01
The fractal conservation law (FCL) is based on the Cauchy problem of the partial differential equation (PDE), which is modified by an anti-diffusive term of lower order. The analysis indicates that it can eliminate the high frequencies and preserve or amplify the low/medium frequencies. The performance of FCL depends on the threshold selected for the PDE. This threshold corresponds to the cut-off frequency of FCL in the frequency domain. Generally, the threshold is fixed. Thus, the FCL cannot track the signal beyond the cut-off frequency, and it removes the higher-frequency components of the signal. To solve this problem, an adaptive FCL filtering method is presented. The main purpose of this method is to select the optimal FCL threshold in each sample index such that it can adaptively track the rapid changes in the signal. In the adaptive FCL, we select FCL estimations with different thresholds and construct a convex hull of these estimations of each sample index. Consequently, we introduce a quadratic functional with respect to FCL estimation to ensure that we select the optimal estimation from the convex hull of each sample index. This leads to a box-constrained convex problem, which can be solved by the Viterbi algorithm.
2011-01-01
Background Amputation impairs the ability to balance. We examined adaptation strategies in balance following dysvascularity-induced unilateral tibial amputation in skilled prosthetic users (SPU) and first fitted amputees (FFA) (N = 28). Methods Excursions of center of pressure (COP) were determined during 20 s quiet standing using a stabilometry system with eyes-open on both legs or on the non-affected leg(s). Main measures: COP trajectories and time functions; distribution of reaction forces between the two legs; inclination angles obtained through second order regression analysis using stabilogram data. Results FFA vs SPU demonstrated 27.8% greater postural sway in bilateral stance (p = 0.0004). Postural sway area was smaller in FFA standing on the non-affected leg compared with SPU (p = 0.028). The slope of the regression line indicating postural stability was nearly identical in FFA and SPU and the direction of regression line was opposite for the left and right leg amputees. Conclusion Of the two adaptation strategies in balance, the first appears before amputation due to pain and fatigue in the affected leg. This strategy appears in the form of reduced postural sway while standing on the non-affected leg. The second adaptation occurs during rehabilitation and regular use of the prosthesis resulting in normal weightbearing associated with reduced postural sway on two legs and return to the normal postural stability on one leg. PMID:21619618
Searching for Control: Priming Randomness Increases the Evaluation of Ritual Efficacy
ERIC Educational Resources Information Center
Legare, Cristine H.; Souza, André L.
2014-01-01
Reestablishing feelings of control after experiencing uncertainty has long been considered a fundamental motive for human behavior. We propose that rituals (i.e., socially stipulated, causally opaque practices) provide a means for coping with the aversive feelings associated with randomness due to the perception of a connection between ritual…
Searching for control: priming randomness increases the evaluation of ritual efficacy.
Legare, Cristine H; Souza, André L
2014-01-01
Reestablishing feelings of control after experiencing uncertainty has long been considered a fundamental motive for human behavior. We propose that rituals (i.e., socially stipulated, causally opaque practices) provide a means for coping with the aversive feelings associated with randomness due to the perception of a connection between ritual action and a desired outcome. Two experiments were conducted (one in Brazil [n = 40] and another in the United States [n = 94]) to evaluate how the perceived efficacy of rituals is affected by feelings of randomness. In a between-subjects design, the Scramble Sentence Task was used as a priming procedure in three conditions (i.e., randomness, negativity, and neutral) and participants were then asked to rate the efficacy of rituals used for problem-solving purposes. The results demonstrate that priming randomness increased participants' perception of ritual efficacy relative to negativity and neutral conditions. Implications for increasing our understanding of the relationship between perceived control and ritualistic behavior are discussed. PMID:23941272
Hao, Xiang; Martin-Rouault, Laure; Cui, Meng
2014-07-29
Controlling the propagation of electromagnetic waves is important to a broad range of applications. Recent advances in controlling wave propagation in random scattering media have enabled optical focusing and imaging inside random scattering media. In this work, we propose and demonstrate a new method to deliver optical power more efficiently through scattering media. Drastically different from the random matrix characterization approach, our method can rapidly establish high efficiency communication channels using just a few measurements, regardless of the number of optical modes, and provides a practical and robust solution to boost the signal levels in optical or short wave communications. We experimentally demonstrated analog and digital signal transmission through highly scattering media with greatly improved performance. Besides scattering, our method can also reduce the loss of signal due to absorption. Experimentally, we observed that our method forced light to go around absorbers, leading to even higher signal improvement than in the case of purely scattering media. Interestingly, the resulting signal improvement is highly directional, which provides a new means against eavesdropping.
Kim, Mi-Ok; Liu, Chunyan; Hu, Feifang; Lee, J Jack
2014-10-15
Delay in the outcome variable is challenging for outcome-adaptive randomization, as it creates a lag between the number of subjects accrued and the information known at the time of the analysis. Motivated by a real-life pediatric ulcerative colitis trial, we consider a case where a short-term predictor is available for the delayed outcome. When a short-term predictor is not considered, studies have shown that the asymptotic properties of many outcome-adaptive randomization designs are little affected unless the lag is unreasonably large relative to the accrual process. These theoretical results assumed independent identical delays, however, whereas delays in the presence of a short-term predictor may only be conditionally homogeneous. We consider delayed outcomes as missing and propose mitigating the delay effect by imputing them. We apply this approach to the doubly adaptive biased coin design (DBCD) for motivating pediatric ulcerative colitis trial. We provide theoretical results that if the delays, although non-homogeneous, are reasonably short relative to the accrual process similarly as in the iid delay case, the lag is also asymptotically ignorable in the sense that a standard DBCD that utilizes only observed outcomes attains target allocation ratios in the limit. Empirical studies, however, indicate that imputation-based DBCDs performed more reliably in finite samples with smaller root mean square errors. The empirical studies assumed a common clinical setting where a delayed outcome is positively correlated with a short-term predictor similarly between treatment arm groups. We varied the strength of the correlation and considered fast and slow accrual settings. PMID:24889540
Rath, J J; Veluvolu, K C; Defoort, M
2014-01-01
The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system. PMID:24683321
Rath, J J; Veluvolu, K C; Defoort, M
2014-01-01
The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system.
Rath, J. J.; Veluvolu, K. C.; Defoort, M.
2014-01-01
The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system. PMID:24683321
Search for Random Fluctuations in Periods of Short-period Cepheids
NASA Astrophysics Data System (ADS)
Berdnikov, L. N.; Stevens, I. R.
2010-02-01
Data from SMEI instrument (onboard the CORIOLIS spacecraft) for 16 brightest Cepheids were analyzed with the Eddington-Plakidis method and random fluctuations in periods for four of them, SU Cas (P=1.95d), δ Cep (P=5.37d), κ Pav (P=9.09d), and α UMi (P=3.97d) were detected. Such fluctuations for short period Cepheids were found for the first time.
Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows.
Ivanov, Mark V; Levitsky, Lev I; Gorshkov, Mikhail V
2016-09-01
A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms. Graphical Abstract ᅟ. PMID:27349255
Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows
NASA Astrophysics Data System (ADS)
Ivanov, Mark V.; Levitsky, Lev I.; Gorshkov, Mikhail V.
2016-09-01
A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms.
Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows.
Ivanov, Mark V; Levitsky, Lev I; Gorshkov, Mikhail V
2016-09-01
A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms. Graphical Abstract ᅟ.
NASA Astrophysics Data System (ADS)
Franck, Bas A. M.; Dreschler, Wouter A.; Lyzenga, Johannes
2004-12-01
In this study we investigated the reliability and convergence characteristics of an adaptive multidirectional pattern search procedure, relative to a nonadaptive multidirectional pattern search procedure. The procedure was designed to optimize three speech-processing strategies. These comprise noise reduction, spectral enhancement, and spectral lift. The search is based on a paired-comparison paradigm, in which subjects evaluated the listening comfort of speech-in-noise fragments. The procedural and nonprocedural factors that influence the reliability and convergence of the procedure are studied using various test conditions. The test conditions combine different tests, initial settings, background noise types, and step size configurations. Seven normal hearing subjects participated in this study. The results indicate that the reliability of the optimization strategy may benefit from the use of an adaptive step size. Decreasing the step size increases accuracy, while increasing the step size can be beneficial to create clear perceptual differences in the comparisons. The reliability also depends on starting point, stop criterion, step size constraints, background noise, algorithms used, as well as the presence of drifting cues and suboptimal settings. There appears to be a trade-off between reliability and convergence, i.e., when the step size is enlarged the reliability improves, but the convergence deteriorates. .
Search on a hypercubic lattice using a quantum random walk. II. d=2
NASA Astrophysics Data System (ADS)
Patel, Apoorva; Raghunathan, K. S.; Rahaman, Md. Aminoor
2010-09-01
We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d=2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article [A. Patel and M. A. Rahaman, Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.82.032330 82, 032330 (2010)] provides an O(NlnN) algorithm, which is not optimal. The scaling behavior can be improved to O(NlnN) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi [Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.78.012310 78, 012310 (2008)]. We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.
Normal and Tumoral Melanocytes Exhibit q-Gaussian Random Search Patterns
da Silva, Priscila C. A.; Rosembach, Tiago V.; Santos, Anésia A.; Rocha, Márcio S.; Martins, Marcelo L.
2014-01-01
In multicellular organisms, cell motility is central in all morphogenetic processes, tissue maintenance, wound healing and immune surveillance. Hence, failures in its regulation potentiates numerous diseases. Here, cell migration assays on plastic 2D surfaces were performed using normal (Melan A) and tumoral (B16F10) murine melanocytes in random motility conditions. The trajectories of the centroids of the cell perimeters were tracked through time-lapse microscopy. The statistics of these trajectories was analyzed by building velocity and turn angle distributions, as well as velocity autocorrelations and the scaling of mean-squared displacements. We find that these cells exhibit a crossover from a normal to a super-diffusive motion without angular persistence at long time scales. Moreover, these melanocytes move with non-Gaussian velocity distributions. This major finding indicates that amongst those animal cells supposedly migrating through Lévy walks, some of them can instead perform q-Gaussian walks. Furthermore, our results reveal that B16F10 cells infected by mycoplasmas exhibit essentially the same diffusivity than their healthy counterparts. Finally, a q-Gaussian random walk model was proposed to account for these melanocytic migratory traits. Simulations based on this model correctly describe the crossover to super-diffusivity in the cell migration tracks. PMID:25203532
Normal and tumoral melanocytes exhibit q-Gaussian random search patterns.
da Silva, Priscila C A; Rosembach, Tiago V; Santos, Anésia A; Rocha, Márcio S; Martins, Marcelo L
2014-01-01
In multicellular organisms, cell motility is central in all morphogenetic processes, tissue maintenance, wound healing and immune surveillance. Hence, failures in its regulation potentiates numerous diseases. Here, cell migration assays on plastic 2D surfaces were performed using normal (Melan A) and tumoral (B16F10) murine melanocytes in random motility conditions. The trajectories of the centroids of the cell perimeters were tracked through time-lapse microscopy. The statistics of these trajectories was analyzed by building velocity and turn angle distributions, as well as velocity autocorrelations and the scaling of mean-squared displacements. We find that these cells exhibit a crossover from a normal to a super-diffusive motion without angular persistence at long time scales. Moreover, these melanocytes move with non-Gaussian velocity distributions. This major finding indicates that amongst those animal cells supposedly migrating through Lévy walks, some of them can instead perform q-Gaussian walks. Furthermore, our results reveal that B16F10 cells infected by mycoplasmas exhibit essentially the same diffusivity than their healthy counterparts. Finally, a q-Gaussian random walk model was proposed to account for these melanocytic migratory traits. Simulations based on this model correctly describe the crossover to super-diffusivity in the cell migration tracks. PMID:25203532
Cermak, Sharon A.; Stein Duker, Leah I.; Williams, Marian E.; Dawson, Michael E.; Lane, Christianne J.; Polido, José C.
2015-01-01
This pilot and feasibility study examined the impact of a sensory adapted dental environment (SADE) to reduce distress, sensory discomfort, and perception of pain during oral prophylaxis for children with autism spectrum disorder (ASD). Participants were 44 children ages 6-12 (n=22 typical, n=22 ASD). In an experimental crossover design, each participant underwent two professional dental cleanings, one in a regular dental environment (RDE) and one in a SADE, administered in a randomized and counterbalanced order three to four months apart. Outcomes included measures of physiological anxiety, behavioral distress, pain intensity, and sensory discomfort. Both groups exhibited decreased physiological anxiety and reported lower pain and sensory discomfort in the SADE condition compared to RDE, indicating a beneficial effect of the SADE. PMID:25931290
NASA Astrophysics Data System (ADS)
Garcia-Santiago, C. A.; Del Ser, J.; Upton, C.; Quilligan, F.; Gil-Lopez, S.; Salcedo-Sanz, S.
2015-11-01
When seeking near-optimal solutions for complex scheduling problems, meta-heuristics demonstrate good performance with affordable computational effort. This has resulted in a gravitation towards these approaches when researching industrial use-cases such as energy-efficient production planning. However, much of the previous research makes assumptions about softer constraints that affect planning strategies and about how human planners interact with the algorithm in a live production environment. This article describes a job-shop problem that focuses on minimizing energy consumption across a production facility of shared resources. The application scenario is based on real facilities made available by the Irish Center for Manufacturing Research. The formulated problem is tackled via harmony search heuristics with random keys encoding. Simulation results are compared to a genetic algorithm, a simulated annealing approach and a first-come-first-served scheduling. The superior performance obtained by the proposed scheduler paves the way towards its practical implementation over industrial production chains.
Berry, Scott M; Petzold, Elizabeth A; Dull, Peter; Thielman, Nathan M; Cunningham, Coleen K; Corey, G Ralph; McClain, Micah T; Hoover, David L; Russell, James; Griffiss, J McLeod; Woods, Christopher W
2016-02-01
The outbreak of Ebola virus disease in West Africa is the largest ever recorded. Numerous treatment alternatives for Ebola have been considered, including widely available repurposed drugs, but initiation of enrollment into clinical trials has been limited. The proposed trial is an adaptive platform design. Multiple agents and combinations will be investigated simultaneously. Additionally, new agents may enter the trial as they become available, and failing agents may be removed. In order to accommodate the many possible agents and combinations, a critical feature of this design is the use of response adaptive randomization to assign treatment regimens. As the trial progresses, the randomization ratio evolves to favor the arms that are performing better, making the design also suitable for all-cause pandemic preparedness planning. The study was approved by US and Sierra Leone ethics committees, and reviewed by the US Food and Drug Administration. Additionally, data management, drug supply lines, and local sites were prepared. However, in response to the declining epidemic seen in February 2015, the trial was not initiated. Sierra Leone remains ready to rapidly activate the protocol as an emergency response trial in the event of a resurgence of Ebola. (ClinicalTrials.gov Identifier: NCT02380625.) In summary, we have designed a single controlled trial capable of efficiently identifying highly effective or failing regimens among a rapidly evolving list of proposed therapeutic alternatives for Ebola virus disease and to treat the patients within the trial effectively based on accruing data. Provision of these regimens, if found safe and effective, would have a major impact on future epidemics by providing effective treatment options. PMID:26768569
Berry, Scott M; Petzold, Elizabeth A; Dull, Peter; Thielman, Nathan M; Cunningham, Coleen K; Corey, G Ralph; McClain, Micah T; Hoover, David L; Russell, James; Griffiss, J McLeod; Woods, Christopher W
2016-02-01
The outbreak of Ebola virus disease in West Africa is the largest ever recorded. Numerous treatment alternatives for Ebola have been considered, including widely available repurposed drugs, but initiation of enrollment into clinical trials has been limited. The proposed trial is an adaptive platform design. Multiple agents and combinations will be investigated simultaneously. Additionally, new agents may enter the trial as they become available, and failing agents may be removed. In order to accommodate the many possible agents and combinations, a critical feature of this design is the use of response adaptive randomization to assign treatment regimens. As the trial progresses, the randomization ratio evolves to favor the arms that are performing better, making the design also suitable for all-cause pandemic preparedness planning. The study was approved by US and Sierra Leone ethics committees, and reviewed by the US Food and Drug Administration. Additionally, data management, drug supply lines, and local sites were prepared. However, in response to the declining epidemic seen in February 2015, the trial was not initiated. Sierra Leone remains ready to rapidly activate the protocol as an emergency response trial in the event of a resurgence of Ebola. (ClinicalTrials.gov Identifier: NCT02380625.) In summary, we have designed a single controlled trial capable of efficiently identifying highly effective or failing regimens among a rapidly evolving list of proposed therapeutic alternatives for Ebola virus disease and to treat the patients within the trial effectively based on accruing data. Provision of these regimens, if found safe and effective, would have a major impact on future epidemics by providing effective treatment options.
Daniels, Noah M; Gallant, Andrew; Ramsey, Norman; Cowen, Lenore J
2015-01-01
We introduce MRFy, a tool for protein remote homology detection that captures beta-strand dependencies in the Markov random field. Over a set of 11 SCOP beta-structural superfamilies, MRFy shows a 14 percent improvement in mean Area Under the Curve for the motif recognition problem as compared to HMMER, 25 percent improvement as compared to RAPTOR, 14 percent improvement as compared to HHPred, and a 18 percent improvement as compared to CNFPred and RaptorX. MRFy was implemented in the Haskell functional programming language, and parallelizes well on multi-core systems. MRFy is available, as source code as well as an executable, from http://mrfy.cs.tufts.edu/.
Schwarz, Andreas; Scherer, Reinhold; Steyrl, David; Faller, Josef; Muller-Putz, Gernot R
2015-08-01
Sensorimotor rhythm (SMR) based Brain-Computer Interfaces (BCI) typically require lengthy user training. This can be exhausting and fatiguing for the user as data collection may be monotonous and typically without any feedback for user motivation. Hence new ways to reduce user training and improve performance are needed. We recently introduced a two class motor imagery BCI system which continuously adapted with increasing run-time to the brain patterns of the user. The system was designed to provide visual feedback to the user after just five minutes. The aim of the current work was to improve user-specific online adaptation, which was expected to lead to higher performances. To maximize SMR discrimination, the method of filter-bank common spatial patterns (fbCSP) and Random Forest (RF) classifier were combined. In a supporting online study, all volunteers performed significantly better than chance. Overall peak accuracy of 88.6 ± 6.1 (SD) % was reached, which significantly exceeded the performance of our previous system by 13%. Therefore, we consider this system the next step towards fully auto-calibrating motor imagery BCIs. PMID:26736445
Naeem, Farooq; Saeed, Sofiya; Irfan, Muhammad; Kiran, Tayyeba; Mehmood, Nasir; Gul, Mirrat; Munshi, Tariq; Ahmad, Sohail; Kazmi, Ajmal; Husain, Nusrat; Farooq, Saeed; Ayub, Muhammad; Kingdon, David
2015-05-01
Evidence for the effectiveness of Culturally adapted CBT for psychosis in Low And Middle Income Countries (LAMIC) is limited. Therefore, brief Culturally adapted CBT for psychosis (CaCBTp) targeted at symptoms of schizophrenia for outpatients plus treatment as usual (TAU) is compared with TAU. A total of 116 participants with schizophrenia were recruited from 2 hospitals in Karachi, Pakistan, and randomized into two groups with 1:1 allocation (CaCBTp plus TAU=59, TAU=57). A brief version of CaCBTp (6 individual sessions with the involvement of main carer, plus one session for the family) was provided over 4months. Psychopathology was measured using Positive and Negative Syndrome Scale of Schizophrenia (PANSS), Psychotic Symptom Rating Scales (PSYRATS), and the Schedule for Assessment of Insight (SAI) at baseline and end of therapy. Participants in treatment group, showed statistically significant improvement in all measures of psychopathology at the end of the study compared with control group. Participants in treatment group showed statistically significant improvement in Positive Symptoms (PANSS, Positive Symptoms Subscale; p=0.000), Negative Symptoms (PANSS, Negative Symptoms subscales; p=0.000), Delusions (PSYRATS, Delusions Subscale; p=0.000), Hallucinations (PSYRATS, Hallucination Subscale; p=0.000) and Insight (SAI; p=0.007). The results suggest that brief, Culturally adapted CBT for psychosis can be an effective treatment when provided in combination with TAU, for patients with schizophrenia in a LAMIC setting. This is the first trial of CBT for psychosis from outside the western world. These findings need replicating in other low and middle income countries.
Williams, Karen; Gerkovich, Mary M.; Gqaleni, Nceba; Syce, James; Bartman, Patricia; Johnson, Quinton; Folk, William R.
2015-01-01
Background Sutherlandia frutescens (L.) R. Br. is widely used as an over the counter complementary medicine and in traditional medications by HIV seropositive adults living in South Africa; however the plant’s safety has not been objectively studied. An adaptive two-stage randomized double-blind placebo controlled study was used to evaluate the safety of consuming dried S. frutescens by HIV seropositive adults with CD4 T-lymphocyte count of >350 cells/μL. Methods In Stage 1 56 participants were randomized to S. frutescens 400, 800 or 1,200 mg twice daily or matching placebo for 24 weeks. In Stage 2 77 additional participants were randomized to either 1,200 mg S. frutescens or placebo. In the final analysis data from Stage 1 and Stage 2 were combined such that 107 participants were analysed (54 in the S. frutescens 1,200 mg arm and 53 in the placebo arm). Results S. frutescens did not change HIV viral load, and CD4 T-lymphocyte count was similar in the two arms at 24 weeks; however, mean and total burden of infection (BOI; defined as days of infection-related events in each participant) was greater in the S. frutescens arm: mean (SD) 5.0 (5.5) vs. 9.0 (12.7) days (p = 0.045), attributed to two tuberculosis cases in subjects taking isoniazid preventive therapy (IPT). Conclusion A possible interaction between S. frutescens and IPT needs further evaluation, and may presage antagonistic interactions with other herbs having similar biochemical (antioxidant) properties. No other safety issues relating to consumption of S. frutescens in this cohort were identified. Trial Registration ClinicalTrials.gov NCT00549523 PMID:26186450
NASA Astrophysics Data System (ADS)
Žeželj, M.; Stanković, I.
2016-10-01
Random networks of as-grown single-walled carbon nanotubes (CNTs) contain both metallic (m-CNTs) and semiconducting (s-CNTs) nanotubes in an approximate ratio of 1:2, which leads to a trade-off between on-conductance and the on/off ratio. We demonstrate how this design problem can be solved with a realistic numerical approach. We determine the CNT density, length, and channel dimensions under which CNT thin-film transistors simultaneously attain on-conductance higher than 1 μS and an on/off ratio higher than 104. The fact that asymmetric systems have more pronounced finite-size scaling behavior than symmetric systems allows us additional design freedom. A realization probability of the desired characteristics higher than 99% is obtained for the channels with aspect ratio {L}{{CH}}/{W}{{CH}}\\lt 1.2 and normalized size {L}{{CH}}{W}{{CH}}/{l}{{CNT}}2\\gt 250 when the CNT length is {l}{{CNT}}=4-20 μ {{m}} and the normalized density of CNTs is close to the value where the probability of percolation through only s-CNT pathways reaches its maximum.
Hemmelmayr, Vera C.; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-01-01
In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. PMID:23483764
Farnier, Kevin; Dyer, Adrian G; Taylor, Gary S; Peters, Richard A; Steinbauer, Martin J
2015-05-15
Insects have evolved morphological and physiological adaptations in response to selection pressures inherent to their ecology. Consequently, visual performance and acuity often significantly vary between different insect species. Whilst psychophysics has allowed for the accurate determination of visual acuity for some Lepidoptera and Hymenoptera, very little is known about other insect taxa that cannot be trained to positively respond to a given stimulus. In this study, we demonstrate that prior knowledge of insect colour preferences can be used to facilitate acuity testing. We focused on four psyllid species (Hemiptera: Psylloidea: Aphalaridae), namely Ctenarytaina eucalypti, Ctenarytaina bipartita, Anoeconeossa bundoorensis and Glycaspis brimblecombei, that differ in their colour preferences and utilization of different host-plant modules (e.g. apical buds, stems, leaf lamellae) and tested their visual acuity in a modified Y-maze adapted to suit psyllid searching behaviour. Our study revealed that psyllids have visual acuity ranging from 6.3 to 8.7 deg. Morphological measurements for different species showed a close match between inter-ommatidial angles and behaviourally determined visual angles (between 5.5 and 6.6 deg) suggesting detection of colour stimuli at the single ommatidium level. Whilst our data support isometric scaling of psyllids' eyes for C. eucalypti, C. bipartita and G. brimblecombei, a morphological trade-off between light sensitivity and spatial resolution was found in A. bundoorensis. Overall, species whose microhabitat preferences require more movement between modules appear to possess superior visual acuity. The psyllid searching behaviours that we describe with the help of tracking software depict species-specific strategies that presumably evolved to optimize searching for food and oviposition sites.
Bernat, David; Bouchez, Antonin H.; Cromer, John L.; Dekany, Richard G.; Moore, Anna M.; Ireland, Michael; Tuthill, Peter; Martinache, Frantz; Angione, John; Burruss, Rick S.; Guiwits, Stephen R.; Henning, John R.; Hickey, Jeff; Kibblewhite, Edward; McKenna, Daniel L.; Petrie, Harold L.; Roberts, Jennifer; Shelton, J. Chris; Thicksten, Robert P.; Trinh, Thang
2010-06-01
We present a close companion search around 16 known early L dwarfs using aperture masking interferometry with Palomar laser guide star adaptive optics (LGS AO). The use of aperture masking allows the detection of close binaries, corresponding to projected physical separations of 0.6-10.0 AU for the targets of our survey. This survey achieved median contrast limits of {Delta}K {approx} 2.3 for separations between 1.2 {lambda}/D-4{lambda}/D and {Delta}K {approx} 1.4 at 2/3 {lambda}/D. We present four candidate binaries detected with moderate-to-high confidence (90%-98%). Two have projected physical separations less than 1.5 AU. This may indicate that tight-separation binaries contribute more significantly to the binary fraction than currently assumed, consistent with spectroscopic and photometric overluminosity studies. Ten targets of this survey have previously been observed with the Hubble Space Telescope as part of companion searches. We use the increased resolution of aperture masking to search for close or dim companions that would be obscured by full aperture imaging, finding two candidate binaries. This survey is the first application of aperture masking with LGS AO at Palomar. Several new techniques for the analysis of aperture masking data in the low signal-to-noise regime are explored.
Anderson, Melissa L; Bradley, Katharine; An, Lawrence C; Catz, Sheryl L
2016-01-01
Background Mobile health (mHealth) interventions hold great promise for helping smokers quit since these programs can have wide reach and facilitate access to comprehensive, interactive, and adaptive treatment content. However, the feasibility, acceptability, and effectiveness of these programs remain largely untested. Objective To assess feasibility and acceptability of the My Mobile Advice Program (MyMAP) smoking cessation program and estimate its effects on smoking cessation and medication adherence to inform future research planning. Methods Sixty-six smokers ready to quit were recruited from a large regional health care system and randomized to one of two mHealth programs: (1) standard self-help including psychoeducational materials and guidance how to quit smoking or (2) an adaptive and interactive program consisting of the same standard mHealth self-help content as controls received plus a) real-time, adaptively tailored advice for managing nicotine withdrawal symptoms and medication side-effects and b) asynchronous secure messaging with a cessation counselor. Participants in both arms were also prescribed a 12-week course of varenicline. Follow-up assessments were conducted at 2 weeks post-target quit date (TQD), 3 months post-TQD, and 5 months post-TQD. Indices of program feasibility and acceptability included acceptability ratings, utilization metrics including use of each MyMAP program component (self-help content, secure messaging, and adaptively tailored advice), and open-ended feedback from participants. Smoking abstinence and medication adherence were also assessed to estimate effects on these treatment outcomes. Results Utilization data indicated the MyMAP program was actively used, with higher mean program log-ins by experimental than control participants (10.6 vs 2.7, P<.001). The majority of experimental respondents thought the MyMAP program could help other people quit smoking (22/24, 92%) and consistently take their stop-smoking medication (17
Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal
2016-01-01
Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive
Poirier, Josée; Bennett, Wendy L; Jerome, Gerald J; Shah, Nina G; Lazo, Mariana; Yeh, Hsin-Chieh; Clark, Jeanne M
2016-01-01
Background The benefits of physical activity are well documented, but scalable programs to promote activity are needed. Interventions that assign tailored and dynamically adjusting goals could effect significant increases in physical activity but have not yet been implemented at scale. Objective Our aim was to examine the effectiveness of an open access, Internet-based walking program that assigns daily step goals tailored to each participant. Methods A two-arm, pragmatic randomized controlled trial compared the intervention to no treatment. Participants were recruited from a workplace setting and randomized to a no-treatment control (n=133) or to treatment (n=132). Treatment participants received a free wireless activity tracker and enrolled in the walking program, Walkadoo. Assessments were fully automated: activity tracker recorded primary outcomes (steps) without intervention by the participant or investigators. The two arms were compared on change in steps per day from baseline to follow-up (after 6 weeks of treatment) using a two-tailed independent samples t test. Results Participants (N=265) were 66.0% (175/265) female with an average age of 39.9 years. Over half of the participants (142/265, 53.6%) were sedentary (<5000 steps/day) and 44.9% (119/265) were low to somewhat active (5000-9999 steps/day). The intervention group significantly increased their steps by 970 steps/day over control (P<.001), with treatment effects observed in sedentary (P=.04) and low-to-somewhat active (P=.004) participants alike. Conclusions The program is effective in increasing daily steps. Participants benefited from the program regardless of their initial activity level. A tailored, adaptive approach using wireless activity trackers is realistically implementable and scalable. Trial Registration Clinicaltrials.gov NCT02229409, https://clinicaltrials.gov/ct2/show/NCT02229409 (Archived by WebCite at http://www.webcitation.org/6eiWCvBYe) PMID:26860434
Walitzer, Kimberly S; Deffenbacher, Jerry L; Shyhalla, Kathleen
2015-12-01
A randomized controlled trial for an innovative alcohol-adapted anger management treatment (AM) for outpatient alcohol dependent individuals scoring moderate or above on anger is described. AM treatment outcomes were compared to those of an empirically-supported intervention, Alcoholics Anonymous Facilitation treatment (AAF). Clients in AM, relative to clients in AAF, were hypothesized to have greater improvement in anger and anger-related cognitions and lesser AA involvement during the 6-month follow-up. Anger-related variables were hypothesized to be stronger predictors of improved alcohol outcomes in the AM treatment condition and AA involvement was hypothesized to be a stronger predictor of alcohol outcomes in the AAF treatment group. Seventy-six alcohol dependent men and women were randomly assigned to treatment condition and followed for 6 months after treatment end. Both AM and AAF treatments were followed by significant reductions in heavy drinking days, alcohol consequences, anger, and maladaptive anger-related thoughts and increases in abstinence and self-confidence regarding not drinking to anger-related triggers. Treatment with AAF was associated with greater AA involvement relative to treatment with AM. Changes in anger and AA involvement were predictive of posttreatment alcohol outcomes for both treatments. Change in trait anger was a stronger predictor of posttreatment alcohol consequences for AM than for AAF clients; during-treatment AA meeting attendance was a stronger predictor of posttreatment heavy drinking and alcohol consequences for AAF than for AM clients. Anger-related constructs and drinking triggers should be foci in treatment of alcohol dependence for anger-involved clients.
ERIC Educational Resources Information Center
Han, Kyung T.; Guo, Fanmin
2014-01-01
The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing…
ERIC Educational Resources Information Center
Raudenbush, Stephen W.
2009-01-01
Fixed effects models are often useful in longitudinal studies when the goal is to assess the impact of teacher or school characteristics on student learning. In this article, I introduce an alternative procedure: adaptive centering with random effects. I show that this procedure can replicate the fixed effects analysis while offering several…
Practical High-Order Adaptive Optics Systems For Extrasolar Planet Searches
Macintosh, B A; Olivier, S; Bauman, B; Brase, J; Carr, E; Carrano, C J; Gavel, D; Max, C E; Patience, J
2001-08-29
Direct detection of photons emitted or reflected by an extrasolar planet is an extremely difficult but extremely exciting application of adaptive optics. Typical contrast levels for an extrasolar planet would be 10{sup 9}-Jupiter is a billion times fainter than the sun. Current adaptive optics systems can only achieve contrast levels of 10{sup 6}, but so-called ''extreme'' adaptive optics systems with 10{sup 4}-10{sup 5} degrees of freedom could potentially detect extrasolar planets. We explore the scaling laws defining the performance of these systems, first set out by Angel (1994), and derive a different definition of an optimal system. Our sensitivity predictions are somewhat more pessimistic than the original paper, due largely to slow decorrelation timescales for some noise sources, though choosing to site an ExAO system at a location with exceptional r{sub 0} (e.g. Mauna Kea) can offset this. We also explore the effects of segment aberrations in a Keck-like telescope on ExAO; although the effects are significant, they can be mitigated through Lyot coronagraphy.
NASA Astrophysics Data System (ADS)
Grayver, Alexander V.; Kuvshinov, Alexey V.
2016-05-01
This paper presents a methodology to sample equivalence domain (ED) in nonlinear partial differential equation (PDE)-constrained inverse problems. For this purpose, we first applied state-of-the-art stochastic optimization algorithm called Covariance Matrix Adaptation Evolution Strategy (CMAES) to identify low-misfit regions of the model space. These regions were then randomly sampled to create an ensemble of equivalent models and quantify uncertainty. CMAES is aimed at exploring model space globally and is robust on very ill-conditioned problems. We show that the number of iterations required to converge grows at a moderate rate with respect to number of unknowns and the algorithm is embarrassingly parallel. We formulated the problem by using the generalized Gaussian distribution. This enabled us to seamlessly use arbitrary norms for residual and regularization terms. We show that various regularization norms facilitate studying different classes of equivalent solutions. We further show how performance of the standard Metropolis-Hastings Markov chain Monte Carlo algorithm can be substantially improved by using information CMAES provides. This methodology was tested by using individual and joint inversions of magneotelluric, controlled-source electromagnetic (EM) and global EM induction data.
Poslawsky, Irina E; Naber, Fabiënne Ba; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H
2015-07-01
In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child interaction and reducing the child's individual Autism Spectrum Disorder-related symptomatology in five home visits. VIPP-AUTI, as compared with usual care, demonstrated efficacy in reducing parental intrusiveness. Moreover, parents who received VIPP-AUTI showed increased feelings of self-efficacy in child rearing. No significant group differences were found on other aspects of parent-child interaction or on child play behavior. At 3-months follow-up, intervention effects were found on child-initiated joint attention skills, not mediated by intervention effects on parenting. Implementation of VIPP-AUTI in clinical practice is facilitated by the use of a detailed manual and a relatively brief training of interveners.
Onoma, D P; Ruan, S; Thureau, S; Nkhali, L; Modzelewski, R; Monnehan, G A; Vera, P; Gardin, I
2014-12-01
A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.
Chen, Tinggui; Xiao, Renbin
2014-01-01
Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023
Chen, Tinggui; Xiao, Renbin
2014-01-01
Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023
Broad-area search for targets in SAR imagery with context-adaptive algorithms
NASA Astrophysics Data System (ADS)
Patterson, Tim J.; Fairchild, Scott R.
1996-06-01
This paper describes an ATR system based on gray scale morphology which has proven very effective in performing broad area search for targets of interest. Gray scale morphology is used to extract several distinctive sets of features which combine intensity and spatial information. Results of direct comparisons with other algorithms are presented. In a series of tests which were scored independently the morphological approach has shown superior results. An automated training systems based on a combination of genetic algorithms and classification and regression trees is described. Further performance gains are expected by allowing context sensitive selection of parameter sets for the morphological processing. Context is acquired from the image using texture measures to identify the local clutter environment. The system is designed to be able to build new classifiers on the fly to match specific image to image variations.
Kim, Sungho; Lee, Joohyoung
2014-07-22
This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate.
Kim, Sungho; Lee, Joohyoung
2014-01-01
This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate. PMID:25054633
2014-01-01
Objective The Alzheimer's Disease Anti-Inflammatory Prevention Trial (ADAPT) and follow-up study (ADAPT-FS) examined effects of naproxen and celecoxib on cognition in the elderly. We report here results describing trajectories of cognitive evaluation test scores. Methods 2356 participants completed baseline and at least one follow-up cognitive evaluation between 2001-2004. Study treatments were discontinued in 2004, but participants were followed until 2007. 1537 participants were re-evaluated in 2010-2011. Outcomes include seven cognitive evaluations administered yearly in-person in ADAPT and three of these evaluations that were administered by telephone near the end of ADAPT and again in ADAPT-FS. Results There were no important differences over time by treatment group on any ADAPT cognitive measure, a global composite, or the three cognitive measures re-assessed in ADAPT-FS by telephone. Conclusions Treatment for 1 – 3 years with naproxen or celecoxib did not protect against cognitive decline in older adults with a family history of AD. PMID:25022541
Oeberst, Aileen; Cress, Ulrike
2014-01-01
Background The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective. Objective The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts’ evaluations. Methods A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts’ blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants’ treatment recommendation after information search. Results Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t 173=7.67, P<.001, d=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F 2,168=10.61, P<.001, partial eta squared=0.112), blog post selection (F 2,168=6.55, P=.002, partial eta squared=0.072), and treatment efficacy ratings (F 2,168=8.48, P<.001, partial eta squared=0.092), compared
NASA Astrophysics Data System (ADS)
Skutnik, Steven E.; Davis, David R.
2016-05-01
The use of passive gamma and neutron signatures from fission indicators is a common means of estimating used fuel burnup, enrichment, and cooling time. However, while characteristic fission product signatures such as 134Cs, 137Cs, 154Eu, and others are generally reliable estimators for used fuel burnup within the context where the assembly initial enrichment and the discharge time are known, in the absence of initial enrichment and/or cooling time information (such as when applying NDA measurements in a safeguards/verification context), these fission product indicators no longer yield a unique solution for assembly enrichment, burnup, and cooling time after discharge. Through the use of a new Mesh-Adaptive Direct Search (MADS) algorithm, it is possible to directly probe the shape of this "degeneracy space" characteristic of individual nuclides (and combinations thereof), both as a function of constrained parameters (such as the assembly irradiation history) and unconstrained parameters (e.g., the cooling time before measurement and the measurement precision for particular indicator nuclides). In doing so, this affords the identification of potential means of narrowing the uncertainty space of potential assembly enrichment, burnup, and cooling time combinations, thereby bounding estimates of assembly plutonium content. In particular, combinations of gamma-emitting nuclides with distinct half-lives (e.g., 134Cs with 137Cs and 154Eu) in conjunction with gross neutron counting (via 244Cm) are able to reasonably constrain the degeneracy space of possible solutions to a space small enough to perform useful discrimination and verification of fuel assemblies based on their irradiation history.
Ripa, M; Pogliaghi, M; Chiappetta, S; Galli, L; Pensieroso, S; Cavarelli, M; Scarlatti, G; De Biasi, S; Cossarizza, A; De Battista, D; Malnati, M; Lazzarin, A; Nozza, S; Tambussi, G
2015-09-01
We evaluated the dynamics of innate and adaptive immunity in patients treated with combined antiretroviral therapy (cART) during primary human immunodeficiency virus infection (PHI), enrolled in a prospective randomized trial (MAIN, EUDRACT 2008-007004-29). After 48 weeks of cART, we documented a reduction in activated B cells and CD8(+) T cells. Natural killer cell and dendritic cell frequencies were measured and a decrease in CD16(+) CD56(dim) with a reciprocal rise in CD56(high) natural killer cells and an increase in myeloid and plasmacytoid dendritic cells were recorded. In conclusion, 48 weeks of cART during PHI showed significant benefits for both innate and adaptive immunity.
Farsi, Zahra; Azarmi, Somayeh
2016-01-01
Background: Any defect in the extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy’s adaptation model-guided education on coping strategies of the veterans with lower extremities amputation. Methods: In a double-blind randomized controlled clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of Veterans Clinic in Tehran, Iran were recruited using convenience method and randomly assigned to intervention and control groups in 2013-2014. Lazarus and Folkman coping strategies questionnaire was used to collect the data. After completing the questionnaires in both groups, maladaptive behaviours were determined in the intervention group and an education program based on Roy’s adaptation model was implemented. After 2 months, both groups completed the questionnaires again. Data were analyzed using SPSS software. Results: Independent T-test showed that the score of the dimensions of coping strategies did not have a statistically significant difference between the intervention and control groups in the pre-intervention stage (P>0.05). This test showed a statistically significant difference between the two groups in the post-intervention stage in terms of the scores of different dimensions of coping strategies (P>0.05), except in dimensions of social support seeking and positive appraisal (P>0.05). Conclusion: The findings of this research indicated that the Roy’s adaptation model-guided education improved the majority of coping strategies in veterans with lower extremities amputation. It is recommended that further interventions based on Roy’s adaptation model should be performed to improve the coping of the veterans with lower extremities amputation. Trial Registration Number: IRCT2014081118763N1 PMID:27218110
ERIC Educational Resources Information Center
Cermak, Sharon A.; Stein Duker, Leah I.; Williams, Marian E.; Dawson, Michael E.; Lane, Christianne J.; Polido, José C.
2015-01-01
This pilot and feasibility study examined the impact of a sensory adapted dental environment (SADE) to reduce distress, sensory discomfort, and perception of pain during oral prophylaxis for children with autism spectrum disorder (ASD). Participants were 44 children ages 6-12 (n = 22 typical, n = 22 ASD). In an experimental crossover design, each…
NASA Astrophysics Data System (ADS)
Izquierdo, Joaquín; Montalvo, Idel; Campbell, Enrique; Pérez-García, Rafael
2016-08-01
Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same regardless of the size, complexity and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm using techniques derived from knowledge discovery (data-mining techniques) on databases of so-far visited solutions. The aim is to improve the search mechanisms, increase computational efficiency and use rules to enrich the formulation of optimization problems, while reducing the search space and catering to realistic problems.
Moss, Aleezé S; Reibel, Diane K; Greeson, Jeffrey M; Thapar, Anjali; Bubb, Rebecca; Salmon, Jacqueline; Newberg, Andrew B
2015-06-01
The purpose of this study was to test the feasibility and effectiveness of an adapted 8-week Mindfulness-Based Stress Reduction (MBSR) program for elders in a continuing care community. This mixed-methods study used both quantitative and qualitative measures. A randomized waitlist control design was used for the quantitative aspect of the study. Thirty-nine elderly were randomized to MBSR (n = 20) or a waitlist control group (n = 19), mean age was 82 years. Both groups completed pre-post measures of health-related quality of life, acceptance and psychological flexibility, facets of mindfulness, self-compassion, and psychological distress. A subset of MBSR participants completed qualitative interviews. MBSR participants showed significantly greater improvement in acceptance and psychological flexibility and in role limitations due to physical health. In the qualitative interviews, MBSR participants reported increased awareness, less judgment, and greater self-compassion. Study results demonstrate the feasibility and potential effectiveness of an adapted MBSR program in promoting mind-body health for elders.
Surdina, A V; Rassokhin, T I; Golovin, A V; Spiridonova, V A; Kraal, B; Kopylov, A M
2008-06-01
In E. coli cells ribosomal small subunit biogenesis is regulated by RNA-protein interactions involving protein S7. S7 initiates the subunit assembly interacting with 16S rRNA. During shift-down of rRNA synthesis level, free S7 inhibits self-translation by interacting with 96 nucleotides long specific region of streptomycin (str) mRNA between cistrons S12 and S7 (intercistron). Many bacteria do not have the extended intercistron challenging development of specific approaches for searching putative mRNA regulatory regions, which are able to interact with proteins. The paper describes application of SERF approach (Selection of Random RNA Fragments) to reveal regulatory regions of str mRNA. Set of random DNA fragments has been generated from str operon by random hydrolysis and then transcribed into RNA; the fragments being able to bind protein S7 (serfamers) have been selected by iterative rounds. S7 binds to single serfamer, 109 nucleotide long (RNA109), derived from the intercistron. After multiple copying and selection, the intercistronic mutant (RNA109) has been isolated; it has enhanced affinity to S7. RNA109 binds to the protein better than authentic intercistronic str mRNA; apparent dissociation constants are 26 +/- 5 and 60 +/- 8 nM, respectively. Location of S7 binding site on the mRNA, as well as putative mode of regulation of coupled translation of S12 and S7 cistrons have been hypothesized.
NASA Astrophysics Data System (ADS)
Tian, Yu-Kun; Zhou, Hui; Chen, Han-Ming; Zou, Ya-Ming; Guan, Shou-Jun
2013-12-01
Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber-Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.
Anderson, Jacqueline; Dolk, Anders; Torgerson, Jarl; Nyberg, Svante; Skau, Tommy; Forsberg, Birger C.; Werr, Joachim; Öhlen, Gunnar
2016-01-01
Background A small group of frequent visitors to Emergency Departments accounts for a disproportionally large fraction of healthcare consumption including unplanned hospitalizations and overall healthcare costs. In response, several case and disease management programs aimed at reducing healthcare consumption in this group have been tested; however, results vary widely. Objectives To investigate whether a telephone-based, nurse-led case management intervention can reduce healthcare consumption for frequent Emergency Department visitors in a large-scale setup. Methods A total of 12 181 frequent Emergency Department users in three counties in Sweden were randomized using Zelen’s design or a traditional randomized design to receive either a nurse-led case management intervention or no intervention, and were followed for healthcare consumption for up to 2 years. Results The traditional design showed an overall 12% (95% confidence interval 4–19%) decreased rate of hospitalization, which was mostly driven by effects in the last year. Similar results were achieved in the Zelen studies, with a significant reduction in hospitalization in the last year, but mixed results in the early development of the project. Conclusion Our study provides evidence that a carefully designed telephone-based intervention with accurate and systematic patient selection and appropriate staff training in a centralized setup can lead to significant decreases in healthcare consumption and costs. Further, our results also show that the effects are sensitive to the delivery model chosen. PMID:25969342
ELL, KATHLEEN; KATON, WAYNE; CABASSA, LEOPOLDO J.; XIE, BIN; LEE, PEY-JIUAN; KAPETANOVIC, SUAD; GUTERMAN, JEFFRY
2012-01-01
Objective This article describes design elements of the Multifaceted Depression and Diabetes Program (MDDP) randomized clinical trial. The MDDP trial hypothesizes that a socioculturally adapted collaborative care depression management intervention will reduce depressive symptoms and improve patient adherence to diabetes self-care regimens, glycemic control, and quality-of-life. In addition, baseline data of 387 low-income, 96% Hispanic, enrolled patients with major depression and diabetes are examined to identify study population characteristics consistent with trial design adaptations. Methods The PHQ-9 depression scale was used to identify patients meeting criteria for major depressive disorder (1 cardinal depression symptom + a PHQ-9 score of ≥ 10) from two community safety net clinics. Design elements included sociocultural adaptations in recruitment and efforts to reduce attrition and collaborative depression care management. Results Of 1,803 diabetes patients screened, 30.2% met criteria for major depressive disorder. Of 387 patients enrolled in the clinical trial, 98% had Type 2 diabetes, and 83% had glycated hemoglobin (HbA1c) levels ≥ 7%. Study recruitment rates and baseline data analyses identified socioeconomic and clinical factors that support trial design and intervention adaptations. Depression severity was significantly associated with diabetes complications, medical comorbidity, greater anxiety, dysthymia, financial worries, social stress, and poorer quality-of-life. Conclusion Low-income Hispanic patients with diabetes experience high prevalence of depressive disorder and depression severity is associated with socioeconomic stressors and clinical severity. Improving depression care management among Hispanic patients in public sector clinics should include intervention components that address self-care of diabetes and socioeconomic stressors. PMID:19860071
Khayati, Rasoul; Vafadust, Mansur; Towhidkhah, Farzad; Nabavi, Massood
2008-03-01
In this paper, an approach is proposed for fully automatic segmentation of MS lesions in fluid attenuated inversion recovery (FLAIR) Magnetic Resonance (MR) images. The proposed approach, based on a Bayesian classifier, utilizes the adaptive mixtures method (AMM) and Markov random field (MRF) model to obtain and upgrade the class conditional probability density function (CCPDF) and the a priori probability of each class. To compare the performance of the proposed approach with those of previous approaches including manual segmentation, the similarity criteria of different slices related to 20 MS patients were calculated. Also, volumetric comparison of lesions volume between the fully automated segmentation and the gold standard was performed using correlation coefficient (CC). The results showed a better performance for the proposed approach, compared to those of previous works.
Spence, Angela L; Carter, Howard H; Naylor, Louise H; Green, Daniel J
2013-01-01
This randomized trial evaluated the impact of different exercise training modalities on the function and size of conduit arteries in healthy volunteers. Young (27 ± 5 years) healthy male subjects were randomized to undertake 6 months of either endurance training (ET; n= 10) or resistance training (RT; n= 13). High-resolution ultrasound was used to determine brachial, femoral and carotid artery diameter and wall thickness (IMT) and femoral and brachial flow-mediated dilatation (FMD) and glyceryl trinitrate (GTN)-mediated dilatation. Improvements in peak oxygen uptake occurred with ET (from 3.6 ± 0.7 to 3.8 ± 0.6 l min−1, P= 0.024) but not RT. Upper body muscular strength increased following RT (from 57.8 ± 17.7 to 69.0 ± 19.5 kg, P < 0.001), but not ET. Both groups exhibited increases in lean body mass (ΔET, 1.4 ± 1.8 kg and ΔRT, 2.3 ± 1.3 kg, P < 0.05). Resistance training increased brachial artery resting diameter (from 3.8 ± 0.5 to 4.1 ± 0.4 mm, P < 0.05), peak FMD diameter (+0.2 ± 0.2 mm, P < 0.05) and GTN-mediated diameter (+0.3 ± 0.3 mm, P < 0.01), as well as brachial FMD (from 5.1 ± 2.2 to 7.0 ± 3.9%, P < 0.05). No improvements in any brachial parameters were observed following ET. Conversely, ET increased femoral artery resting diameter (from 6.2 ± 0.7 to 6.4 ± 0.6 mm, P < 0.05), peak FMD diameter (+0.4 ± 0.4 mm, P < 0.05) and GTN-induced diameter (+0.3 ± 0.3 mm, P < 0.05), as well as femoral FMD-to-GTN ratio (from 0.6 ± 0.3 to 1.1 ± 0.8, P < 0.05). Resistance training did not induce changes in femoral artery parameters. Carotid artery IMT decreased in response to both forms of training. These findings indicate that 6 months of supervised exercise training induced changes in brachial and femoral artery size and function and decreased carotid artery IMT. These impacts of both RT and ET would be expected to translate to decreased cardiovascular risk. PMID:23247114
Wesemann, Ulrich; Kowalski, Jens T; Jacobsen, Thomas; Beudt, Susan; Jacobs, Herbert; Fehr, Julia; Büchler, Jana; Zimmermann, Peter L
2016-08-01
To prevent deployment-related disorders, Chaos Driven Situations Management Retrieval System (CHARLY), a computer-aided training platform with a biofeedback interface has been developed. It simulates critical situations photorealistic for certain target and occupational groups. CHARLY was evaluated as a 1.5 days predeployment training method comparing it with the routine training. The evaluation was carried out for a matched random sample of N = 67 soldiers deployed in Afghanistan (International Security Assistance Force). Data collection took place before and after the prevention program and 4 to 6 weeks after deployment, which included mental state, post-traumatic stress disorder (PTSD) symptoms, knowledge of and attitude toward PTSD, and deployment-specific stressors. CHARLY has been significantly superior to the control group in terms of psychoeducation and attitude change. As to the mental state, both groups showed a significant increase in stress after deployment with significant lower increase in CHARLY. For PTSD-specific symptoms, CHARLY achieved a significant superiority. The fact that PTSD-specific scales showed significant differences at the end of deployment substantiates the validity of a specifically preventive effect of CHARLY. The study results tentatively indicate that highly standardized, computer-based primary prevention of mental disorders in soldiers on deployment might be superior to other more personal and less standardized forms of prevention. PMID:27483525
2014-01-01
Background Currently, there is no consensus regarding iron supplementation dose that is most beneficial for maternal and offspring health during gestation. Recommended iron supplementation dose does not preempt anemia in around 20% of the pregnancies, nor the risk of hemoconcentration in 15%. This deficit, or excess, of iron prejudices the mother-child wellbeing. Therefore the aims of the study are to determine the highest level of effectiveness of iron supplementation adapted to hemoglobin (Hb) levels in early pregnancy, which would be optimum for mother-child health. Methods/Design Design: Randomized Clinical Trial (RCT) triple-blinded Setting: 10 Primary Care Centers from Catalunya (Spain) Study subjects: 878 non-anemic pregnant women at early gestation stage, and their subsequent newborns Methods: The study is structured as a RCT with 2 strata, depending on the Hb levels before week 12 of gestation. Stratum #1: If Hb from 110 to 130 g/L, randomly assigned at week 12 to receive iron supplement of 40 or 80 mg/d. Stratum #2: If Hb >130 g/L, randomly assigned at week 12 to receive iron supplement of 40 or 20 mg/d. Measurements: In the mother: socio-economic data, clinical history, food item frequency, lifestyle and emotional state, and adherence to iron supplement prescription. Biochemical measurements include: Hb, serum ferritin, C reactive protein, cortisol, and alterations in the HFE gene (C282Y, H63D). In children: ultrasound fetal biometry, anthropometric measurements, and temperament development. Statistical analyses, using the SPSS program for Windows, will include bivariate and multivariate analyses adjusted for variables associated with the relationship under study. Discussion Should conclusive outcomes be reached, the study would indicate the optimal iron supplementation dose required to promote maternal and infant health. These results would contribute towards developing guidelines for good clinical practice. Trial registration This clinical trial is
Sazzini, M; Schiavo, G; De Fanti, S; Martelli, P L; Casadio, R; Luiselli, D
2014-09-01
Adaptation to low temperatures has been reasonably developed in the human species during the colonization of the Eurasian landmass subsequent to Out of Africa migrations of anatomically modern humans. In addition to morphological and cultural changes, also metabolic ones are supposed to have favored human isolation from cold and body heat production and this can be hypothesized also for most Neandertal and at least for some Denisovan populations, which lived in geographical areas that strongly experienced the last glacial period. Modulation of non-shivering thermogenesis, for which adipocytes belonging to the brown adipose tissue are the most specialized cells, might have driven these metabolic adaptations. To perform an exploratory analysis aimed at looking into this hypothesis, variation at 28 genes involved in such functional pathway was investigated in modern populations from different climate zones, as well as in Neandertal and Denisovan genomes. Patterns of variation at the LEPR gene, strongly related to increased heat dissipation by mitochondria, appeared to have been shaped by positive selection in modern East Asians, but not in Europeans. Moreover, a single potentially cold-adapted LEPR allele, different from the supposed adaptive one identified in Homo sapiens, was found also in Neandertal and Denisovan genomes. These findings suggest that independent mechanisms for cold adaptations might have been developed in different non-African human groups, as well as that the evolution of possible enhanced thermal efficiency in Neandertals and in some Denisovan populations has plausibly entailed significant changes also in other functional pathways than in the examined one.
Sazzini, M; Schiavo, G; De Fanti, S; Martelli, P L; Casadio, R; Luiselli, D
2014-01-01
Adaptation to low temperatures has been reasonably developed in the human species during the colonization of the Eurasian landmass subsequent to Out of Africa migrations of anatomically modern humans. In addition to morphological and cultural changes, also metabolic ones are supposed to have favored human isolation from cold and body heat production and this can be hypothesized also for most Neandertal and at least for some Denisovan populations, which lived in geographical areas that strongly experienced the last glacial period. Modulation of non-shivering thermogenesis, for which adipocytes belonging to the brown adipose tissue are the most specialized cells, might have driven these metabolic adaptations. To perform an exploratory analysis aimed at looking into this hypothesis, variation at 28 genes involved in such functional pathway was investigated in modern populations from different climate zones, as well as in Neandertal and Denisovan genomes. Patterns of variation at the LEPR gene, strongly related to increased heat dissipation by mitochondria, appeared to have been shaped by positive selection in modern East Asians, but not in Europeans. Moreover, a single potentially cold-adapted LEPR allele, different from the supposed adaptive one identified in Homo sapiens, was found also in Neandertal and Denisovan genomes. These findings suggest that independent mechanisms for cold adaptations might have been developed in different non-African human groups, as well as that the evolution of possible enhanced thermal efficiency in Neandertals and in some Denisovan populations has plausibly entailed significant changes also in other functional pathways than in the examined one. PMID:24667833
2013-01-01
Background Persons with serious mental illness (SMI) are disproportionately burdened by premature mortality. This disparity is exacerbated by poor continuity of care with the health system. The Veterans Health Administration (VA) developed Re-Engage, an effective population-based outreach program to identify veterans with SMI lost to care and to reconnect them with VA services. However, such programs often encounter barriers getting implemented into routine care. Adaptive designs are needed when the implementation intervention requires augmentation within sites that do not initially respond to an initial implementation intervention. This protocol describes the methods used in an adaptive implementation design study that aims to compare the effectiveness of a standard implementation strategy (Replicating Effective Programs, or REP) with REP enhanced with External Facilitation (enhanced REP) to promote the uptake of Re-Engage. Methods/Design This study employs a four-phase, two-arm, longitudinal, clustered randomized trial design. VA sites (n = 158) across the United States with a designated Re-Engage provider, at least one Veteran with SMI lost to care, and who received standard REP during a six-month run-in phase. Subsequently, 88 sites with inadequate uptake were stratified at the cluster level by geographic region (n = 4) and VA regional service network (n = 20) and randomized to REP (n = 49) vs. enhanced REP (n = 39) in phase two. The primary outcome was the percentage of veterans on each facility outreach list documented on an electronic web registry. The intervention was at the site and network level and consisted of standard REP versus REP enhanced by external phone facilitation consults. At 12 months, enhanced REP sites returned to standard REP and 36 sites with inadequate participation received enhanced REP for six months in phase three. Secondary implementation outcomes included the percentage of veterans contacted directly by site
Tuning into Scorpius X-1: adapting a continuous gravitational-wave search for a known binary system
NASA Astrophysics Data System (ADS)
Meadors, Grant David; Goetz, Evan; Riles, Keith
2016-05-01
We describe how the TwoSpect data analysis method for continuous gravitational waves (GWs) has been tuned for directed sources such as the low-mass X-ray binary (LMXB), Scorpius X-1 (Sco X-1). A comparison of five search algorithms generated simulations of the orbital and GW parameters of Sco X-1. Whereas that comparison focused on relative performance, here the simulations help quantify the sensitivity enhancement and parameter estimation abilities of this directed method, derived from an all-sky search for unknown sources, using doubly Fourier-transformed data. Sensitivity is shown to be enhanced when the source sky location and period are known, because we can run a fully templated search, bypassing the all-sky hierarchical stage using an incoherent harmonic sum. The GW strain and frequency, as well as the projected semi-major axis of the binary system, are recovered and uncertainty estimated, for simulated signals that are detected. Upper limits for GW strain are set for undetected signals. Applications to future GW observatory data are discussed. Robust against spin-wandering and computationally tractable despite an unknown frequency, this directed search is an important new tool for finding gravitational signals from LMXBs.
Nikali, K.; Suomalainen, A.; Koskinen, T.; Peltonen, L.; Terwilliger, J.; Weissenbach, J.
1995-05-01
Infantile-onset spinocerebellar ataxia (IOSCA) is an autosomal recessively inherited progressive neurological disorder of unknown etiology. This ataxia, identified so far only in the genetically isolated Finnish population, does not share gene locus with any of the previously identified hereditary ataxias, and a random mapping approach was adopted to assign the IOSCA locus. Based on the assumption of one founder mutation, a primary screening of the genome was performed using samples from just four affected individuals in two consanguineous pedigrees. The identification of a shared chromosomal region in these four patients provided the first evidence that the IOSCA gene locus is on chromosome 10q23.3-q24.1, which was confirmed by conventional linkage analysis in the complete family material. Strong linkage disequilibrium observed between IOSCA and the linked markers was utilized to define accurately the critical chromosomal region. The results showed the power of linkage disequilibrium in the locus assignment of diseases with very limited family materials. 30 refs., 3 figs., 2 tabs.
Pekmezi, Dori; Dunsiger, Shira; Gans, Kim; Bock, Beth; Gaskins, Ronnesia; Marquez, Becky; Lee, Christina; Neighbors, Charles; Jennings, Ernestine; Tilkemeier, Peter; Marcus, Bess
2012-01-01
Background Latinos are now the largest (and fastest growing) ethnic minority group in the United States. Latinas report high rates of physical inactivity and suffer disproportionately from obesity, diabetes, and other conditions that are associated with sedentary lifestyles. Effective physical activity interventions are urgently needed to address these health disparities. Method/Design An ongoing randomized controlled trial will test the efficacy of a home-based, individually tailored physical activity print intervention for Latinas (1R01NR011295). This program was culturally and linguistically adapted for the target population through extensive formative research (6 focus groups, 25 cognitive interviews, iterative translation process). This participant feedback was used to inform intervention development. Then, 268 sedentary Latinas were randomly assigned to receive either the Tailored Intervention or the Wellness Contact Control arm. The intervention, based on Social Cognitive Theory and the Transtheoretical Model, consists of six months of regular mailings of motivation-matched physical activity manuals and tip sheets and individually tailored feedback reports generated by a computer expert system, followed by a tapered dose of mailings during the second six months (maintenance phase). The main outcome is change in minutes/week of physical activity at six months and one year as measured by the 7-Day Physical Activity Recall (7-Day PAR). To validate these findings, accelerometer data will be collected at the same time points. Discussion High reach, low cost, culturally relevant interventions to encourage physical activity among Latinas could help reduce health disparities and thus have a substantial positive impact on public health. PMID:22789455
NASA Astrophysics Data System (ADS)
Stainforth, D.; Harrison, S.; Smith, L. A.
2009-12-01
The reality of anthropogenic climate change is founded on well understood scientific principles and is now widely accepted. The need for international efforts to limit the extent of future changes in climate - climate change mitigation - is therefore clear. Since anthropogenic climate change is well underway, however, and the planet is committed to further changes based on past emissions alone, there will certainly be a need for global society to adapt to the consequences. The physical sciences are increasingly being looked to as sources of information and guidance on adaptation policy and decision making. Unlike mitigation efforts such decisions generally require information on local or regional scales. What is the source of such information? How can we tell when it is robust and fit for the purpose of supporting a specific decision? The availability of rapidly increasing computational resources has led to a steady increase in the resolution of global climate models and of embedded regional climate models. They are approaching a point where they can provide data at a resolution which may be usable in adaptation decision support. Yet models are not equivalent to reality and model errors are significant even at the global scale. By contrast scientific understanding of climatic processes now and in the past can provide information about plausible responses which are more qualitative but may be equally useful. This talk will focus on the relative roles of fundamentally reductionist, model approaches with alternatives based on observations and process understanding. The latter, although more qualitative, are able to inform us about emergent properties; properties which may be difficult or impossible to reproduce within a reductionist paradigm. The contrast between emergent and reductionist approaches has a long history in the physical sciences; a history which provides valuable lessons for the relationship between climate science and societal / policy decisions. Here
Hurley, Jane C; Hollingshead, Kevin E; Todd, Michael; Jarrett, Catherine L; Tucker, Wesley J; Angadi, Siddhartha S
2015-01-01
Background Walking is a widely accepted and frequently targeted health promotion approach to increase physical activity (PA). Interventions to increase PA have produced only small improvements. Stronger and more potent behavioral intervention components are needed to increase time spent in PA, improve cardiometabolic risk markers, and optimize health. Objective Our aim is to present the rationale and methods from the WalkIT Trial, a 4-month factorial randomized controlled trial (RCT) in inactive, overweight/obese adults. The main purpose of the study was to evaluate whether intensive adaptive components result in greater improvements to adults’ PA compared to the static intervention components. Methods Participants enrolled in a 2x2 factorial RCT and were assigned to one of four semi-automated, text message–based walking interventions. Experimental components included adaptive versus static steps/day goals, and immediate versus delayed reinforcement. Principles of percentile shaping and behavioral economics were used to operationalize experimental components. A Fitbit Zip measured the main outcome: participants’ daily physical activity (steps and cadence) over the 4-month duration of the study. Secondary outcomes included self-reported PA, psychosocial outcomes, aerobic fitness, and cardiorespiratory risk factors assessed pre/post in a laboratory setting. Participants were recruited through email listservs and websites affiliated with the university campus, community businesses and local government, social groups, and social media advertising. Results This study has completed data collection as of December 2014, but data cleaning and preliminary analyses are still in progress. We expect to complete analysis of the main outcomes in late 2015 to early 2016. Conclusions The Walking Interventions through Texting (WalkIT) Trial will further the understanding of theory-based intervention components to increase the PA of men and women who are healthy, insufficiently
2014-01-01
Background Although childhood sexual and/or physical abuse (CSA/CPA) is known to have severe psychopathological consequences, there is little evidence on psychotherapeutic interventions for adolescents and young adults suffering from post-traumatic stress disorder (PTSD). Equally sparse are data on moderators of treatment response on PTSD-related epigenetic changes, health care costs and loss of productivity, alterations in cognitive processing, and on how successful interventions affect all of these factors. Early treatment may prevent later (co)morbidity. In this paper, we present a study protocol for the evaluation of a newly developed psychotherapeutic manual for PTSD after CSA/CPA in adolescents and young adults – the Developmentally Adapted Cognitive Processing Therapy (D-CPT). Methods/design In a multicenter randomized controlled trial (RCT) D-CPT is compared to treatment as usual (TAU). A sample of 90 adolescent outpatients aged 14 to 21 years will be randomized to one of these conditions. Four assessments will be carried out at baseline, at end of treatment, and 3 and 6 months after end of therapy. Each time, patients will be assessed via clinical interviews and a wide range of questionnaires. In addition to PTSD symptoms and comorbidities, we will evaluate moderators of treatment response, epigenetic profiles, direct and indirect costs of this disorder, and neurophysiological processing of threat cues in PTSD and their respective changes in the course of these two treatments (D-CPT and TAU). Discussion The study will provide new insights in the understudied field of PTSD in adolescents and young adults. A newly developed intervention will be evaluated in this therapeutically underserved population. Results will provide data on treatment efficacy, direct and indirect treatment costs, as well as on associations of treatment outcome and PTSD intensity both to epigenetic profiles and to the neurobiological processing of threat cues. Besides, they will
Searching for Binary Y Dwarfs with the Gemini Multi-conjugate Adaptive Optics System (GeMS)
NASA Astrophysics Data System (ADS)
Opitz, Daniela; Tinney, C. G.; Faherty, Jacqueline K.; Sweet, Sarah; Gelino, Christopher R.; Kirkpatrick, J. Davy
2016-03-01
The NASA Wide-field Infrared Survey Explorer (WISE) has discovered almost all the known members of the new class of Y-type brown dwarfs. Most of these Y dwarfs have been identified as isolated objects in the field. It is known that binaries with L- and T-type brown dwarf primaries are less prevalent than either M-dwarf or solar-type primaries, they tend to have smaller separations and are more frequently detected in near-equal mass configurations. The binary statistics for Y-type brown dwarfs, however, are sparse, and so it is unclear if the same trends that hold for L- and T-type brown dwarfs also hold for Y-type ones. In addition, the detection of binary companions to very cool Y dwarfs may well be the best means available for discovering even colder objects. We present results for binary properties of a sample of five WISE Y dwarfs with the Gemini Multi-Conjugate Adaptive Optics System. We find no evidence for binary companions in these data, which suggests these systems are not equal-luminosity (or equal-mass) binaries with separations larger than ˜0.5-1.9 AU. For equal-mass binaries at an age of 5 Gyr, we find that the binary binding energies ruled out by our observations (i.e., 1042 erg) are consistent with those observed in previous studies of hotter ultra-cool dwarfs.
Sieh Kiong, Tiong; Tariqul Islam, Mohammad; Ismail, Mahamod; Salem, Balasem
2014-01-01
Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program. PMID:25147859
Darzi, Soodabeh; Kiong, Tiong Sieh; Islam, Mohammad Tariqul; Ismail, Mahamod; Kibria, Salehin; Salem, Balasem
2014-01-01
Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program.
Naeem, Sadaf; Hylands, Peter; Barlow, David
2012-02-01
Data on phytochemical constituents of plants commonly used in traditional Indonesian medicine have been compiled as a computer database. This database (the Indonesian Herbal constituents database, IHD) currently contains details on ∼1,000 compounds found in 33 different plants. For each entry, the IHD gives details of chemical structure, trivial and systematic name, CAS registry number, pharmacology (where known), toxicology (LD(50)), botanical species, the part(s) of the plant(s) where the compounds are found, typical dosage(s) and reference(s). A second database has been also been compiled for plant-derived compounds with known activity against the enzyme, aldose reductase (AR). This database (the aldose reductase inhibitors database, ARID) contains the same details as the IHD, and currently comprises information on 120 different AR inhibitors. Virtual screening of all compounds in the IHD has been performed using Random Forest (RF) modelling, in a search for novel leads active against AR-to provide for new forms of symptomatic relief in diabetic patients. For the RF modelling, a set of simple 2D chemical descriptors were employed to classify all compounds in the combined ARID and IHD databases as either active or inactive as AR inhibitors. The resulting RF models (which gave misclassification rates of 21%) were used to identify putative new AR inhibitors in the IHD, with such compounds being identified as those giving RF scores >0.5 (in each of the three different RF models developed). In vitro assays were subsequently performed for four of the compounds obtained as hits in this in silico screening, to determine their inhibitory activity against human recombinant AR. The two compounds having the highest RF scores (prunetin and ononin) were shown to have the highest activities experimentally (giving ∼58% and ∼52% inhibition at a concentration of 15μM, respectively), while the compounds with lowest RF scores (vanillic acid and cinnamic acid) showed the
NASA Astrophysics Data System (ADS)
Elliott, P.; Huélamo, N.; Bouy, H.; Bayo, A.; Melo, C. H. F.; Torres, C. A. O.; Sterzik, M. F.; Quast, G. R.; Chauvin, G.; Barrado, D.
2015-08-01
Context. Young loose nearby associations are unique samples of close (<150 pc), young (≈5-100 Myr) pre-main-sequence (PMS) stars. A significant number of members of these associations have been identified in the SACY (search for associations containing young stars) collaboration. We can use the proximity and youth of these members to investigate key ingredients in star formation processes, such as multiplicity. Aims: With the final goal of better understanding multiplicity properties at different evolutionary stages of PMS stars, we present the statistics of identified multiple systems from 113 confirmed SACY members. We derive multiplicity frequencies, mass-ratio, and physical separation distributions in a consistent parameter space, and compare our results to other PMS populations and the field. Methods: We have obtained adaptive-optics assisted near-infrared observations with the Nasmyth Adaptive Optics System and Near-Infrared Imager and Spectrograph (NACO), ESO/VLT, and the Infrared Camera for Adaptive optics at Lick observatory (IRCAL), Lick Observatory, for at least one epoch of all 113 SACY members. We have identified multiple systems using co-moving proper-motion analysis for targets with multi-epoch data, and using contamination estimates in terms of mass-ratio and physical separation for targets with single-epoch data. We have explored ranges in projected separation and mass-ratio of a [3-1000 au], and q [0.1-1], respectively. Results: We have identified 31 multiple systems (28 binaries and 3 triples). We derive a multiplicity frequency (MF) of MF3-1000 au=28.4+4.7_{-3.9}% and a triple frequency (TF) of TF3-1000 au =2.8 +2.5-0.8% in the separation range of 3-1000 au. We do not find any evidence for an increase in the MF with primary mass. The estimated mass-ratio of our statistical sample (with power-law index γ = -0.04 ± 0.14) is consistent with a flat distribution (γ = 0). Conclusions: Analysis from previous work using tight binaries indicated
NASA Astrophysics Data System (ADS)
Monthus, Cécile
2016-07-01
The iterative methods to diagonalize matrices and many-body Hamiltonians can be reformulated as flows of Hamiltonians towards diagonalization driven by unitary transformations that preserve the spectrum. After a comparative overview of the various types of discrete flows (Jacobi, QR-algorithm) and differential flows (Toda, Wegner, White) that have been introduced in the past, we focus on the random XXZ chain with random fields in order to determine the best closed flow within a given subspace of running Hamiltonians. For the special case of the free-fermion random XX chain with random fields, the flow coincides with the Toda differential flow for tridiagonal matrices which is related to the classical integrable Toda chain and which can be seen as the continuous analog of the discrete QR-algorithm. For the random XXZ chain with random fields that displays a many-body-localization transition, the present differential flow should be an interesting alternative to compare with the discrete flow that has been proposed recently to study the many-body-localization properties in a model of interacting fermions (Rademaker and Ortuno 2016 Phys. Rev. Lett. 116, 010404).
Standardization of Keyword Search Mode
ERIC Educational Resources Information Center
Su, Di
2010-01-01
In spite of its popularity, keyword search mode has not been standardized. Though information professionals are quick to adapt to various presentations of keyword search mode, novice end-users may find keyword search confusing. This article compares keyword search mode in some major reference databases and calls for standardization. (Contains 3…
Scaling laws of marine predator search behaviour.
Sims, David W; Southall, Emily J; Humphries, Nicolas E; Hays, Graeme C; Bradshaw, Corey J A; Pitchford, Jonathan W; James, Alex; Ahmed, Mohammed Z; Brierley, Andrew S; Hindell, Mark A; Morritt, David; Musyl, Michael K; Righton, David; Shepard, Emily L C; Wearmouth, Victoria J; Wilson, Rory P; Witt, Matthew J; Metcalfe, Julian D
2008-02-28
Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. Lévy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators-sharks, bony fishes, sea turtles and penguins-exhibit Lévy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions.
Nest and food search behaviour in desert ants, Cataglyphis: a critical comparison.
Pfeffer, Sarah E; Bolek, Siegfried; Wolf, Harald; Wittlinger, Matthias
2015-07-01
North African desert ants, Cataglyphis, use path integration to calculate a home vector during their foraging trips, constantly informing them about their position relative to the nest. This home vector is also used to find the way back to a productive feeding site the ant has encountered and thus memorized. When the animal fails to arrive at its goal after having run off the home or food vector, a systematic search is initiated. The basic search strategies are identical for nest and food searches, consisting of a search spiral superimposed by a random walk. While nest searches have been investigated in much detail, food site searches have received comparatively little attention. Here, we quantify and compare nest and food site searches recorded under similar conditions, particularly constant nest-feeder distance, and we observe notable differences in nest and food search performances. The parameters of nest searches are relatively constant and improve little with experience, although those small improvements had not been recognized previously. Food searches, by contrast, are more flexible and cover smaller or larger areas, mainly depending on the reliability of food encounter over several visits. Intriguingly, food site searches may be significantly more focussed than nest searches, although the nest should be the most important goal in an ant's life. These results demonstrate both adaptability and high accuracy of the ants' search programme.
ERIC Educational Resources Information Center
Berends, Mark; Garet, Michael S.
2002-01-01
Asserts that integrating randomized field trials (RFTs) and nationally representative surveys can strengthen the evidence base for school reform, suggesting national surveys can help determine the focus of RFTs by identifying factors that place schools at risk of poor achievement or buffer schools from risk. Surveys can provide data on the…
Heim, Eva; Chowdhary, Neerja; Maercker, Andreas; Albanese, Emiliano
2016-01-01
Background Cultural adaptation of mental health care interventions is key, particularly when there is little or no therapist interaction. There is little published information on the methods of adaptation of bibliotherapy and e-mental health interventions. Objective To systematically search for evidence of the effectiveness of minimally guided interventions for the treatment of common mental disorders among culturally diverse people with common mental disorders; to analyze the extent and effects of cultural adaptation of minimally guided interventions for the treatment of common mental disorders. Methods We searched Embase, PubMed, the Cochrane Library, and PsycINFO for randomized controlled trials that tested the efficacy of minimally guided or self-help interventions for depression or anxiety among culturally diverse populations. We calculated pooled standardized mean differences using a random-effects model. In addition, we administered a questionnaire to the authors of primary studies to assess the cultural adaptation methods used in the included primary studies. We entered this information into a meta-regression to investigate effects of the extent of adaptation on intervention efficacy. Results We included eight randomized controlled trials (RCTs) out of the 4911 potentially eligible records identified by the search: four on e-mental health and four on bibliotherapy. The extent of cultural adaptation varied across the studies, with language translation and use of metaphors being the most frequently applied elements of adaptation. The pooled standardized mean difference for primary outcome measures of depression and anxiety was -0.81 (95% CI -0.10 to -0.62). Higher cultural adaptation scores were significantly associated with greater effect sizes (P=.04). Conclusions Our results support the results of previous systematic reviews on the cultural adaptation of face-to-face interventions: the extent of cultural adaptation has an effect on intervention efficacy
2013-01-01
Background Studies have shown that lifestyle interventions are effective in preventing or delaying the onset of type 2 diabetes in high-risk patients. However, research on the effectiveness of lifestyle interventions in high-risk immigrant populations with different cultural and socioeconomic backgrounds is scarce. The aim was to design a culturally adapted lifestyle intervention for an immigrant population and to evaluate its effectiveness and cost-effectiveness. Methods/design In this randomized controlled trial, 308 participants (born in Iraq, living in Malmö, Sweden and at high risk of type 2 diabetes) will be allocated to either a culturally adapted intervention or a control group. The intervention will consist of 10 group counseling sessions focusing on diet, physical activity and behavioral change over 6 months, and the offer of exercise sessions. Cultural adaptation includes gender-specific exercise sessions, and counseling by a health coach community member. The control group will receive the information about healthy lifestyle habits provided by the primary health care center. The primary outcome is change in fasting glucose level. Secondary outcomes are changes in body mass index, insulin sensitivity, physical activity, food habits and health-related quality of life. Measurements will be taken at baseline, after 3 and 6 months. Data will be analyzed by the intention-to-treat approach. The cost-effectiveness during the trial period and over the longer term will be assessed by simulation modeling from patient, health care and societal perspectives. Discussion This study will provide a basis to measure the effectiveness of a lifestyle intervention designed for immigrants from the Middle East in terms of improvement in glucose metabolism, and will also assess its cost-effectiveness. Results from this trial may help health care providers and policy makers to adapt and implement lifestyle interventions suitable for this population group that can be
Curcó, David; Alemán, Carlos
2004-04-30
The performance of a recently developed method to generate representative atomistic models of amorphous polymers has been investigated. This method, which is denoted SuSi, can be defined as a random generator of energy minima. The effects produced by different parameters used to define the size of the system and the characteristics of the generation algorithm have been examined. Calculations have been performed on poly(L,D-lactic) acid (rho = 1.25 g/cm3) and nylon 6 (rho = 1.084 g/cm(3)), which are important commercial polymers.
Akhmadeeva, L R; Setchenkova, N M; Magzhanov, R V; Abdrashitova, E V; Bulgakova, A Z
2010-01-01
The effectiveness of dynamic transcutaneous electrostimulation was compared to its imitation in patients with low back pain. Patients were randomized into two groups: 21 patients were treated with transcutaneous electrostimulation and 21 patients received placebo. Patients had one session of electrostimulation (20 minutes) daily during 7-10 days. Pain was assessed by the Visual Analogous scale (VAS) daily. The Oswestry Low Back Pain Scale, the Beck Depression scale and the Spilberger-Khanin Anxiety test were used as well before and after the treatment. The significant improvement on the VAS (p=0,048) and the Oswestry scale (p=0,047) was found in the main group compared to the placebo one. No side-effects of transcutaneous electrostimulation were observed.
NASA Astrophysics Data System (ADS)
Land, Phillip; Robinson, Dennis; Roeder, James; Cook, Dean; Majumdar, Arun K.
2016-05-01
A new technique has been developed for improving the Signal-to-Noise Ratio (SNR) of underwater acoustic signals measured above the water's surface. This technique uses a Laser Doppler Vibrometer (LDV) and an Adaptive Optics (AO) system (consisting of a fast steering mirror, deformable mirror, and Shack-Hartmann Wavefront Sensor) for mitigating the effect of surface water distortions encountered while remotely recording underwater acoustic signals. The LDV is used to perform non-contact vibration measurements of a surface via a two beam laser interferometer. We have demonstrated the feasibility of this technique to overcome water distortions artificially generated on the surface of the water in a laboratory tank. In this setup, the LDV beam penetrates the surface of the water and travels down to be reflected off a submerged acoustic transducer. The reflected or returned beam is then recorded by the LDV as a vibration wave measurement. The LDV extracts the acoustic wave information while the AO mitigates the water surface distortions, increasing the overall SNR. The AO system records the Strehl ratio, which is a measure of the quality of optical image formation. In a perfect optical system the Strehl ratio is unity, however realistic systems with imperfections have Strehl ratios below one. The operation of the AO control system in open-loop and closed-loop configurations demonstrates the utility of the AO-based LDV for many applications.
An adaptive data-smoothing routine
NASA Technical Reports Server (NTRS)
Taylor, Clayborne D.; Nicolas, David P.
1989-01-01
An adaptive noise reduction algorithm that can be implemented on a microcomputer is developed. Smoothing polynomials are used where the polynomial coefficients are chosen such that the mean-square-error between the noisy and smoothed data is minimized. This approach is equivalent to the implementation of a low-pass finite impulse response filter. The noise reduction depends on the order of the smoothing polynomial. A whiteness test on the error sequence is incorporated to search for the optimal smoothing. Expansion coefficients may be computed via the fast Fourier transform, and the resulting smoothing process is the equivalent of the implementation of an adaptive ideal low-pass filter. Results are obtained for an analytical signal with added white Gaussian noise. The routine may be applied to any smooth signal with additive random noise.
Improving Search Algorithms by Using Intelligent Coordinates
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar
2004-01-01
We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.
Improving search algorithms by using intelligent coordinates
NASA Astrophysics Data System (ADS)
Wolpert, David; Tumer, Kagan; Bandari, Esfandiar
2004-01-01
We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent η is self-interested; it sets its variable to maximize its own function gη. Three factors govern such a distributed algorithm’s performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit all three factors by modifying a search algorithm’s exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based “player” engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.
Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets
NASA Astrophysics Data System (ADS)
Toft, I. E.; Bagnall, A. J.
This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.
ERIC Educational Resources Information Center
Rama, Irene; Kontu, Elina
2012-01-01
The purpose of this article is to introduce a research design, which aims to find useful pedagogical adaptations for teaching pupils with autism. Autism is a behavioural syndrome characterised by disabilities and dysfunctions in interaction and communication, which is why it is interesting to explore educational processes particularly from an…
Self-correcting random number generator
Humble, Travis S.; Pooser, Raphael C.
2016-09-06
A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, to provide a random number according to one or more performance criteria.
A hybrid search algorithm for swarm robots searching in an unknown environment.
Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao
2014-01-01
This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.
Training neural nets with the reactive tabu search.
Battiti, R; Tecchiolli, G
1995-01-01
In this paper the task of training subsymbolic systems is considered as a combinatorial optimization problem and solved with the heuristic scheme of the reactive tabu search (RTS). An iterative optimization process based on a "modified local search" component is complemented with a meta-strategy to realize a discrete dynamical system that discourages limit cycles and the confinement of the search trajectory in a limited portion of the search space. The possible cycles are discouraged by prohibiting (i.e., making tabu) the execution of moves that reverse the ones applied in the most recent part of the search. The prohibition period is adapted in an automated way. The confinement is avoided and a proper exploration is obtained by activating a diversification strategy when too many configurations are repeated excessively often. The RTS method is applicable to nondifferentiable functions, is robust with respect to the random initialization, and effective in continuing the search after local minima. Three tests of the technique on feedforward and feedback systems are presented.
Random Thoughts--In Search for Answers
ERIC Educational Resources Information Center
Sobelman, C. P.
1976-01-01
This paper discusses the problem of textbook selection for Chinese instruction, and considers the role of Chinese language teachers and content of Chinese courses. Lists of supplementary materials for PRC and DeFrancis texts are appended. (CHK)
... of this page: https://medlineplus.gov/cloud.html Search Cloud To use the sharing features on this ... of Top 110 zoster vaccine Share the MedlinePlus search cloud with your users by embedding our search ...
Quasi-Random Sequence Generators.
1994-03-01
Version 00 LPTAU generates quasi-random sequences. The sequences are uniformly distributed sets of L=2**30 points in the N-dimensional unit cube: I**N=[0,1]. The sequences are used as nodes for multidimensional integration, as searching points in global optimization, as trial points in multicriteria decision making, as quasi-random points for quasi Monte Carlo algorithms.
ERIC Educational Resources Information Center
Flournoy, Nancy
Designs for sequential sampling procedures that adapt to cumulative information are discussed. A familiar illustration is the play-the-winner rule in which there are two treatments; after a random start, the same treatment is continued as long as each successive subject registers a success. When a failure occurs, the other treatment is used until…
Random geometric prior forest for multiclass object segmentation.
Liu, Xiao; Song, Mingli; Tao, Dacheng; Bu, Jiajun; Chen, Chun
2015-10-01
Recent advances in object detection have led to the development of segmentation by detection approaches that integrate top-down geometric priors for multiclass object segmentation. A key yet under-addressed issue in utilizing top-down cues for the problem of multiclass object segmentation by detection is efficiently generating robust and accurate geometric priors. In this paper, we propose a random geometric prior forest scheme to obtain object-adaptive geometric priors efficiently and robustly. In the scheme, a testing object first searches for training neighbors with similar geometries using the random geometric prior forest, and then the geometry of the testing object is reconstructed by linearly combining the geometries of its neighbors. Our scheme enjoys several favorable properties when compared with conventional methods. First, it is robust and very fast because its inference does not suffer from bad initializations, poor local minimums or complex optimization. Second, the figure/ground geometries of training samples are utilized in a multitask manner. Third, our scheme is object-adaptive but does not require the labeling of parts or poselets, and thus, it is quite easy to implement. To demonstrate the effectiveness of the proposed scheme, we integrate the obtained top-down geometric priors with conventional bottom-up color cues in the frame of graph cut. The proposed random geometric prior forest achieves the best segmentation results of all of the methods tested on VOC2010/2012 and is 90 times faster than the current state-of-the-art method. PMID:25974937
Moran, Robert F.; McKay, David; Pickard, Chris J.; Berry, Andrew J.; Griffin, John M.
2016-01-01
The structural chemistry of materials containing low levels of nonstoichiometric hydrogen is difficult to determine, and producing structural models is challenging where hydrogen has no fixed crystallographic site. Here we demonstrate a computational approach employing ab initio random structure searching (AIRSS) to generate a series of candidate structures for hydrous wadsleyite (β-Mg2SiO4 with 1.6 wt% H2O), a high-pressure mineral proposed as a repository for water in the Earth's transition zone. Aligning with previous experimental work, we solely consider models with Mg3 (over Mg1, Mg2 or Si) vacancies. We adapt the AIRSS method by starting with anhydrous wadsleyite, removing a single Mg2+ and randomly placing two H+ in a unit cell model, generating 819 candidate structures. 103 geometries were then subjected to more accurate optimisation under periodic DFT. Using this approach, we find the most favourable hydration mechanism involves protonation of two O1 sites around the Mg3 vacancy. The formation of silanol groups on O3 or O4 sites (with loss of stable O1–H hydroxyls) coincides with an increase in total enthalpy. Importantly, the approach we employ allows observables such as NMR parameters to be computed for each structure. We consider hydrous wadsleyite (∼1.6 wt%) to be dominated by protonated O1 sites, with O3/O4–H silanol groups present as defects, a model that maps well onto experimental studies at higher levels of hydration (J. M. Griffin et al., Chem. Sci., 2013, 4, 1523). The AIRSS approach adopted herein provides the crucial link between atomic-scale structure and experimental studies. PMID:27020937
Student Search and Seizure: 1998 Update.
ERIC Educational Resources Information Center
Krumm, Bernita L.; Thompson, David P.
This article examines the effects of the "Acton" decision, a Supreme Court ruling that upheld random urinalysis of secondary-school students who participate in extracurricular athletics. The paper focuses on cases involving general (mass) searches, "medical assessment" searches, strip searches, and drug testing. Although the intent of the Court is…
Chhun, Nok; Cleland, Charles M; Crespo-Fierro, Michele; Parés-Avila, José A; Lizcano, John A; Shedlin, Michele G; Johnston, Barbara E; Sharp, Victoria L
2016-01-01
Background Human immunodeficiency virus (HIV) disease in the United States disproportionately affects minorities, including Latinos. Barriers including language are associated with lower antiretroviral therapy (ART) adherence seen among Latinos, yet ART and interventions for clinic visit adherence are rarely developed or delivered in Spanish. Objective The aim was to adapt a computer-based counseling tool, demonstrated to reduce HIV-1 viral load and sexual risk transmission in a population of English-speaking adults, for use during routine clinical visits for an HIV-positive Spanish-speaking population (CARE+ Spanish); the Technology Acceptance Model (TAM) was the theoretical framework guiding program development. Methods A longitudinal randomized controlled trial was conducted from June 4, 2010 to March 29, 2012. Participants were recruited from a comprehensive HIV treatment center comprising three clinics in New York City. Eligibility criteria were (1) adults (age ≥18 years), (2) Latino birth or ancestry, (3) speaks Spanish (mono- or multilingual), and (4) on antiretrovirals. Linear and generalized mixed linear effects models were used to analyze primary outcomes, which included ART adherence, sexual transmission risk behaviors, and HIV-1 viral loads. Exit interviews were offered to purposively selected intervention participants to explore cultural acceptability of the tool among participants, and focus groups explored the acceptability and system efficiency issues among clinic providers, using the TAM framework. Results A total of 494 Spanish-speaking HIV clinic attendees were enrolled and randomly assigned to the intervention (arm A: n=253) or risk assessment-only control (arm B, n=241) group and followed up at 3-month intervals for one year. Gender distribution was 296 (68.4%) male, 110 (25.4%) female, and 10 (2.3%) transgender. By study end, 433 of 494 (87.7%) participants were retained. Although intervention participants had reduced viral loads, increased
NASA Astrophysics Data System (ADS)
Oshlakov, V. G.; Andreev, M. I.; Malykh, D. D.
2009-09-01
Using the polarization characteristics of a target and its underlying surface one can change the target contrast range. As the target one can use the compact and discrete structures with different characteristics to reflect electromagnetic waves. An important problem, solved by the adaptive polarization lidar, is to determine the availability and identification of different targets based on their polarization characteristics against the background of underlying surface, which polarization characteristics are unknown. Another important problem of the adaptive polarization lidar is a search for the objects, which polarization characteristics are unknown, against the background of underlying surface, which polarization characteristics are known. The adaptive polarization lidar makes it possible to determine the presence of impurities in sea water. The characteristics of the adaptive polarization lidar undergo variations, i.e., polarization characteristics of a sensing signal and polarization characteristics of the receiver are varied depending on the problem to be solved. One of the versions of construction of the adaptive polarization lidar is considered. The increase of the contrast in the adaptive lidar has been demonstrated by the numerical experiment when sensing hydrosols on the background of the Rayleigh scattering, caused by clear water. The numerical experiment has also demonstrated the increase of the contrast in the adaptive lidar when sensing at two wavelengths of dry haze and dense haze on the background of the Rayleigh scattering, caused by the clear atmosphere. The most effective wavelength was chosen.
Ezendam, Nicole PM; Pijnenborg, Johanna MA; Boll, Dorry; Vos, Maria Caroline; Kruitwagen, Roy FPM; van de Poll-Franse, Lonneke V
2016-01-01
Background The Institute of Medicine recommends Survivorship Care Plans (SCPs) for all cancer survivors. However, it is unclear whether certain patient groups may or may not benefit from SCPs. Objective The aim was to assess whether the effects of an automatically generated paper SCP on patients’ satisfaction with information provision and care, illness perceptions, and health care utilization were moderated by disease-related Internet use. Methods Twelve hospitals were randomized to either SCP care or usual care in the pragmatic cluster randomized Registrationsystem Oncological GYnecology (ROGY) Care trial. Newly diagnosed endometrial cancer patients completed questionnaires after diagnosis (N=221; response: 74.7%, 221/296), 6 months (n=158), and 12 months (n=147), including patients’ satisfaction with information provision and care, illness perceptions, health care utilization (how many times patients visited a medical specialist or primary care physician about their cancer in the past 6 months), and disease-related Internet use (whether patients used the Internet to look for information about cancer). Results In total, 80 of 221 (36.2%) patients used the Internet to obtain disease-related information. Disease-related Internet use moderated the SCP care effect on the amount of information received about the disease (P=.03) and medical tests (P=.01), helpfulness of the information (P=.01), and how well patients understood their illness (P=.04). All stratified analyses were not statistically significant. However, it appeared that patients who did not seek disease-related information on the Internet in the SCP care arm reported receiving more information about their disease (mean 63.9, SD 20.1 vs mean 58.3, SD 23.7) and medical tests (mean 70.6, SD 23.5 vs mean 64.7, SD 24.9), finding the information more helpful (76.7, SD 22.9 vs mean 67.8, SD 27.2; scale 0-100), and understanding their illness better (mean 6.6, SD 3.0 vs mean 6.1, SD 3.2; scale 1-10) than
The Adaptive Analysis of Visual Cognition using Genetic Algorithms
Cook, Robert G.; Qadri, Muhammad A. J.
2014-01-01
Two experiments used a novel, open-ended, and adaptive test procedure to examine visual cognition in animals. Using a genetic algorithm, a pigeon was tested repeatedly from a variety of different initial conditions for its solution to an intermediate brightness search task. On each trial, the animal had to accurately locate and peck a target element of intermediate brightness from among a variable number of surrounding darker and lighter distractor elements. Displays were generated from six parametric variables, or genes (distractor number, element size, shape, spacing, target brightness, distractor brightness). Display composition changed over time, or evolved, as a function of the bird’s differential accuracy within the population of values for each gene. Testing three randomized initial conditions and one set of controlled initial conditions, element size and number of distractors were identified as the most important factors controlling search accuracy, with distractor brightness, element shape, and spacing making secondary contributions. The resulting changes in this multidimensional stimulus space suggested the existence of a set of conditions that the bird repeatedly converged upon regardless of initial conditions. This psychological “attractor” represents the cumulative action of the cognitive operations used by the pigeon in solving and performing this search task. The results are discussed regarding their implications for visual cognition in pigeons and the usefulness of adaptive, subject-driven experimentation for investigating human and animal cognition more generally. PMID:24000905
NASA Technical Reports Server (NTRS)
Messaro. Semma; Harrison, Phillip
2010-01-01
Ares I Zonal Random vibration environments due to acoustic impingement and combustion processes are develop for liftoff, ascent and reentry. Random Vibration test criteria for Ares I Upper Stage pyrotechnic components are developed by enveloping the applicable zonal environments where each component is located. Random vibration tests will be conducted to assure that these components will survive and function appropriately after exposure to the expected vibration environments. Methodology: Random Vibration test criteria for Ares I Upper Stage pyrotechnic components were desired that would envelope all the applicable environments where each component was located. Applicable Ares I Vehicle drawings and design information needed to be assessed to determine the location(s) for each component on the Ares I Upper Stage. Design and test criteria needed to be developed by plotting and enveloping the applicable environments using Microsoft Excel Spreadsheet Software and documenting them in a report Using Microsoft Word Processing Software. Conclusion: Random vibration liftoff, ascent, and green run design & test criteria for the Upper Stage Pyrotechnic Components were developed by using Microsoft Excel to envelope zonal environments applicable to each component. Results were transferred from Excel into a report using Microsoft Word. After the report is reviewed and edited by my mentor it will be submitted for publication as an attachment to a memorandum. Pyrotechnic component designers will extract criteria from my report for incorporation into the design and test specifications for components. Eventually the hardware will be tested to the environments I developed to assure that the components will survive and function appropriately after exposure to the expected vibration environments.
Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive managem...
ERIC Educational Resources Information Center
Kenney, Linda Chion
2003-01-01
Will the stealth superintendent hunt in Cincinnati become tomorrow's standard approach? Search consultants and superintendents offer their views on how far confidentiality should go. Also includes a search firm's process for shielding identities and a confidentiality pledge. (MLF)
ERIC Educational Resources Information Center
Jacso, Peter
2002-01-01
Explains desktop metasearch engines, which search the databases of several search engines simultaneously. Reviews two particular versions, the Copernic 2001 Pro and the BullsEye Pro 3, comparing costs, subject categories, display capabilities, and layout for presenting results. (LRW)
Ginsberg, M.L.
1996-12-31
We introduce a new form of game search called partition search that incorporates dependency analysis, allowing substantial reductions in the portion of the tree that needs to be expanded. Both theoretical results and experimental data are presented. For the game of bridge, partition search provides approximately as much of an improvement over existing methods as {alpha}-{beta} pruning provides over minimax.
ERIC Educational Resources Information Center
School Library Media Activities Monthly, 2000
2000-01-01
Describes an activity for young children that helps them conduct subject searches using an automated system that allows customization of access to a library's collection. Explains a timed game that makes use of subject searching and word searching on the topic of dinosaurs. (LRW)
ERIC Educational Resources Information Center
Zirkel, Perry A.
2000-01-01
In a federal case involving a vice-principal's pat-down search of middle-school students in a cafeteria (for a missing pizza knife), the court upheld the search, saying it was relatively unintrusive and met "TLO's" reasonable-suspicion standards. Principals need reasonable justification for searching a group. (Contains 18 references.) (MLH)
NASA Astrophysics Data System (ADS)
Tapiero, Charles S.; Vallois, Pierre
2016-11-01
The premise of this paper is that a fractional probability distribution is based on fractional operators and the fractional (Hurst) index used that alters the classical setting of random variables. For example, a random variable defined by its density function might not have a fractional density function defined in its conventional sense. Practically, it implies that a distribution's granularity defined by a fractional kernel may have properties that differ due to the fractional index used and the fractional calculus applied to define it. The purpose of this paper is to consider an application of fractional calculus to define the fractional density function of a random variable. In addition, we provide and prove a number of results, defining the functional forms of these distributions as well as their existence. In particular, we define fractional probability distributions for increasing and decreasing functions that are right continuous. Examples are used to motivate the usefulness of a statistical approach to fractional calculus and its application to economic and financial problems. In conclusion, this paper is a preliminary attempt to construct statistical fractional models. Due to the breadth and the extent of such problems, this paper may be considered as an initial attempt to do so.
Pearl, J.
1983-01-01
This work is comprised of articles which are representative of current research on search and heuristics. The general theme is the quest for understanding the workings of heuristic knowledge; how it is acquired, stored and used by people, how it can be represented and utilized by machines and what makes one heuristic succeed where others fail. Topics covered include the following: search and reasoning in problem solving; theory formation by heuristic search; the nature of heuristics II: background and examples; Eurisko: a program that learns new heuristics and domain concepts; the nature of heuristics III: program design and results; searching for an optimal path in a tree with random costs; search rearrangement backtracking and polynomial average time; consistent-labeling problems and their algorithms: expected-complexities and theory-based heuristics; general branch and bound formulation for understanding and synthesizing and/or tree search procedures; a minimax algorithm better than alpha-beta. yes and no; and pathology on game trees revisited, and an alternative to minimaxing.
Hunt, R.L.
1983-12-27
An adapter is disclosed for use with a fireplace. The stove pipe of a stove standing in a room to be heated may be connected to the flue of the chimney so that products of combustion from the stove may be safely exhausted through the flue and outwardly of the chimney. The adapter may be easily installed within the fireplace by removing the damper plate and fitting the adapter to the damper frame. Each of a pair of bolts has a portion which hooks over a portion of the damper frame and a threaded end depending from the hook portion and extending through a hole in the adapter. Nuts are threaded on the bolts and are adapted to force the adapter into a tight fit with the adapter frame.
A hybrid search algorithm for swarm robots searching in an unknown environment.
Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao
2014-01-01
This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency. PMID:25386855
A Hybrid Search Algorithm for Swarm Robots Searching in an Unknown Environment
Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao
2014-01-01
This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency. PMID:25386855
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 2 2011-07-01 2011-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 28 Judicial Administration 2 2014-07-01 2014-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 28 Judicial Administration 2 2012-07-01 2012-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 28 Judicial Administration 2 2010-07-01 2010-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 28 Judicial Administration 2 2013-07-01 2013-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.
2008-01-01
Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485
NASA Astrophysics Data System (ADS)
Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang
2016-09-01
Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.
Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang
2016-01-01
Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests. PMID:27666514
ERIC Educational Resources Information Center
Harrell, William
1999-01-01
Provides information on various adaptive technology resources available to people with disabilities. (Contains 19 references, an annotated list of 129 websites, and 12 additional print resources.) (JOW)
Anstis, Stuart
2013-01-01
It is known that adaptation to a disk that flickers between black and white at 3-8 Hz on a gray surround renders invisible a congruent gray test disk viewed afterwards. This is contrast adaptation. We now report that adapting simply to the flickering circular outline of the disk can have the same effect. We call this "contour adaptation." This adaptation does not transfer interocularly, and apparently applies only to luminance, not color. One can adapt selectively to only some of the contours in a display, making only these contours temporarily invisible. For instance, a plaid comprises a vertical grating superimposed on a horizontal grating. If one first adapts to appropriate flickering vertical lines, the vertical components of the plaid disappears and it looks like a horizontal grating. Also, we simulated a Cornsweet (1970) edge, and we selectively adapted out the subjective and objective contours of a Kanisza (1976) subjective square. By temporarily removing edges, contour adaptation offers a new technique to study the role of visual edges, and it demonstrates how brightness information is concentrated in edges and propagates from them as it fills in surfaces.
Is random access memory random?
NASA Technical Reports Server (NTRS)
Denning, P. J.
1986-01-01
Most software is contructed on the assumption that the programs and data are stored in random access memory (RAM). Physical limitations on the relative speeds of processor and memory elements lead to a variety of memory organizations that match processor addressing rate with memory service rate. These include interleaved and cached memory. A very high fraction of a processor's address requests can be satified from the cache without reference to the main memory. The cache requests information from main memory in blocks that can be transferred at the full memory speed. Programmers who organize algorithms for locality can realize the highest performance from these computers.
Searching strategies in Dictyostelium
NASA Astrophysics Data System (ADS)
Li, Liang; Cox, Edward
2007-03-01
Levy walks are known to be the best strategy for optimizing non-destructive search times, while an intermittent two-state searching process optimizes the destructive case. Here we ask about hunting strategy in Dictyostelium amoebae when they cannot know where their food is. We show that correlated random walks with two typical correlation time scales bias their search, improving the search outcome. Further analysis indicates that cell trajectories consist of runs and turns. Strikingly, amoebae remember the last turn, and have a strong turning preference away from the last turn. Autocorrelation analysis of turn sequences indicates that this tendency does not persist beyond the nth+1 turn. Computer simulations reveal that this bias contributes to the longer of the two correlation times. The search rules are essentially the same when cells are continuously stimulated by cAMP, with different persistence times and lengths. Interestingly, new pseudopods form in an orientation opposite to the following turn. One of the correlation timescales is approximately 30 seconds in all cases, thus indicating a short-lived cellular process, while the other is 9 to 15 minutes suggesting a process sensitive to external signals, perhaps pseudopod extensions during turning.
Foraging search: Prototypical intelligence
NASA Astrophysics Data System (ADS)
Mobus, George
2000-05-01
We think because we eat. Or as Descartes might have said, on a little more reflection, "I need to eat, therefore I think." Animals that forage for a living repeatedly face the problem of searching for a sparsely distributed resource in a vast space. Furthermore, the resource may occur sporadically and episodically under conditions of true uncertainty (nonstationary, complex and non-linear dynamics). I assert that this problem is the canonical problem solved by intelligence. It's solution is the basis for the evolution of more advanced intelligence in which the space of search includes that of concepts (objects and relations) encoded in cortical structures. In humans the conscious experience of searching through concept space we call thinking. The foraging search model is based upon a higher-order autopoeitic system (the forager) employing anticipatory processing to enhance its success at finding food while avoiding becoming food or having accidents in a hostile world. I present a semi-formal description of the general foraging search problem and an approach to its solution. The latter is a brain-like structure employing dynamically adaptive neurons. A physical robot, MAVRIC, embodies some principles of foraging. It learns cues that lead to improvements in finding targets in a dynamic and nonstationary environment. This capability is based on a unique learning mechanism that encodes causal relations in the neural-like processing element. An argument is advanced that searching for resources in the physical world, as per the foraging model, is a prototype for generalized search for conceptual resources as when we think. A problem represents a conceptual disturbance in a homeostatic sense. The finding of a solution restores the homeostatic balance. The establishment of links between conceptual cues and solutions (resources) and the later use of those cues to think through to solutions of quasi-isomorphic problems is, essentially, foraging for ideas. It is a quite
NASA Astrophysics Data System (ADS)
Kinzig, Ann P.
2015-03-01
This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.
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.…
ERIC Educational Resources Information Center
Haskin, David
1997-01-01
Compares six leading Web search engines (AltaVista, Excite, HotBot, Infoseek, Lycos, and Northern Light), looking at the breadth of their coverage, accuracy, and ease of use, and finds a clear favorite of the six. Includes tips that can improve search results. (AEF)
Chan, Louis K H; Hayward, William G
2013-07-01
Visual search is the act of looking for a predefined target among other objects. This task has been widely used as an experimental paradigm to study visual attention, and because of its influence has also become a subject of research itself. When used as a paradigm, visual search studies address questions including the nature, function, and limits of preattentive processing and focused attention. As a subject of research, visual search studies address the role of memory in search, the procedures involved in search, and factors that affect search performance. In this article, we review major theories of visual search, the ways in which preattentive information is used to guide attentional allocation, the role of memory, and the processes and decisions involved in its successful completion. We conclude by summarizing the current state of knowledge about visual search and highlight some unresolved issues. WIREs Cogn Sci 2013, 4:415-429. doi: 10.1002/wcs.1235 The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.
Adaptive clinical trial designs in oncology
Zang, Yong; Lee, J. Jack
2015-01-01
Adaptive designs have become popular in clinical trial and drug development. Unlike traditional trial designs, adaptive designs use accumulating data to modify the ongoing trial without undermining the integrity and validity of the trial. As a result, adaptive designs provide a flexible and effective way to conduct clinical trials. The designs have potential advantages of improving the study power, reducing sample size and total cost, treating more patients with more effective treatments, identifying efficacious drugs for specific subgroups of patients based on their biomarker profiles, and shortening the time for drug development. In this article, we review adaptive designs commonly used in clinical trials and investigate several aspects of the designs, including the dose-finding scheme, interim analysis, adaptive randomization, biomarker-guided randomization, and seamless designs. For illustration, we provide examples of real trials conducted with adaptive designs. We also discuss practical issues from the perspective of using adaptive designs in oncology trials. PMID:25811018
Evolutionary pattern search algorithms
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimental analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.
Fast Randomized STDMA Link Scheduling
NASA Astrophysics Data System (ADS)
Gomez, Sergio; Gras, Oriol; Friderikos, Vasilis
In this paper a fast randomized parallel link swap based packing (RSP) algorithm for timeslot allocation in a spatial time division multiple access (STDMA) wireless mesh network is presented. The proposed randomized algorithm extends several greedy scheduling algorithms that utilize the physical interference model by applying a local search that leads to a substantial improvement in the spatial timeslot reuse. Numerical simulations reveal that compared to previously scheduling schemes the proposed randomized algorithm can achieve a performance gain of up to 11%. A significant benefit of the proposed scheme is that the computations can be parallelized and therefore can efficiently utilize commoditized and emerging multi-core and/or multi-CPU processors.
NASA Astrophysics Data System (ADS)
Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.
2015-09-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C →U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.
Mak, Chi H; Pham, Phuong; Afif, Samir A; Goodman, Myron F
2015-09-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C→U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.
Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.
2015-01-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C → U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics. PMID:26465508
Mak, Chi H; Pham, Phuong; Afif, Samir A; Goodman, Myron F
2015-09-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C→U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics. PMID:26465508
Begin: Online Database Searching Now!
ERIC Educational Resources Information Center
Lodish, Erica K.
1986-01-01
Because of the increasing importance of online databases, school library media specialists are encouraged to introduce students to online searching. Four books that would help media specialists gain a basic background are reviewed and it is noted that although they are very technical, they can be adapted to individual needs. (EM)
ERIC Educational Resources Information Center
Exceptional Parent, 1987
1987-01-01
Suggestions are presented for helping disabled individuals learn to use or adapt toothbrushes for proper dental care. A directory lists dental health instructional materials available from various organizations. (CB)
Search and Seizure in the Schools
ERIC Educational Resources Information Center
Staros, Kari; Williams, Charles F.
2007-01-01
The Fourth Amendment to the U.S. Constitution protects the people of the United States from unreasonable searches and seizures. On first reading, these protections seem clearly defined. The amendment was meant to protect Americans from the kinds of random searches and seizures that the colonists experienced under British colonial rule. Under…
NASA Astrophysics Data System (ADS)
Knepper, Margaret M.; Fox, Kevin L.; Frieder, Ophir
Information overload is now a reality. We no longer worry about obtaining a sufficient volume of data; we now are concerned with sifting and understanding the massive volumes of data available to us. To do so, we developed an integrated information processing toolkit that provides the user with a variety of ways to view their information. The views include keyword search results, a domain specific ranking system that allows for adaptively capturing topic vocabularies to customize and focus the search results, navigation pages for browsing, and a geospatial and temporal component to visualize results in time and space, and provide “what if” scenario playing. Integrating the information from different tools and sources gives the user additional information and another way to analyze the data. An example of the integration is illustrated on reports of the avian influenza (bird flu).
NASA Technical Reports Server (NTRS)
2005-01-01
The goal of this research is to develop and demonstrate innovative adaptive seal technologies that can lead to dramatic improvements in engine performance, life, range, and emissions, and enhance operability for next generation gas turbine engines. This work is concentrated on the development of self-adaptive clearance control systems for gas turbine engines. Researchers have targeted the high-pressure turbine (HPT) blade tip seal location for following reasons: Current active clearance control (ACC) systems (e.g., thermal case-cooling schemes) cannot respond to blade tip clearance changes due to mechanical, thermal, and aerodynamic loads. As such they are prone to wear due to the required tight running clearances during operation. Blade tip seal wear (increased clearances) reduces engine efficiency, performance, and service life. Adaptive sealing technology research has inherent impact on all envisioned 21st century propulsion systems (e.g. distributed vectored, hybrid and electric drive propulsion concepts).
Clinician Search Behaviors May Be Influenced by Search Engine Design
Coiera, Enrico; Zrimec, Tatjana; Compton, Paul
2010-01-01
Background Searching the Web for documents using information retrieval systems plays an important part in clinicians’ practice of evidence-based medicine. While much research focuses on the design of methods to retrieve documents, there has been little examination of the way different search engine capabilities influence clinician search behaviors. Objectives Previous studies have shown that use of task-based search engines allows for faster searches with no loss of decision accuracy compared with resource-based engines. We hypothesized that changes in search behaviors may explain these differences. Methods In all, 75 clinicians (44 doctors and 31 clinical nurse consultants) were randomized to use either a resource-based or a task-based version of a clinical information retrieval system to answer questions about 8 clinical scenarios in a controlled setting in a university computer laboratory. Clinicians using the resource-based system could select 1 of 6 resources, such as PubMed; clinicians using the task-based system could select 1 of 6 clinical tasks, such as diagnosis. Clinicians in both systems could reformulate search queries. System logs unobtrusively capturing clinicians’ interactions with the systems were coded and analyzed for clinicians’ search actions and query reformulation strategies. Results The most frequent search action of clinicians using the resource-based system was to explore a new resource with the same query, that is, these clinicians exhibited a “breadth-first” search behaviour. Of 1398 search actions, clinicians using the resource-based system conducted 401 (28.7%, 95% confidence interval [CI] 26.37-31.11) in this way. In contrast, the majority of clinicians using the task-based system exhibited a “depth-first” search behavior in which they reformulated query keywords while keeping to the same task profiles. Of 585 search actions conducted by clinicians using the task-based system, 379 (64.8%, 95% CI 60.83-68.55) were
Optimal search behavior and classic foraging theory
NASA Astrophysics Data System (ADS)
Bartumeus, F.; Catalan, J.
2009-10-01
Random walk methods and diffusion theory pervaded ecological sciences as methods to analyze and describe animal movement. Consequently, statistical physics was mostly seen as a toolbox rather than as a conceptual framework that could contribute to theory on evolutionary biology and ecology. However, the existence of mechanistic relationships and feedbacks between behavioral processes and statistical patterns of movement suggests that, beyond movement quantification, statistical physics may prove to be an adequate framework to understand animal behavior across scales from an ecological and evolutionary perspective. Recently developed random search theory has served to critically re-evaluate classic ecological questions on animal foraging. For instance, during the last few years, there has been a growing debate on whether search behavior can include traits that improve success by optimizing random (stochastic) searches. Here, we stress the need to bring together the general encounter problem within foraging theory, as a mean for making progress in the biological understanding of random searching. By sketching the assumptions of optimal foraging theory (OFT) and by summarizing recent results on random search strategies, we pinpoint ways to extend classic OFT, and integrate the study of search strategies and its main results into the more general theory of optimal foraging.
Allen, Craig R.; Garmestani, Ahjond S.
2015-01-01
Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive management has explicit structure, including a careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. The process is iterative, and serves to reduce uncertainty, build knowledge and improve management over time in a goal-oriented and structured process.
How to Do Random Allocation (Randomization)
Shin, Wonshik
2014-01-01
Purpose To explain the concept and procedure of random allocation as used in a randomized controlled study. Methods We explain the general concept of random allocation and demonstrate how to perform the procedure easily and how to report it in a paper. PMID:24605197
Bremer, P. -T.
2014-08-26
ADAPT is a topological analysis code that allow to compute local threshold, in particular relevance based thresholds for features defined in scalar fields. The initial target application is vortex detection but the software is more generally applicable to all threshold based feature definitions.
ERIC Educational Resources Information Center
Boring, Michael R.
This guide is intended to be a tool to help those involved in the superintendent selection process. Section titles reflect the guide's contents. "The Decision to Seek a Superintendent"; "The Case for Using a Search Consultant"; "Setting a Timeline"; "Involvement of Parents, Citizens, Students and Staff"; "Describing the Person Sought and the…
Randomized selection on the GPU
Monroe, Laura Marie; Wendelberger, Joanne R; Michalak, Sarah E
2011-01-13
We implement here a fast and memory-sparing probabilistic top N selection algorithm on the GPU. To our knowledge, this is the first direct selection in the literature for the GPU. The algorithm proceeds via a probabilistic-guess-and-chcck process searching for the Nth element. It always gives a correct result and always terminates. The use of randomization reduces the amount of data that needs heavy processing, and so reduces the average time required for the algorithm. Probabilistic Las Vegas algorithms of this kind are a form of stochastic optimization and can be well suited to more general parallel processors with limited amounts of fast memory.
NASA Technical Reports Server (NTRS)
Hacker, Scott C. (Inventor); Dean, Richard J. (Inventor); Burge, Scott W. (Inventor); Dartez, Toby W. (Inventor)
2007-01-01
An adapter for installing a connector to a terminal post, wherein the connector is attached to a cable, is presented. In an embodiment, the adapter is comprised of an elongated collet member having a longitudinal axis comprised of a first collet member end, a second collet member end, an outer collet member surface, and an inner collet member surface. The inner collet member surface at the first collet member end is used to engage the connector. The outer collet member surface at the first collet member end is tapered for a predetermined first length at a predetermined taper angle. The collet includes a longitudinal slot that extends along the longitudinal axis initiating at the first collet member end for a predetermined second length. The first collet member end is formed of a predetermined number of sections segregated by a predetermined number of channels and the longitudinal slot.
NASA Astrophysics Data System (ADS)
Odriozola, Iñigo; Lazkano, Elena; Sierra, Basi
2011-10-01
This paper investigates the improvement of the Vector Field Histogram (VFH) local planning algorithm for mobile robot systems. The Adaptive Vector Field Histogram (AVFH) algorithm has been developed to improve the effectiveness of the traditional VFH path planning algorithm overcoming the side effects of using static parameters. This new algorithm permits the adaptation of planning parameters for the different type of areas in an environment. Genetic Algorithms are used to fit the best VFH parameters to each type of sector and, afterwards, every section in the map is labelled with the sector-type which best represents it. The Player/Stage simulation platform has been chosen for making all sort of tests and to prove the new algorithm's adequateness. Even though there is still much work to be carried out, the developed algorithm showed good navigation properties and turned out to be softer and more effective than the traditional VFH algorithm.
Watson, B.L.; Aeby, I.
1980-08-26
An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.
Watson, Bobby L.; Aeby, Ian
1982-01-01
An adaptive data compression device for compressing data having variable frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.
Adaptive Dynamic Bayesian Networks
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
NASA Astrophysics Data System (ADS)
Barton, P.
1987-04-01
The basic principles of adaptive antennas are outlined in terms of the Wiener-Hopf expression for maximizing signal to noise ratio in an arbitrary noise environment; the analogy with generalized matched filter theory provides a useful aid to understanding. For many applications, there is insufficient information to achieve the above solution and thus non-optimum constrained null steering algorithms are also described, together with a summary of methods for preventing wanted signals being nulled by the adaptive system. The three generic approaches to adaptive weight control are discussed; correlation steepest descent, weight perturbation and direct solutions based on sample matrix conversion. The tradeoffs between hardware complexity and performance in terms of null depth and convergence rate are outlined. The sidelobe cancellor technique is described. Performance variation with jammer power and angular distribution is summarized and the key performance limitations identified. The configuration and performance characteristics of both multiple beam and phase scan array antennas are covered, with a brief discussion of performance factors.
Signatures of active and passive optimized Lévy searching in jellyfish.
Reynolds, Andy M
2014-10-01
Some of the strongest empirical support for Lévy search theory has come from telemetry data for the dive patterns of marine predators (sharks, bony fishes, sea turtles and penguins). The dive patterns of the unusually large jellyfish Rhizostoma octopus do, however, sit outside of current Lévy search theory which predicts that a single search strategy is optimal. When searching the water column, the movement patterns of these jellyfish change over time. Movement bouts can be approximated by a variety of Lévy and Brownian (exponential) walks. The adaptive value of this variation is not known. On some occasions movement pattern data are consistent with the jellyfish prospecting away from a preferred depth, not finding an improvement in conditions elsewhere and so returning to their original depth. This 'bounce' behaviour also sits outside of current Lévy walk search theory. Here, it is shown that the jellyfish movement patterns are consistent with their using optimized 'fast simulated annealing'--a novel kind of Lévy walk search pattern--to locate the maximum prey concentration in the water column and/or to locate the strongest of many olfactory trails emanating from more distant prey. Fast simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a large search space. This new finding shows that the notion of active optimized Lévy walk searching is not limited to the search for randomly and sparsely distributed resources, as previously thought, but can be extended to embrace other scenarios, including that of the jellyfish R. octopus. In the presence of convective currents, it could become energetically favourable to search the water column by riding the convective currents. Here, it is shown that these passive movements can be represented accurately by Lévy walks of the type occasionally seen in R. octopus. This result vividly illustrates that Lévy walks are not necessarily
Efficient search of multiple types of targets
NASA Astrophysics Data System (ADS)
Wosniack, M. E.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2015-12-01
Random searches often take place in fragmented landscapes. Also, in many instances like animal foraging, significant benefits to the searcher arise from visits to a large diversity of patches with a well-balanced distribution of targets found. Up to date, such aspects have been widely ignored in the usual single-objective analysis of search efficiency, in which one seeks to maximize just the number of targets found per distance traversed. Here we address the problem of determining the best strategies for the random search when these multiple-objective factors play a key role in the process. We consider a figure of merit (efficiency function), which properly "scores" the mentioned tasks. By considering random walk searchers with a power-law asymptotic Lévy distribution of step lengths, p (ℓ ) ˜ℓ-μ , with 1 <μ ≤3 , we show that the standard optimal strategy with μopt≈2 no longer holds universally. Instead, optimal searches with enhanced superdiffusivity emerge, including values as low as μopt≈1.3 (i.e., tending to the ballistic limit). For the general theory of random search optimization, our findings emphasize the necessity to correctly characterize the multitude of aims in any concrete metric to compare among possible candidates to efficient strategies. In the context of animal foraging, our results might explain some empirical data pointing to stronger superdiffusion (μ <2 ) in the search behavior of different animal species, conceivably associated to multiple goals to be achieved in fragmented landscapes.
Random broadcast on random geometric graphs
Bradonjic, Milan; Elsasser, Robert; Friedrich, Tobias
2009-01-01
In this work, we consider the random broadcast time on random geometric graphs (RGGs). The classic random broadcast model, also known as push algorithm, is defined as: starting with one informed node, in each succeeding round every informed node chooses one of its neighbors uniformly at random and informs it. We consider the random broadcast time on RGGs, when with high probability: (i) RGG is connected, (ii) when there exists the giant component in RGG. We show that the random broadcast time is bounded by {Omicron}({radical} n + diam(component)), where diam(component) is a diameter of the entire graph, or the giant component, for the regimes (i), or (ii), respectively. In other words, for both regimes, we derive the broadcast time to be {Theta}(diam(G)), which is asymptotically optimal.
Markov random field surface reconstruction.
Paulsen, Rasmus R; Baerentzen, Jakob Andreas; Larsen, Rasmus
2010-01-01
A method for implicit surface reconstruction is proposed. The novelty in this paper is the adaptation of Markov Random Field regularization of a distance field. The Markov Random Field formulation allows us to integrate both knowledge about the type of surface we wish to reconstruct (the prior) and knowledge about data (the observation model) in an orthogonal fashion. Local models that account for both scene-specific knowledge and physical properties of the scanning device are described. Furthermore, how the optimal distance field can be computed is demonstrated using conjugate gradients, sparse Cholesky factorization, and a multiscale iterative optimization scheme. The method is demonstrated on a set of scanned human heads and, both in terms of accuracy and the ability to close holes, the proposed method is shown to have similar or superior performance when compared to current state-of-the-art algorithms.
Peters, Krisztian
2009-11-01
We present the status and prospects of Higgs searches at the Tevatron and the LHC. Results from the Tevatron are using up to 5 fb{sup -} of data collected with the CDF and D0 detectors. The major contributing processes include associated production (WH {yields} l{nu}bb, ZH {yields} {nu}{nu}bb, ZH {yields} llbb) and gluon fusion (gg {yields} H {yields} WW{sup (*)}). Improvements across the full mass range resulting from the larger data sets, improved analyses techniques and increased signal acceptance are discussed. Recent results exclude the SM Higgs boson in a mass range of 160 < m{sub H} < 170 GeV. Searches for the neutral MSSM Higgs boson in the region 90 < m{sub A} < 200 GeV exclude tan {beta} values down to 30 for several benchmark scenarios.
A Search Model for Imperfectly Detected Targets
NASA Technical Reports Server (NTRS)
Ahumada, Albert
2012-01-01
Under the assumptions that 1) the search region can be divided up into N non-overlapping sub-regions that are searched sequentially, 2) the probability of detection is unity if a sub-region is selected, and 3) no information is available to guide the search, there are two extreme case models. The search can be done perfectly, leading to a uniform distribution over the number of searches required, or the search can be done with no memory, leading to a geometric distribution for the number of searches required with a success probability of 1/N. If the probability of detection P is less than unity, but the search is done otherwise perfectly, the searcher will have to search the N regions repeatedly until detection occurs. The number of searches is thus the sum two random variables. One is N times the number of full searches (a geometric distribution with success probability P) and the other is the uniform distribution over the integers 1 to N. The first three moments of this distribution were computed, giving the mean, standard deviation, and the kurtosis of the distribution as a function of the two parameters. The model was fit to the data presented last year (Ahumada, Billington, & Kaiwi, 2 required to find a single pixel target on a simulated horizon. The model gave a good fit to the three moments for all three observers.
Quantumness, Randomness and Computability
NASA Astrophysics Data System (ADS)
Solis, Aldo; Hirsch, Jorge G.
2015-06-01
Randomness plays a central role in the quantum mechanical description of our interactions. We review the relationship between the violation of Bell inequalities, non signaling and randomness. We discuss the challenge in defining a random string, and show that algorithmic information theory provides a necessary condition for randomness using Borel normality. We close with a view on incomputablity and its implications in physics.
Borg: an auto-adaptive many-objective evolutionary computing framework.
Hadka, David; Reed, Patrick
2013-01-01
This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-objective, multimodal optimization. The Borg MOEA combines ε-dominance, a measure of convergence speed named ε-progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization framework. A comparative study on 33 instances of 18 test problems from the DTLZ, WFG, and CEC 2009 test suites demonstrates Borg meets or exceeds six state of the art MOEAs on the majority of the tested problems. The performance for each test problem is evaluated using a 1,000 point Latin hypercube sampling of each algorithm's feasible parameterization space. The statistical performance of every sampled MOEA parameterization is evaluated using 50 replicate random seed trials. The Borg MOEA is not a single algorithm; instead it represents a class of algorithms whose operators are adaptively selected based on the problem. The adaptive discovery of key operators is of particular importance for benchmarking how variation operators enhance search for complex many-objective problems. PMID:22385134
Adaptive Sampling in Hierarchical Simulation
Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R
2007-07-09
We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.
Evolutionary dynamics on random structures
Fraser, S.M.; Reidys, C.M. |
1997-04-01
In this paper the authors consider the evolutionary dynamics of populations of sequences, under a process of selection at the phenotypic level of structures. They use a simple graph-theoretic representation of structures which captures well the properties of the mapping between RNA sequences and their molecular structure. Each sequence is assigned to a structure by means of a sequence-to-structure mapping. The authors make the basic assumption that every fitness landscape can be factorized through the structures. The set of all sequences that map into a particular random structure can then be modeled as a random graph in sequence space, the so-called neutral network. They analyze in detail how an evolving population searches for new structures, in particular how they switch from one neutral network to another. They verify that transitions occur directly between neutral networks, and study the effects of different population sizes and the influence of the relatedness of the structures on these transitions. In fitness landscapes where several structures exhibit high fitness, the authors then study evolutionary paths on the structural level taken by the population during its search. They present a new way of expressing structural similarities which are shown to have relevant implications for the time evolution of the population.
Randomized approximate nearest neighbors algorithm.
Jones, Peter Wilcox; Osipov, Andrei; Rokhlin, Vladimir
2011-09-20
We present a randomized algorithm for the approximate nearest neighbor problem in d-dimensional Euclidean space. Given N points {x(j)} in R(d), the algorithm attempts to find k nearest neighbors for each of x(j), where k is a user-specified integer parameter. The algorithm is iterative, and its running time requirements are proportional to T·N·(d·(log d) + k·(d + log k)·(log N)) + N·k(2)·(d + log k), with T the number of iterations performed. The memory requirements of the procedure are of the order N·(d + k). A by-product of the scheme is a data structure, permitting a rapid search for the k nearest neighbors among {x(j)} for an arbitrary point x ∈ R(d). The cost of each such query is proportional to T·(d·(log d) + log(N/k)·k·(d + log k)), and the memory requirements for the requisite data structure are of the order N·(d + k) + T·(d + N). The algorithm utilizes random rotations and a basic divide-and-conquer scheme, followed by a local graph search. We analyze the scheme's behavior for certain types of distributions of {x(j)} and illustrate its performance via several numerical examples.
Adaptive optics imaging of the retina.
Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha
2014-01-01
Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified.
Adaptive optics imaging of the retina
Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha
2014-01-01
Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified. PMID:24492503
Directed random walk with random restarts: The Sisyphus random walk
NASA Astrophysics Data System (ADS)
Montero, Miquel; Villarroel, Javier
2016-09-01
In this paper we consider a particular version of the random walk with restarts: random reset events which suddenly bring the system to the starting value. We analyze its relevant statistical properties, like the transition probability, and show how an equilibrium state appears. Formulas for the first-passage time, high-water marks, and other extreme statistics are also derived; we consider counting problems naturally associated with the system. Finally we indicate feasible generalizations useful for interpreting different physical effects.
Intermittent search process and teleportation.
Bénichou, O; Moreau, M; Suet, P-H; Voituriez, R
2007-06-21
The authors study an intermittent search process combining diffusion and "teleportation" phases in a d-dimensional spherical continuous system and in a regular lattice. The searcher alternates diffusive phases, during which targets can be discovered, and fast phases (teleportation) which randomly relocate the searcher, but do not allow for target detection. The authors show that this alternation can be favorable for minimizing the time of first discovery, and that this time can be optimized by a convenient choice of the mean waiting times of each motion phase. The optimal search strategy is explicitly derived in the continuous case and in the lattice case. Arguments are given to show that much more general intermittent motions do provide optimal search strategies in d dimensions. These results can be useful in the context of heterogeneous catalysis or in various biological examples of transport through membrane pores.
When Gravity Fails: Local Search Topology
NASA Technical Reports Server (NTRS)
Frank, Jeremy; Cheeseman, Peter; Stutz, John; Lau, Sonie (Technical Monitor)
1997-01-01
Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called {\\em plateau moves), dominate the time spent in local search. We analyze and characterize {\\em plateaus) for three different classes of randomly generated Boolean Satisfiability problems. We identify several interesting features of plateaus that impact the performance of local search algorithms. We show that local minima tend to be small but occasionally may be very large. We also show that local minima can be escaped without unsatisfying a large number of clauses, but that systematically searching for an escape route may be computationally expensive if the local minimum is large. We show that plateaus with exits, called benches, tend to be much larger than minima, and that some benches have very few exit states which local search can use to escape. We show that the solutions (i.e. global minima) of randomly generated problem instances form clusters, which behave similarly to local minima. We revisit several enhancements of local search algorithms and explain their performance in light of our results. Finally we discuss strategies for creating the next generation of local search algorithms.
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.
Adaptive noise cancellation based on beehive pattern evolutionary digital filter
NASA Astrophysics Data System (ADS)
Zhou, Xiaojun; Shao, Yimin
2014-01-01
Evolutionary digital filtering (EDF) exhibits the advantage of avoiding the local optimum problem by using cloning and mating searching rules in an adaptive noise cancellation system. However, convergence performance is restricted by the large population of individuals and the low level of information communication among them. The special beehive structure enables the individuals on neighbour beehive nodes to communicate with each other and thus enhance the information spread and random search ability of the algorithm. By introducing the beehive pattern evolutionary rules into the original EDF, this paper proposes an improved beehive pattern evolutionary digital filter (BP-EDF) to overcome the defects of the original EDF. In the proposed algorithm, a new evolutionary rule which combines competing cloning, complete cloning and assistance mating methods is constructed to enable the individuals distributed on the beehive to communicate with their neighbours. Simulation results are used to demonstrate the improved performance of the proposed algorithm in terms of convergence speed to the global optimum compared with the original methods. Experimental results also verify the effectiveness of the proposed algorithm in extracting feature signals that are contaminated by significant amounts of noise during the fault diagnosis task.
Adaptive interface for personalizing information seeking.
Narayanan, S; Koppaka, Lavanya; Edala, Narasimha; Loritz, Don; Daley, Raymond
2004-12-01
An adaptive interface autonomously adjusts its display and available actions to current goals and abilities of the user by assessing user status, system task, and the context. Knowledge content adaptability is needed for knowledge acquisition and refinement tasks. In the case of knowledge content adaptability, the requirements of interface design focus on the elicitation of information from the user and the refinement of information based on patterns of interaction. In such cases, the emphasis on adaptability is on facilitating information search and knowledge discovery. In this article, we present research on adaptive interfaces that facilitates personalized information seeking from a large data warehouse. The resulting proof-of-concept system, called source recommendation system (SRS), assists users in locating and navigating data sources in the repository. Based on the initial user query and an analysis of the content of the search results, the SRS system generates a profile of the user tailored to the individual's context during information seeking. The user profiles are refined successively and are used in progressively guiding the user to the appropriate set of sources within the knowledge base. The SRS system is implemented as an Internet browser plug-in to provide a seamless and unobtrusive, personalized experience to the users during the information search process. The rationale behind our approach, system design, empirical evaluation, and implications for research on adaptive interfaces are described in this paper.
Interrupted Visual Searches Reveal Volatile Search Memory
ERIC Educational Resources Information Center
Shen, Y. Jeremy; Jiang, Yuhong V.
2006-01-01
This study investigated memory from interrupted visual searches. Participants conducted a change detection search task on polygons overlaid on scenes. Search was interrupted by various disruptions, including unfilled delay, passive viewing of other scenes, and additional search on new displays. Results showed that performance was unaffected by…
Web Search Engines: Search Syntax and Features.
ERIC Educational Resources Information Center
Ojala, Marydee
2002-01-01
Presents a chart that explains the search syntax, features, and commands used by the 12 most widely used general Web search engines. Discusses Web standardization, expanded types of content searched, size of databases, and search engines that include both simple and advanced versions. (LRW)
NASA Astrophysics Data System (ADS)
Aziz, S.; Matott, L.
2012-12-01
The uncertain parameters of a given environmental model are often inferred from an optimization procedure that seeks to minimize discrepancies between simulated output and observed data. However, optimization search procedures can potentially yield different results across multiple calibration trials. For example, global search procedures like the genetic algorithm and simulated annealing are driven by inherent randomness that can result in variable inter-trial behavior. Despite this potential for variability in search algorithm performance, practitioners are reluctant to run multiple trials of an algorithm because of the added computational burden. As a result, estimated parameters are subject to an unrecognized source of uncertainty that could potentially bias or contaminate subsequent predictive analyses. In this study, a series of numerical experiments were performed to explore the influence of search algorithm uncertainty on parameter estimates. The experiments applied multiple trials of the simulated annealing algorithm to a suite of calibration problems involving watershed rainfall-runoff, groundwater flow, and subsurface contaminant transport. Results suggest that linking the simulated annealing algorithm with an adaptive range-reduction technique can significantly improve algorithm effectiveness while simultaneously reducing inter-trial variability. Therefore these range-reduction procedures appear to be a suitable mechanism for minimizing algorithm variance and improving the consistency of parameter estimates.
Criticality of Adaptive Control Dynamics
NASA Astrophysics Data System (ADS)
Patzelt, Felix; Pawelzik, Klaus
2011-12-01
We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.
Periodic behavior in a random environment.
Broadbent, H A
1994-04-01
Animals' tendency to search periodically in temporally random environments was studied by presenting rats with random-interval (RI) 60-s and 120-s schedules. Power spectra revealed a periodicity of responding of 20-50 s for all animals regardless of condition. A second periodicity of 5-10-s was strongest under the RI 60-s schedule. Optimality theory suggests that periodic responding is better than random responding in obtaining food sooner on average, but the theory does not account for multiple periodicities. These multiple periodicities also cannot be explained by a single-oscillator, information-processing version of scalar expectancy theory (J. Gibbon & R. M. Church, 1992) or by the behavioral theory of timing (P.R. Killeen & J. G. Fetterman, 1988). The periodicities are consistent with a connectionist version of scalar expectancy theory that has nonscalar emergent properties, including multiple periodicities that are not proportional to the rate of random events.
Adaptive firefly algorithm: parameter analysis and its application.
Cheung, Ngaam J; Ding, Xue-Ming; Shen, Hong-Bin
2014-01-01
As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm - adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem - protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise. PMID:25397812
Adaptive firefly algorithm: parameter analysis and its application.
Cheung, Ngaam J; Ding, Xue-Ming; Shen, Hong-Bin
2014-01-01
As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm - adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem - protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise.
Adaptive compressive sensing camera
NASA Astrophysics Data System (ADS)
Hsu, Charles; Hsu, Ming K.; Cha, Jae; Iwamura, Tomo; Landa, Joseph; Nguyen, Charles; Szu, Harold
2013-05-01
We have embedded Adaptive Compressive Sensing (ACS) algorithm on Charge-Coupled-Device (CCD) camera based on the simplest concept that each pixel is a charge bucket, and the charges comes from Einstein photoelectric conversion effect. Applying the manufactory design principle, we only allow altering each working component at a minimum one step. We then simulated what would be such a camera can do for real world persistent surveillance taking into account of diurnal, all weather, and seasonal variations. The data storage has saved immensely, and the order of magnitude of saving is inversely proportional to target angular speed. We did design two new components of CCD camera. Due to the matured CMOS (Complementary metal-oxide-semiconductor) technology, the on-chip Sample and Hold (SAH) circuitry can be designed for a dual Photon Detector (PD) analog circuitry for changedetection that predicts skipping or going forward at a sufficient sampling frame rate. For an admitted frame, there is a purely random sparse matrix [Φ] which is implemented at each bucket pixel level the charge transport bias voltage toward its neighborhood buckets or not, and if not, it goes to the ground drainage. Since the snapshot image is not a video, we could not apply the usual MPEG video compression and Hoffman entropy codec as well as powerful WaveNet Wrapper on sensor level. We shall compare (i) Pre-Processing FFT and a threshold of significant Fourier mode components and inverse FFT to check PSNR; (ii) Post-Processing image recovery will be selectively done by CDT&D adaptive version of linear programming at L1 minimization and L2 similarity. For (ii) we need to determine in new frames selection by SAH circuitry (i) the degree of information (d.o.i) K(t) dictates the purely random linear sparse combination of measurement data a la [Φ]M,N M(t) = K(t) Log N(t).
Accounting for correlation and compliance in cluster randomized trials.
Loeys, T; Vansteelandt, S; Goetghebeur, E
2001-12-30
This paper discusses causal inference with survival data from cluster randomized trials. It is argued that cluster randomization carries the potential for post-randomization exposures which involve differentially selective compliance between treatment arms, even for an all or nothing exposure at the individual level. Structural models can be employed to account for post-randomization exposures, but should not ignore clustering. We show how marginal modelling and random effects models allow to adapt structural estimators to account for clustering. Our findings are illustrated with data from a vitamin A trial for the prevention of infant mortality in the rural plains of Nepal. PMID:11782031
Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA
NASA Astrophysics Data System (ADS)
Hwang, Jiing-Dong; Tsai, Zhi-Ren
This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.
Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua
2014-01-01
This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341
Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua
2014-01-01
This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.
Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua
2014-01-01
This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341
Cognitive adaptation to nonmelanoma skin cancer.
Czajkowska, Zofia; Radiotis, George; Roberts, Nicole; Körner, Annett
2013-01-01
Taylor's (1983) cognitive adaptation theory posits that when people go through life transitions, such as being diagnosed with a chronic disease, they adjust to their new reality. The adjustment process revolves around three themes: search for positive meaning in the experience or optimism, attempt to regain a sense of mastery in life, as well as an effort to enhance self-esteem. In the sample of 57 patients with nonmelanoma skin cancer the Cognitive Adaptation Index successfully predicted participants' distress (p < .001) accounting for 60% of the variance and lending support for the Taylor's theory of cognitive adaptation in this population.
Cognitive adaptation to nonmelanoma skin cancer.
Czajkowska, Zofia; Radiotis, George; Roberts, Nicole; Körner, Annett
2013-01-01
Taylor's (1983) cognitive adaptation theory posits that when people go through life transitions, such as being diagnosed with a chronic disease, they adjust to their new reality. The adjustment process revolves around three themes: search for positive meaning in the experience or optimism, attempt to regain a sense of mastery in life, as well as an effort to enhance self-esteem. In the sample of 57 patients with nonmelanoma skin cancer the Cognitive Adaptation Index successfully predicted participants' distress (p < .001) accounting for 60% of the variance and lending support for the Taylor's theory of cognitive adaptation in this population. PMID:23844920
Ringed Seal Search for Global Optimization via a Sensitive Search Model.
Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar
2016-01-01
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global
Ringed Seal Search for Global Optimization via a Sensitive Search Model
Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar
2016-01-01
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global
Ringed Seal Search for Global Optimization via a Sensitive Search Model.
Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar
2016-01-01
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global
NASA Technical Reports Server (NTRS)
Erdmann, Michael
1992-01-01
This paper investigates the role of randomization in the solution of robot manipulation tasks. One example of randomization is shown by the strategy of shaking a bin holding a part in order to orient the part in a desired stable state with some high probability. Randomization can be useful for mobile robot navigation and as a means of guiding the design process.
ERIC Educational Resources Information Center
De Boeck, Paul
2008-01-01
It is common practice in IRT to consider items as fixed and persons as random. Both, continuous and categorical person parameters are most often random variables, whereas for items only continuous parameters are used and they are commonly of the fixed type, although exceptions occur. It is shown in the present article that random item parameters…
A simplified method for random vibration analysis of structures with random parameters
NASA Astrophysics Data System (ADS)
Ghienne, Martin; Blanzé, Claude
2016-09-01
Piezoelectric patches with adapted electrical circuits or viscoelastic dissipative materials are two solutions particularly adapted to reduce vibration of light structures. To accurately design these solutions, it is necessary to describe precisely the dynamical behaviour of the structure. It may quickly become computationally intensive to describe robustly this behaviour for a structure with nonlinear phenomena, such as contact or friction for bolted structures, and uncertain variations of its parameters. The aim of this work is to propose a non-intrusive reduced stochastic method to characterize robustly the vibrational response of a structure with random parameters. Our goal is to characterize the eigenspace of linear systems with dynamic properties considered as random variables. This method is based on a separation of random aspects from deterministic aspects and allows us to estimate the first central moments of each random eigenfrequency with a single deterministic finite elements computation. The method is applied to a frame with several Young's moduli modeled as random variables. This example could be expanded to a bolted structure including piezoelectric devices. The method needs to be enhanced when random eigenvalues are closely spaced. An indicator with no additional computational cost is proposed to characterize the ’’proximity” of two random eigenvalues.
On the use of the Positive and Negative Syndrome Scale in randomized clinical trials.
Nicotra, Eraldo; Casu, Gianluca; Piras, Sara; Marchese, Giorgio
2015-07-01
In the last 25 years, the Positive and Negative Syndrome Scale (PANSS) has been largely used to assess schizophrenia symptom intensity, but little information is available on how this scale was generally applied when evaluating the efficacy of schizophrenia therapies in randomized clinical trials. In the attempt to address this topic, a systematic PubMed Search was carried out using the keywords "PANSS" and "Randomized Clinical Trials". The analysis of retrieved articles highlighted that PANSS has constituted a suitable psychometric instrument to investigate the efficacy of pharmacological and non-pharmacological therapies. However, the information potentially provided by this scale was only partially reported in research articles, when characterizing the symptomatic features of patients at baseline. Furthermore, a consensus is needed to identify methodological strategies that may properly adapt PANSS-subscale structure with the symptomatic profiles of individuals enrolled in randomized controlled trials. The possibility that PANSS interview procedures and enrollment eligibility criteria may influence the symptomatic composition of patients involved in these studies is also discussed. PMID:25937460
Hybrid and adaptive meta-model-based global optimization
NASA Astrophysics Data System (ADS)
Gu, J.; Li, G. Y.; Dong, Z.
2012-01-01
As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.
SEARCH, blackbox optimization, and sample complexity
Kargupta, H.; Goldberg, D.E.
1996-05-01
The SEARCH (Search Envisioned As Relation and Class Hierarchizing) framework developed elsewhere (Kargupta, 1995; Kargupta and Goldberg, 1995) offered an alternate perspective toward blackbox optimization -- optimization in presence of little domain knowledge. The SEARCH framework investigates the conditions essential for transcending the limits of random enumerative search using a framework developed in terms of relations, classes and partial ordering. This paper presents a summary of some of the main results of that work. A closed form bound on the sample complexity in terms of the cardinality of the relation space, class space, desired quality of the solution and the reliability is presented. This also leads to the identification of the class of order-k delineable problems that can be solved in polynomial sample complexity. These results are applicable to any blackbox search algorithms, including evolutionary optimization techniques.
Adaptive evolution of molecular phenotypes
NASA Astrophysics Data System (ADS)
Held, Torsten; Nourmohammad, Armita; Lässig, Michael
2014-09-01
Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak.
Quantum random number generation
Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing
2016-06-28
Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less
Randomness in quantum mechanics - nature's ultimate cryptogram?
NASA Astrophysics Data System (ADS)
Erber, T.; Putterman, S.
1985-11-01
The possibility that a single atom irradiated by coherent light will be equivalent to an infinite computer with regard to its ability to generate random numbers is addressed. A search for unexpected patterns of order by crypt analysis of the telegraph signal generated by the on/off time of the atom's fluorescence is described. The results will provide new experimental tests of the fundamental principles of quantum theory.
Search strategy effects on PN acquisition performance. [Pseudonoise
NASA Technical Reports Server (NTRS)
Weinberg, A.
1981-01-01
The present paper focusses on 'random' and 'expanding window' PN acquisition search strategies and analytically develops the PN acquisition time statistics as functions of salient system parameters such as prediction SNR, detection and false alarm probabilities and a priori information on epoch location. The significance of this analysis is its general applicability to arbitrary postdetection processing schemes. Computed performance results account for the above salient parameters, wherein sequential detection is employed in conjunction with random and selected expanding window search strategies.
Genetic algorithms in adaptive fuzzy control
NASA Technical Reports Server (NTRS)
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
ERIC Educational Resources Information Center
Bell, Suzanne S.
1997-01-01
Provides strategies for effective Internet searches. Categorizes queries into four types and describes tools: subject lists; indexes/directories; keyword search engines; Usenet newsgroups; and special purpose search tools. Discusses the importance of deciphering information and adjusting to changes. (AEF)
Caroline Müllenbroich, M; McGhee, Ewan J; Wright, Amanda J; Anderson, Kurt I; Mathieson, Keith
2014-01-01
We have developed a nonlinear adaptive optics microscope utilizing a deformable membrane mirror (DMM) and demonstrated its use in compensating for system- and sample-induced aberrations. The optimum shape of the DMM was determined with a random search algorithm optimizing on either two photon fluorescence or second harmonic signals as merit factors. We present here several strategies to overcome photobleaching issues associated with lengthy optimization routines by adapting the search algorithm and the experimental methodology. Optimizations were performed on extrinsic fluorescent dyes, fluorescent beads loaded into organotypic tissue cultures and the intrinsic second harmonic signal of these cultures. We validate the approach of using these preoptimized mirror shapes to compile a robust look-up table that can be applied for imaging over several days and through a variety of tissues. In this way, the photon exposure to the fluorescent cells under investigation is limited to imaging. Using our look-up table approach, we show signal intensity improvement factors ranging from 1.7 to 4.1 in organotypic tissue cultures and freshly excised mouse tissue. Imaging zebrafish in vivo, we demonstrate signal improvement by a factor of 2. This methodology is easily reproducible and could be applied to many photon starved experiments, for example fluorescent life time imaging, or when photobleaching is a concern.
Adaptive Behavior for Mobile Robots
NASA Technical Reports Server (NTRS)
Huntsberger, Terrance
2009-01-01
The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.
Genetic-Algorithm Tool For Search And Optimization
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven
1995-01-01
SPLICER computer program used to solve search and optimization problems. Genetic algorithms adaptive search procedures (i.e., problem-solving methods) based loosely on processes of natural selection and Darwinian "survival of fittest." Algorithms apply genetically inspired operators to populations of potential solutions in iterative fashion, creating new populations while searching for optimal or nearly optimal solution to problem at hand. Written in Think C.
On the Use of Librarians Selection Routines in Web Search.
ERIC Educational Resources Information Center
Tsinakos, Avgoustos A.; Margaritis, Kostantinos G.
Information retrieval on the World Wide Web has a major obstacle: although data is abundant, it is unlabeled and randomly indexed. This paper discusses the implementation of a consultative Web search engine that minimizes the expertise level that is required from a user to accomplish an advanced search session. The system takes advantage of the…
ADAPTATION AND ADAPTABILITY, THE BELLEFAIRE FOLLOWUP STUDY.
ERIC Educational Resources Information Center
ALLERHAND, MELVIN E.; AND OTHERS
A RESEARCH TEAM STUDIED INFLUENCES, ADAPTATION, AND ADAPTABILITY IN 50 POORLY ADAPTING BOYS AT BELLEFAIRE, A REGIONAL CHILD CARE CENTER FOR EMOTIONALLY DISTURBED CHILDREN. THE TEAM ATTEMPTED TO GAUGE THE SUCCESS OF THE RESIDENTIAL TREATMENT CENTER IN TERMS OF THE PSYCHOLOGICAL PATTERNS AND ROLE PERFORMANCES OF THE BOYS DURING INDIVIDUAL CASEWORK…
Randomization methods in emergency setting trials: a descriptive review
Moe‐Byrne, Thirimon; Oddie, Sam; McGuire, William
2015-01-01
Background Quasi‐randomization might expedite recruitment into trials in emergency care settings but may also introduce selection bias. Methods We searched the Cochrane Library and other databases for systematic reviews of interventions in emergency medicine or urgent care settings. We assessed selection bias (baseline imbalances) in prognostic indicators between treatment groups in trials using true randomization versus trials using quasi‐randomization. Results Seven reviews contained 16 trials that used true randomization and 11 that used quasi‐randomization. Baseline group imbalance was identified in four trials using true randomization (25%) and in two quasi‐randomized trials (18%). Of the four truly randomized trials with imbalance, three concealed treatment allocation adequately. Clinical heterogeneity and poor reporting limited the assessment of trial recruitment outcomes. Conclusions We did not find strong or consistent evidence that quasi‐randomization is associated with selection bias more often than true randomization. High risk of bias judgements for quasi‐randomized emergency studies should therefore not be assumed in systematic reviews. Clinical heterogeneity across trials within reviews, coupled with limited availability of relevant trial accrual data, meant it was not possible to adequately explore the possibility that true randomization might result in slower trial recruitment rates, or the recruitment of less representative populations. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. PMID:26333419
Data Bus Adapts to Changing Traffic Level
NASA Technical Reports Server (NTRS)
Lew, Eugene; Deruiter, John; Varga, Mike
1987-01-01
Access becomes timed when collisions threaten. Two-mode scheme used to grant terminals access to data bus. Causes bus to alternate between random accessibility and controlled accessibility to optimize performance and adapt to changing data-traffic conditions. Bus is part of 100-Mb/s optical-fiber packet data system.
Hybrid foraging search: Searching for multiple instances of multiple types of target.
Wolfe, Jeremy M; Aizenman, Avigael M; Boettcher, Sage E P; Cain, Matthew S
2016-02-01
This paper introduces the "hybrid foraging" paradigm. In typical visual search tasks, observers search for one instance of one target among distractors. In hybrid search, observers search through visual displays for one instance of any of several types of target held in memory. In foraging search, observers collect multiple instances of a single target type from visual displays. Combining these paradigms, in hybrid foraging tasks observers search visual displays for multiple instances of any of several types of target (as might be the case in searching the kitchen for dinner ingredients or an X-ray for different pathologies). In the present experiment, observers held 8-64 target objects in memory. They viewed displays of 60-105 randomly moving photographs of objects and used the computer mouse to collect multiple targets before choosing to move to the next display. Rather than selecting at random among available targets, observers tended to collect items in runs of one target type. Reaction time (RT) data indicate searching again for the same item is more efficient than searching for any other targets, held in memory. Observers were trying to maximize collection rate. As a result, and consistent with optimal foraging theory, they tended to leave 25-33% of targets uncollected when moving to the next screen/patch. The pattern of RTs shows that while observers were collecting a target item, they had already begun searching memory and the visual display for additional targets, making the hybrid foraging task a useful way to investigate the interaction of visual and memory search.
Adaptive Image Denoising by Mixture Adaptation
NASA Astrophysics Data System (ADS)
Luo, Enming; Chan, Stanley H.; Nguyen, Truong Q.
2016-10-01
We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the Expectation-Maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad-hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper: First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. Experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.
Efficient search of multiple types of targets.
Wosniack, M E; Raposo, E P; Viswanathan, G M; da Luz, M G E
2015-12-01
Random searches often take place in fragmented landscapes. Also, in many instances like animal foraging, significant benefits to the searcher arise from visits to a large diversity of patches with a well-balanced distribution of targets found. Up to date, such aspects have been widely ignored in the usual single-objective analysis of search efficiency, in which one seeks to maximize just the number of targets found per distance traversed. Here we address the problem of determining the best strategies for the random search when these multiple-objective factors play a key role in the process. We consider a figure of merit (efficiency function), which properly "scores" the mentioned tasks. By considering random walk searchers with a power-law asymptotic Lévy distribution of step lengths, p(ℓ)∼ℓ(-μ), with 1<μ≤3, we show that the standard optimal strategy with μ(opt)≈2 no longer holds universally. Instead, optimal searches with enhanced superdiffusivity emerge, including values as low as μ(opt)≈1.3 (i.e., tending to the ballistic limit). For the general theory of random search optimization, our findings emphasize the necessity to correctly characterize the multitude of aims in any concrete metric to compare among possible candidates to efficient strategies. In the context of animal foraging, our results might explain some empirical data pointing to stronger superdiffusion (μ<2) in the search behavior of different animal species, conceivably associated to multiple goals to be achieved in fragmented landscapes. PMID:26764660
Intestinal adaptation after massive intestinal resection
Weale, A; Edwards, A; Bailey, M; Lear, P
2005-01-01
Patients with short bowel syndrome require long term parenteral nutrition support. However, after massive intestinal resection the intestine undergoes adaptation and nutritional autonomy may be obtained. Given that the complications of parenteral nutrition may be life threatening or result in treatment failure and the need for intestinal transplantation, a more attractive option is to wean patients off nutrition support by optimising the adaptive process. The article examines the evidence that after extensive small bowel resection adaptation occurs in humans and focuses on the factors that influence adaptation and the strategies that have been used to optimise this process. The review is based on an English language Medline search with secondary references obtained from key articles. There is evidence that adaptation occurs in humans. Adaptation is a complex process that results in response to nutrient and non-nutrient stimuli. Successful and reproducible strategies to improve adaptation remain elusive despite an abundance of experimental data. Nevertheless given the low patient survival and quality of life associated with other treatments for irreversible intestinal failure it is imperative that clinical research continues into the optimisation of the adaptation. PMID:15749794
The orientation period: essential for new registered nurses' adaptation.
Ashton, Kathleen S
2015-04-01
The purpose of this research study was to explore adaptation in new registered nurses using the Roy adaptation model as the guiding conceptual framework. This quantitative study employed a random sampling of new nurses in the state of North Carolina. Personal attributes of the new registered nurses and characteristics of their work setting were modeled with four measures considered suitable proxies for adaptation. Being in a formal orientation period significantly supported the new nurses' overall adaptation. This may represent the benefit of social support, including education, which seems to facilitate adaptation.
NASA Astrophysics Data System (ADS)
Cappellini, Valerio; Sommers, Hans-Jürgen; Bruzda, Wojciech; Życzkowski, Karol
2009-09-01
Ensembles of random stochastic and bistochastic matrices are investigated. While all columns of a random stochastic matrix can be chosen independently, the rows and columns of a bistochastic matrix have to be correlated. We evaluate the probability measure induced into the Birkhoff polytope of bistochastic matrices by applying the Sinkhorn algorithm to a given ensemble of random stochastic matrices. For matrices of order N = 2 we derive explicit formulae for the probability distributions induced by random stochastic matrices with columns distributed according to the Dirichlet distribution. For arbitrary N we construct an initial ensemble of stochastic matrices which allows one to generate random bistochastic matrices according to a distribution locally flat at the center of the Birkhoff polytope. The value of the probability density at this point enables us to obtain an estimation of the volume of the Birkhoff polytope, consistent with recent asymptotic results.
Generating random density matrices
NASA Astrophysics Data System (ADS)
Życzkowski, Karol; Penson, Karol A.; Nechita, Ion; Collins, Benoît
2011-06-01
We study various methods to generate ensembles of random density matrices of a fixed size N, obtained by partial trace of pure states on composite systems. Structured ensembles of random pure states, invariant with respect to local unitary transformations are introduced. To analyze statistical properties of quantum entanglement in bi-partite systems we analyze the distribution of Schmidt coefficients of random pure states. Such a distribution is derived in the case of a superposition of k random maximally entangled states. For another ensemble, obtained by performing selective measurements in a maximally entangled basis on a multi-partite system, we show that this distribution is given by the Fuss-Catalan law and find the average entanglement entropy. A more general class of structured ensembles proposed, containing also the case of Bures, forms an extension of the standard ensemble of structureless random pure states, described asymptotically, as N → ∞, by the Marchenko-Pastur distribution.
Randomness: Quantum versus classical
NASA Astrophysics Data System (ADS)
Khrennikov, Andrei
2016-05-01
Recent tremendous development of quantum information theory has led to a number of quantum technological projects, e.g. quantum random generators. This development had stimulated a new wave of interest in quantum foundations. One of the most intriguing problems of quantum foundations is the elaboration of a consistent and commonly accepted interpretation of a quantum state. Closely related problem is the clarification of the notion of quantum randomness and its interrelation with classical randomness. In this short review, we shall discuss basics of classical theory of randomness (which by itself is very complex and characterized by diversity of approaches) and compare it with irreducible quantum randomness. We also discuss briefly “digital philosophy”, its role in physics (classical and quantum) and its coupling to the information interpretation of quantum mechanics (QM).
Quantum random number generator
Pooser, Raphael C.
2016-05-10
A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.
Online Database Searching Workbook.
ERIC Educational Resources Information Center
Littlejohn, Alice C.; Parker, Joan M.
Designed primarily for use by first-time searchers, this workbook provides an overview of online searching. Following a brief introduction which defines online searching, databases, and database producers, five steps in carrying out a successful search are described: (1) identifying the main concepts of the search statement; (2) selecting a…
ERIC Educational Resources Information Center
Homan, Michael; Worley, Penny
This course syllabus describes methods for optimizing online searching, using as an example searching on the National Library of Medicine (NLM) online system. Four major activities considered are the online interview, query analysis and search planning, online interaction, and post-search analysis. Within the context of these activities, concepts…
Search Alternatives and Beyond
ERIC Educational Resources Information Center
Bell, Steven J.
2006-01-01
Internet search has become a routine computing activity, with regular visits to a search engine--usually Google--the norm for most people. The vast majority of searchers, as recent studies of Internet search behavior reveal, search only in the most basic of ways and fail to avail themselves of options that could easily and effortlessly improve…
Multimedia Web Searching Trends.
ERIC Educational Resources Information Center
Ozmutlu, Seda; Spink, Amanda; Ozmutlu, H. Cenk
2002-01-01
Examines and compares multimedia Web searching by Excite and FAST search engine users in 2001. Highlights include audio and video queries; time spent on searches; terms per query; ranking of the most frequently used terms; and differences in Web search behaviors of U.S. and European Web users. (Author/LRW)
Adaptive Peer Sampling with Newscast
NASA Astrophysics Data System (ADS)
Tölgyesi, Norbert; Jelasity, Márk
The peer sampling service is a middleware service that provides random samples from a large decentralized network to support gossip-based applications such as multicast, data aggregation and overlay topology management. Lightweight gossip-based implementations of the peer sampling service have been shown to provide good quality random sampling while also being extremely robust to many failure scenarios, including node churn and catastrophic failure. We identify two problems with these approaches. The first problem is related to message drop failures: if a node experiences a higher-than-average message drop rate then the probability of sampling this node in the network will decrease. The second problem is that the application layer at different nodes might request random samples at very different rates which can result in very poor random sampling especially at nodes with high request rates. We propose solutions for both problems. We focus on Newscast, a robust implementation of the peer sampling service. Our solution is based on simple extensions of the protocol and an adaptive self-control mechanism for its parameters, namely—without involving failure detectors—nodes passively monitor local protocol events using them as feedback for a local control loop for self-tuning the protocol parameters. The proposed solution is evaluated by simulation experiments.
Randomized parallel speedups for list ranking
Vishkin, U.
1987-06-01
The following problem is considered: given a linked list of length n, compute the distance of each element of the linked list from the end of the list. The problem has two standard deterministic algorithms: a linear time serial algorithm, and an O(n log n)/ rho + log n) time parallel algorithm using rho processors. The authors present a randomized parallel algorithm for the problem. The algorithm is designed for an exclusive-read exclusive-write parallel random access machine (EREW PRAM). It runs almost surely in time O(n/rho + log n log* n) using rho processors. Using a recently published parallel prefix sums algorithm the list-ranking algorithm can be adapted to run on a concurrent-read concurrent-write parallel random access machine (CRCW PRAM) almost surely in time O(n/rho + log n) using rho processors.
Dynamical analysis of Grover's search algorithm in arbitrarily high-dimensional search spaces
NASA Astrophysics Data System (ADS)
Jin, Wenliang
2016-01-01
We discuss at length the dynamical behavior of Grover's search algorithm for which all the Walsh-Hadamard transformations contained in this algorithm are exposed to their respective random perturbations inducing the augmentation of the dimension of the search space. We give the concise and general mathematical formulations for approximately characterizing the maximum success probabilities of finding a unique desired state in a large unsorted database and their corresponding numbers of Grover iterations, which are applicable to the search spaces of arbitrary dimension and are used to answer a salient open problem posed by Grover (Phys Rev Lett 80:4329-4332, 1998).
ERIC Educational Resources Information Center
Simms, Leonard J.; Clark, Lee Anna
2005-01-01
This is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With…
Enhancing Student Motivation and Learning within Adaptive Tutors
ERIC Educational Resources Information Center
Ostrow, Korinn S.
2015-01-01
My research is rooted in improving K-12 educational practice using motivational facets made possible through adaptive tutoring systems. In an attempt to isolate best practices within the science of learning, I conduct randomized controlled trials within ASSISTments, an online adaptive tutoring system that provides assistance and assessment to…
Autonomous Byte Stream Randomizer
NASA Technical Reports Server (NTRS)
Paloulian, George K.; Woo, Simon S.; Chow, Edward T.
2013-01-01
Net-centric networking environments are often faced with limited resources and must utilize bandwidth as efficiently as possible. In networking environments that span wide areas, the data transmission has to be efficient without any redundant or exuberant metadata. The Autonomous Byte Stream Randomizer software provides an extra level of security on top of existing data encryption methods. Randomizing the data s byte stream adds an extra layer to existing data protection methods, thus making it harder for an attacker to decrypt protected data. Based on a generated crypto-graphically secure random seed, a random sequence of numbers is used to intelligently and efficiently swap the organization of bytes in data using the unbiased and memory-efficient in-place Fisher-Yates shuffle method. Swapping bytes and reorganizing the crucial structure of the byte data renders the data file unreadable and leaves the data in a deconstructed state. This deconstruction adds an extra level of security requiring the byte stream to be reconstructed with the random seed in order to be readable. Once the data byte stream has been randomized, the software enables the data to be distributed to N nodes in an environment. Each piece of the data in randomized and distributed form is a separate entity unreadable on its own right, but when combined with all N pieces, is able to be reconstructed back to one. Reconstruction requires possession of the key used for randomizing the bytes, leading to the generation of the same cryptographically secure random sequence of numbers used to randomize the data. This software is a cornerstone capability possessing the ability to generate the same cryptographically secure sequence on different machines and time intervals, thus allowing this software to be used more heavily in net-centric environments where data transfer bandwidth is limited.
Adaptive optics applied to coherent anti-Stokes Raman scattering microscopy
NASA Astrophysics Data System (ADS)
Girkin, John M.; Poland, Simon P.; Wright, Amanda J.; Freudiger, Christian; Evans, Conor L.; Xie, X. Sunney
2008-02-01
We report on the use of adaptive optics in coherent anti-Stokes Raman scattering microscopy (CARS) to improve the image brightness and quality at increased optical penetration depths in biological material. The principle of the technique is to shape the incoming wavefront in such a way that it counteracts the aberrations introduced by imperfect optics and the varying refractive index of the sample. In recent years adaptive optics have been implemented in multiphoton and confocal microscopy. CARS microscopy is proving to be a powerful tool for non-invasive and label-free biomedical imaging with vibrational contrast. As the contrast mechanism is based on a 3 rd order non-linear optical process, it is highly susceptible to aberrations, thus CARS signals are commonly lost beyond the depth of ~100 μm in tissue. We demonstrate the combination of adaptive optics and CARS microscopy for deep-tissue imaging using a deformable membrane mirror. A random search optimization algorithm using the CARS intensity as the figure of merit determined the correct mirror-shape in order to correct for the aberrations. We highlight two different methods of implementation, using a look up table technique and by performing the optimizing in situ. We demonstrate a significant increase in brightness and image quality in an agarose/polystyrene-bead sample and white chicken muscle, pushing the penetration depth beyond 200 μm.
Attributional Search and Concern about the Future Following Smoking Cessation Treatment.
ERIC Educational Resources Information Center
Schoeneman, Thomas J.; And Others
Some research on attribution processes has suggested that attributional search is exploratory behavior that serves adaptation and mastery motives. This study was conducted to investigate attributional search in reactions to success and failure after quitting smoking, to look for antecedents of attributional search other than expectancy and…
Curating the Web: Building a Google Custom Search Engine for the Arts
ERIC Educational Resources Information Center
Hennesy, Cody; Bowman, John
2008-01-01
Google's first foray onto the web made search simple and results relevant. With its Co-op platform, Google has taken another step toward dramatically increasing the relevancy of search results, further adapting the World Wide Web to local needs. Google Custom Search Engine, a tool on the Co-op platform, puts one in control of his or her own search…
Potential of adaptive clinical trial designs in pharmacogenetic research.
van der Baan, Frederieke H; Knol, Mirjam J; Klungel, Olaf H; Egberts, Antoine Cg; Grobbee, Diederick E; Roes, Kit C B
2012-04-01
Adaptive trial designs can be beneficial in pharmacogenetic research when prior uncertainty exists regarding the exact role and clinical relevance of genetic variability in drug response. This type of design enables us to learn about the effect of the genetic variability on drug response and to immediately use this information for the remainder of the study. For different types of adaptive trial designs, we discuss when and how the designs are suitable for pharmacogenetic research: adaptation of randomization, adaptation of patient enrollment and adaptive enrichment. To illustrate the potential benefits of an adaptive design over a fixed design, we simulated an adaptive trial based on the results of the IPASS trial. With a simple model we show that for this example an adaptive enrichment design would have led to a smaller trial, with less EGF receptor mutation-negative patients unnecessarily exposed to the drug, without compromising the α level or reducing power. PMID:22462749
Bioinformatics: searching the Net.
Kastin, S; Wexler, J
1998-04-01
During the past 30 years, there has been an explosion in the volume of published medical information. As this volume has increased, so has the need for efficient methods for searching the data. MEDLINE, the primary medical database, is currently limited to abstracts of the medical literature. MEDLINE searches use AND/OR/NOT logical searching for keywords that have been assigned to each article and for textwords included in article abstracts. Recently, the complete text of some scientific journals, including figures and tables, has become accessible electronically. Keyword and textword searches can provide an overwhelming number of results. Search engines that use phrase searching, or searches that limit the number of words between two finds, improve the precision of search engines. The development of the Internet as a vehicle for worldwide communication, and the emergence of the World Wide Web (WWW) as a common vehicle for communication have made instantaneous access to much of the entire body of medical information an exciting possibility. There is more than one way to search the WWW for information. At the present time, two broad strategies have emerged for cataloging the WWW: directories and search engines. These allow more efficient searching of the WWW. Directories catalog WWW information by creating categories and subcategories of information and then publishing pointers to information within the category listings. Directories are analogous to yellow pages of the phone book. Search engines make no attempt to categorize information. They automatically scour the WWW looking for words and then automatically create an index of those words. When a specific search engine is used, its index is searched for a particular word. Usually, search engines are nonspecific and produce voluminous results. Use of AND/OR/NOT and "near" and "adjacent" search refinements greatly improve the results of a search. Search engines that limit their scope to specific sites, and
Contrast adaptation in the Limulus lateral eye.
Valtcheva, Tchoudomira M; Passaglia, Christopher L
2015-12-01
Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether this mechanism operates in horseshoe crab eyes, one of the best-understood neural networks in the animal kingdom. The spike trains of optic nerve fibers were recorded in response to light stimuli modulated randomly in time and delivered to single ommatidia or the whole eye. We found that the retina adapts to both the mean luminance and contrast of a white-noise stimulus, that luminance- and contrast-adaptive processes are largely independent, and that they originate within an ommatidium. Network interactions are not involved. A published computer model that simulates existing knowledge of the horseshoe crab eye did not show contrast adaptation, suggesting that a heretofore unknown mechanism may underlie the phenomenon. This mechanism does not appear to reside in photoreceptors because white-noise analysis of electroretinogram recordings did not show contrast adaptation. The likely site of origin is therefore the spike discharge mechanism of optic nerve fibers. The finding of contrast adaption in a retinal network as simple as the horseshoe crab eye underscores the broader importance of this image processing strategy to vision. PMID:26445869
Salient Distractors Can Induce Saccade Adaptation
Khan, Afsheen; McFadden, Sally A.; Wallman, Josh
2014-01-01
When saccadic eye movements consistently fail to land on their intended target, saccade accuracy is maintained by gradually adapting the movement size of successive saccades. The proposed error signal for saccade adaptation has been based on the distance between where the eye lands and the visual target (retinal error). We studied whether the error signal could alternatively be based on the distance between the predicted and actual locus of attention after the saccade. Unlike conventional adaptation experiments that surreptitiously displace the target once a saccade is initiated towards it, we instead attempted to draw attention away from the target by briefly presenting salient distractor images on one side of the target after the saccade. To test whether less salient, more predictable distractors would induce less adaptation, we separately used fixed random noise distractors. We found that both visual attention distractors were able to induce a small degree of downward saccade adaptation but significantly more to the more salient distractors. As in conventional adaptation experiments, upward adaptation was less effective and salient distractors did not significantly increase amplitudes. We conclude that the locus of attention after the saccade can act as an error signal for saccade adaptation. PMID:24876947
Adaptation to ozone: duration of effect
Horvath, S.M.; Gliner, J.A.; Folinsbee, L.J.
1981-05-01
Repeated ozone exposure induces an adaptative response whereby subsequent ozone exposure induces little or no pulmonary function change. The time course of the adaptation and the persistence of this adaptation was determined in 24 subjects. Subjects were studied for 125 min while they exercised intermittently. They were exposed to filtered air for 1 day and then in the next week for 5 consecutive days to 0.5 ppm ozone. After the fifth day, subjects were randomly assigned to return for one more ozone exposure at 1, 2, or 3 wk. The greatest decrement in FEV1 occurred on the second day of exposure. The number of consecutive ozone exposures required to produce adaptation varied from 2 to 5 days. Persistence of adaptation in ozone-sensitive subjects (initial decrease in FEV1 greater than 10%) showed marked individual variability, but the duration of adaptation was shortest for the more sensitive subjects. Adaptation, on the average, lasted for less than 2 wk, being as short as 7 days and as long as 20 days. We concluded that more sensitive subjects required more daily sequential exposures in order to adapt.
Contrast adaptation in the Limulus lateral eye.
Valtcheva, Tchoudomira M; Passaglia, Christopher L
2015-12-01
Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether this mechanism operates in horseshoe crab eyes, one of the best-understood neural networks in the animal kingdom. The spike trains of optic nerve fibers were recorded in response to light stimuli modulated randomly in time and delivered to single ommatidia or the whole eye. We found that the retina adapts to both the mean luminance and contrast of a white-noise stimulus, that luminance- and contrast-adaptive processes are largely independent, and that they originate within an ommatidium. Network interactions are not involved. A published computer model that simulates existing knowledge of the horseshoe crab eye did not show contrast adaptation, suggesting that a heretofore unknown mechanism may underlie the phenomenon. This mechanism does not appear to reside in photoreceptors because white-noise analysis of electroretinogram recordings did not show contrast adaptation. The likely site of origin is therefore the spike discharge mechanism of optic nerve fibers. The finding of contrast adaption in a retinal network as simple as the horseshoe crab eye underscores the broader importance of this image processing strategy to vision.
NASA Astrophysics Data System (ADS)
Chatterjee, Krishnendu; Doyen, Laurent; Gimbert, Hugo; Henzinger, Thomas A.
We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided complete-observation (one player has complete observation); and (c) complete-observation (both players have complete view of the game). On the basis of mode of interaction we have the following classification: (a) concurrent (players interact simultaneously); and (b) turn-based (players interact in turn). The two sources of randomness in these games are randomness in transition function and randomness in strategies. In general, randomized strategies are more powerful than deterministic strategies, and randomness in transitions gives more general classes of games. We present a complete characterization for the classes of games where randomness is not helpful in: (a) the transition function (probabilistic transition can be simulated by deterministic transition); and (b) strategies (pure strategies are as powerful as randomized strategies). As consequence of our characterization we obtain new undecidability results for these games.
Search for a small egg by spermatozoa in restricted geometries.
Yang, J; Kupka, I; Schuss, Z; Holcman, D
2016-08-01
The search by swimmers for a small target in a bounded domain is ubiquitous in cellular biology, where a prominent case is that of the search by spermatozoa for an egg in the uterus. This is one of the severest selection processes in animal reproduction. We present here a mathematical model of the search, its analysis, and numerical simulations. In the proposed model the swimmers' trajectories are rectilinear and the speed is constant. When a trajectory hits an obstacle or the boundary, it is reflected at a random angle and continues the search with the same speed. Because hitting a small target by a trajectory is a rare event, asymptotic approximations and stochastic simulations are needed to estimate the mean search time in various geometries. We consider searches in a disk, in convex planar domains, and in domains with cusps. The exploration of the parameter space for spermatozoa motion in different uterus geometries leads to scaling laws for the search process.
GeoSearcher: GeoSpatial Ranking of Search Engine Results.
ERIC Educational Resources Information Center
Watters, Carolyn; Amoudi, Ghada
2002-01-01
Discusses search engines and describes a prototype system that provides dynamic ranking of search engine results for geospatial queries based on the URL of the host site. Evaluates this approach using user queries and random Web pages, making a contribution to Web retrieval by providing an alternative ranking order for search engine results.…
Technology Transfer Automated Retrieval System (TEKTRAN)
Two types of simulation models of mass trapping were developed: (1) male-searching insects (e.g., moths and many insect species) and (2) female-searching insects (e.g., true bugs, beetles, and flies). The searching sex moved based on correlated random walks (CRW), while the opposite sex remained sta...
Second Graders Learn Animal Adaptations through Form and Function Analogy Object Boxes
ERIC Educational Resources Information Center
Rule, Audrey C.; Baldwin, Samantha; Schell, Robert
2008-01-01
This study examined the use of form and function analogy object boxes to teach second graders (n = 21) animal adaptations. The study used a pretest-posttest design to examine animal adaptation content learned through focused analogy activities as compared with reading and Internet searches for information about adaptations of animals followed by…
Broome, John
1984-10-01
This article considers what justification can be found for selecting randomly and in what circumstances it applies, including that of selecting patients to be treated by a scarce medical procedure. The author demonstrates that balancing the merits of fairness, common good, equal rights, and equal chance as they apply in various situations frequently leads to the conclusion that random selection may not be the most appropriate mode of selection. Broome acknowledges that, in the end, we may be forced to conclude that the only merit of random selection is the political one of guarding against partiality and oppression.
Kastner, Monika; Straus, Sharon; Goldsmith, Charlie H
2007-10-11
Researchers conducting systematic reviews need to search multiple bibliographic databases such as MEDLINE and EMBASE. However, researchers have no rational search stopping rule when looking for potentially-relevant articles. We empirically tested a stopping rule based on the concept of capture-mark-recapture (CMR), which was first pioneered in ecology. The principles of CMR can be adapted to systematic reviews and meta-analyses to estimate the Horizon of articles in the literature with its confidence interval. We retrospectively tested this Horizon Estimation using a systematic review of randomized controlled trials (RCTs) that evaluated clinical decision support tools for osteoporosis disease management. The Horizon Estimation was calculated based on 4 bibliographic databases that were included as the main data sources for the review in the following order: MEDLINE, EMBASE, CINAHL, and EBM Reviews. The systematic review captured 68% of known articles from the 4 data sources, which represented 592 articles that were estimated as missing from the Horizon.
Sims, David W; Humphries, Nicolas E; Bradford, Russell W; Bruce, Barry D
2012-03-01
1. Search processes play an important role in physical, chemical and biological systems. In animal foraging, the search strategy predators should use to search optimally for prey is an enduring question. Some models demonstrate that when prey is sparsely distributed, an optimal search pattern is a specialised random walk known as a Lévy flight, whereas when prey is abundant, simple Brownian motion is sufficiently efficient. These predictions form part of what has been termed the Lévy flight foraging hypothesis (LFF) which states that as Lévy flights optimise random searches, movements approximated by optimal Lévy flights may have naturally evolved in organisms to enhance encounters with targets (e.g. prey) when knowledge of their locations is incomplete. 2. Whether free-ranging predators exhibit the movement patterns predicted in the LFF hypothesis in response to known prey types and distributions, however, has not been determined. We tested this using vertical and horizontal movement data from electronic tagging of an apex predator, the great white shark Carcharodon carcharias, across widely differing habitats reflecting different prey types. 3. Individual white sharks exhibited movement patterns that predicted well the prey types expected under the LFF hypothesis. Shark movements were best approximated by Brownian motion when hunting near abundant, predictable sources of prey (e.g. seal colonies, fish aggregations), whereas movements approximating truncated Lévy flights were present when searching for sparsely distributed or potentially difficult-to-detect prey in oceanic or shelf environments, respectively. 4. That movement patterns approximated by truncated Lévy flights and Brownian behaviour were present in the predicted prey fields indicates search strategies adopted by white sharks appear to be the most efficient ones for encountering prey in the habitats where such patterns are observed. This suggests that C. carcharias appears capable of exhibiting
Sims, David W; Humphries, Nicolas E; Bradford, Russell W; Bruce, Barry D
2012-03-01
1. Search processes play an important role in physical, chemical and biological systems. In animal foraging, the search strategy predators should use to search optimally for prey is an enduring question. Some models demonstrate that when prey is sparsely distributed, an optimal search pattern is a specialised random walk known as a Lévy flight, whereas when prey is abundant, simple Brownian motion is sufficiently efficient. These predictions form part of what has been termed the Lévy flight foraging hypothesis (LFF) which states that as Lévy flights optimise random searches, movements approximated by optimal Lévy flights may have naturally evolved in organisms to enhance encounters with targets (e.g. prey) when knowledge of their locations is incomplete. 2. Whether free-ranging predators exhibit the movement patterns predicted in the LFF hypothesis in response to known prey types and distributions, however, has not been determined. We tested this using vertical and horizontal movement data from electronic tagging of an apex predator, the great white shark Carcharodon carcharias, across widely differing habitats reflecting different prey types. 3. Individual white sharks exhibited movement patterns that predicted well the prey types expected under the LFF hypothesis. Shark movements were best approximated by Brownian motion when hunting near abundant, predictable sources of prey (e.g. seal colonies, fish aggregations), whereas movements approximating truncated Lévy flights were present when searching for sparsely distributed or potentially difficult-to-detect prey in oceanic or shelf environments, respectively. 4. That movement patterns approximated by truncated Lévy flights and Brownian behaviour were present in the predicted prey fields indicates search strategies adopted by white sharks appear to be the most efficient ones for encountering prey in the habitats where such patterns are observed. This suggests that C. carcharias appears capable of exhibiting
Optimality of Spatially Inhomogeneous Search Strategies
NASA Astrophysics Data System (ADS)
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-01
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems—narrow escape, reaction partner finding, reaction escape—can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δopt along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Optimality of Spatially Inhomogeneous Search Strategies.
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-01
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems-narrow escape, reaction partner finding, reaction escape-can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δ_{opt} along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments. PMID:27541477
Randomized benchmarking in measurement-based quantum computing
NASA Astrophysics Data System (ADS)
Alexander, Rafael N.; Turner, Peter S.; Bartlett, Stephen D.
2016-09-01
Randomized benchmarking is routinely used as an efficient method for characterizing the performance of sets of elementary logic gates in small quantum devices. In the measurement-based model of quantum computation, logic gates are implemented via single-site measurements on a fixed universal resource state. Here we adapt the randomized benchmarking protocol for a single qubit to a linear cluster state computation, which provides partial, yet efficient characterization of the noise associated with the target gate set. Applying randomized benchmarking to measurement-based quantum computation exhibits an interesting interplay between the inherent randomness associated with logic gates in the measurement-based model and the random gate sequences used in benchmarking. We consider two different approaches: the first makes use of the standard single-qubit Clifford group, while the second uses recently introduced (non-Clifford) measurement-based 2-designs, which harness inherent randomness to implement gate sequences.
An efficient cuckoo search algorithm for numerical function optimization
NASA Astrophysics Data System (ADS)
Ong, Pauline; Zainuddin, Zarita
2013-04-01
Cuckoo search algorithm which reproduces the breeding strategy of the best known brood parasitic bird, the cuckoos has demonstrated its superiority in obtaining the global solution for numerical optimization problems. However, the involvement of fixed step approach in its exploration and exploitation behavior might slow down the search process considerably. In this regards, an improved cuckoo search algorithm with adaptive step size adjustment is introduced and its feasibility on a variety of benchmarks is validated. The obtained results show that the proposed scheme outperforms the standard cuckoo search algorithm in terms of convergence characteristic while preserving the fascinating features of the original method.
NASA Astrophysics Data System (ADS)
Newman, M. E. J.; Martin, Travis
2014-11-01
Random graph models have played a dominant role in the theoretical study of networked systems. The Poisson random graph of Erdős and Rényi, in particular, as well as the so-called configuration model, have served as the starting point for numerous calculations. In this paper we describe another large class of random graph models, which we call equitable random graphs and which are flexible enough to represent networks with diverse degree distributions and many nontrivial types of structure, including community structure, bipartite structure, degree correlations, stratification, and others, yet are exactly solvable for a wide range of properties in the limit of large graph size, including percolation properties, complete spectral density, and the behavior of homogeneous dynamical systems, such as coupled oscillators or epidemic models.
Luce, Bryan R; Broglio, Kristine R; Ishak, K Jack; Mullins, C Daniel; Vanness, David J; Fleurence, Rachael; Saunders, Elijah; Davis, Barry R
2013-01-01
Background Randomized clinical trials, particularly for comparative effectiveness research (CER), are frequently criticized for being overly restrictive or untimely for health-care decision making. Purpose Our prospectively designed REsearch in ADAptive methods for Pragmatic Trials (RE-ADAPT) study is a ‘proof of concept’ to stimulate investment in Bayesian adaptive designs for future CER trials. Methods We will assess whether Bayesian adaptive designs offer potential efficiencies in CER by simulating a re-execution of the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) study using actual data from ALLHAT. Results We prospectively define seven alternate designs consisting of various combinations of arm dropping, adaptive randomization, and early stopping and describe how these designs will be compared to the original ALLHAT design. We identify the one particular design that would have been executed, which incorporates early stopping and information-based adaptive randomization. Limitations While the simulation realistically emulates patient enrollment, interim analyses, and adaptive changes to design, it cannot incorporate key features like the involvement of data monitoring committee in making decisions about adaptive changes. Conclusion This article describes our analytic approach for RE-ADAPT. The next stage of the project is to conduct the re-execution analyses using the seven prespecified designs and the original ALLHAT data. PMID:23983160
Foraging in Semantic Fields: How We Search Through Memory.
Hills, Thomas T; Todd, Peter M; Jones, Michael N
2015-07-01
When searching for concepts in memory--as in the verbal fluency task of naming all the animals one can think of--people appear to explore internal mental representations in much the same way that animals forage in physical space: searching locally within patches of information before transitioning globally between patches. However, the definition of the patches being searched in mental space is not well specified. Do we search by activating explicit predefined categories (e.g., pets) and recall items from within that category (categorical search), or do we activate and recall a connected sequence of individual items without using categorical information, with each item recalled leading to the retrieval of an associated item in a stream (associative search), or both? Using semantic representations in a search of associative memory framework and data from the animal fluency task, we tested competing hypotheses based on associative and categorical search models. Associative, but not categorical, patch transitions took longer to make than position-matched productions, suggesting that categorical transitions were not true transitions. There was also clear evidence of associative search even within categorical patch boundaries. Furthermore, most individuals' behavior was best explained by an associative search model without the addition of categorical information. Thus, our results support a search process that does not use categorical information, but for which patch boundaries shift with each recall and local search is well described by a random walk in semantic space, with switches to new regions of the semantic space when the current region is depleted.
Recent advances in the dark adaptation investigations
Yang, Guo-Qing; Chen, Tao; Tao, Ye; Zhang, Zuo-Ming
2015-01-01
Dark adaptation is a highly sensitive neural function and may be the first symptom of many status including the physiologic and pathologic entity, suggesting that it could be instrumental for diagnose. However, shortcomings such as the lack of standardized parameters, the long duration of examination, and subjective randomness would substantially impede the use of dark adaptation in clinical work. In this review we summarize the recent research about the dark adaptation, including two visual cycles-canonical and cone-specific visual cycle, affecting factors and the methods for measuring dark adaptation. In the opinions of authors, intensive investigations are needed to be done for the widely use of this significant visual function in clinic. PMID:26682182
Liesefeld, Heinrich René; Moran, Rani; Usher, Marius; Müller, Hermann J; Zehetleitner, Michael
2016-06-01
Searching for an object among distracting objects is a common daily task. These searches differ in efficiency. Some are so difficult that each object must be inspected in turn, whereas others are so easy that the target object directly catches the observer's eye. In 4 experiments, the difficulty of searching for an orientation-defined target was parametrically manipulated between blocks of trials via the target-distractor orientation contrast. We observed a smooth transition from inefficient to efficient search with increasing orientation contrast. When contrast was high, search slopes were flat (indicating pop-out); when contrast was low, slopes were steep (indicating serial search). At the transition from inefficient to efficient search, search slopes were flat for target-present trials and steep for target-absent trials within the same orientation-contrast block-suggesting that participants adapted their behavior on target-absent trials to the most difficult, rather than the average, target-present trials of each block. Furthermore, even when search slopes were flat, indicative of pop-out, search continued to become faster with increasing contrast. These observations provide several new constraints for models of visual search and indicate that differences between search tasks that were traditionally considered qualitative in nature might actually be due to purely quantitative differences in target discriminability. (PsycINFO Database Record
Perl, M.L.
1984-12-01
At present we know of three kinds of neutral leptons: the electron neutrino, the muon neutrino, and the tau neutrino. This paper reviews the search for additional neutral leptons. The method and significance of a search depends upon the model used for the neutral lepton being sought. Some models for the properties and decay modes of proposed neutral leptons are described. Past and present searches are reviewed. The limits obtained by some completed searches are given, and the methods of searches in progress are described. Future searches are discussed. 41 references.
Expressing Adaptation Strategies Using Adaptation Patterns
ERIC Educational Resources Information Center
Zemirline, N.; Bourda, Y.; Reynaud, C.
2012-01-01
Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition…
Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth
2015-03-16
Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with "equivalent" 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target.
Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth
2015-01-01
Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with “equivalent” 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target. PMID:25780063
Roemmich, Ryan T; Hack, Nawaz; Akbar, Umer; Hass, Chris J
2014-07-15
Persons with Parkinson's disease (PD) are characterized by multifactorial gait deficits, though the factors which influence the abilities of persons with PD to adapt and store new gait patterns are unclear. The purpose of this study was to investigate the effects of dopaminergic therapy on the abilities of persons with PD to adapt and store gait parameters during split-belt treadmill (SBT) walking. Ten participants with idiopathic PD who were being treated with stable doses of orally-administered dopaminergic therapy participated. All participants performed two randomized testing sessions on separate days: once while optimally-medicated (ON meds) and once after 12-h withdrawal from dopaminergic medication (OFF meds). During each session, locomotor adaptation was investigated as the participants walked on a SBT for 10 min while the belts moved at a 2:1 speed ratio. We assessed locomotor adaptive learning by quantifying: (1) aftereffects during de-adaptation (once the belts returned to tied speeds immediately following SBT walking) and (2) savings during re-adaptation (as the participants repeated the same SBT walking task after washout of aftereffects following the initial SBT task). The withholding of dopaminergic medication diminished step length aftereffects significantly during de-adaptation. However, both locomotor adaptation and savings were unaffected by levodopa. These findings suggest that dopaminergic pathways influence aftereffect storage but do not influence locomotor adaptation or savings within a single session of SBT walking. It appears important that persons with PD should be optimally-medicated if walking on the SBT as gait rehabilitation.
Nasr, Ramzi; Vernica, Rares; Li, Chen; Baldi, Pierre
2012-04-23
In ligand-based screening, retrosynthesis, and other chemoinformatics applications, one often seeks to search large databases of molecules in order to retrieve molecules that are similar to a given query. With the expanding size of molecular databases, the efficiency and scalability of data structures and algorithms for chemical searches are becoming increasingly important. Remarkably, both the chemoinformatics and information retrieval communities have converged on similar solutions whereby molecules or documents are represented by binary vectors, or fingerprints, indexing their substructures such as labeled paths for molecules and n-grams for text, with the same Jaccard-Tanimoto similarity measure. As a result, similarity search methods from one field can be adapted to the other. Here we adapt recent, state-of-the-art, inverted index methods from information retrieval to speed up similarity searches in chemoinformatics. Our results show a several-fold speed-up improvement over previous methods for both threshold searches and top-K searches. We also provide a mathematical analysis that allows one to predict the level of pruning achieved by the inverted index approach and validate the quality of these predictions through simulation experiments. All results can be replicated using data freely downloadable from http://cdb.ics.uci.edu/ . PMID:22462644
Riggs, Thomas; Walts, Adrienne; Perry, Nicolas; Bickle, Laura; Lynch, Jennifer N.; Myers, Amy; Flynn, Joanne; Linderman, Jennifer J.; Miller, Mark J.; Kirschner, Denise E.
2008-01-01
Generating adaptive immunity after infection or immunization requires physical interactions within a lymph node (LN) T-zone between antigen-bearing dendritic cells (DCs) that arrive from peripheral tissues and rare cognate T cells entering via high endothelial venules (HEVs). This interaction results in activation of cognate T cells, expansion of that T cell lineage and their exit from the LN T zone via efferent lymphatics (ELs). How antigen-specific T cells locate DCs within this complex environment is controversial, and both random T cell migration and chemotaxis have been proposed. We developed an agent-based computational model of a LN that captures many features of T cell and DC dynamics observed by two-photon microscopy. Our simulations matched in vivo two-photon microscopy data regarding T cell speed, short-term directional persistence of motion and cell motility. We also obtained in vivo data regarding density of T cells and DCs within a LN and matched our model environment to measurements of the distance from HEVs to ELs. We used our model to compare chemotaxis with random motion and showed that chemotaxis increased total number of T cell DC contacts, but decreased unique contacts, producing fewer activated T cells. Our results suggest that, within a LN T-zone, a random search strategy is optimal for a rare cognate T cell to find its DC match and maximize production of activated T cells. PMID:18068193
Adaptive multiconfigurational wave functions
Evangelista, Francesco A.
2014-03-28
A method is suggested to build simple multiconfigurational wave functions specified uniquely by an energy cutoff Λ. These are constructed from a model space containing determinants with energy relative to that of the most stable determinant no greater than Λ. The resulting Λ-CI wave function is adaptive, being able to represent both single-reference and multireference electronic states. We also consider a more compact wave function parameterization (Λ+SD-CI), which is based on a small Λ-CI reference and adds a selection of all the singly and doubly excited determinants generated from it. We report two heuristic algorithms to build Λ-CI wave functions. The first is based on an approximate prescreening of the full configuration interaction space, while the second performs a breadth-first search coupled with pruning. The Λ-CI and Λ+SD-CI approaches are used to compute the dissociation curve of N{sub 2} and the potential energy curves for the first three singlet states of C{sub 2}. Special attention is paid to the issue of energy discontinuities caused by changes in the size of the Λ-CI wave function along the potential energy curve. This problem is shown to be solvable by smoothing the matrix elements of the Hamiltonian. Our last example, involving the Cu{sub 2}O{sub 2}{sup 2+} core, illustrates an alternative use of the Λ-CI method: as a tool to both estimate the multireference character of a wave function and to create a compact model space to be used in subsequent high-level multireference coupled cluster computations.
A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing
NASA Technical Reports Server (NTRS)
Takaki, Mitsuo; Cavalcanti, Diego; Gheyi, Rohit; Iyoda, Juliano; dAmorim, Marcelo; Prudencio, Ricardo
2009-01-01
The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compare the effectiveness of a symbolic solver (CVC3), a random solver, three hybrid solvers (i.e., mix of random and symbolic), and two heuristic search solvers. We evaluate the solvers on two benchmarks: one consisting of manually generated constraints and another generated with a concolic execution of 8 subjects. In addition to fully decidable constraints, the benchmarks include constraints with non-linear integer arithmetic, integer modulo and division, bitwise arithmetic, and floating-point arithmetic. As expected symbolic solving (in particular, CVC3) subsumes the other solvers for the concolic execution of subjects that only generate decidable constraints. For the remaining subjects the solvers are complementary.
Improved limited discrepancy search
Korf, R.E.
1996-12-31
We present an improvement to Harvey and Ginsberg`s limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from the root to the maximum search depth only once. For a complete binary tree of depth d this reduces the asymptotic complexity from O(d+2/2 2{sup d}) to O(2{sup d}). The savings is much less in a partial tree search, or in a heavily pruned tree. The overhead of the improved algorithm on a complete binary tree is only a factor of b/(b - 1) compared to depth-first search. While this constant factor is greater on a heavily pruned tree, this improvement makes limited discrepancy search a viable alternative to depth-first search, whenever the entire tree may not be searched. Finally, we present both positive and negative empirical results on the utility of limited discrepancy search, for the problem of number partitioning.
Randomization Methods in Emergency Setting Trials: A Descriptive Review
ERIC Educational Resources Information Center
Corbett, Mark Stephen; Moe-Byrne, Thirimon; Oddie, Sam; McGuire, William
2016-01-01
Background: Quasi-randomization might expedite recruitment into trials in emergency care settings but may also introduce selection bias. Methods: We searched the Cochrane Library and other databases for systematic reviews of interventions in emergency medicine or urgent care settings. We assessed selection bias (baseline imbalances) in prognostic…
An adaptive contextual quantum language model
NASA Astrophysics Data System (ADS)
Li, Jingfei; Zhang, Peng; Song, Dawei; Hou, Yuexian
2016-08-01
User interactions in search system represent a rich source of implicit knowledge about the user's cognitive state and information need that continuously evolves over time. Despite massive efforts that have been made to exploiting and incorporating this implicit knowledge in information retrieval, it is still a challenge to effectively capture the term dependencies and the user's dynamic information need (reflected by query modifications) in the context of user interaction. To tackle these issues, motivated by the recent Quantum Language Model (QLM), we develop a QLM based retrieval model for session search, which naturally incorporates the complex term dependencies occurring in user's historical queries and clicked documents with density matrices. In order to capture the dynamic information within users' search session, we propose a density matrix transformation framework and further develop an adaptive QLM ranking model. Extensive comparative experiments show the effectiveness of our session quantum language models.
The Shortcut Search. Governance.
ERIC Educational Resources Information Center
Nyland, Larry
1998-01-01
Faced with a late-season superintendent search, many districts defer the formal search-and-hire process and entice a senior administrator or former superintendent to serve a one- or two-year stint. One appealing alternative is an abbreviated search. Boards should advertise immediately and efficiently, develop their own criteria, recruit…
ERIC Educational Resources Information Center
Cooper, Rosie
2011-01-01
Lou Marinoff's article, "Inside a Search," discusses the issues college search committees face in the pursuit of qualified faculty members that will be a good fit for their institutions. More often than not, faculty searches are more complex and challenging than the featured article suggests. The economic downturn facing the nation has resulted in…
ERIC Educational Resources Information Center
Murray, Kenneth T.
This paper examines the practice of search and seizure from a legal perspective. All issues concerning lawful or unlawful search and seizure, whether in a public school or otherwise, are predicated upon the Fourth Amendment to the United States Constitution. The terms "search,""seizure,""probable cause,""reasonable suspicion," and "exclusionary…
ERIC Educational Resources Information Center
Doraiswamy, Uma
2011-01-01
This paper in the form of story discusses a college student's information search process. In this story we see Kuhlthau's information search process: initiation, selection, exploration, formulation, collection, and presentation. Katie is a student who goes in search of information for her class research paper. Katie's class readings, her interest…
Atmospheric Science Data Center
2016-10-05
Description: Search and order ASDC and Earth science data from various NASA and affiliated centers. Search and order options: project, parameter, data set, geographic region and ... Reverb will soon be retired. Please query the Earthdata Search Tool for your desired products. Details: ...
ERIC Educational Resources Information Center
Miller-Whitehead, Marie
Keyword and text string searches of online library catalogs often provide different results according to library and database used and depending upon how books and journals are indexed. For this reason, online databases such as ERIC often provide tutorials and recommendations for searching their site, such as how to use Boolean search strategies.…
Towards Motivation-Based Adaptation of Difficulty in E-Learning Programs
ERIC Educational Resources Information Center
Endler, Anke; Rey, Gunter Daniel; Butz, Martin V.
2012-01-01
The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of…
NASA Astrophysics Data System (ADS)
Bruzda, Wojciech; Cappellini, Valerio; Sommers, Hans-Jürgen; Życzkowski, Karol
2009-01-01
We define a natural ensemble of trace preserving, completely positive quantum maps and present algorithms to generate them at random. Spectral properties of the superoperator Φ associated with a given quantum map are investigated and a quantum analogue of the Frobenius-Perron theorem is proved. We derive a general formula for the density of eigenvalues of Φ and show the connection with the Ginibre ensemble of real non-symmetric random matrices. Numerical investigations of the spectral gap imply that a generic state of the system iterated several times by a fixed generic map converges exponentially to an invariant state.
NASA Astrophysics Data System (ADS)
Donnelly, Isaac
Random walks on lattices are a well used model for diffusion on continuum. They have been to model subdiffusive systems, systems with forcing and reactions as well as a combination of the three. We extend the traditional random walk framework to the network to obtain novel results. As an example due to the small graph diameter, the early time behaviour of subdiffusive dynamics dominates the observed system which has implications for models of the brain or airline networks. I would like to thank the Australian American Fulbright Association.
Whitley, L. Darrell; Howe, Adele E.; Watson, Jean-Paul
2004-09-01
Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features that influence problem difficulty. We consider these questions in the context of the job-shop scheduling problem (JSP), a domain where tabu search algorithms have been shown to be remarkably effective. Previously, we demonstrated that the mean distance between random local optima and the nearest optimal solution is highly correlated with problem difficulty for a well-known tabu search algorithm for the JSP introduced by Taillard. In this paper, we discuss various shortcomings of this measure and develop a new model of problem difficulty that corrects these deficiencies. We show that Taillard's algorithm can be modeled with high fidelity as a simple variant of a straightforward random walk. The random walk model accounts for nearly all of the variability in the cost required to locate both optimal and sub-optimal solutions to random JSPs, and provides an explanation for differences in the difficulty of random versus structured JSPs. Finally, we discuss and empirically substantiate two novel predictions regarding tabu search algorithm behavior. First, the method for constructing the initial solution is highly unlikely to impact the performance of tabu search. Second, tabu tenure should be selected to be as small as possible while simultaneously avoiding search stagnation; values larger than necessary lead to significant degradations in performance.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-22
... Employment and Training Administration Comment Request for Information Collection for ETA 9162, Random Audit... collection of data about Random Audit of Claimants in the Emergency Unemployment Compensation Program of 2008... is intended to provide data describing random audits of the work search provision of Public Law...
[Advanced online search techniques and dedicated search engines for physicians].
Nahum, Yoav
2008-02-01
In recent years search engines have become an essential tool in the work of physicians. This article will review advanced search techniques from the world of information specialists, as well as some advanced search engine operators that may help physicians improve their online search capabilities, and maximize the yield of their searches. This article also reviews popular dedicated scientific and biomedical literature search engines.
University Students' Online Information Searching Strategies in Different Search Contexts
ERIC Educational Resources Information Center
Tsai, Meng-Jung; Liang, Jyh-Chong; Hou, Huei-Tse; Tsai, Chin-Chung
2012-01-01
This study investigates the role of search context played in university students' online information searching strategies. A total of 304 university students in Taiwan were surveyed with questionnaires in which two search contexts were defined as searching for learning, and searching for daily life information. Students' online search strategies…
VisSearch: A Collaborative Web Searching Environment
ERIC Educational Resources Information Center
Lee, Young-Jin
2005-01-01
VisSearch is a collaborative Web searching environment intended for sharing Web search results among people with similar interests, such as college students taking the same course. It facilitates students' Web searches by visualizing various Web searching processes. It also collects the visualized Web search results and applies an association rule…
Benefits and Harms of Sick Leave: Lack of Randomized, Controlled Trials
ERIC Educational Resources Information Center
Axelsson, Inge; Marnetoft, Sven-Uno
2010-01-01
The aim of this study was to try to identify those randomized controlled trials that compare sick leave with no sick leave or a different duration or degree of sick leave. A comprehensive, systematic, electronic search of Clinical Evidence, the Cochrane Library and PubMed, and a manual search of the Campbell Library and a journal supplement was…
Randomness Of Amoeba Movements
NASA Astrophysics Data System (ADS)
Hashiguchi, S.; Khadijah, Siti; Kuwajima, T.; Ohki, M.; Tacano, M.; Sikula, J.
2005-11-01
Movements of amoebas were automatically traced using the difference between two successive frames of the microscopic movie. It was observed that the movements were almost random in that the directions and the magnitudes of the successive two steps are not correlated, and that the distance from the origin was proportional to the square root of the step number.
NASA Astrophysics Data System (ADS)
Leonetti, Marco; López, Cefe
2012-06-01
A random laser is formed by a haphazard assembly of nondescript optical scatters with optical gain. Multiple light scattering replaces the optical cavity of traditional lasers and the interplay between gain, scattering and size determines its unique properties. Random lasers studied till recently, consisted of irregularly shaped or polydisperse scatters, with some average scattering strength constant across the gain frequency band. Photonic glasses can sustain scattering resonances that can be placed in the gain window, since they are formed by monodisperse spheres [1]. The unique resonant scattering of this novel material allows controlling the lasing color via the diameter of the particles and their refractive index. Thus a random laser with a priori set lasing peak can be designed [2]. A special pumping scheme that enables to select the number of activated modes in a random laser permits to prepare RLs in two distinct regimes by controlling directionality through the shape of the pump [3]. When pumping is essentially unidirectional, few (barely interacting) modes are turned on that show as sharp, uncorrelated peaks in the spectrum. By increasing angular span of the pump beams, many resonances intervene generating a smooth emission spectrum with a high degree of correlation, and shorter lifetime. These are signs of a phaselocking transition, in which phases are clamped together so that modes oscillate synchronously.
ERIC Educational Resources Information Center
Griffiths, Martin
2011-01-01
One of the author's undergraduate students recently asked him whether it was possible to generate a random positive integer. After some thought, the author realised that there were plenty of interesting mathematical ideas inherent in her question. So much so in fact, that the author decided to organise a workshop, open both to undergraduates and…
Contouring randomly spaced data
NASA Technical Reports Server (NTRS)
Kibler, J. F.; Morris, W. D.; Hamm, R. W.
1977-01-01
Computer program using triangulation contouring technique contours data points too numerous to fit into rectangular grid. Using random access procedures, program can handle up to 56,000 data points and provides up to 20 contour intervals for multiple number of parameters.
Uniform random number generators
NASA Technical Reports Server (NTRS)
Farr, W. R.
1971-01-01
Methods are presented for the generation of random numbers with uniform and normal distributions. Subprogram listings of Fortran generators for the Univac 1108, SDS 930, and CDC 3200 digital computers are also included. The generators are of the mixed multiplicative type, and the mathematical method employed is that of Marsaglia and Bray.
Randomization and sampling issues
Geissler, P.H.
1996-01-01
The need for randomly selected routes and other sampling issues have been debated by the Amphibian electronic discussion group. Many excellent comments have been made, pro and con, but we have not reached consensus yet. This paper brings those comments together and attempts a synthesis. I hope that the resulting discussion will bring us closer to a consensus.
Migration in asymmetric, random environments
NASA Astrophysics Data System (ADS)
Deem, Michael; Wang, Dong
Migration is a key mechanism for expansion of communities. As a population migrates, it experiences a changing environment. In heterogeneous environments, rapid adaption is key to the evolutionary success of the population. In the case of human migration, environmental heterogeneity is naturally asymmetric in the North-South and East-West directions. We here consider migration in random, asymmetric, modularly correlated environments. Knowledge about the environment determines the fitness of each individual. We find that the speed of migration is proportional to the inverse of environmental change, and in particular we find that North-South migration rates are lower than East-West migration rates. Fast communication within the population of pieces of knowledge between individuals, similar to horizontal gene transfer in genetic systems, can help to spread beneficial knowledge among individuals. We show that increased modularity of the relation between knowledge and fitness enhances the rate of evolution. We investigate the relation between optimal information exchange rate and modularity of the dependence of fitness on knowledge. These results for the dependence of migration rate on heterogeneity, asymmetry, and modularity are consistent with existing archaeological facts.
On extreme value statistics of correlated random variables
NASA Astrophysics Data System (ADS)
Clusel, Maxime; Fortin, Jean-Yves
2013-03-01
The statistics of extreme values of a set on independent and identically distributed random variables is a well established mathematical theory that can be traced back to the late 1920s, with pioneering work by Fisher and Tippett. While efforts have been made to go beyond the uncorrelated case, little is known about the extremes of strongly correlated variables. Notable exceptions are the distribution of extreme eigenvalues of random matrices (Tracy and Widom 1994), the Airy law for one-dimensional random walks (Majumdar and Comtet 2005), and random variables with logarithmic interactions (Fyodorov and Bouchaud 2008). We propose to adapt the equivalence between extremes and sums (Bertin and Clusel 2006) to obtain asymptotic distributions of correlated random variables. We will show how this approach works in the logarithmic case, before extending it to power-law correlations and beyond. We will eventually illustrate these cases with a simple model, a one-dimensional gas of interacting particles.
Accelerating search kinetics by following boundaries
NASA Astrophysics Data System (ADS)
Calandre, T.; Bénichou, O.; Voituriez, R.
2014-06-01
We derive exact expressions of the mean first-passage time to a bulk target for a random searcher that performs boundary-mediated diffusion in a circular domain. Although nonintuitive for bulk targets, it is found that boundary excursions, if fast enough, can minimize the search time. A scaling analysis generalizes these findings to domains of arbitrary shapes and underlines their robustness. Overall, these results provide a generic mechanism of optimization of search kinetics in interfacial systems, which could have important implications in chemical physics. In the context of animal behavior sciences, it shows that following the boundaries of a domain can accelerate a search process, and therefore suggests that thigmotactism could be a kinetically efficient behavior.
IntentSearch: Capturing User Intention for One-Click Internet Image Search.
Tang, Xiaoou; Liu, Ke; Cui, Jingyu; Wen, Fang; Wang, Xiaogang
2012-07-01
Web-scale image search engines (e.g., Google image search, Bing image search) mostly rely on surrounding text features. It is difficult for them to interpret users' search intention only by query keywords and this leads to ambiguous and noisy search results which are far from satisfactory. It is important to use visual information in order to solve the ambiguity in text-based image retrieval. In this paper, we propose a novel Internet image search approach. It only requires the user to click on one query image with minimum effort and images from a pool retrieved by text-based search are reranked based on both visual and textual content. Our key contribution is to capture the users' search intention from this one-click query image in four steps. 1) The query image is categorized into one of the predefined adaptive weight categories which reflect users' search intention at a coarse level. Inside each category, a specific weight schema is used to combine visual features adaptive to this kind of image to better rerank the text-based search result. 2) Based on the visual content of the query image selected by the user and through image clustering, query keywords are expanded to capture user intention. 3) Expanded keywords are used to enlarge the image pool to contain more relevant images. 4) Expanded keywords are also used to expand the query image to multiple positive visual examples from which new query specific visual and textual similarity metrics are learned to further improve content-based image reranking. All these steps are automatic, without extra effort from the user. This is critically important for any commercial web-based image search engine, where the user interface has to be extremely simple. Besides this key contribution, a set of visual features which are both effective and efficient in Internet image search are designed. Experimental evaluation shows that our approach significantly improves the precision of top-ranked images and also the user
ERIC Educational Resources Information Center
Ben-Ari, Morechai
2004-01-01
The term "random" is frequently used in discussion of the theory of evolution, even though the mathematical concept of randomness is problematic and of little relevance in the theory. Therefore, since the core concept of the theory of evolution is the non-random process of natural selection, the term random should not be used in teaching the…
Fast randomized Hough transformation track initiation algorithm based on multi-scale clustering
NASA Astrophysics Data System (ADS)
Wan, Minjie; Gu, Guohua; Chen, Qian; Qian, Weixian; Wang, Pengcheng
2015-10-01
A fast randomized Hough transformation track initiation algorithm based on multi-scale clustering is proposed to overcome existing problems in traditional infrared search and track system(IRST) which cannot provide movement information of the initial target and select the threshold value of correlation automatically by a two-dimensional track association algorithm based on bearing-only information . Movements of all the targets are presumed to be uniform rectilinear motion throughout this new algorithm. Concepts of space random sampling, parameter space dynamic linking table and convergent mapping of image to parameter space are developed on the basis of fast randomized Hough transformation. Considering the phenomenon of peak value clustering due to shortcomings of peak detection itself which is built on threshold value method, accuracy can only be ensured on condition that parameter space has an obvious peak value. A multi-scale idea is added to the above-mentioned algorithm. Firstly, a primary association is conducted to select several alternative tracks by a low-threshold .Then, alternative tracks are processed by multi-scale clustering methods , through which accurate numbers and parameters of tracks are figured out automatically by means of transforming scale parameters. The first three frames are processed by this algorithm in order to get the first three targets of the track , and then two slightly different gate radius are worked out , mean value of which is used to be the global threshold value of correlation. Moreover, a new model for curvilinear equation correction is applied to the above-mentioned track initiation algorithm for purpose of solving the problem of shape distortion when a space three-dimensional curve is mapped to a two-dimensional bearing-only space. Using sideways-flying, launch and landing as examples to build models and simulate, the application of the proposed approach in simulation proves its effectiveness , accuracy , and adaptivity
Quality of Reporting of Randomized Clinical Trials in Tai Chi Interventions—A Systematic Review
Li, Jing-Yi; Zhang, Yuan-Fen; Smith, Gordon S.; Xue, Chuan-Jiang; Luo, Yan-Nan; Chen, Wei-Heng; Skinner, Craig J.; Finkelstein, Joseph
2011-01-01
Objectives. To evaluate the reporting quality of published randomized clinical trials (RCTs) in the Tai Chi literature following the publication of the CONSORT guidelines in 2001. Data Sources. The OVID MEDLINE and PUBMED databases. Review Methods. To survey the general characteristics of Tai Chi RCTs in the literature, we included any report if (i) it was an original report of the trial; (ii) its design was RCT; (iii) one of the treatments being tested was Tai Chi; and (iv) it was in English. In addition, we assessed the reporting quality of RCTs that were published between 2002 and 2007, using a modified CONSORT checklist of 40 items. The adequate description of Tai Chi interventions in these trials was examined against a 10-item checklist adapted from previous reviews. Results. The search yielded 31 Tai Chi RCTs published from 2002 to 2007 and only 11 for 1992–2001. Among trials published during 2002–2007, the most adequately reported criteria were related to background, participant eligibility and interpretation of the study results. Nonetheless, the most poorly reported items were associated with randomization allocation concealment, implementation of randomization and the definitions of period of recruitment and follow-up. In addition, only 23% of RCTs provided adequate details of Tai Chi intervention used in the trials. Conclusion. The findings in this review indicated that the reporting quality of Tai Chi intervention trials is sub-optimal. Substantial improvement is required to meet the CONSORT guidelines and allow assessment of the quality of evidence. We believe that not only investigators, but also journal editors, reviewers and funding agencies need to follow the CONSORT guidelines to improve the standards of research and strengthen the evidence base for Tai Chi and for complementary and alternative medicine. PMID:19351709
Countermeasure development to space adaptation
NASA Technical Reports Server (NTRS)
Larochelle, F. T.; Charles, J.; Harm, D. L.; Fortney, S. M.; Siconolfi, S.
1992-01-01
At the Johnson Space Center we are actively involved, with the collaboration of other NASA Centers and the scientific community at large, in the search for ways to counter the negative affects of spaceflight beginning with the improvement in our understanding of the adaptation. Heretofore this search will be broadly referred to as countermeasures development and includes not only the preservation of physiological well-being but also pyschological well-being. The psychological integrity of crews will, undoubtedly, become progressively more important as lengths, remoteness, and risks of missions increase. The character and priorities of our contermeasure development is very much dependent upon the character of the mission and requires a very close liaison between Medical Operations and the investigators. Because of the demands which countermeasure implementation imposes upon crew schedules and because of the potential weight, power, and budget impacts of the hardware and its development, a countermeasure can only become operational when it is either adequately validated or the human risk of not applying the existing technology exceeds the other negative impacts not directly related to crew health and safety.
Uncertainty about nest position influences systematic search strategies in desert ants.
Merkle, Tobias; Knaden, Markus; Wehner, Rüdiger
2006-09-01
Foraging desert ants return to their starting point, the nest, by means of path integration. If the path-integration vector has been run off but the nest has not yet been reached, the ants engage in systematic search behavior. This behavior results in a system of search loops of ever increasing size and finally leads to a search density profile peaking at the location where the path integration system has been reset to zero. In this study we investigate whether this systematic search behavior is adapted to the uncertainty resulting from the preceding foraging run. We show first that the longer the distances of the foraging excursions, the larger the errors occurring during path integration, and second that the ants adapt their systematic search strategy to their increasing uncertainty by extending their search pattern. Hence, the density of the systematic search pattern is correlated with the ants' confidence in their path integrator. This confidence decreases with increasing foraging distances.
Filtering and analysis on the random drift of FOG
NASA Astrophysics Data System (ADS)
Tian, Yun-Peng; Yang, Xiao-Jun; Guo, Yun-Zeng; Liu, Feng
2015-10-01
Fiber optic gyro (FOG) is an optical gyroscope which is based on the Sagnac effect and uses the optical fiber coil as light propagation channel. Gyro drift consists of two components: systemic drift and random drift. Systemic drift can be compensated by testing and calibrating. Random drift changes with time, so it becomes an important indicator to measure the precision of gyroscope, which has a great impact on the inertial navigation system. It can't be compensated by the simple method. Random drift is a main error of fiber optic gyro (FOG). The static output of FOG is a random project and it has more random noise when as the inertial navigation sensor, which will affect the measurement accuracy. It is an efficient method to reduce the random drift and improve the accuracy by modeling and compensation from the output of FOG. According to the characteristic of fiber optic gyro, the random drift model is studied. Using the time series method, the constant component of the random noise original data is extracted. After stationarity and normality tests, a normal random process is acquired. Based on this, the model is established using the recursive least squares, and then the model is applied to the normal Kalman and adaptive Kalman, finally the data is process with the filter. After experimental verification, the noise variance was reduced after filtering, and the effect is obvious.
Meta-Analysis of Randomized, Controlled Treatment Trials for Pediatric Obsessive-Compulsive Disorder
ERIC Educational Resources Information Center
Watson, Hunna J.; Rees, Clare S.
2008-01-01
Objective: To conduct a meta-analysis on randomized, controlled treatment trials of pediatric obsessive-compulsive disorder (OCD). Method: Studies were included if they employed randomized, controlled methodology and treated young people (19 years or under) with OCD. A comprehensive literature search identified 13 RCTs containing 10…
A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps
Mao, Wei; Li, Hao-ru
2016-01-01
As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426
ICAT: a computational model for the adaptive control of fixation durations.
Trukenbrod, Hans A; Engbert, Ralf
2014-08-01
Eye movements depend on cognitive processes related to visual information processing. Much has been learned about the spatial selection of fixation locations, while the principles governing the temporal control (fixation durations) are less clear. Here, we review current theories for the control of fixation durations in tasks like visual search, scanning, scene perception, and reading and propose a new model for the control of fixation durations. We distinguish two local principles from one global principle of control. First, an autonomous saccade timer initiates saccades after random time intervals (local-I). Second, foveal inhibition permits immediate prolongation of fixation durations by ongoing processing (local-II). Third, saccade timing is adaptive, so that the mean timer value depends on task requirements and fixation history (Global). We demonstrate by numerical simulations that our model qualitatively reproduces patterns of mean fixation durations and fixation duration distributions observed in typical experiments. When combined with assumptions of saccade target selection and oculomotor control, the model accounts for both temporal and spatial aspects of eye movement control in two versions of a visual search task. We conclude that the model provides a promising framework for the control of fixation durations in saccadic tasks.
A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.
Mao, Wei; Lan, Heng-You; Li, Hao-Ru
2016-01-01
As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426
Organizational Adaptation and Higher Education.
ERIC Educational Resources Information Center
Cameron, Kim S.
1984-01-01
Organizational adaptation and types of adaptation needed in academe in the future are reviewed and major conceptual approaches to organizational adaptation are presented. The probable environment that institutions will face in the future that will require adaptation is discussed. (MLW)
Taylor, Nigel A S
2014-01-01
In this overview, human morphological and functional adaptations during naturally and artificially induced heat adaptation are explored. Through discussions of adaptation theory and practice, a theoretical basis is constructed for evaluating heat adaptation. It will be argued that some adaptations are specific to the treatment used, while others are generalized. Regarding ethnic differences in heat tolerance, the case is put that reported differences in heat tolerance are not due to natural selection, but can be explained on the basis of variations in adaptation opportunity. These concepts are expanded to illustrate how traditional heat adaptation and acclimatization represent forms of habituation, and thermal clamping (controlled hyperthermia) is proposed as a superior model for mechanistic research. Indeed, this technique has led to questioning the perceived wisdom of body-fluid changes, such as the expansion and subsequent decay of plasma volume, and sudomotor function, including sweat habituation and redistribution. Throughout, this contribution was aimed at taking another step toward understanding the phenomenon of heat adaptation and stimulating future research. In this regard, research questions are posed concerning the influence that variations in morphological configuration may exert upon adaptation, the determinants of postexercise plasma volume recovery, and the physiological mechanisms that modify the cholinergic sensitivity of sweat glands, and changes in basal metabolic rate and body core temperature following adaptation.
NASA Astrophysics Data System (ADS)
Jiang, Hao; Stewart, Derek A.
2016-04-01
Metal oxide resistive memory devices based on Ta2O5 have demonstrated high switching speed, long endurance, and low set voltage. However, the physical origin of this improved performance is still unclear. Ta2O5 is an important archetype of a class of materials that possess an adaptive crystal structure that can respond easily to the presence of defects. Using first principles nudged elastic band calculations, we show that this adaptive crystal structure leads to low energy barriers for in-plane diffusion of oxygen vacancies in λ phase Ta2O5. Identified diffusion paths are associated with collective motion of neighboring atoms. The overall vacancy diffusion is anisotropic with higher diffusion barriers found for oxygen vacancy movement between Ta-O planes. Coupled with the fact that oxygen vacancy formation energy in Ta2O5 is relatively small, our calculated low diffusion barriers can help explain the low set voltage in Ta2O5 based resistive memory devices. Our work shows that other oxides with adaptive crystal structures could serve as potential candidates for resistive random access memory devices. We also discuss some general characteristics for ideal resistive RAM oxides that could be used in future computational material searches.
Multi-Agent Methods for the Configuration of Random Nanocomputers
NASA Technical Reports Server (NTRS)
Lawson, John W.
2004-01-01
As computational devices continue to shrink, the cost of manufacturing such devices is expected to grow exponentially. One alternative to the costly, detailed design and assembly of conventional computers is to place the nano-electronic components randomly on a chip. The price for such a trivial assembly process is that the resulting chip would not be programmable by conventional means. In this work, we show that such random nanocomputers can be adaptively programmed using multi-agent methods. This is accomplished through the optimization of an associated high dimensional error function. By representing each of the independent variables as a reinforcement learning agent, we are able to achieve convergence must faster than with other methods, including simulated annealing. Standard combinational logic circuits such as adders and multipliers are implemented in a straightforward manner. In addition, we show that the intrinsic flexibility of these adaptive methods allows the random computers to be reconfigured easily, making them reusable. Recovery from faults is also demonstrated.
Robots that can adapt like animals.
Cully, Antoine; Clune, Jeff; Tarapore, Danesh; Mouret, Jean-Baptiste
2015-05-28
Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, such as in search and rescue, disaster response, health care and transportation. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets to deep oceans. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility. Whereas animals can quickly adapt to injuries, current robots cannot 'think outside the box' to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage, but current techniques are slow even with small, constrained search spaces. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot's prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles
Robots that can adapt like animals.
Cully, Antoine; Clune, Jeff; Tarapore, Danesh; Mouret, Jean-Baptiste
2015-05-28
Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, such as in search and rescue, disaster response, health care and transportation. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets to deep oceans. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility. Whereas animals can quickly adapt to injuries, current robots cannot 'think outside the box' to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage, but current techniques are slow even with small, constrained search spaces. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot's prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles
Robots that can adapt like animals
NASA Astrophysics Data System (ADS)
Cully, Antoine; Clune, Jeff; Tarapore, Danesh; Mouret, Jean-Baptiste
2015-05-01
Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, such as in search and rescue, disaster response, health care and transportation. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets to deep oceans. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility. Whereas animals can quickly adapt to injuries, current robots cannot `think outside the box' to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage, but current techniques are slow even with small, constrained search spaces. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot's prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles
Relativistic Weierstrass random walks.
Saa, Alberto; Venegeroles, Roberto
2010-08-01
The Weierstrass random walk is a paradigmatic Markov chain giving rise to a Lévy-type superdiffusive behavior. It is well known that special relativity prevents the arbitrarily high velocities necessary to establish a superdiffusive behavior in any process occurring in Minkowski spacetime, implying, in particular, that any relativistic Markov chain describing spacetime phenomena must be essentially Gaussian. Here, we introduce a simple relativistic extension of the Weierstrass random walk and show that there must exist a transition time t{c} delimiting two qualitative distinct dynamical regimes: the (nonrelativistic) superdiffusive Lévy flights, for t
Relativistic Weierstrass random walks.
Saa, Alberto; Venegeroles, Roberto
2010-08-01
The Weierstrass random walk is a paradigmatic Markov chain giving rise to a Lévy-type superdiffusive behavior. It is well known that special relativity prevents the arbitrarily high velocities necessary to establish a superdiffusive behavior in any process occurring in Minkowski spacetime, implying, in particular, that any relativistic Markov chain describing spacetime phenomena must be essentially Gaussian. Here, we introduce a simple relativistic extension of the Weierstrass random walk and show that there must exist a transition time t{c} delimiting two qualitative distinct dynamical regimes: the (nonrelativistic) superdiffusive Lévy flights, for t
NASA Astrophysics Data System (ADS)
Mousavi, S. Jamshid; Shourian, M.
2010-03-01
Global optimization models in many problems suffer from high computational costs due to the need for performing high-fidelity simulation models for objective function evaluations. Metamodeling is a useful approach to dealing with this problem in which a fast surrogate model replaces the detailed simulation model. However, training of the surrogate model needs enough input-output data which in case of absence of observed data, each of them must be obtained by running the simulation model and may still cause computational difficulties. In this paper a new metamodeling approach called adaptive sequentially space filling (ASSF) is presented by which the regions in the search space that need more training data are sequentially identified and the process of design of experiments is performed adaptively. Performance of the ASSF approach is tested against a benchmark function optimization problem and optimum basin-scale water allocation problems, in which the MODSIM river basin decision support system is approximated. Results show the ASSF model with fewer actual function evaluations is able to find comparable solutions to other metamodeling techniques using random sampling and evolution control strategies.
Technology transfer for adaptation
NASA Astrophysics Data System (ADS)
Biagini, Bonizella; Kuhl, Laura; Gallagher, Kelly Sims; Ortiz, Claudia
2014-09-01
Technology alone will not be able to solve adaptation challenges, but it is likely to play an important role. As a result of the role of technology in adaptation and the importance of international collaboration for climate change, technology transfer for adaptation is a critical but understudied issue. Through an analysis of Global Environment Facility-managed adaptation projects, we find there is significantly more technology transfer occurring in adaptation projects than might be expected given the pessimistic rhetoric surrounding technology transfer for adaptation. Most projects focused on demonstration and early deployment/niche formation for existing technologies rather than earlier stages of innovation, which is understandable considering the pilot nature of the projects. Key challenges for the transfer process, including technology selection and appropriateness under climate change, markets and access to technology, and diffusion strategies are discussed in more detail.
Liongue, Clifford; John, Liza B; Ward, Alister
2011-01-01
Adaptive immunity, involving distinctive antibody- and cell-mediated responses to specific antigens based on "memory" of previous exposure, is a hallmark of higher vertebrates. It has been argued that adaptive immunity arose rapidly, as articulated in the "big bang theory" surrounding its origins, which stresses the importance of coincident whole-genome duplications. Through a close examination of the key molecules and molecular processes underpinning adaptive immunity, this review suggests a less-extreme model, in which adaptive immunity emerged as part of longer evolutionary journey. Clearly, whole-genome duplications provided additional raw genetic materials that were vital to the emergence of adaptive immunity, but a variety of other genetic events were also required to generate some of the key molecules, whereas others were preexisting and simply co-opted into adaptive immunity.
Webster, Michael A.
2011-01-01
Visual coding is a highly dynamic process and continuously adapting to the current viewing context. The perceptual changes that result from adaptation to recently viewed stimuli remain a powerful and popular tool for analyzing sensory mechanisms and plasticity. Over the last decade, the footprints of this adaptation have been tracked to both higher and lower levels of the visual pathway and over a wider range of timescales, revealing that visual processing is much more adaptable than previously thought. This work has also revealed that the pattern of aftereffects is similar across many stimulus dimensions, pointing to common coding principles in which adaptation plays a central role. However, why visual coding adapts has yet to be fully answered. PMID:21602298
Parallel Anisotropic Tetrahedral Adaptation
NASA Technical Reports Server (NTRS)
Park, Michael A.; Darmofal, David L.
2008-01-01
An adaptive method that robustly produces high aspect ratio tetrahedra to a general 3D metric specification without introducing hybrid semi-structured regions is presented. The elemental operators and higher-level logic is described with their respective domain-decomposed parallelizations. An anisotropic tetrahedral grid adaptation scheme is demonstrated for 1000-1 stretching for a simple cube geometry. This form of adaptation is applicable to more complex domain boundaries via a cut-cell approach as demonstrated by a parallel 3D supersonic simulation of a complex fighter aircraft. To avoid the assumptions and approximations required to form a metric to specify adaptation, an approach is introduced that directly evaluates interpolation error. The grid is adapted to reduce and equidistribute this interpolation error calculation without the use of an intervening anisotropic metric. Direct interpolation error adaptation is illustrated for 1D and 3D domains.
Liongue, Clifford; John, Liza B; Ward, Alister
2011-01-01
Adaptive immunity, involving distinctive antibody- and cell-mediated responses to specific antigens based on "memory" of previous exposure, is a hallmark of higher vertebrates. It has been argued that adaptive immunity arose rapidly, as articulated in the "big bang theory" surrounding its origins, which stresses the importance of coincident whole-genome duplications. Through a close examination of the key molecules and molecular processes underpinning adaptive immunity, this review suggests a less-extreme model, in which adaptive immunity emerged as part of longer evolutionary journey. Clearly, whole-genome duplications provided additional raw genetic materials that were vital to the emergence of adaptive immunity, but a variety of other genetic events were also required to generate some of the key molecules, whereas others were preexisting and simply co-opted into adaptive immunity. PMID:21395512
Gravitational adaptation of animals
NASA Technical Reports Server (NTRS)
Smith, A. H.; Burton, R. R.
1982-01-01
The effect of gravitational adaptation is studied in a group of five Leghorn cocks which had become physiologically adapted to 2 G after 162 days of centrifugation. After this period of adaptation, they are periodically exposed to a 2 G field, accompanied by five previously unexposed hatch-mates, and the degree of retained acceleration adaptation is estimated from the decrease in lymphocyte frequency after 24 hr at 2 G. Results show that the previously adapted birds exhibit an 84% greater lymphopenia than the unexposed birds, and that the lymphocyte frequency does not decrease to a level below that found at the end of 162 days at 2 G. In addition, the capacity for adaptation to chronic acceleration is found to be highly heritable. An acceleration tolerant strain of birds shows lesser mortality during chronic acceleration, particularly in intermediate fields, although the result of acceleration selection is largely quantitative (a greater number of survivors) rather than qualitative (behavioral or physiological changes).
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths
NASA Astrophysics Data System (ADS)
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [http://www.cs.ubc.ca/~hoos/5/benchm.html]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.