NASA Technical Reports Server (NTRS)
Boussalis, Dhemetrios; Wang, Shyh J.
1992-01-01
This paper presents a method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems.
Tang, Lisa Y W; Hamarneh, Ghassan
2013-01-01
We develop a random walk-based image registration method that incorporates two novelties: 1) a progressive optimization scheme that conducts the solution search efficiently via a novel use of information derived from the obtained probabilistic solution, and 2) a data-likelihood re-weighting step that contextually performs feature selection in a spatially adaptive manner so that the data costs are based primarily on trusted information sources. Synthetic experiments on three public datasets of different anatomical regions and modalities showed that our method performed efficient search without sacrificing registration accuracy. Experiments performed on 60 real brain image pairs from a public dataset also demonstrated our method's better performance over existing non-probabilistic image registration methods. PMID:24579122
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.
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.
A random search algorithm for laboratory computers
NASA Technical Reports Server (NTRS)
Curry, R. E.
1975-01-01
The small laboratory computer is ideal for experimental control and data acquisition. Postexperimental data processing is often performed on large computers because of the availability of sophisticated programs, but costs and data compatibility are negative factors. Parameter optimization can be accomplished on the small computer, offering ease of programming, data compatibility, and low cost. A previously proposed random-search algorithm ('random creep') was found to be very slow in convergence. A method is proposed (the 'random leap' algorithm) which starts in a global search mode and automatically adjusts step size to speed convergence. A FORTRAN executive program for the random-leap algorithm is presented which calls a user-supplied function subroutine. An example of a function subroutine is given which calculates maximum-likelihood estimates of receiver operating-characteristic parameters from binary response data. Other applications in parameter estimation, generalized least squares, and matrix inversion are discussed.
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.
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
Randomized spatial context for object search.
Jiang, Yuning; Meng, Jingjing; Yuan, Junsong; Luo, Jiebo
2015-06-01
Searching visual objects in large image or video data sets is a challenging problem, because it requires efficient matching and accurate localization of query objects that often occupy a small part of an image. Although spatial context has been shown to help produce more reliable detection than methods that match local features individually, how to extract appropriate spatial context remains an open problem. Instead of using fixed-scale spatial context, we propose a randomized approach to deriving spatial context, in the form of spatial random partition. The effect of spatial context is achieved by averaging the matching scores over multiple random patches. Our approach offers three benefits: 1) the aggregation of the matching scores over multiple random patches provides robust local matching; 2) the matched objects can be directly identified on the pixelwise confidence map, which results in efficient object localization; and 3) our algorithm lends itself to easy parallelization and also allows a flexible tradeoff between accuracy and speed through adjusting the number of partition times. Both theoretical studies and experimental comparisons with the state-of-the-art methods validate the advantages of our approach. PMID:25781874
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 Cuckoo Search Algorithm for Unconstrained Optimization
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. PMID:25298971
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. PMID:26099995
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
Opinion dynamics on an adaptive random network
NASA Astrophysics Data System (ADS)
Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.
2009-04-01
We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.
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 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.
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.
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.
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.
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.
Tabu search method with random moves for globally optimal design
NASA Astrophysics Data System (ADS)
Hu, Nanfang
1992-09-01
Optimum engineering design problems are usually formulated as non-convex optimization problems of continuous variables. Because of the absence of convexity structure, they can have multiple minima, and global optimization becomes difficult. Traditional methods of optimization, such as penalty methods, can often be trapped at a local optimum. The tabu search method with random moves to solve approximately these problems is introduced. Its reliability and efficiency are examined with the help of standard test functions. By the analysis of the implementations, it is seen that this method is easy to use, and no derivative information is necessary. It outperforms the random search method and composite genetic algorithm. In particular, it is applied to minimum weight design examples of a three-bar truss, coil springs, a Z-section and a channel section. For the channel section, the optimal design using the tabu search method with random moves saved 26.14 percent over the weight of the SUMT method.
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…
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.
Searching method through biased random walks on complex networks.
Lee, Sungmin; Yook, Soon-Hyung; Kim, Yup
2009-07-01
Information search is closely related to the first-passage property of diffusing particle. The physical properties of diffusing particle is affected by the topological structure of the underlying network. Thus, the interplay between dynamical process and network topology is important to study information search on complex networks. Designing an efficient method has been one of main interests in information search. Both reducing the network traffic and decreasing the searching time have been two essential factors for designing efficient method. Here we propose an efficient method based on biased random walks. Numerical simulations show that the average searching time of the suggested model is more efficient than other well-known models. For a practical interest, we demonstrate how the suggested model can be applied to the peer-to-peer system. PMID:19658839
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.
Robustness of optimal random searches in fragmented environments
NASA Astrophysics Data System (ADS)
Wosniack, M. E.; Santos, M. C.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2015-05-01
The random search problem is a challenging and interdisciplinary topic of research in statistical physics. Realistic searches usually take place in nonuniform heterogeneous distributions of targets, e.g., patchy environments and fragmented habitats in ecological systems. Here we present a comprehensive numerical study of search efficiency in arbitrarily fragmented landscapes with unlimited visits to targets that can only be found within patches. We assume a random walker selecting uniformly distributed turning angles and step lengths from an inverse power-law tailed distribution with exponent μ . Our main finding is that for a large class of fragmented environments the optimal strategy corresponds approximately to the same value μopt≈2 . Moreover, this exponent is indistinguishable from the well-known exact optimal value μopt=2 for the low-density limit of homogeneously distributed revisitable targets. Surprisingly, the best search strategies do not depend (or depend only weakly) on the specific details of the fragmentation. Finally, we discuss the mechanisms behind this observed robustness and comment on the relevance of our results to both the random search theory in general, as well as specifically to the foraging problem in the biological context.
Optimal random search for a single hidden target.
Snider, Joseph
2011-01-01
A single target is hidden at a location chosen from a predetermined probability distribution. Then, a searcher must find a second probability distribution from which random search points are sampled such that the target is found in the minimum number of trials. Here it will be shown that if the searcher must get very close to the target to find it, then the best search distribution is proportional to the square root of the target distribution regardless of dimension. For a Gaussian target distribution, the optimum search distribution is approximately a Gaussian with a standard deviation that varies inversely with how close the searcher must be to the target to find it. For a network where the searcher randomly samples nodes and looks for the fixed target along edges, the optimum is either to sample a node with probability proportional to the square root of the out-degree plus 1 or not to do so at all. PMID:21405659
Cheung, Ying Kuen; Chakraborty, Bibhas; Davidson, Karina W
2015-06-01
Implementation study is an important tool for deploying state-of-the-art treatments from clinical efficacy studies into a treatment program, with the dual goals of learning about effectiveness of the treatments and improving the quality of care for patients enrolled into the program. In this article, we deal with the design of a treatment program of dynamic treatment regimens (DTRs) for patients with depression post-acute coronary syndrome. We introduce a novel adaptive randomization scheme for a sequential multiple assignment randomized trial of DTRs. Our approach adapts the randomization probabilities to favor treatment sequences having comparatively superior Q-functions used in Q-learning. The proposed approach addresses three main concerns of an implementation study: it allows incorporation of historical data or opinions, it includes randomization for learning purposes, and it aims to improve care via adaptation throughout the program. We demonstrate how to apply our method to design a depression treatment program using data from a previous study. By simulation, we illustrate that the inputs from historical data are important for the program performance measured by the expected outcomes of the enrollees, but also show that the adaptive randomization scheme is able to compensate poorly specified historical inputs by improving patient outcomes within a reasonable horizon. The simulation results also confirm that the proposed design allows efficient learning of the treatments by alleviating the curse of dimensionality. PMID:25354029
Random search optimization based on genetic algorithm and discriminant function
NASA Technical Reports Server (NTRS)
Kiciman, M. O.; Akgul, M.; Erarslanoglu, G.
1990-01-01
The general problem of optimization with arbitrary merit and constraint functions, which could be convex, concave, monotonic, or non-monotonic, is treated using stochastic methods. To improve the efficiency of the random search methods, a genetic algorithm for the search phase and a discriminant function for the constraint-control phase were utilized. The validity of the technique is demonstrated by comparing the results to published test problem results. Numerical experimentation indicated that for cases where a quick near optimum solution is desired, a general, user-friendly optimization code can be developed without serious penalties in both total computer time and accuracy.
Dementia alters standing postural adaptation during a visual search task in older adult men
Joŕdan, Azizah J.; McCarten, J. Riley; Rottunda, Susan; Stoffregen, Thomas A.; Manor, Brad; Wade, Michael G.
2015-01-01
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. PMID:25770830
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
2014-07-29
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
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.
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.
Locally-adaptive and memetic evolutionary pattern search algorithms.
Hart, William E
2003-01-01
Recent convergence analyses of evolutionary pattern search algorithms (EPSAs) have shown that these methods have a weak stationary point convergence theory for a broad class of unconstrained and linearly constrained problems. This paper describes how the convergence theory for EPSAs can be adapted to allow each individual in a population to have its own mutation step length (similar to the design of evolutionary programing and evolution strategies algorithms). These are called locally-adaptive EPSAs (LA-EPSAs) since each individual's mutation step length is independently adapted in different local neighborhoods. The paper also describes a variety of standard formulations of evolutionary algorithms that can be used for LA-EPSAs. Further, it is shown how this convergence theory can be applied to memetic EPSAs, which use local search to refine points within each iteration. PMID:12804096
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
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.
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
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. PMID:26990103
Automatic sub-volume registration by probabilistic random search
NASA Astrophysics Data System (ADS)
Han, Jingfeng; Qiao, Min; Hornegger, Joachim; Kuwert, Torsten; Bautz, Werner; Römer, Wolfgang
2006-03-01
Registration of an individual's image data set to an anatomical atlas provides valuable information to the physician. In many cases, the individual image data sets are partial data, which may be mapped to one part or one organ of the entire atlas data. Most of the existing intensity based image registration approaches are designed to align images of the entire view. When they are applied to the registration with partial data, a manual pre-registration is usually required. This paper proposes a fully automatic approach to the registration of the incomplete image data to an anatomical atlas. The spatial transformations are modelled as any parametric functions. The proposed method is built upon a random search mechanism, which allows to find the optimal transformation randomly and globally even when the initialization is not ideal. It works more reliably than the existing methods for the partial data registration because it successfully overcomes the local optimum problem. With appropriate similarity measures, this framework is applicable to both mono-modal and multi-modal registration problems with partial data. The contribution of this work is the description of the mathematical framework of the proposed algorithm and the implementation of the related software. The medical evaluation on the MRI data and the comparison of the proposed method with different existing registration methods show the feasibility and superiority of the proposed method.
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.
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 Search for a General Phenomenon of Adaptive Mutability
Galitski, T.; Roth, J. R.
1996-01-01
The most prominent systems for the study of adaptive mutability depend on the specialized activities of genetic elements like bacteriophage Mu and the F plasmid. Searching for general adaptive mutability, we have investigated the behavior of Salmonella typhimurium strains with chromosomal lacZ mutations. We have studied 30 revertible nonsense, missense, frameshift, and insertion alleles. One-third of the mutants produced >=10 late revertant colonies (appearing three to seven days after plating on selective medium). For the prolific mutants, the number of late revertants showed rank correlation with the residual β-galactosidase activity; for the same mutants, revertant number showed no correlation with the nonselective reversion rate (from fluctuation tests). Leaky mutants, which grew slowly on selective medium, produced late revertants whereas tight nongrowing mutants generally did not produce late revertants. However, the number of late revertants was not proportional to residual growth. Using total residual growth and the nonselective reversion rate, the expected number of late revertants was calculated. For several leaky mutants, the observed revertant number exceeded the expected number. We suggest that excess late revertants from these mutants arise from general adaptive mutability available to any chromosomal gene. PMID:8725216
Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields.
Huang, Haiping; Kabashima, Yoshiyuki
2013-06-01
The adaptive Thouless-Anderson-Palmer equation is derived for inverse Ising problems in the presence of quenched random fields. We test the proposed scheme on Sherrington-Kirkpatrick, Hopfield, and random orthogonal models and find that the adaptive Thouless-Anderson-Palmer approach allows accurate inference of quenched random fields whose distribution can be either Gaussian or bimodal. In particular, another competitive method for inferring external fields, namely, the naive mean field method with diagonal weights, is compared and discussed. PMID:23848649
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. PMID:25215330
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
2016-01-01
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
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 nowcasting of influenza outbreaks using Google searches.
Preis, Tobias; Moat, Helen Susannah
2014-10-01
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
ERIC Educational Resources Information Center
Pirovich, L. Ya
The article shows the effect of the irregularity of using separate symbols on search noise on punch cards with superimposed symbol coding in information-search system (IPS). A binomial law of random value distribution of repetition of each symbol is established and analyzed. A method of determining the maximum value of symbol repetition is…
Lee, Christina S.; López, Steven R.; Colby, Suzanne M.; Rohsenow, Damaris; Hernández, Lynn; Borrelli, Belinda; Caetano, Raul
2014-01-01
A randomized clinical trial of culturally adapted (CAMI) and un-adapted motivational interviewing (MI) to reduce drinking and related problems among heavy drinking Latinos randomized and assessed 58 participants at baseline, at 2 (86% retention) and 6 months (84% retention). Significant declines across both were found in heavy drinking days/month and drinking consequences (p < .001), with greater reductions for drinking consequences for CAMI at 2 months (p = .009) and continuing reductions in CAMI at 6 months. Findings provide preliminary support for the value of culturally adaptation to enhance the efficacy of motivational interviewing with Latino heavy drinkers. PMID:24215227
Data-adaptive unfolding of nonergodic spectra: Two-Body Random Ensemble
NASA Astrophysics Data System (ADS)
Fossion, R.; Torres Vargas, G.; Velázquez, V.; López Vieyra, J. C.
2015-01-01
The statistics of spectral fluctuations is sensitive to the unfolding procedure that separates global from local properties. Previously, we presented a parameter-free and data- adaptive unfolding method that we demonstrated to be highly effective for standard random- matrix ensembles from Random Matrix Theory (RMT). More general ensembles often break the ergodicity property, which leads to ambiguities between individual-spectrum averaged and ensemble-averaged fluctuation measures. Here, we apply our data-adaptive unfolding to a nonergodic Two-Body Random Ensemble (TBRE). In the present approach, both fluctuation measures can be calculated simultaneously within the same unfolding step, and possible arbitrarities introduced by traditional unfolding procedures are avoided.
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.
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.
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
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.
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.
Levy flights do not always optimize random blind search for sparse targets.
Palyulin, Vladimir V; Chechkin, Aleksei V; Metzler, Ralf
2014-02-25
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
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
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.
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
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…
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
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.
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
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.
NASA Astrophysics Data System (ADS)
Lu, Dawei; Zhu, Jing; Zou, Ping; Peng, Xinhua; Yu, Yihua; Zhang, Shanmin; Chen, Qun; Du, Jiangfeng
2010-02-01
An important quantum search algorithm based on the quantum random walk performs an oracle search on a database of N items with O(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.
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.
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.
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. PMID:24407307
Witteveen, Jeroen A.S. Bijl, Hester
2009-10-01
The Unsteady Adaptive Stochastic Finite Elements (UASFE) method resolves the effect of randomness in numerical simulations of single-mode aeroelastic responses with a constant accuracy in time for a constant number of samples. In this paper, the UASFE framework is extended to multi-frequency responses and continuous structures by employing a wavelet decomposition pre-processing step to decompose the sampled multi-frequency signals into single-frequency components. The effect of the randomness on the multi-frequency response is then obtained by summing the results of the UASFE interpolation at constant phase for the different frequency components. Results for multi-frequency responses and continuous structures show a three orders of magnitude reduction of computational costs compared to crude Monte Carlo simulations in a harmonically forced oscillator, a flutter panel problem, and the three-dimensional transonic AGARD 445.6 wing aeroelastic benchmark subject to random fields and random parameters with various probability distributions.
NASA Astrophysics Data System (ADS)
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), 10.1103/PhysRevLett.113.220602]. 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).
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. PMID:16953784
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.
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
NASA Astrophysics Data System (ADS)
Frenken, Koen
2001-06-01
The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
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.
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. PMID:27557166
A trellis-searched APC (adaptive predictive coding) speech coder
Malone, K.T. ); Fischer, T.R. . Dept. of Electrical and Computer Engineering)
1990-01-01
In this paper we formulate a speech coding system that incorporates trellis coded vector quantization (TCVQ) and adaptive predictive coding (APC). A method for optimizing'' the TCVQ codebooks is presented and experimental results concerning survivor path mergings are reported. Simulation results are given for encoding rates of 16 and 9.6 kbps for a variety of coder parameters. The quality of the encoded speech is deemed excellent at an encoding rate of 16 kbps and very good at 9.6 kbps. 13 refs., 2 figs., 4 tabs.
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
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.
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
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.
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
A Bayesian decision-theoretic sequential response-adaptive randomization design.
Jiang, Fei; Jack Lee, J; Müller, Peter
2013-05-30
We propose a class of phase II clinical trial designs with sequential stopping and adaptive treatment allocation to evaluate treatment efficacy. Our work is based on two-arm (control and experimental treatment) designs with binary endpoints. Our overall goal is to construct more efficient and ethical randomized phase II trials by reducing the average sample sizes and increasing the percentage of patients assigned to the better treatment arms of the trials. The designs combine the Bayesian decision-theoretic sequential approach with adaptive randomization procedures in order to achieve simultaneous goals of improved efficiency and ethics. The design parameters represent the costs of different decisions, for example, the decisions for stopping or continuing the trials. The parameters enable us to incorporate the actual costs of the decisions in practice. The proposed designs allow the clinical trials to stop early for either efficacy or futility. Furthermore, the designs assign more patients to better treatment arms by applying adaptive randomization procedures. We develop an algorithm based on the constrained backward induction and forward simulation to implement the designs. The algorithm overcomes the computational difficulty of the backward induction method, thereby making our approach practicable. The designs result in trials with desirable operating characteristics under the simulated settings. Moreover, the designs are robust with respect to the response rate of the control group. PMID:23315678
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.
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. PMID:26093936
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…
Motile male gametes of the araphid diatom Tabularia fasciculata search randomly for mates.
Edgar, Robyn; Drolet, David; Ehrman, James M; Kaczmarska, Irena
2014-01-01
Sexuality in the marine araphid diatom Tabularia involves an unusual type of gamete, not only among diatoms but possibly in all of nature. The non-flagellated male gamete is free and vigorously motile, propelled by pseudopodia. However, the cues (if any) in their search for compatible female gametes and the general search patterns to locate them are unknown. We tracked and compared male gamete movements in the presence and absence of receptive female gametes. Path linearity of male movement was not affected by presence of female gametes. Male gametes did not move towards female gametes regardless of their proximity to each other, suggesting that the detection range for a compatible mate is very small compared to known algal examples (mostly spermatozoids) and that mate recognition requires (near) contact with a female gamete. We therefore investigated how male gametes move to bring insight into their search strategy and found that it was consistent with the predictions of a random-walk model with changes in direction coming from an even distribution. We further investigated the type of random walk by determining the best-fit distribution on the tail of the move length distribution and found it to be consistent with a truncated power law distribution with an exponent of 2.34. Although consistent with a Lévy walk search pattern, the range of move lengths in the tail was too narrow for Lévy properties to emerge and so would be best described as Brownian motion. This is somewhat surprising because female gametes were often outnumbered by male gametes, thus contrary to the assumption that a Brownian search mode may be most optimal with an abundant target resource. This is also the first mathematically analysed search pattern of a non-flagellated protistan gamete, supporting the notion that principles of Brownian motion have wide application in biology. PMID:24991803
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
Adaptive Randomization to Improve Utility-Based Dose-Finding with Bivariate Ordinal Outcomes
Nguyen, Hoang Q.
2012-01-01
Summary A sequentially outcome-adaptive Bayesian design is proposed for choosing the dose of an experimental therapy based on elicited utilities of a bivariate ordinal (toxicity, efficacy) outcome. Subject to posterior acceptability criteria to control the risk of severe toxicity and exclude unpromising doses, patients are randomized adaptively among the doses having posterior mean utilities near the maximum. The utility increment used to define near-optimality is non-increasing with sample size. The adaptive randomization uses each dose’s posterior probability of a set of good outcomes, defined by a lower utility cut-off. Saturated parametric models are assumed for the marginal dose-toxicity and dose-efficacy distributions, allowing the possible requirement of monotonicity in dose, and a copula is used to obtain a joint distribution. Prior means are computed by simulation using elicited outcome probabilities, and prior variances are calibrated to control prior effective sample size and obtain a design with good operating characteristics. The method is illustrated by a phase I/II trial of radiation therapy for children with brain stem gliomas. PMID:22651115
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.
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.
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.
Study of a global search algorithm for optimal control.
NASA Technical Reports Server (NTRS)
Brocker, D. H.; Kavanaugh, W. P.; Stewart, E. C.
1967-01-01
Adaptive random search algorithm utilizing boundary cost-function hypersurfaces measurement to implement Pontryagin maximum principle, discussing hybrid computer use, iterative solution and convergence properties
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.
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. PMID:27212938
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.
Random Search Algorithm for Solving the Nonlinear Fredholm Integral Equations of the Second Kind
Hong, Zhimin; Yan, Zaizai; Yan, Jiao
2014-01-01
In this paper, a randomized numerical approach is used to obtain approximate solutions for a class of nonlinear Fredholm integral equations of the second kind. The proposed approach contains two steps: at first, we define a discretized form of the integral equation by quadrature formula methods and solution of this discretized form converges to the exact solution of the integral equation by considering some conditions on the kernel of the integral equation. And then we convert the problem to an optimal control problem by introducing an artificial control function. Following that, in the next step, solution of the discretized form is approximated by a kind of Monte Carlo (MC) random search algorithm. Finally, some examples are given to show the efficiency of the proposed approach. PMID:25072373
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.
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. PMID:25784928
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
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.
Simulation study for evaluating the performance of response-adaptive randomization.
Du, Yining; Wang, Xuan; Jack Lee, J
2015-01-01
A response-adaptive randomization (RAR) design refers to the method in which the probability of treatment assignment changes according to how well the treatments are performing in the trial. Holding the promise of treating more patients with the better treatments, RARs have been successfully implemented in clinical trials. We compared equal randomization (ER) with three RARs: Bayesian adaptive randomization, sequential maximum likelihood, and sequential posterior mean. We fixed the total number of patients, considered as patient horizon, but varied the number of patients in the trial. Among the designs, we compared the proportion of patients assigned to the superior arm, overall response rate, statistical power, and total patients enrolled in the trial with and without adding an efficacy early stopping rule. Without early stopping, ER is preferred when the number of patients beyond the trial is much larger than the number of patients in the trial. RAR is favored for large treatment difference or when the number of patients beyond the trial is small. With early stopping, the difference between these two types of designs was reduced. By carefully choosing the design parameters, both RAR and ER methods can achieve the desirable statistical properties. Within three RAR methods, we recommend SPM considering the larger proportion in the better arm and higher overall response rate than BAR and similar power and trial size with ER. The ultimate choice of RAR or ER methods depends on the investigator's preference, the trade-off between group ethics and individual ethics, and logistic considerations in the trial conduct, etc. PMID:25460340
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.
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
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)
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
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. PMID:27409319
Adaptive force produced by stress-induced regulation of random variation intensity.
Shimansky, Yury P
2010-08-01
The Darwinian theory of life evolution is capable of explaining the majority of related phenomena. At the same time, the mechanisms of optimizing traits beneficial to a population as a whole but not directly to an individual remain largely unclear. There are also significant problems with explaining the phenomenon of punctuated equilibrium. From another perspective, multiple mechanisms for the regulation of the rate of genetic mutations according to the environmental stress have been discovered, but their precise functional role is not well understood yet. Here a novel mathematical paradigm called a Kinetic-Force Principle (KFP), which can serve as a general basis for biologically plausible optimization methods, is introduced and its rigorous derivation is provided. Based on this principle, it is shown that, if the rate of random changes in a biological system is proportional, even only roughly, to the amount of environmental stress, a virtual force is created, acting in the direction of stress relief. It is demonstrated that KFP can provide important insights into solving the above problems. Evidence is presented in support of a hypothesis that the nature employs KFP for accelerating adaptation in biological systems. A detailed comparison between KFP and the principle of variation and natural selection is presented and their complementarity is revealed. It is concluded that KFP is not a competing alternative, but a powerful addition to the principle of variation and natural selection. It is also shown KFP can be used in multiple ways for adaptation of individual biological organisms. PMID:20361203
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.
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.
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.
Inversion of seismological data using a controlled random search global optimization technique
NASA Astrophysics Data System (ADS)
Shanker, K.; Mohan, C.; Khattri, K. N.
1991-11-01
Inversion problems in seismology deal with the estimation of the location and the time of occurrence of an earthquake from observations of the arrival time of the body waves. These problems can be regarded as non-linear optimization problems in which the objective function to be minimized is the discrepancy between the recorded arrival times and the calculated arrival times at a prescribed set of observation stations, as a function of the hypocentral parameters and the wave speed structure of the Earth. The objective of the present paper is to demonstrate the effectiveness of a controlled random search algorithm of global optimization (Shanker and Mohan, 1987; Mohan and Shanker, 1988) in solving such types of inversion problems. The performance of the algorithm has been tested on earthquake arrival time data of earthquakes recorded in the vicinity of local networks in the Garhwal Kumaon region of the Himalayas.
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.
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
Random intermittent search and the tug-of-war model of motor-driven transport
NASA Astrophysics Data System (ADS)
Newby, Jay; Bressloff, Paul C.
2010-04-01
We formulate the 'tug-of-war' model of microtubule cargo transport by multiple molecular motors as an intermittent random search for a hidden target. A motor complex consisting of multiple molecular motors with opposing directional preference is modeled using a discrete Markov process. The motors randomly pull each other off of the microtubule so that the state of the motor complex is determined by the number of bound motors. The tug-of-war model prescribes the state transition rates and corresponding cargo velocities in terms of experimentally measured physical parameters. We add space to the resulting Chapman-Kolmogorov (CK) equation so that we can consider delivery of the cargo to a hidden target at an unknown location along the microtubule track. The target represents some subcellular compartment such as a synapse in a neuron's dendrites, and target delivery is modeled as a simple absorption process. Using a quasi-steady-state (QSS) reduction technique we calculate analytical approximations of the mean first passage time (MFPT) to find the target. We show that there exists an optimal adenosine triphosphate (ATP) concentration that minimizes the MFPT for two different cases: (i) the motor complex is composed of equal numbers of kinesin motors bound to two different microtubules (symmetric tug-of-war model) and (ii) the motor complex is composed of different numbers of kinesin and dynein motors bound to a single microtubule (asymmetric tug-of-war model).
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
NASA Astrophysics Data System (ADS)
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 ωm. 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 ωm-dependent optimal frequency ω =ωopt 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)
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.
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 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
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
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
Cassin, Stephanie E; von Ranson, Kristin M; Heng, Kenneth; Brar, Joti; Wojtowicz, Amy E
2008-09-01
In this randomized controlled trial, 108 women with binge-eating disorder (BED) recruited from the community were assigned to either an adapted motivational interviewing (AMI) group (1 individual AMI session + self-help handbook) or control group (handbook only). They were phoned 4, 8, and 16 weeks following the initial session to assess binge eating and associated symptoms (depression, self-esteem, quality of life). Postintervention, the AMI group participants were more confident than those in the control group in their ability to change binge eating. Although both groups reported improved binge eating, mood, self-esteem, and general quality of life 16 weeks following the intervention, the AMI group improved to a greater extent. A greater proportion of women in the AMI group abstained from binge eating (27.8% vs. 11.1%) and no longer met the binge frequency criterion of the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000) for BED (87.0% vs. 57.4%). AMI may constitute a brief, effective intervention for BED and associated symptoms. PMID:18778135
Analysis of (1+1) evolutionary algorithm and randomized local search with memory.
Sung, Chi Wan; Yuen, Shiu Yin
2011-01-01
This paper considers the scenario of the (1+1) evolutionary algorithm (EA) and randomized local search (RLS) with memory. Previously explored solutions are stored in memory until an improvement in fitness is obtained; then the stored information is discarded. This results in two new algorithms: (1+1) EA-m (with a raw list and hash table option) and RLS-m+ (and RLS-m if the function is a priori known to be unimodal). These two algorithms can be regarded as very simple forms of tabu search. Rigorous theoretical analysis of the expected time to find the globally optimal solutions for these algorithms is conducted for both unimodal and multimodal functions. A unified mathematical framework, involving the new concept of spatially invariant neighborhood, is proposed. Under this framework, both (1+1) EA with standard uniform mutation and RLS can be considered as particular instances and in the most general cases, all functions can be considered to be unimodal. Under this framework, it is found that for unimodal functions, the improvement by memory assistance is always positive but at most by one half. For multimodal functions, the improvement is significant; for functions with gaps and another hard function, the order of growth is reduced; for at least one example function, the order can change from exponential to polynomial. Empirical results, with a reasonable fitness evaluation time assumption, verify that (1+1) EA-m and RLS-m+ are superior to their conventional counterparts. Both new algorithms are promising for use in a memetic algorithm. In particular, RLS-m+ makes the previously impractical RLS practical, and surprisingly, does not require any extra memory in actual implementation. PMID:20868262
Pelham, William E; Fabiano, Gregory A; Waxmonsky, James G; Greiner, Andrew R; Gnagy, Elizabeth M; Pelham, William E; Coxe, Stefany; Verley, Jessica; Bhatia, Ira; Hart, Katie; Karch, Kathryn; Konijnendijk, Evelien; Tresco, Katy; Nahum-Shani, Inbal; Murphy, Susan A
2016-01-01
Behavioral and pharmacological treatments for children with attention deficit/hyperactivity disorder (ADHD) were evaluated to address whether endpoint outcomes are better depending on which treatment is initiated first and, in case of insufficient response to initial treatment, whether increasing dose of initial treatment or adding the other treatment modality is superior. Children with ADHD (ages 5-12, N = 146, 76% male) were treated for 1 school year. Children were randomized to initiate treatment with low doses of either (a) behavioral parent training (8 group sessions) and brief teacher consultation to establish a Daily Report Card or (b) extended-release methylphenidate (equivalent to .15 mg/kg/dose bid). After 8 weeks or at later monthly intervals as necessary, insufficient responders were rerandomized to secondary interventions that either increased the dose/intensity of the initial treatment or added the other treatment modality, with adaptive adjustments monthly as needed to these secondary treatments. The group beginning with behavioral treatment displayed significantly lower rates of observed classroom rule violations (the primary outcome) at study endpoint and tended to have fewer out-of-class disciplinary events. Further, adding medication secondary to initial behavior modification resulted in better outcomes on the primary outcomes and parent/teacher ratings of oppositional behavior than adding behavior modification to initial medication. Normalization rates on teacher and parent ratings were generally high. Parents who began treatment with behavioral parent training had substantially better attendance than those assigned to receive training following medication. Beginning treatment with behavioral intervention produced better outcomes overall than beginning treatment with medication. PMID:26882332
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
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
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
NASA Astrophysics Data System (ADS)
Palyulin, Vladimir V.; Chechkin, Aleksei V.; Metzler, Ralf
2014-11-01
Based on the space-fractional Fokker-Planck equation with a δ-sink term, we study the efficiency of random search processes based on Lévy flights with power-law distributed jump lengths in the presence of an external drift, for instance, an underwater current, an airflow, or simply the preference of the searcher based on prior experience. While Lévy flights turn out to be efficient search processes when the target is upstream relative to the starting point, in the downstream scenario, regular Brownian motion turns out to be advantageous. This is caused by the occurrence of leapovers of Lévy flights, due to which Lévy flights typically overshoot a point or small interval. Studying the solution of the fractional Fokker-Planck equation, we establish criteria when the combination of the external stream and the initial distance between the starting point and the target favours Lévy flights over the regular Brownian search. Contrary to the common belief that Lévy flights with a Lévy index α = 1 (i.e. Cauchy flights) are optimal for sparse targets, we find that the optimal value for α may range in the entire interval (1, 2) and explicitly include Brownian motion as the most efficient search strategy overall.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
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
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
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
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. PMID:24683321
Search on a hypercubic lattice using a quantum random walk. II. d=2
Patel, Apoorva; Raghunathan, K. S.; Rahaman, Md. Aminoor
2010-09-15
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. A 82, 032330 (2010)] provides an O({radical}(N)lnN) algorithm, which is not optimal. The scaling behavior can be improved to O({radical}(NlnN)) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi [Phys. Rev. A 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.
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
NASA Astrophysics Data System (ADS)
Ivanov, Mark V.; Levitsky, Lev I.; Gorshkov, Mikhail V.
2016-06-01
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. PMID:27349255
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. .
Identification of the Jiles-Atherton model parameters using random and deterministic searches
NASA Astrophysics Data System (ADS)
Del Moral Hernandez, Emilio; S. Muranaka, Carlos; Cardoso, José R.
2000-01-01
The five parameters of the Jiles-Atherton (J-A) model are identified using a simple program based on the Matlab platform which identifies the J-A parameters automatically from experimental B- H hysteresis curves of magnetic cores. This computational tool is based on adaptive adjustment of the J-A model parameters and conjugates its parametric non-linear coupled differential equations with techniques of simulated annealing.
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 the projection-slice theorem for stock valuation estimation using random Markov fields
NASA Astrophysics Data System (ADS)
Riasati, Vahid R.
2009-04-01
The Projection-Slice Synthetic Discriminant function filter is utilized with Random Markov Fields, RMF to estimate trends that may be used as prediction for stock valuation through the representation of the market behavior as a hidden Markov Model, HMM. In this work, we utilize a set of progressive and contiguous time segments of a given stock, and treat the set as a two dimensional object that has been represented by its one-d projections. The abstract two-D object is thus an incarnation of N-temporal projections. The HMM is then utilized to generate N+1 projections that maximizes the two-dimensional correlation peak between the data and the HMM-generated stochastic processes. This application of the PSDF provides a method of stock valuation prediction via the market stochastic behavior utilized in the filter.
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
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
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.
Hu, Yu-Chi J; Grossberg, Michael D; Mageras, Gikas S
2008-01-01
Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the entire 3D stack of images without using the geometric correspondence between images. In addition, the image segmentation from the CRF can be formulated as a minimum s-t graph cut problem which has a solution that is both globally optimal and fast. The combination of a fast segmentation and minimal user input that is reusable, make this a powerful technique for the segmentation of medical images. PMID:19163362
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)
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.
Gyllenhaal, C.; Kadushin, M.R.; Southavong, B.; Sydara, K.; Bouamanivong, S.; Xaiveu, M.; Xuan, L.T.; Hiep, N.T.; Hung, N.V.; Loc, P.K.; Dac, L.X.; Bich, T.Q.; Cuong, N.M.; Ly, H.M.; Zhang, H.J.; Franzblau, S.G.; Xie, H.; Riley, M.C.; Elkington, B.G.; Nguyen, H.T.; Waller, D.P.; Ma, C.Y.; Tamez, P.; Tan, G.T.; Pezzuto, J.M.; Soejarto, D.D.
2012-01-01
Context Whether natural product drug discovery programs should rely on wild plants collected “randomly” from the natural environment, or whether they should also include plants collected on the basis of use in traditional medicine remains an open question. Objective This study analyzes whether plants with ethnomedical uses from Vietnam and Laos have a higher hit rate in bioassay testing than plants collected from a national park in Vietnam with the goal of maximizing taxonomic diversity (“random” collection). Materials and Methods All plants were extracted and subjected to bioassay in the same laboratories. Results of assays of plant collections and plant parts (samples) were scored as active or inactive based on whether any extracts had a positive result in a bioassay. Contingency tables were analyzed using χ2 statistics. Results Random collections had a higher hit rate than ethnomedical collections, but for samples, ethnomedical plants were more likely to be active. Ethnomedical collections and samples had higher hit rates for tuberculosis, while samples, but not collections, had a higher hit rate for malaria. Little evidence was found to support an advantage for ethnomedical plants in HIV, chemoprevention and cancer bioassays. Plants whose ethnomedical uses directly correlated to a bioassay did not have a significantly higher hit rate than random plants. Discussion Plants with ethnomedical uses generally had a higher rate of activity in some drug discovery bioassays, but the assays did not directly confirm specific uses. Conclusions Ethnomedical uses may contribute to a higher rate of activity in drug discovery screening. PMID:22196581
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
Image retargeting using non-uniform scaling with adaptive local search window
NASA Astrophysics Data System (ADS)
Wang, Shanshan; Abdel-Dayem, Amr
2011-10-01
This paper presents a new content-aware image-retargeting scheme, based on non-uniform scaling, to adaptively adjust the image's dimensions for various screen sizes. Based on an importance map, the energy contribution for each line in the reduced dimension to the overall energy within the image is computed. Then, the image is adaptively mapped and resampled based on the energy contribution function. Experimental results showed that the performance of the proposed scheme is comparable to seam carving in visual quality. However, it is computationally less expensive.
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
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. PMID:26387049
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
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…
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. PMID:24919961
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.
Santos, Glenn-Milo; Colfax, Grant; Das, Moupali; Matheson, Tim; DeMicco, Erin; Dilley, James; Vittinghoff, Eric; Raiford, Jerris L.; Carry, Monique; Herbst, Jeffrey H.
2015-01-01
Episodic drug use and binge drinking are associated with HIV risk among substance-using men who have sex with men (SUMSM), yet no evidence-based interventions exist for these men. We adapted personalized cognitive counseling (PCC) to address self-justifications for high-risk sex among HIV-negative, episodic SUMSM, then randomized men to PCC (n = 162) with HIV testing or control (n = 164) with HIV testing alone. No significant between-group differences were found in the three primary study outcomes: number of unprotected anal intercourse events (UAI), number of UAI partners, and UAI with three most recent non-primary partners. In a planned subgroup analysis of non-substance dependent men, there were significant reductions in UAI with most recent non-primary partners among PCC participants (RR = 0.56; 95 %CI 0.34–0.92; P = 0.02). We did not find evidence that PCC reduced sexual risk behaviors overall, but observed significant reductions in UAI events among non-dependent SUMSM. PCC may be beneficial among SUMSM screening negative for substance dependence. PMID:24510401
NASA Astrophysics Data System (ADS)
Grayver, Alexander V.; Kuvshinov, Alexey V.
2016-02-01
This paper presents a methodology to sample equivalence domain (ED) in non-linear 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 (MCMC) 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.
Fogel, Catherine I.; Crandell, Jamie L.; Neevel, A. M.; Parker, Sharon D.; Carry, Monique; White, Becky L.; Fasula, Amy M.; Herbst, Jeffrey H.; Gelaude, Deborah J.
2014-01-01
Objectives We tested the efficacy of an adapted evidence-based HIV–sexually transmitted infection (STI) behavioral intervention (Providing Opportunities for Women′s Empowerment, Risk-Reduction, and Relationships, or POWER) among incarcerated women. Methods We conducted a randomized trial with 521 women aged 18 to 60 years in 2 correctional facilities in North Carolina in 2010 and 2011. Intervention participants attended 8 POWER sessions; control participants received a single standard-of-care STI prevention session. We followed up at 3 and 6 months after release. We examined intervention efficacy with mixed-effects models. Results POWER participants reported fewer male sexual partners than did control participants at 3 months, although this finding did not reach statistical significance; at 6 months they reported significantly less vaginal intercourse without a condom outside of a monogamous relationship and more condom use with a main male partner. POWER participants also reported significantly fewer condom barriers, and greater HIV knowledge, health-protective communication, and tangible social support. The intervention had no significant effects on incident STIs. Conclusions POWER is a behavioral intervention with potential to reduce risk of acquiring or transmitting HIV and STIs among incarcerated women returning to their communities. PMID:25211714
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.
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
Armstrong, Jerawan C.; Favorite, Jeffrey A.
2012-06-20
The Levenberg-Marquardt (or simply Marquardt) and differential evolution (DE) optimization methods were recently applied to solve inverse transport problems. The Marquardt method is fast but convergence of the method is dependent on the initial guess. While it has been shown to work extremely well at finding an optimum independent of the initial guess, the DE method does not provide a global optimal solution in some problems. In this paper, we apply the Mesh Adaptive Direct Search (MADS) algorithm to solve the inverse problem of material interface location identification in one-dimensional spherical radiation source/shield systems, and we compare the results obtained by MADS to those obtained by Levenberg-Marquardt and DE.
Putungan, Darwin Barayang; Lin, Shi-Hsin; Wei, Ching-Ming; Kuo, Jer-Lai
2015-05-01
Utilizing ab initio random structure searching, we investigated Li adsorption on MoS2 and hydrogen molecules on Li-decorated MoS2. In contrast to graphene, Li can be adsorbed on both sides of MoS2, with even stronger binding than on the single side. We found that high coverages of Li can be attained without Li clustering, which is essential for hydrogen storage and Li ion batteries. Moreover, regarding battery applications, Li diffusion was also found to be easy. The fully-lithiated MoS2 can then adsorb H2 with 4.4 wt%. Interestingly, our calculations revealed that hydrogen molecules can be dissociated at high Li coverage with a minimal energy barrier. We further showed that the dissociated hydrogen atom can readily diffuse on the surface, thus keeping the reaction site active. We therefore propose that Li-MoS2 could be an inexpensive alternative catalyst to noble metals in hydrogen dissociation reactions. PMID:25849099
Searching for the dust/molecular torus in a typical AGN using adaptive optics
NASA Astrophysics Data System (ADS)
Marco, O.; Alloin, D.
Adaptive optics systems are now routinely operated on several 4 meter class telescopes, allowing to achieve angular resolutions down to 70 msec in the near-infrared. Although these systems have excellent performances, their use for exploring the physics and structure of AGN is still limited for the following reasons: the limiting magnitude of the wavefront sensor is too high, the sensitivity of infrared detectors does not give access to medium/high spectral solution spectroscopy and the angular resolution achieved does not always fit the apparent size of the physical components responsible for emission features close to the central engine. The new generation of 8-10m class telescopes bring improvements in this matter. However, some interesting results have been obtained so far with Adonis, the ESO La Silla adaptive optics system on the 3.60 meter telescope, in the investigation of AGN structure. In particular, a prominent structure has been detected in the central arcsec core of NGC 1068, which might feature the dusty/molecular torus expected on theoretical grounds.
Searching for the Dust/Molecular Torus in a Typical AGN using Adaptive Optics
NASA Astrophysics Data System (ADS)
Marco, O.; Alloin, D.
Adaptive Optics systems are now routinely operated on several 4 meter class telescopes, allowing to achieve angular resolutions down to 70 msec in the near-infrared. Although these systems have excellent performances, their use for exploring the physics and structure of AGN is still limited for the following reasons: the limiting magnitude of the wavefront sensor is too high, the sensitivity of infrared detectors does not give access to medium/high spectral resolution spectroscopy and the angular resolution achieved does not always fit the apparent size of the physical components responsible for emission features close to the central engine. The new generation of 8-10 m class telescopes bring improvements in this matter. However, some interesting results have been obtained so far with Adonis, the ESO La Silla adaptive optics system on the 3.60 meter telescope, in the investigation of AGN structure. In particular, a prominent structure has been detected in the central arcs! ec core of NGC1068, which might feature the dusty/molecular torus expected on theoretical grounds.
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
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
The local enhancement conundrum: in search of the adaptive value of a social learning mechanism.
Arbilly, Michal; Laland, Kevin N
2014-02-01
Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer-scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed. PMID:24044984
Biogenic hydrogen peroxide as a possible adaptation of life on Mars: the search for biosignatures
NASA Astrophysics Data System (ADS)
Houtkooper, J. M.; Schulze-Makuch, D.
2007-08-01
The hypothesis that putative Martian organisms incorporate H2O2 into their intracellular liquids (Houtkooper and Schulze-Makuch, 2007) has significant implications, as it explains the Viking observations quite well; it provides a functional adaptation to Martian environmental conditions; and, it is feasible as an adaptation based on the biochemistry of terrestrial organisms. It would explain many of the puzzling Viking observations such as (1) the lack of organics detected by GC-MS, (2) the lack of detected oxidant(s) to support a chemical explanation, (3) evolution of O2 upon wetting (GEx experiment), (4) limited organic synthesis reactions (PR experiment), and (5) the gas release observations made (LR experiment). An intracellular liquid containing a high concentration of H2O2 has advantages such as providing a low freezing point, a source of oxygen, and hygroscopicity, allowing an organism to obtain water vapor from the Martian atmosphere or from the adsorbed layers of water molecules on mineral grains. Perhaps surprisingly, H2O2 is used by many terrestrial organisms for diverse purposes, e.g., metabolism (Acetobacter peroxidans), as defense mechanism (Bombardier beetle), and also to mediate diverse physiological responses such as cell proliferation, differentiation, and migration. The detection of H2O2-containing organisms may well suffer from the same problems as the Viking experiments: Because of the excess oxidative contents, as derived from the GEx experiment, the organisms may decompose completely into H2O, CO2, O2 and N2. This can happen when exposed to an excess of water vapor (through hyperhydration), too high a temperature or a combination of both. Therefore, the addition of too much water vapor may be fatal. Moreover, employing pyrolysis in order to detect organic molecules may result in the organisms autooxidizing completely. Although the instrument suite aboard the Phoenix Lander offers some interesting possibilities (Schulze-Makuch and Houtkooper
High-contrast Adaptive Optics and a Search for Late-type Companions to Hyades FGK Dwarfs
NASA Astrophysics Data System (ADS)
Morzinski, Katie M.
2011-01-01
The Hyades is an intermediate-age open cluster with hundreds of main-sequence stars and is thus well-suited to stellar formation and evolution studies. Being nearby with high proper motion, it is a choice cluster for direct-imaging surveys. We conduct a high-contrast adaptive optics (AO) search for late-type companions as faint as MH 15 (late-L/early-T) within 5-230 AU around 88 FGK main-sequence Hyades dwarfs. Departures from the ideal point-spread function (PSF) in the image plane are caused by phase and amplitude errors that redistribute stellar light and limit the achievable contrast. An AO system on a ground-based telescope mitigates the phase errors in the pupil, but constructive interference of spatially coherent light causes amplitude spikes in the PSF called speckles. The locally-optimized combination of images (LOCI) algorithm is used to identify and subtract the quasistatic speckles and static PSF structure, allowing imaging of faint point-source companions. We use LOCI on deep near-infrared AO Hyad imaging at Keck and Lick Observatories. Background objects are subsequently ruled out by comparing relative astrometry in two epochs separated by five years. We present our confirmed Hyades companions. Furthermore, we look ahead to AO for exoplanet-imaging wherein a ''dark hole'' in the PSF facilitates high-contrast imaging. The size of the dark hole is set by the highest spatial frequency controllable by the deformable mirror (DM). Decreasing rejection at increasing spatial frequencies reduces the correction efficiency within the high-contrast region, owing to the nature of the MEMS (micro-electro-mechanical systems) DM transfer function. This effect can be mitigated by a dual-DM ''woofer/tweeter'' AO system whereby each DM controls a different spatial frequency regime. We present empirical results on selecting a woofer DM in order to maintain the dark hole for the upcoming Gemini Planet Imager. (Supported by NASA Michelson Fellowship, NSF Center for
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.
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
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. PMID:25492049
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
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
Chemaly, Roy F.; Torres, Harrys A.; Munsell, Mark F.; Shah, Dimpy P.; Rathod, Dhanesh B.; Bodey, Gerald P.; Hosing, Chitra; Saifan, Chadi; Raad, Issam I.; Champlin, Richard E.
2012-01-01
A continuous dosing schedule of aerosolized ribavirin has been used for respiratory syncytial virus (RSV) upper respiratory tract infection and lower respiratory tract infection (LRTI) but is associated with high cost and inconvenient administration. We conducted an adaptive randomized trial to evaluate the effectiveness of an intermittent dosing schedule of ribavirin versus that of a continuous dosing schedule of ribavirin in preventing RSV LRTIs in 50 hematopoietic stem cell transplant recipients or patients with hematologic malignancies. LRTI occurred in 3 patients (9%) receiving the intermittent schedule and in 4 (22%) receiving the continuous schedule, with a 0.889 posterior probability. Because the intermittent schedule is easy to administer and has a higher efficacy than the continuous schedule, we recommend the intermittent schedule for patients who are at risk for RSV LRTI. Clinical Trials Registration. NCT00500578. PMID:22927454
Spence, Angela L; Carter, Howard H; Naylor, Louise H; Green, Daniel J
2013-03-01
Abstract 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 (ET, 1.4 ± 1.8 kg and RT, 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
Alomari, Yazan M.; MdZin, Reena Rahayu
2015-01-01
Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved. PMID:25793010
Alomari, Yazan M; Sheikh Abdullah, Siti Norul Huda; MdZin, Reena Rahayu; Omar, Khairuddin
2015-01-01
Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved. PMID:25793010
NASA Astrophysics Data System (ADS)
Kaplan, Sezgin; Rabadi, Ghaith
2013-01-01
This article addresses the aerial refuelling scheduling problem (ARSP), where a set of fighter jets (jobs) with certain ready times must be refuelled from tankers (machines) by their due dates; otherwise, they reach a low fuel level (deadline) incurring a high cost. ARSP is an identical parallel machine scheduling problem with release times and due date-to-deadline windows to minimize the total weighted tardiness. A simulated annealing (SA) and metaheuristic for randomized priority search (Meta-RaPS) with the newly introduced composite dispatching rule, apparent piecewise tardiness cost with ready times (APTCR), are applied to the problem. Computational experiments compared the algorithms' solutions to optimal solutions for small problems and to each other for larger problems. To obtain optimal solutions, a mixed integer program with a piecewise weighted tardiness objective function was solved for up to 12 jobs. The results show that Meta-RaPS performs better in terms of average relative error but SA is more efficient.
NASA Astrophysics Data System (ADS)
Schwalger, T.; Miklody, D.; Lindner, B.
2013-10-01
Sequences of first-passage times can describe the interspike intervals (ISI) between subsequent action potentials of sensory neurons. Here, we consider the ISI statistics of a stochastic neuron model, a leaky integrate-and-fire neuron, which is driven by a strong mean input current, white Gaussian current noise, and a spike-frequency adaptation current. In previous studies, it has been shown that without a leak current, i.e. for a so-called perfect integrate-and-fire (PIF) neuron, the ISI density can be well approximated by an inverse Gaussian corresponding to the first-passage-time density of a biased random walk. Furthermore, the serial correlations between ISIs, which are induced by the adaptation current, can be described by a geometric series. By means of stochastic simulations, we inspect whether these results hold true in the presence of a modest leak current. Specifically, we measure mean and variance of the ISI in the full model with leak and use the analytical results for the perfect IF model to relate these cumulants of the ISI to effective values of the mean input and noise intensity of an equivalent perfect IF model. This renormalization procedure yields semi-analytical approximations for the ISI density and the ISI serial correlation coeffcient in the full model with leak. We find that both in the absence and the presence of an adaptation current, the ISI density can be well approximated in this way if the leak current constitutes only a weak modification of the dynamics. Moreover, also the serial correlations of the model with leak are well reproduced by the expressions for a PIF model with renormalized parameters. Our results explain, why expressions derived for the rather special perfect integrate-and-fire model can nevertheless be often well fit to experimental data.
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
Rixen, Dieter; Steinhausen, Eva; Sauerland, Stefan; Lefering, Rolf; Meier, Matthias; Maegele, Marc G; Bouillon, Bertil; Neugebauer, Edmund AM
2009-01-01
Background Fractures of the long bones and femur fractures in particular are common in multiple trauma patients, but the optimal management of femur fractures in these patients is not yet resolved. Although there is a trend towards the concept of "Damage Control Orthopedics" (DCO) in the management of multiple trauma patients with long bone fractures as reflected by a significant increase in primary external fixation of femur fractures, current literature is insufficient. Thus, in the era of "evidence-based medicine", there is the need for a more specific, clarifying trial. Methods/Design The trial is designed as a randomized controlled open-label multicenter study. Multiple trauma patients with femur shaft fractures and a calculated probability of death between 20 and 60% will be randomized to either temporary fracture fixation with fixateur externe and defined secondary definitive treatment (DCO) or primary reamed nailing (early total care). The primary objective is to reduce the extent of organ failure as measured by the maximum sepsis-related organ failure assessment (SOFA) score. Discussion The Damage Control Study is the first to evaluate the risk adapted damage control orthopedic surgery concept of femur shaft fractures in multiple trauma patients in a randomized controlled design. The trial investigates the differences in clinical outcome of two currently accepted different ways of treating multiple trauma patients with femoral shaft fractures. This study will help to answer the question whether the "early total care" or the „damage control” concept is associated with better outcome. Trial registration Current Controlled Trials ISRCTN10321620 PMID:19691847
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
Holzapfel, L; Chastang, C; Demingeon, G; Bohe, J; Piralla, B; Coupry, A
1999-03-01
The objective of this randomized study was to compare the occurrence of nosocomial pneumonia in nasotracheally intubated patients who were randomly allocated either to a systematic search of sinusitis by CT scan (study group) or not (control group). A total of 399 patients were included: 272 male and 127 female; mean age, 61 +/- 17 yr; SAPS: 12.6 +/- 4.9. The study group consisted of 199 patients and the control group consisted of 200. In the study group, sinus CT scans were performed in case of fever at Days 4 and 8 and then every 7 d. Nosocomial sinusitis was defined as follows: fever of >/= 38 degrees C, radiographic (sinusal air-fluid level or opacification on CT scan) signs, and presence of purulent aspirate from the involved sinus puncture with >/= 10(3) cfu/ml. Patients with sinusitis received sinus lavage and intravenously administered antibiotics. In the study group, 80 patients experienced nosocomial sinusitis. In the control group, no patient was treated for a sinusitis. Ventilator-associated bronchopneumonia (VAP) was observed in 88 patients: 37 in the study group (1 mo Kaplan-Meier estimate, 34%) versus 51 in the control group (1 mo Kaplan-Meier estimate, 47%); (p = 0.02, log-rank test; relative risk [RR] = 0.61; 95% confidence interval [CI], 0.40 to 0.93). Two months overall mortality was estimated at 36% in the study group versus 46% in the control group (p = 0.03, log-rank test; RR = 0.71; 95% CI, 0.52 to 0.97). We conclude that the occurrence of VAP in patients undergoing prolonged mechanical ventilation via a nasotracheal intubation can be prevented by the systematic search and treatment of nosocomial sinusitis. The effect on mortality should be confirmed. PMID:10051239
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. PMID:24667833
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
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.
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
Searching for Binary Y dwarfs with the Gemini GeMS Multi-Conjugate Adaptive Optics System
NASA Astrophysics Data System (ADS)
Opitz, Daniela; Tinney, Chris
2015-01-01
The NASA Wide-field Infrared Survey Explorer (WISE) has delivered an exceptional harvest of new ultra-cool Y-type brown dwarfs. We present results from a diffraction-limited study of the binary status of a sample of Y dwarfs observed with the Gemini GeMS Multi-Conjugate Adaptive Optics System. We report no evidence of equal mass/luminosity binaries at separations larger than ˜ 0.5-2.0 AU for five Y dwarfs.
2013-01-01
Background Failure of locoregional control is the main cause of recurrence in advanced head and neck cancer. This multi-center trial aims to improve outcome in two ways. Firstly, by redistribution of the radiation dose to the metabolically most FDG-PET avid part of the tumour. Hereby, a biologically more effective dose distribution might be achieved while simultaneously sparing normal tissues. Secondly, by improving patient selection. Both cisplatin and Epidermal Growth Factor Receptor (EGFR) antibodies like Cetuximab in combination with Radiotherapy (RT) are effective in enhancing tumour response. However, it is unknown which patients will benefit from either agent in combination with irradiation. We will analyze the predictive value of biological markers and 89Zr-Cetuximab uptake for treatment outcome of chemoradiation with Cetuximab or cisplatin to improve patient selection. Methods ARTFORCE is a randomized phase II trial for 268 patients with a factorial 2 by 2 design: cisplatin versus Cetuximab and standard RT versus redistributed RT. Cisplatin is dosed weekly 40 mg/m2 for 6 weeks. Cetuximab is dosed 250mg/m2 weekly (loading dose 400 mg/m2) for 6 weeks. The standard RT regimen consists of elective RT up to 54.25 Gy with a simultaneous integrated boost (SIB) to 70 Gy in 35 fractions in 6 weeks. Redistributed adaptive RT consists of elective RT up to 54.25 Gy with a SIB between 64-80 Gy in 35 fractions in 6 weeks with redistributed dose to the gross tumour volume (GTV) and clinical target volume (CTV), and adaptation of treatment for anatomical changes in the third week of treatment. Patients with locally advanced, biopsy confirmed squamous cell carcinoma of the oropharynx, oral cavity or hypopharynx are eligible. Primary endpoints are: locoregional recurrence free survival at 2 years, correlation of the median 89Zr-cetuximab uptake and biological markers with treatment specific outcome, and toxicity. Secondary endpoints are quality of life, swallowing function
Safer, Debra L.; Robinson, Athena Hagler; Jo, Booil
2011-01-01
Dialectical Behavior Therapy for Binge Eating Disorder (DBT-BED) aims to reduce binge eating by improving adaptive emotion-regulation skills. Preliminary findings have been promising but have only compared DBT-BED to a wait-list. To control for the hypothesized specific effects of DBT-BED, the present study compared DBT-BED to an active comparison group therapy (ACGT). Men and women (n = 101) meeting DSM-IV BED research criteria were randomly assigned to 20 group sessions of DBT-BED (n = 50) or ACGT (n = 51). DBT-BED had a significantly lower dropout rate (4%) than ACGT (33.3%). Linear Mixed Models revealed that posttreatment binge abstinence and reductions in binge frequency were achieved more quickly for DBT-BED than for ACGT (posttreatment abstinence rate = 64% for DBT-BED vs. 36% for ACGT) though differences did not persist over the 3-, 6-, and 12-month follow-up assessments (e.g., 12-month follow-up abstinence rate = 64% for DBT-BED vs. 56% for ACGT). Secondary outcome measures revealed no sustained impact on emotion regulation. Although both DBT-BED and ACGT reduced binge eating, DBT-BED showed significantly fewer dropouts and greater initial efficacy (e.g., at posttreatment) than ACGT. The lack of differential findings over follow-up suggests that the hypothesized specific effects of DBT-BED do not show long-term impact beyond those attributable to nonspecific common therapeutic factors. PMID:20171332
Wang, Zun; Wang, Lei; Fan, Hongjuan; Jiang, Wenjun; Wang, Sheng; Gu, Zhaohua; Wang, Tong
2014-01-01
[Purpose] To evaluate the feasibility and efficacy of adapted low intensity ergometer aerobic training for early and severely impaired stroke survivors. [Subjects] The subjects were forty-eight early stroke survivors. [Methods] Eligible subjects were recruited and randomly assigned to an experimental group and a control group. Both groups participated in comprehensive rehabilitation training. Low intensity aerobic training was only performed by the experimental group. Outcome measures were the Fugl-Meyer motor score, Barthel index, exercise test time, peak heart rate, plasma glucose level and serum lipid profiles. [Results] Patients in the experimental group finished 88.6% of the total aerobic training sessions prescribed. In compliant participants (adherence≥80%), aerobic training significantly improved the Barthel index (from 40.1±21.1 to 79.2±14.2), Fugl-Meyer motor score (from 26.4±19.4 to 45.4±12.7), exercise test time (from 12.2±3.62 min to 13.9±3.6 min), 2-hour glucose level (from 9.22±1.16 mmol/L to 7.21±1.36 mmol/L) and homeostasis model of assessment for insulin resistence index (from 1.72±1.01 to 1.28±0.88). [Conclusion] Preliminary findings suggest that early and severely impaired stroke patients may benefit from low intensity ergometer aerobic training. PMID:25276034
HE, YI; XIAO, YI; LIWO, ADAM; SCHERAGA, HAROLD A.
2009-01-01
We explored the energy-parameter space of our coarse-grained UNRES force field for large-scale ab initio simulations of protein folding, to obtain good initial approximations for hierarchical optimization of the force field with new virtual-bond-angle bending and side-chain-rotamer potentials which we recently introduced to replace the statistical potentials. 100 sets of energy-term weights were generated randomly, and good sets were selected by carrying out replica-exchange molecular dynamics simulations of two peptides with a minimal α-helical and a minimal β-hairpin fold, respectively: the tryptophan cage (PDB code: 1L2Y) and tryptophan zipper (PDB code: 1LE1). Eight sets of parameters produced native-like structures of these two peptides. These eight sets were tested on two larger proteins: the engrailed homeodomain (PDB code: 1ENH) and FBP WW domain (PDB code: 1E0L); two sets were found to produce native-like conformations of these proteins. These two sets were tested further on a larger set of nine proteins with α or α + β structure and found to locate native-like structures of most of them. These results demonstrate that, in addition to finding reasonable initial starting points for optimization, an extensive search of parameter space is a powerful method to produce a transferable force field. PMID:19242966
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
VLT adaptive optics search for luminous substructures in the lens galaxy towards SDSS J0924+0219
NASA Astrophysics Data System (ADS)
Faure, C.; Sluse, D.; Cantale, N.; Tewes, M.; Courbin, F.; Durrer, P.; Meylan, G.
2011-12-01
The anomalous flux ratios between quasar images are suspected of being caused by substructures in lens galaxies. We present new deep and high-resolution H and Ks imaging of the strongly lensed quasar SDSS J0924+0219 obtained using the ESO VLT with adaptive optics and the laser guide star system. SDSS J0924+0219 is particularly interesting because the observed flux ratio between the quasar images vastly disagree with the predictions from smooth mass models. With our adaptive optics observations we find a luminous object, Object L, located ~0.3'' to the north of the lens galaxy, but we show that it cannot be responsible for the anomalous flux ratios. Object L as well as a luminous extension of the lens galaxy to the south are seen in the archival HST/ACS image in the F814W filter. This suggests that Object L is part of a bar in the lens galaxy, as also supported by the presence of a significant disk component in the light profile of the lens galaxy. Finally, we find no evidence of any other luminous substructure that may explain the quasar images flux ratios. However, owing to the persistence of the flux ratio anomaly over time (~7 years), a combination of microlensing and millilensing is the favorite explanation for the observations. Based on observations obtained with the ESO VLT at Paranal observatory (Prog ID 084.A-0762(A); PI: Meylan). Also based in part on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with the CASTLES (Cfa-Arizona Space Telescope LEns Survey) survey (ID: 9744, PI: C. S. Kochanek).
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
2010-01-01
Background The primary aim of this study was to compare the efficacy of three physical activity (PA) behavioural intervention strategies in a sample of adults with type 2 diabetes. Method/Design Participants (N = 287) were randomly assigned to one of three groups consisting of the following intervention strategies: (1) standard printed PA educational materials provided by the Canadian Diabetes Association [i.e., Group 1/control group)]; (2) standard printed PA educational materials as in Group 1, pedometers, a log book and printed PA information matched to individuals' PA stage of readiness provided every 3 months (i.e., Group 2); and (3) PA telephone counseling protocol matched to PA stage of readiness and tailored to personal characteristics, in addition to the materials provided in Groups 1 and 2 (i.e., Group 3). PA behaviour measured by the Godin Leisure Time Exercise Questionnaire and related social-cognitive measures were assessed at baseline, 3, 6, 9, 12 and 18-months (i.e., 6-month follow-up). Clinical (biomarkers) and health-related quality of life assessments were conducted at baseline, 12-months, and 18-months. Linear Mixed Model (LMM) analyses will be used to examine time-dependent changes from baseline across study time points for Groups 2 and 3 relative to Group 1. Discussion ADAPT will determine whether tailored but low-cost interventions can lead to sustainable increases in PA behaviours. The results may have implications for practitioners in designing and implementing theory-based physical activity promotion programs for this population. Clinical Trials Registration ClinicalTrials.gov identifier: NCT00221234 PMID:20067626
Searching for Binary Y dwarfs with the Gemini Multi-Conjugate Adaptive Optics System (GeMS)
NASA Astrophysics Data System (ADS)
Opitz, Daniela; Tinney, Chris
2015-08-01
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 be closely separated and are more frequently detected in near-equal mass configurations. The binary status of Y- type brown dwarfs is still unclear and therefore, determining if Y-type primaries hold the same trend, is of considerable interest. 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 from a diffraction-limited study of a sample of five WISE Y dwarfs observed with the Gemini Multi-Conjugate Adaptive Optics System (GeMS). We find no evidence for binary companions in these data, which suggests these systems are not equal luminosity (or equivalently equal mass) binaries at separations larger than ~ 0.3-1.9 AU.
Hawker, P C; Morris, A I; McKay, J; Turnberg, L A
1980-01-01
To explore the possibility that small intestinal 'adaptation' may occur after colectomy we examined the ability of ileal mucosal biopsies, taken from patients with ileostomies, to transport electrolytes in vitro. Ileostomy mucosal electrical potential difference was higher (5.4+/-0.5 mV) than in normal mucosa (3.3+/-0.3, P less than 0.001), resistance was higher (98+/-12, against 40.3+/-2.8 omega cm-2), while short circuit current was lower (54.8+/-6.0; against 89.9+/-6.1 muA.cm-2). Net sodium absorption, 1.25+/-0.41 mumol.cm-2.h-1 (n=6), rose on addition of glucose (15 mM.1-1) to 11.57+/-0.8 mumol.cm-2.h-1 (n=4), and these were similar to results from normal ileum. Net chloride transport was also similar to noraml. In one subject, with intermittent ileostomy diarrhoea, net sodium absorption was normal, 2.14 mumol.cm-2.h-1, but there was marked active chloride secretion, 14.03 mumol.cm-2.h-1. These studies do not provide any evidence of enhanced electrolyte absorption across ileal mucosa as a response to colectomy. Some cases of ileostomy diarrhoea may be due to active chloride secretion. PMID:7380338
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.
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. PMID:25147859
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
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).
Wang, Sijian; Nan, Bin; Rosset, Saharon; Zhu, Ji
2011-03-01
We propose a computationally intensive method, the random lasso method, for variable selection in linear models. The method consists of two major steps. In step 1, the lasso method is applied to many bootstrap samples, each using a set of randomly selected covariates. A measure of importance is yielded from this step for each covariate. In step 2, a similar procedure to the first step is implemented with the exception that for each bootstrap sample, a subset of covariates is randomly selected with unequal selection probabilities determined by the covariates' importance. Adaptive lasso may be used in the second step with weights determined by the importance measures. The final set of covariates and their coefficients are determined by averaging bootstrap results obtained from step 2. The proposed method alleviates some of the limitations of lasso, elastic-net and related methods noted especially in the context of microarray data analysis: it tends to remove highly correlated variables altogether or select them all, and maintains maximal flexibility in estimating their coefficients, particularly with different signs; the number of selected variables is no longer limited by the sample size; and the resulting prediction accuracy is competitive or superior compared to the alternatives. We illustrate the proposed method by extensive simulation studies. The proposed method is also applied to a Glioblastoma microarray data analysis. PMID:22997542
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…
Visual search and eye movements in novel and familiar contexts
NASA Astrophysics Data System (ADS)
McDermott, Kyle; Mulligan, Jeffrey B.; Bebis, George; Webster, Michael A.
2006-02-01
Adapting to the visual characteristics of a specific environment may facilitate detecting novel stimuli within that environment. We monitored eye movements while subjects searched for a color target on familiar or unfamiliar color backgrounds, in order to test for these performance changes and to explore whether they reflect changes in salience from adaptation vs. changes in search strategies or perceptual learning. The target was an ellipse of variable color presented at a random location on a dense background of ellipses. In one condition, the colors of the background varied along either the LvsM or SvsLM cardinal axes. Observers adapted by viewing a rapid succession of backgrounds drawn from one color axis, and then searched for a target on a background from the same or different color axis. Searches were monitored with a Cambridge Research Systems Video Eyetracker. Targets were located more quickly on the background axis that observers were pre-exposed to, confirming that this exposure can improve search efficiency for stimuli that differ from the background. However, eye movement patterns (e.g. fixation durations and saccade magnitudes) did not clearly differ across the two backgrounds, suggesting that how the novel and familiar backgrounds were sampled remained similar. In a second condition, we compared search on a nonselective color background drawn from a circle of hues at fixed contrast. Prior exposure to this background did not facilitate search compared to an achromatic adapting field, suggesting that subjects were not simply learning the specific colors defining the background distributions. Instead, results for both conditions are consistent with a selective adaptation effect that enhances the salience of novel stimuli by partially discounting the background.
ERIC Educational Resources Information Center
Coard, Stephanie I.; Foy-Watson, Shani; Zimmer, Catherine; Wallace, Amy
2007-01-01
A randomized prevention pilot trial compared caregivers who participated in the Black Parenting Strengths and Strategies (BPSS) Program with control caregivers. BPSS is a strengths- and culturally based parenting program designed to improve aspects of parenting associated with the early development of conduct problems and the promotion of social…
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. PMID:25805650