An adaptive random search for short term generation scheduling with network constraints
Velasco, Jonás; Selley, Héctor J.
2017-01-01
This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach. PMID:28234954
An adaptive random search for short term generation scheduling with network constraints.
Marmolejo, J A; Velasco, Jonás; Selley, Héctor J
2017-01-01
This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.
NASA Astrophysics Data System (ADS)
Tanizawa, Ken; Hirose, Akira
Adaptive polarization mode dispersion (PMD) compensation is required for the speed-up and advancement of the present optical communications. The combination of a tunable PMD compensator and its adaptive control method achieves adaptive PMD compensation. In this paper, we report an effective search control algorithm for the feedback control of the PMD compensator. The algorithm is based on the hill-climbing method. However, the step size changes randomly to prevent the convergence from being trapped at a local maximum or a flat, unlike the conventional hill-climbing method. The randomness depends on the Gaussian probability density functions. We conducted transmission simulations at 160Gb/s and the results show that the proposed method provides more optimal compensator control than the conventional hill-climbing method.
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.
1975-07-01
cookie cutter mode of detection. Only one-dimensional search is considered here. _. 7 DD ,^:"n 1473 EDITION OP I NOV 68 IS OBSOLETE S/N 0103-014-6601...assumed about its motion? We will return to this question shortly. Assumption (A3) concerns a mode of detection - the so-called cookie cutter
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.
Visualizing Search Behavior with Adaptive Discriminations
Cook, Robert G.; Qadri, Muhammad A. J.
2014-01-01
We examined different aspects of the visual search behavior of a pigeon using an open-ended, adaptive testing procedure controlled by a genetic algorithm. The animal had to accurately search for and peck a gray target element randomly located from among a variable number of surrounding darker and lighter distractor elements. Display composition was controlled by a genetic algorithm involving the multivariate configuration of different parameters or genes (number of distractors, element size, shape, spacing, target brightness, and distractor brightness). Sessions were composed of random displays, testing randomized combinations of these genes, and selected displays, representing the varied descendants of displays correctly identified by the pigeon. Testing a larger number of random displays than done previously, it was found that the bird’s solution to the search task was highly stable and did not change with extensive experience in the task. The location and shape of this attractor was visualized using multivariate behavioral surfaces in which element size and the number of distractors were the most important factors controlling search accuracy and search time. The resulting visualizations of the bird’s search behavior are discussed with reference to the potential of using adaptive, open-ended experimental techniques for investigating animal cognition and their implications for Bond and Kamil’s innovative development of virtual ecologies using an analogous methodology. PMID:24370702
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.
Adaptive Search through Constraint Violations
1990-01-01
ZIP Code) 3939 O’Hara Street 800 North Quincy Street Pittsburgh, PA 15260 Arlington, VA 22217-5000 8a NAME OF FUNDING/SPONSORING Bb OFFICE SYMBOL 9...Pittsburgh, PA . Smith, D. A., Greeno, J. G., & Vitolo, T. M., (in press). A model of competence for counting. Cognitive Science. VanLehn, K. (in press...1990). Adaptive search through constraint violations (Technical Report No. KUL-90-01). Pittsburgh, PA : Learning Research and Development Center
NASA Astrophysics Data System (ADS)
Ma, Yitao; Miura, Sadahiko; Honjo, Hiroaki; Ikeda, Shoji; Hanyu, Takahiro; Ohno, Hideo; Endoh, Tetsuo
2017-04-01
A high-density nonvolatile associative memory (NV-AM) based on spin transfer torque magnetoresistive random access memory (STT-MRAM), which achieves highly concurrent and ultralow-power nearest neighbor search with full adaptivity of the template data format, has been proposed and fabricated using the 90 nm CMOS/70 nm perpendicular-magnetic-tunnel-junction hybrid process. A truly compact current-mode circuitry is developed to realize flexibly controllable and high-parallel similarity evaluation, which makes the NV-AM adaptable to any dimensionality and component-bit of template data. A compact dual-stage time-domain minimum searching circuit is also developed, which can freely extend the system for more template data by connecting multiple NM-AM cores without additional circuits for integrated processing. Both the embedded STT-MRAM module and the computing circuit modules in this NV-AM chip are synchronously power-gated to completely eliminate standby power and maximally reduce operation power by only activating the currently accessed circuit blocks. The operations of a prototype chip at 40 MHz are demonstrated by measurement. The average operation power is only 130 µW, and the circuit density is less than 11 µm2/bit. Compared with the latest conventional works in both volatile and nonvolatile approaches, more than 31.3% circuit area reductions and 99.2% power improvements are achieved, respectively. Further power performance analyses are discussed, which verify the special superiority of the proposed NV-AM in low-power and large-memory-based VLSIs.
Search along persistent random walks
NASA Astrophysics Data System (ADS)
Friedrich, Benjamin M.
2008-06-01
Optimal search strategies and their implementations in biological systems are a subject of active research. Here we study a search problem which is motivated by the hunt of sperm cells for the egg. We ask for the probability for an active swimmer to find a target under the condition that the swimmer starts at a certain distance from the target. We find that success probability is maximal for a certain level of fluctuations characterized by the persistence length of the swimming path of the swimmer. We derive a scaling law for the optimal persistence length as a function of the initial target distance and search time by mapping the search on a polymer physics problem.
Dichotomous Search Strategies for Computerized Adaptive Testing.
ERIC Educational Resources Information Center
Xiao, Beiling
Dichotomous search strategies (DSSs) for computerized adaptive testing are similar to golden section search strategies (GSSSs). Each middle point of successive search regions is a testing point. After each item is administered, the subject's obtained score is compared with the expected score at successive testing points. If the subject's obtained…
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.
Random search for a dark resonance
NASA Astrophysics Data System (ADS)
Kiilerich, Alexander Holm; Mølmer, Klaus
2017-02-01
A pair of resonant laser fields can drive a three-level system into a dark state where it ceases to absorb and emit radiation due to destructive interference. We propose a scheme to search for this resonance by randomly changing the frequency of one of the fields each time a fluorescence photon is detected. The longer the system is probed, the more likely the frequency is close to resonance and the system populates the dark state. Due to the correspondingly long waiting times between detection events, the evolution is nonergodic and the precision of the frequency estimate does not follow from the conventional Cramér-Rao bound of parameter estimation. Instead, a Lévy statistical analysis yields the scaling of the estimation error with time for precision probing of this kind.
Adaptive random testing with combinatorial input domain.
Huang, Rubing; Chen, Jinfu; 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.
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.
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
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Particle Swarm Based Collective Searching Model for Adaptive Environment
Cui, Xiaohui; Patton, Robert M; Potok, Thomas E; Treadwell, Jim N
2008-01-01
This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.
Particle Swarm Based Collective Searching Model for Adaptive Environment
Cui, Xiaohui; Patton, Robert M; Potok, Thomas E; Treadwell, Jim N
2007-01-01
This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.
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.
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,…
Visual Scan Adaptation During Repeated Visual Search
2010-01-01
repeated distractor –target configurations both require environmental stability. For stable distractor – target configurations, Chun and Jiang (1998) have...demon- strated search time savings from repeating distractor –target configurations, and Song and Jiang (2005) demonstrated that as little as 25% of the...search environment (i.e., two distractor locations and the target location out of 12 total locations per trial) repeated from trial to trial resulted
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.
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.
Stochastic inequality probabilities for adaptively randomized clinical trials.
Cook, John D; Nadarajah, Saralees
2006-06-01
We examine stochastic inequality probabilities of the form P (X > Y) and P (X > max (Y, Z)) where X, Y, and Z are random variables with beta, gamma, or inverse gamma distributions. We discuss the applications of such inequality probabilities to adaptively randomized clinical trials as well as methods for calculating their values.
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.
System and Method for Tracking Vehicles Using Random Search Algorithms.
1997-01-31
patent application is available for licensing. Requests for information should be addressed to: OFFICE OF NAVAL RESEARCH DEPARTMENT OF THE NAVY...relates to a system and a method for 22 tracking vehicles using random search algorithm methodolgies . 23 (2) Description of the Prior Art 24 Contact...algorithm methodologies for finding peaks in non-linear 14 functions. U.S. Patent No. 5,148,513 to Koza et al., for 15 example, relates to a non-linear
Hierarchical random walks in trace fossils and the origin of optimal search behavior
Sims, David W.; Reynolds, Andrew M.; Humphries, Nicolas E.; Southall, Emily J.; Wearmouth, Victoria J.; Metcalfe, Brett; Twitchett, Richard J.
2014-01-01
Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa. PMID:25024221
Searching for adaptive traits in genetic resources - phenology based approach
NASA Astrophysics Data System (ADS)
Bari, Abdallah
2015-04-01
Searching for adaptive traits in genetic resources - phenology based approach Abdallah Bari, Kenneth Street, Eddy De Pauw, Jalal Eddin Omari, and Chandra M. Biradar International Center for Agricultural Research in the Dry Areas, Rabat Institutes, Rabat, Morocco Phenology is an important plant trait not only for assessing and forecasting food production but also for searching in genebanks for adaptive traits. Among the phenological parameters we have been considering to search for such adaptive and rare traits are the onset (sowing period) and the seasonality (growing period). Currently an application is being developed as part of the focused identification of germplasm strategy (FIGS) approach to use climatic data in order to identify crop growing seasons and characterize them in terms of onset and duration. These approximations of growing period characteristics can then be used to estimate flowering and maturity dates for dryland crops, such as wheat, barley, faba bean, lentils and chickpea, and assess, among others, phenology-related traits such as days to heading [dhe] and grain filling period [gfp]. The approach followed here is based on first calculating long term average daily temperatures by fitting a curve to the monthly data over days from beginning of the year. Prior to the identification of these phenological stages the onset is extracted first from onset integer raster GIS layers developed based on a model of the growing period that considers both moisture and temperature limitations. The paper presents some examples of real applications of the approach to search for rare and adaptive traits.
Stochastic Leader Gravitational Search Algorithm for Enhanced Adaptive Beamforming Technique
Darzi, Soodabeh; Islam, Mohammad Tariqul; Tiong, Sieh Kiong; Kibria, Salehin; Singh, Mandeep
2015-01-01
In this paper, stochastic leader gravitational search algorithm (SL-GSA) based on randomized k is proposed. Standard GSA (SGSA) utilizes the best agents without any randomization, thus it is more prone to converge at suboptimal results. Initially, the new approach randomly choses k agents from the set of all agents to improve the global search ability. Gradually, the set of agents is reduced by eliminating the agents with the poorest performances to allow rapid convergence. The performance of the SL-GSA was analyzed for six well-known benchmark functions, and the results are compared with SGSA and some of its variants. Furthermore, the SL-GSA is applied to minimum variance distortionless response (MVDR) beamforming technique to ensure compatibility with real world optimization problems. The proposed algorithm demonstrates superior convergence rate and quality of solution for both real world problems and benchmark functions compared to original algorithm and other recent variants of SGSA. PMID:26552032
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.
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.
Adaptive Designs for Randomized Trials in Public Health
Brown, C. Hendricks; Have, Thomas R. Ten; Jo, Booil; Dagne, Getachew; Wyman, Peter A.; Muthén, Bengt; Gibbons, Robert D.
2009-01-01
In this article, we present a discussion of two general ways in which the traditional randomized trial can be modified or adapted in response to the data being collected. We use the term adaptive design to refer to a trial in which characteristics of the study itself, such as the proportion assigned to active intervention versus control, change during the trial in response to data being collected. The term adaptive sequence of trials refers to a decision-making process that fundamentally informs the conceptualization and conduct of each new trial with the results of previous trials. Our discussion below investigates the utility of these two types of adaptations for public health evaluations. Examples are provided to illustrate how adaptation can be used in practice. From these case studies, we discuss whether such evaluations can or should be analyzed as if they were formal randomized trials, and we discuss practical as well as ethical issues arising in the conduct of these new-generation trials. PMID:19296774
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.
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search
Fricke, G. Matthew; Letendre, Kenneth A.; Moses, Melanie E.; Cannon, Judy L.
2016-01-01
Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call “hotspots” within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search. PMID:26990103
Generalized pattern search algorithms with adaptive precision function evaluations
Polak, Elijah; Wetter, Michael
2003-05-14
In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to a form that uses adaptive precision approximations to the cost function. These numerical approximations need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. Such an approach leads to substantial time savings in minimizing computationally expensive functions.
Design of Sequentially Randomized Trials for Testing Adaptive Treatment Strategies
Ogbagaber, Semhar B.; Karp, Jordan; Wahed, Abdus S.
2016-01-01
An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatment of complex diseases based on patients’ disease status and treatment history. Conditions such as AIDS, depression, and cancer usually require several stages of treatment due to the chronic, multifactorial nature of illness progression and management. Sequential multiple assignment randomized (SMAR) designs permit simultaneous inference about multiple ATSs, where patients are sequentially randomized to treatments at different stages depending upon response status. The purpose of the article is to develop a sample size formula to ensure adequate power for comparing two or more ATSs. Based on a Wald-type statistic for comparing multiple ATSs with a continuous endpoint, we develop a sample size formula and test it through simulation studies. We show via simulation that the proposed sample size formula maintains the nominal power. The proposed sample size formula is not applicable to designs with time-to-event endpoints but the formula will be useful for practitioners while designing SMAR trials to compare adaptive treatment strategies. PMID:26412033
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.
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.
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 Local Information Transfer in Random Boolean Networks.
Haruna, Taichi
2017-01-01
Living systems such as gene regulatory networks and neuronal networks have been supposed to work close to dynamical criticality, where their information-processing ability is optimal at the whole-system level. We investigate how this global information-processing optimality is related to the local information transfer at each individual-unit level. In particular, we introduce an internal adjustment process of the local information transfer and examine whether the former can emerge from the latter. We propose an adaptive random Boolean network model in which each unit rewires its incoming arcs from other units to balance stability of its information processing based on the measurement of the local information transfer pattern. First, we show numerically that random Boolean networks can self-organize toward near dynamical criticality in our model. Second, the proposed model is analyzed by a mean-field theory. We recognize that the rewiring rule has a bootstrapping feature. The stationary indegree distribution is calculated semi-analytically and is shown to be close to dynamical criticality in a broad range of model parameter values.
δ-exceedance records and random adaptive walks
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2016-08-01
We study a modified record process where the kth record in a series of independent and identically distributed random variables is defined recursively through the condition {Y}k\\gt {Y}k-1-{δ }k-1 with a deterministic sequence {δ }k\\gt 0 called the handicap. For constant {δ }k\\equiv δ and exponentially distributed random variables it has been shown in previous work that the process displays a phase transition as a function of δ between a normal phase where the mean record value increases indefinitely and a stationary phase where the mean record value remains bounded and a finite fraction of all entries are records (Park et al 2015 Phys. Rev. E 91 042707). Here we explore the behavior for general probability distributions and decreasing and increasing sequences {δ }k, focusing in particular on the case when {δ }k matches the typical spacing between subsequent records in the underlying simple record process without handicap. We find that a continuous phase transition occurs only in the exponential case, but a novel kind of first order transition emerges when {δ }k is increasing. The problem is partly motivated by the dynamics of evolutionary adaptation in biological fitness landscapes, where {δ }k corresponds to the change of the deterministic fitness component after k mutational steps. The results for the record process are used to compute the mean number of steps that a population performs in such a landscape before being trapped at a local fitness maximum.
Adaptive Randomization of Neratinib in Early Breast Cancer
Park, John W.; Liu, Minetta C.; Yee, Douglas; Yau, Christina; van 't Veer, Laura J.; Symmans, W. Fraser; Paoloni, Melissa; Perlmutter, Jane; Hylton, Nola M.; Hogarth, Michael; DeMichele, Angela; Buxton, Meredith B.; Chien, A. Jo; Wallace, Anne M.; Boughey, Judy C.; Haddad, Tufia C.; Chui, Stephen Y.; Kemmer, Kathleen A.; Kaplan, Henry G.; Liu, Minetta C.; Isaacs, Claudine; Nanda, Rita; Tripathy, Debasish; Albain, Kathy S.; Edmiston, Kirsten K.; Elias, Anthony D.; Northfelt, Donald W.; Pusztai, Lajos; Moulder, Stacy L.; Lang, Julie E.; Viscusi, Rebecca K.; Euhus, David M.; Haley, Barbara B.; Khan, Qamar J.; Wood, William C.; Melisko, Michelle; Schwab, Richard; Lyandres, Julia; Davis, Sarah E.; Hirst, Gillian L.; Sanil, Ashish; Esserman, Laura J.; Berry, Donald A.
2017-01-01
Background I-SPY2, a standing, multicenter, adaptive phase 2 neoadjuvant trial ongoing in high-risk clinical stage II/III breast cancer, is designed to evaluate multiple, novel experimental agents added to standard chemotherapy for their ability to improve the rate of pathologic complete response (pCR). Experimental therapies are compared against a common control arm. We report efficacy for the tyrosine kinase inhibitor neratinib. Methods Eligible women had ≥2.5 cm stage II/III breast cancer, categorized into 8 biomarker subtypes based on HER2, hormone-receptor status (HR), and MammaPrint. Neratinib was evaluated for 10 signatures (prospectively defined subtype combinations), with primary endpoint pCR. MR volume changes inform likelihood of pCR for each patient prior to surgery. Adaptive assignment to experimental arms within disease subtype was based on current Bayesian probabilities of superiority over control. Accrual to experimental arm stop at any time for futility or graduation within a particular signature based on Bayesian predictive probability of success in a confirmatory trial. The maximum sample size in any experimental arm is 120 patients, Results With 115 patients and 78 concurrently randomized controls, neratinib graduated in the HER2+/HR− signature, with mean pCR rate 56% (95% PI: 37 to 73%) vs 33% for controls (11 to 54%). Final predictive probability of success, updated when all pathology data were available, was 79%. Conclusion Adaptive, multi-armed trials can efficiently identify responding tumor subtypes. Neratinib added to standard therapy is highly likely to improve pCR rates in HER2+/HR2212; breast cancer. Confirmation in I-SPY 3, a phase 3 neoadjuvant registration trial, is planned. PMID:27406346
An Adaptive Optics Search for Young Extrasolar Planets
NASA Astrophysics Data System (ADS)
Macintosh, B.; Zuckerman, B.; Kaisler, D.; Becklin, E. E.; Lowrance, P.; Webb, R.; Olivier, S.; Max, C. E.
2000-12-01
Several dozen extrasolar planets are now known, all detected through radial velocity variations induced in their parent stars. Though powerful, the radial velocity technique is most sensitive to objects in close orbits and measures only the mass and orbit of the planet, not its other properties. Other indirect techniques such as astrometry will have similar limitations. The direct detection of photons emitted by extrasolar planets, particularly those in wide orbits, is potentially a powerful complement to indirect techniques. The halo of scattered light that surrounds a bright star makes this extremely challenging, but adaptive optics (AO) on 8-10 m telescopes brings this possibility into reach. The first such large-telescope AO system has been operating on the 10-m W.M. Keck II telescope since 1999. Keck AO is now capable of detecting objects at contrast ratios as high as 106 at separations of 1-2 arcseconds. A mature Jupiter-like planet is approximately 109 times dimmer than its parent star, undetectable at the current time. However, a young (10 MYr) Jupiter-mass planet retains enough heat to radiate brightly in the near- infrared, making it only 105 times dimmer than a star. We are carrying out a search for such planetary companions to young nearby stars, including members of the TW Hydrae association. Initially we have been following up candidate companions discovered by NICMOS, including the brown dwarf TWA5B. Our observations of TWA5B confirm its companionship and therefore its brown dwarf nature. In addition, TWA5A is resolved as an 0.06 arcsecond double, opening up the possibility of precise mass determinations for this young system. I will discuss followup observations of other candidates and the current sensitivity limits and limitations of our search. This research was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-ENG-48, and also supported in part by the Center for Adaptive
An adaptive optics search for young extrasolar planets
NASA Astrophysics Data System (ADS)
Macintosh, B.; Zuckerman, B.; Becklin, E. E.; Kaisler, D.; Lowrance, P.; Max, C. E.; Olivier, S.
2000-10-01
In the past five years, many extrasolar planets have been detected indirectly, through radial velocity variations induced in their parent stars. Advances in technology now open up the possibility of directly detecting extrasolar planets through the photons they emit. Direct detection would allow determination of the temperature, radius, and composition of a planet, particularly one in a wide orbit - an important complement to radial velocity techniques. Seeing a planet against the halo of scattered light from its parent star is extremely challenging, but adaptive optics (AO) on 8-10 m telescopes can make this possible. The first such large-telescope AO system is now operational on the 10-m W.M. Keck II telescope. Its current performance is sufficient to detect objects at contrast ratios of 105 at separations of 1" and 106 at 2". This is insufficient to detect the reflected light from a mature Jupiter-like planet, but we can easily detect the near-infrared thermal emission from young (<10-50 MYr) planets, or older brown dwarfs. We are carrying out a search for such planetary companions to young nearby stars, including the TW Hydrae association. We present preliminary results from this survey, including sensitivity limits and follow-up of candidate companions originally detected by NICMOS. We have also imaged the Epsilon Eridani system, and present upper limits on the brightness of the planet detected via radial velocity variations by Cochran et al. This research was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-ENG-48, and also supported in part by the Center for Adaptive Optics under the STC Program of the National Science Foundation under Agreement No. AST-9876783
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
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…
Adaptive Randomization of Veliparib–Carboplatin Treatment in Breast Cancer
Rugo, Hope S.; Olopade, Olufunmilayo I.; DeMichele, Angela; Yau, Christina; van ‘t Veer, Laura J.; Buxton, Meredith B.; Hogarth, Michael; Hylton, Nola M.; Paoloni, Melissa; Perlmutter, Jane; Symmans, W. Fraser; Yee, Douglas; Chien, A. Jo; Wallace, Anne M.; Kaplan, Henry G.; Boughey, Judy C.; Haddad, Tufia C.; Albain, Kathy S.; Liu, Minetta C.; Isaacs, Claudine; Khan, Qamar J.; Lang, Julie E.; Viscusi, Rebecca K.; Pusztai, Lajos; Moulder, Stacy L.; Chui, Stephen Y.; Kemmer, Kathleen A.; Elias, Anthony D.; Edmiston, Kirsten K.; Euhus, David M.; Haley, Barbara B.; Nanda, Rita; Northfelt, Donald W.; Tripathy, Debasish; Wood, William C.; Lyandres, Julia; Davis, Sarah E.; Hirst, Gillian L.; Sanil, Ashish; Berry, Donald A.; Esserman, Laura J.
2017-01-01
Background I-SPY 2 is a phase 2 standing multicenter platform trial designed to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to matching experimental regimens with responding patient subtypes. We report results for veliparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin (VC). Methods Eligible women had ≥2.5 cm stage II/III breast cancer, categorized into 8 biomarker subtypes based on HER2, hormone-receptor status (HR) and MammaPrint. Patients are adaptively randomized within subtype to better performing regimens compared to standard therapy (control). Regimens are evaluated within 10 signatures, prospectively defined combinations of subtypes. VC plus standard therapy was considered for HER2-negative tumors and therefore evaluated in 3 signatures. The primary endpoint of I-SPY 2 is pathologic complete response (pCR). MR volume changes during treatment inform the likelihood that a patient will achieve pCR. Regimens graduate if and when they have a high (Bayesian) predictive probability of success in a subsequent phase 3 neoadjuvant trial within the graduating signature. Results VC graduated in triple-negative breast cancer with 88% predicted probability of phase 3 success. A total of 72 patients were randomized to VC and 44 to concurrent controls. Respective pCR estimates (95% probability intervals) were 51% (35%–69%) vs 26% (11%–40%). Greater toxicity of VC was manageable. Conclusion The design of I-SPY 2 has the potential to efficiently identify responding tumor subtypes for the various therapies being evaluated. VC added to standard therapy improves pCR rates specifically in triple-negative breast cancer. PMID:27406347
Spatial downscaling of precipitation using adaptable random forests
NASA Astrophysics Data System (ADS)
He, Xiaogang; Chaney, Nathaniel W.; Schleiss, Marc; Sheffield, Justin
2016-10-01
This paper introduces Prec-DWARF (Precipitation Downscaling With Adaptable Random Forests), a novel machine-learning based method for statistical downscaling of precipitation. Prec-DWARF sets up a nonlinear relationship between precipitation at fine resolution and covariates at coarse/fine resolution, based on the advanced binary tree method known as Random Forests (RF). In addition to a single RF, we also consider a more advanced implementation based on two independent RFs which yield better results for extreme precipitation. Hourly gauge-radar precipitation data at 0.125° from NLDAS-2 are used to conduct synthetic experiments with different spatial resolutions (0.25°, 0.5°, and 1°). Quantitative evaluation of these experiments demonstrates that Prec-DWARF consistently outperforms the baseline (i.e., bilinear interpolation in this case) and can reasonably reproduce the spatial and temporal patterns, occurrence and distribution of observed precipitation fields. However, Prec-DWARF with a single RF significantly underestimates precipitation extremes and often cannot correctly recover the fine-scale spatial structure, especially for the 1° experiments. Prec-DWARF with a double RF exhibits improvement in the simulation of extreme precipitation as well as its spatial and temporal structures, but variogram analyses show that the spatial and temporal variability of the downscaled fields are still strongly underestimated. Covariate importance analysis shows that the most important predictors for the downscaling are the coarse-scale precipitation values over adjacent grid cells as well as the distance to the closest dry grid cell (i.e., the dry drift). The encouraging results demonstrate the potential of Prec-DWARF and machine-learning based techniques in general for the statistical downscaling of precipitation.
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.
2015-10-01
Page 1 of 3 Award Number: W81XWH-11-2-0231 TITLE: Plasticity-Based Adaptive Cognitive Remediation (PACR) for OIF/OEF Veterans: A Randomized...DATES COVERED 30Sep2014 - 29Sep2015 4. TITLE AND SUBTITLE Plasticity-Based Adaptive Cognitive Remediation (PACR) for OIF/OEF Veterans: A Randomized
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.
NASA Astrophysics Data System (ADS)
Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua
2014-03-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
Sheng, Zheng; Wang, Jun; Zhou, 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.
Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields
NASA Astrophysics Data System (ADS)
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.
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
Online games: a novel approach to explore how partial information influences human random searches
Martínez-García, Ricardo; Calabrese, Justin M.; López, Cristóbal
2017-01-01
Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches. PMID:28059115
Online games: a novel approach to explore how partial information influences human random searches
NASA Astrophysics Data System (ADS)
Martínez-García, Ricardo; Calabrese, Justin M.; López, Cristóbal
2017-01-01
Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.
Adaptation of enzymes to temperature: searching for basic "strategies".
Somero, George N
2004-11-01
The pervasive influence of temperature on biological systems necessitates a suite of temperature--compensatory adaptations that span all levels of biological organization--from behavior to fine-scale molecular structure. Beginning about 50 years ago, physiological studies conducted with whole organisms or isolated tissues, by such pioneers of comparative thermal physiology as V.Ya. Alexandrov, T.H. Bullock, F.E.J. Fry, H. Precht, C.L. Prosser, and P.F. Scholander, began to document in detail the abilities of ectothermic animals to sustain relatively similar rates of metabolic activity at widely different temperatures of adaptation or acclimation. These studies naturally led to investigation of the roles played by enzymatic proteins in metabolic temperature compensation. Peter Hochachka's laboratory became an epicenter of this new focus in comparative physiology. The studies of the enzyme lactate dehydrogenase (LDH) that he initiated as a PhD student at Duke University in the mid-1960s and continued for several years at the University of British Columbia laid much of the foundation for subsequent studies of protein adaptation to temperature. Studies of orthologs of LDH have revealed the importance of conserving kinetic properties (catalytic rate constants (kcat) and Michaelis-Menten constants (Km) and structural stability during adaptation to temperature, and recently have identified the types of amino acid substitutions causing this adaptive variation. The roles of pH and low-molecular-mass organic solutes (osmolytes) in conserving the functional and structural properties of enzymes also have been elucidated using LDH. These studies, begun in Peter Hochachka's laboratory almost 40 years ago, have been instrumental in the development of a conceptual framework for the study of biochemical adaptation, a field whose origin can be traced largely to his creative influences. This framework emphasizes the complementary roles of three "strategies" of adaptation: (1) changes
Adapting GNU random forest program for Unix and Windows
NASA Astrophysics Data System (ADS)
Jirina, Marcel; Krayem, M. Said; Jirina, Marcel, Jr.
2013-10-01
The Random Forest is a well-known method and also a program for data clustering and classification. Unfortunately, the original Random Forest program is rather difficult to use. Here we describe a new version of this program originally written in Fortran 77. The modified program in Fortran 95 needs to be compiled only once and information for different tasks is passed with help of arguments. The program was tested with 24 data sets from UCI MLR and results are available on the net.
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.
Face adaptation does not improve performance on search or discrimination tasks.
Ng, Minna; Boynton, Geoffrey M; Fine, Ione
2008-01-04
The face adaptation effect, as described by M. A. Webster and O. H. MacLin (1999), is a robust perceptual shift in the appearance of faces after a brief adaptation period. For example, prolonged exposure to Asian faces causes a Eurasian face to appear distinctly Caucasian. This adaptation effect has been documented for general configural effects, as well as for the facial properties of gender, ethnicity, expression, and identity. We began by replicating the finding that adaptation to ethnicity, gender, and a combination of both features induces selective shifts in category appearance. We then investigated whether this adaptation has perceptual consequences beyond a shift in the perceived category boundary by measuring the effects of adaptation on RSVP, spatial search, and discrimination tasks. Adaptation had no discernable effect on performance for any of these tasks.
An autonomous adaptive scheduling agent for period searching
NASA Astrophysics Data System (ADS)
Saunders, E. S.; Naylor, T.; Allan, A.
2008-03-01
We describe the design and implementation of an autonomous adaptive software agent that addresses the practical problem of observing undersampled, periodic, time-varying phenomena using a network of HTN-compliant robotic telescopes. The algorithm governing the behaviour of the agent uses an optimal geometric sampling technique to cover the period range of interest, but additionally implements proactive behaviour that maximises the optimality of the dataset in the face of an uncertain and changing operating environment.
Visual alchemy: stereoscopic adaptation produces kinetic depth from random noise.
Nawrot, M; Blake, R
1993-01-01
Observers perceive incoherent motion and no hint of depth when viewing stochastic motion, in which stimulus elements move in all possible directions. As earlier work has shown, depth can be specified by introducing a brief interocular delay between the presentation of corresponding animation frames of this 'noise' to the left and right eyes. A study is reported in which observers were adapted to a stereoscopic display consisting of coherent planes of motion at different depths. This stereoscopic adaptation caused incoherent depthless motion to take on the qualities of structure and depth, and it could nullify the depth induced by interocular delay. The findings are interpreted within the context of a neural model consisting of units selectively responsive to different directions of motion at different planes of depth.
Campos, Daniel; Méndez, Vicenç
2015-12-01
Recent works have explored the properties of Lévy flights with resetting in one-dimensional domains and have reported the existence of phase transitions in the phase space of parameters which minimizes the mean first passage time (MFPT) through the origin [L. Kusmierz et al., Phys. Rev. Lett. 113, 220602 (2014)]. Here, we show how actually an interesting dynamics, including also phase transitions for the minimization of the MFPT, can also be obtained without invoking the use of Lévy statistics but for the simpler case of random walks with exponentially distributed flights of constant speed. We explore this dynamics both in the case of finite and infinite domains, and for different implementations of the resetting mechanism to show that different ways to introduce resetting consistently lead to a quite similar dynamics. The use of exponential flights has the strong advantage that exact solutions can be obtained easily for the MFPT through the origin, so a complete analytical characterization of the system dynamics can be provided. Furthermore, we discuss in detail how the phase transitions observed in random walks with resetting are closely related to several ideas recurrently used in the field of random search theory, in particular, to other mechanisms proposed to understand random search in space as mortal random walks or multiscale random walks. As a whole, we corroborate that one of the essential ingredients behind MFPT minimization lies in the combination of multiple movement scales (regardless of their specific origin).
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.
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.
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.
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.
Self-adaptive differential evolution algorithm incorporating local search for protein-ligand docking
NASA Astrophysics Data System (ADS)
Chung, Hwan Won; Cho, Seung Joo; Lee, Kwang-Ryeol; Lee, Kyu-Hwan
2013-02-01
Differential Evolution (DE) algorithm is powerful in optimization problems over several real parameters. DE depends on strategies to generate new trial solutions and the associated parameter values for searching performance. In self-adaptive DE, the automatic learning about previous evolution was used to determine the best mutation strategy and its parameter settings. By combining the self-adaptive DE and Hooke Jeeves local search, we developed a new docking method named SADock (Strategy Adaptation Dock) with the help of AutoDock4 scoring function. As the accuracy and performance of SADock was evaluated in self-docking using the Astex diverse set, the introduced SADock showed better success ratio (89%) than the success ratio (60%) of the Lamarckian genetic algorithm (LGA) of AutoDock4. The self-adapting scheme enabled our new docking method to converge fast and to be robust through the various docking problems.
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.
Cooper, R.J.; Mordecai, Rua S.; Mattsson, B.G.; Conroy, M.J.; Pacifici, K.; Peterson, J.T.; Moore, C.T.
2008-01-01
We describe a survey design and field protocol for the Ivory-billed Woodpecker (Campephilus principalis) search effort that will: (1) allow estimation of occupancy, use, and detection probability for habitats at two spatial scales within the bird?s former range, (2) assess relationships between occupancy, use, and habitat characteristics at those scales, (3) eventually allow the development of a population viability model that depends on patch occupancy instead of difficult-to-measure demographic parameters, and (4) be adaptive, allowing newly collected information to update the above models and search locations. The approach features random selection of patches to be searched from a sampling frame stratified and weighted by patch quality, and requires multiple visits per patch. It is adaptive within a season in that increased search activity is allowed in and around locations of strong visual and/or aural evidence, and adaptive among seasons in that habitat associations allow modification of stratum weights. This statistically rigorous approach is an improvement over simply visiting the ?best? habitat in an ad hoc fashion because we can learn from prior effort and modify the search accordingly. Results from the 2006-07 search season indicate weak relationships between occupancy and habitat (although we suggest modifications of habitat measurement protocols), and a very low detection probability, suggesting more visits per patch are required. Sample size requirements will be discussed.
Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array
Liu, Miao; Li, Zhao; Liang, Fulai; Jing, Xijing; Lu, Guohua; Wang, Jianqi
2016-01-01
It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor’s respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person’s head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors. PMID:27073860
Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array.
Li, Chuantao; Chen, Fuming; Qi, Fugui; Liu, Miao; Li, Zhao; Liang, Fulai; Jing, Xijing; Lu, Guohua; Wang, Jianqi
2016-01-01
It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor's respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person's head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors.
Deterministic quantum-public-key encryption: Forward search attack and randomization
NASA Astrophysics Data System (ADS)
Nikolopoulos, Georgios M.; Ioannou, Lawrence M.
2009-04-01
In the classical setting, public-key encryption requires randomness in order to be secure against a forward search attack, whereby an adversary compares the encryption of a guess of the secret message with the encryption of the actual secret message. We show that this is also true in the information-theoretic setting—where the public keys are quantum systems—by defining and giving an example of a forward search attack for any deterministic quantum-public-key bit-encryption scheme. However, unlike in the classical setting, we show that any such deterministic scheme can be used as a black box to build a randomized bit-encryption scheme that is no longer susceptible to this attack.
ERIC Educational Resources Information Center
Waffenschmidt, Siw; Guddat, Charlotte
2015-01-01
Background: It is unclear which terms should be included in bibliographic searches for randomized controlled trials (RCTs) of drugs, and identifying relevant drug terms can be extremely laborious. The aim of our analysis was to determine whether a bibliographic search using only the generic drug name produces sufficient results for the generation…
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…
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.
Adaptive biased urn randomization in small strata when blinding is impossible.
Schouten, H J
1995-12-01
Adaptive biased urn randomization, applied in, e.g., a clinical trial, has certain attractive properties. If stratified randomization is desired, a good balance between group sizes can be guaranteed, even in (very) small strata. Yet treatment assignment may be kept unpredictable, which is necessary to avoid selection bias if blinding is impossible. In the present paper a more flexible urn model is described. The investigator may choose assignment probabilities that strongly depend on the degree of imbalance when the groups are still small, but with a tendency toward complete randomization when the groups become large. It is also possible to keep the difference in group size below a chosen maximum, which is useful if population characteristics may change during the course of a trial. The new urn model includes random permutations and complete randomization as special cases. An extension of the model allows the promotion of unequal group sizes. Some attention is paid to a randomized version of the minimization method.
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
Performance Evaluation of Adaptive Probabilistic Search in P2P Networks
NASA Astrophysics Data System (ADS)
Zhang, Haoxiang; Zhang, Lin; Shan, Xiuming; Li, Victor O. K.
The overall performance of P2P-based file sharing applications is becoming increasingly important. Based on the Adaptive Resource-based Probabilistic Search algorithm (ARPS), which was previously proposed by the authors, a novel probabilistic search algorithm with QoS guarantees is proposed in this letter. The algorithm relies on generating functions to satisfy the user's constraints and to exploit the power-law distribution in the node degree. Simulation results demonstrate that it performs well under various P2P scenarios. The proposed algorithm provides guarantees on the search performance perceived by the user while minimizing the search cost. Furthermore, it allows different QoS levels, resulting in greater flexibility and scalability.
SmART: Adaptive grayscale search tools for alignment and registration
NASA Astrophysics Data System (ADS)
Hospod, Thomas F.
1999-03-01
For OEMs, system integrators and end-users of machine vision requiring highly accurate and robust pattern finding tools capable of precisely locating patterns despite normal process variations, Imaging Technology Incorporated offers its SmARTTM (Smart Alignment and Registration Tool) Search. SmART Search is an extremely accurate and robust pattern locating tool featuring the industry's first and only Training WizardTM--a time-saving utility that takes the guesswork and uncertainty out of the pattern training process. With state-of-the-art GeoSearchTM-assist, SmART Search enables manufacturers of vision-automated equipment to build more robust machines that will automatically adapt to changes in object appearance due to normal process variations.
2012-01-01
Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742
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
ERIC Educational Resources Information Center
Hol, A. Michiel; Vorst, Harrie C. M.; Mellenbergh, Gideon J.
2005-01-01
A total of 520 high school students were randomly assigned to a paper-and-pencil test (PPT), a computerized standard test (CST), or a computerized adaptive test (CAT) version of the Dutch School Attitude Questionnaire (SAQ), consisting of ordinal polytomous items. The CST administered items in the same order as the PPT. The CAT administered all…
Neural signatures of adaptive post-error adjustments in visual search.
Steinhauser, Robert; Maier, Martin E; Steinhauser, Marco
2017-02-22
Errors in speeded choice tasks can lead to post-error adjustments both on the behavioral and on the neural level. There is an ongoing debate whether such adjustments result from adaptive processes that serve to optimize performance or whether they reflect interference from error monitoring or attentional orientation. The present study aimed at identifying adaptive adjustments in a two-stage visual search task, in which participants had to select and subsequently identify a target stimulus presented to the left or right visual hemifield. Target selection and identification can be measured by two distinct event-related potentials, the N2pc and the SPCN. Using a decoder analysis based on multivariate pattern analysis, we were able to isolate the processing stages related to error sources and post-error adjustments. Whereas errors were linked to deviations in the N2pc and the SPCN, only for the N2pc we identified a post-error adjustment, which exhibits key features of source-specific adaptivity. While errors were associated with an increased N2pc, post-error adjustments consisted in an N2pc decrease. We interpret this as an adaptive adjustment of target selection to prevent errors due to disproportionate processing of the task-irrelevant target location. Our study thus provides evidence for adaptive post-error adjustments in visual search.
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938
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.
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.
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.
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.
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
Holliday, Jason A; Wang, Tongli; Aitken, Sally
2012-09-01
Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.
Adaptive search range adjustment scheme for fast motion estimation in AVC/H.264
NASA Astrophysics Data System (ADS)
Lee, Sunyoung; Choi, Kiho; Jang, Euee S.
2011-06-01
AVC/H.264 supports the use of multiple reference frames (e.g., 5 frames in AVC/H.264) for motion estimation (ME), which demands a huge computational complexity in ME. We propose an adaptive search range adjustment scheme to reduce the computational complexity of ME by reducing the search range of each reference frame--from the (t-1)'th frame to the (t-5)'th frame--for each macroblock. Based on the statistical analysis that the 16×16 mode type is dominantly selected rather than the other block partition mode types, the proposed method reduces the search range of the remaining ME process in the given reference frame according to the motion vector (MV) position of the 16×16 block ME. In the case of the (t-1)'th frame, the MV position of the 8×8 block ME--in addition to that of 16×16 block ME--is also used for the search range reduction to sub-block partition mode types of the 8×8 block. The experimental results show that the proposed method reduces about 50% and 65% of the total encoding time over CIF/SIF and full HD test sequences, respectively, without any noticeable visual degradation, compared to the full search method of the AVC/H.264 encoder.
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.
Adaptive PSO using random inertia weight and its application in UAV path planning
NASA Astrophysics Data System (ADS)
Zhu, Hongguo; Zheng, Changwen; Hu, Xiaohui; Li, Xiang
2008-10-01
A novel particle swarm optimization algorithm, called APSO_RW is presented. Random inertia weight improves its global optimization performance and an adaptive reinitialize mechanism is used when the global best particle is detected to be trapped. The new algorithm is tested on a set of benchmark functions and experimental results show its efficiency. APSO_RW is later applied in UAV (Unmanned Aerial Vehicle) path planning.
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.
Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions
Klasnja, Predrag; Hekler, Eric B.; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A.
2015-01-01
Objective This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors. Micro-randomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. Methods The paper describes the micro-randomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Results Micro-randomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Conclusions Micro-randomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions’ effects, enabling creation of more effective JITAIs. PMID:26651463
Miller, Ross H; Gillette, Jason C; Derrick, Timothy R; Caldwell, Graham E
2009-04-01
Muscle forces during locomotion are often predicted using static optimisation and SQP. SQP has been criticised for over-estimating force magnitudes and under-estimating co-contraction. These problems may be related to SQP's difficulty in locating the global minimum to complex optimisation problems. Algorithms designed to locate the global minimum may be useful in addressing these problems. Muscle forces for 18 flexors and extensors of the lower extremity were predicted for 10 subjects during the stance phase of running. Static optimisation using SQP and two random search (RS) algorithms (a genetic algorithm and simulated annealing) estimated muscle forces by minimising the sum of cubed muscle stresses. The RS algorithms predicted smaller peak forces (42% smaller on average) and smaller muscle impulses (46% smaller on average) than SQP, and located solutions with smaller cost function scores. Results suggest that RS may be a more effective tool than SQP for minimising the sum of cubed muscle stresses in static optimisation.
NASA Astrophysics Data System (ADS)
Tai, Shen-Chuan; Chen, Peng-Yu; Chao, Chian-Yen
2016-07-01
The Consultative Committee for Space Data Systems proposed an efficient image compression standard that can do lossless compression (CCSDS-ICS). CCSDS-ICS is the most widely utilized standard for satellite communications. However, the original CCSDS-ICS is weak in terms of error resilience with even a single incorrect bit possibly causing numerous missing pixels. A restoration algorithm based on the neighborhood similar pixel interpolator is proposed to fill in missing pixels. The linear regression model is used to generate the reference image from other panchromatic or multispectral images. Furthermore, an adaptive search window is utilized to sieve out similar pixels from the pixels in the search region defined in the neighborhood similar pixel interpolator. The experimental results show that the proposed methods are capable of reconstructing missing regions with good visual quality.
Design, rationale, and baseline demographics of SEARCH I: a prospective cluster-randomized study
Albers, Frank; Shaikh, Asif; Iqbal, Ahmar
2012-01-01
Questionnaires are available to identify patients at risk for several chronic diseases, including COPD, but are infrequently utilized in primary care. COPD is often underdiagnosed, while at the same time the US Preventive Services Task Force recommends against spirometric screening for COPD in asymptomatic adults. Use of a symptom-based questionnaire and subsequent handheld spirometric device depending on the answers to the questionnaire is a promising approach to identify patients at risk for COPD. Screening, Evaluating and Assessing Rate CHanges of diagnosing respiratory conditions in primary care 1 (SEARCH I) was a prospective cluster-randomized study in 168 US primary care practices evaluating the effect of the COPD-Population Screener (COPD-PS™) questionnaire. The effect of this questionnaire alone or sequentially with the handheld copd-6TM device was evaluated on new diagnoses of COPD and on respiratory diagnostic practice patterns (including referrals for pulmonary function testing, referrals to pulmonologists, new diagnoses of COPD, and new respiratory medication prescriptions). Participating practices entered a total of 9704 consecutive consenting subjects aged ≥ 40 years attending primary care clinics. Study arm results were compared for new COPD diagnosis rates between usual care and (1) COPD-PS plus copd-6 and (2) COPD-PS alone. A cluster-randomization design allowed comparison of the intervention effects at the practice level instead of individuals being the subjects of the intervention. Regional principal investigators controlled the flow of study information to sub-investigators at participating practices to reduce observation bias (Hawthorne effect). The results of SEARCH I, to be published subsequently, will provide insight into the real world utility of the COPD-PS as well as two-stage COPD case finding with COPD-PS and copd-6. PMID:22848157
Pure random search for ambient sensor distribution optimisation in a smart home environment.
Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming
2011-01-01
Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.
Ab initio random structure search for 13-atom clusters of fcc elements.
Chou, J P; Hsing, C R; Wei, C M; Cheng, C; Chang, C M
2013-03-27
The 13-atom metal clusters of fcc elements (Al, Rh, Ir, Ni, Pd, Pt, Cu, Ag, Au) were studied by density functional theory calculations. The global minima were searched for by the ab initio random structure searching method. In addition to some new lowest-energy structures for Pd13 and Au13, we found that the effective coordination numbers of the lowest-energy clusters would increase with the ratio of the dimer-to-bulk bond length. This correlation, together with the electronic structures of the lowest-energy clusters, divides the 13-atom clusters of these fcc elements into two groups (except for Au13, which prefers a two-dimensional structure due to the relativistic effect). Compact-like clusters that are composed exclusively of triangular motifs are preferred for elements without d-electrons (Al) or with (nearly) filled d-band electrons (Ni, Pd, Cu, Ag). Non-compact clusters composed mainly of square motifs connected by some triangular motifs (Rh, Ir, Pt) are favored for elements with unfilled d-band electrons.
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
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
Ryeznik, Yevgen; Sverdlov, Oleksandr; Wong, Weng Kee
2015-08-01
Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool, a user interface software developed in MATLAB for designing response-adaptive randomized comparative clinical trials with censored time-to-event outcomes. The RARtool software can compute different types of optimal treatment allocation designs, and it can simulate response-adaptive randomization procedures targeting selected optimal allocations. Through simulations, an investigator can assess design characteristics under a variety of experimental scenarios and select the best procedure for practical implementation. We illustrate the utility of our RARtool software by redesigning a survival trial from the literature.
Optimal search strategies of space-time coupled random walkers with finite lifetimes.
Campos, D; Abad, E; Méndez, V; Yuste, S B; Lindenberg, K
2015-05-01
We present a simple paradigm for detection of an immobile target by a space-time coupled random walker with a finite lifetime. The motion of the walker is characterized by linear displacements at a fixed speed and exponentially distributed duration, interrupted by random changes in the direction of motion and resumption of motion in the new direction with the same speed. We call these walkers "mortal creepers." A mortal creeper may die at any time during its motion according to an exponential decay law characterized by a finite mean death rate ω(m). While still alive, the creeper has a finite mean frequency ω of change of the direction of motion. In particular, we consider the efficiency of the target search process, characterized by the probability that the creeper will eventually detect the target. Analytic results confirmed by numerical results show that there is an ω(m)-dependent optimal frequency ω=ω(opt) that maximizes the probability of eventual target detection. We work primarily in one-dimensional (d=1) domains and examine the role of initial conditions and of finite domain sizes. Numerical results in d=2 domains confirm the existence of an optimal frequency of change of direction, thereby suggesting that the observed effects are robust to changes in dimensionality. In the d=1 case, explicit expressions for the probability of target detection in the long time limit are given. In the case of an infinite domain, we compute the detection probability for arbitrary times and study its early- and late-time behavior. We further consider the survival probability of the target in the presence of many independent creepers beginning their motion at the same location and at the same time. We also consider a version of the standard "target problem" in which many creepers start at random locations at the same time.
NASA Astrophysics Data System (ADS)
Phillips, Carolyn L.
2014-09-01
In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.
Dawson, Ree; Lavori, Philip W.
2015-01-01
Nonadherence to assigned treatment jeopardizes the power and interpretability of intent-to-treat comparisons from clinical trial data and continues to be an issue for effectiveness studies, despite their pragmatic emphasis. We posit that new approaches to design need to complement developments in methods for causal inference to address nonadherence, in both experimental and practice settings. This paper considers the conventional study design for psychiatric research and other medical contexts, in which subjects are randomized to treatments that are fixed throughout the trial and presents an alternative that converts the fixed treatments into an adaptive intervention that reflects best practice. The key element is the introduction of an adaptive decision point midway into the study to address a patient's reluctance to remain on treatment before completing a full-length trial of medication. The clinical uncertainty about the appropriate adaptation prompts a second randomization at the new decision point to evaluate relevant options. Additionally, the standard ‘all-or-none’ principal stratification (PS) framework is applied to the first stage of the design to address treatment discontinuation that occurs too early for a mid-trial adaptation. Drawing upon the adaptive intervention features, we develop assumptions to identify the PS causal estimand and introduce restrictions on outcome distributions to simplify Expectation-Maximization calculations. We evaluate the performance of the PS setup, with particular attention to the role played by a binary covariate. The results emphasize the importance of collecting covariate data for use in design and analysis. We consider the generality of our approach beyond the setting of psychiatric research. PMID:25581413
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.
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.
Li, Zhiguo
2017-02-10
In sequential multiple assignment randomized trials, longitudinal outcomes may be the most important outcomes of interest because this type of trials is usually conducted in areas of chronic diseases or conditions. We propose to use a weighted generalized estimating equation (GEE) approach to analyzing data from such type of trials for comparing two adaptive treatment strategies based on generalized linear models. Although the randomization probabilities are known, we consider estimated weights in which the randomization probabilities are replaced by their empirical estimates and prove that the resulting weighted GEE estimator is more efficient than the estimators with true weights. The variance of the weighted GEE estimator is estimated by an empirical sandwich estimator. The time variable in the model can be linear, piecewise linear, or more complicated forms. This provides more flexibility that is important because, in the adaptive treatment setting, the treatment changes over time and, hence, a single linear trend over the whole period of study may not be practical. Simulation results show that the weighted GEE estimators of regression coefficients are consistent regardless of the specification of the correlation structure of the longitudinal outcomes. The weighted GEE method is then applied in analyzing data from the Clinical Antipsychotic Trials of Intervention Effectiveness. Copyright © 2016 John Wiley & Sons, Ltd.
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.
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
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.
Random access with adaptive packet aggregation in LTE/LTE-A.
Zhou, Kaijie; Nikaein, Navid
While random access presents a promising solution for efficient uplink channel access, the preamble collision rate can significantly increase when massive number of devices simultaneously access the channel. To address this issue and improve the reliability of the random access, an adaptive packet aggregation method is proposed. With the proposed method, a device does not trigger a random access for every single packet. Instead, it starts a random access when the number of aggregated packets reaches a given threshold. This method reduces the packet collision rate at the expense of an extra latency, which is used to accumulate multiple packets into a single transmission unit. Therefore, the tradeoff between packet loss rate and channel access latency has to be carefully selected. We use semi-Markov model to derive the packet loss rate and channel access latency as functions of packet aggregation number. Hence, the optimal amount of aggregated packets can be found, which keeps the loss rate below the desired value while minimizing the access latency. We also apply for the idea of packet aggregation for power saving, where a device aggregates as many packets as possible until the latency constraint is reached. Simulations are carried out to evaluate our methods. We find that the packet loss rate and/or power consumption are significantly reduced with the proposed method.
NASA Astrophysics Data System (ADS)
Liu, Yingzhe; Wang, Jinxiang; Fu, Fangfa
2013-04-01
The H.264/AVC video standard adopts a fixed search range (SR) and fixed reference frame (RF) for motion estimation. These fixed settings result in a heavy computational load in the video encoder. We propose a dynamic SR and multiframe selection algorithm to improve the computational efficiency of motion estimation. By exploiting the relationship between the predicted motion vector and the SR size, we develop an adaptive SR adjustment algorithm. We also design a RF selection scheme based on the correlation between the different block sizes of the macroblock. Experimental results show that our algorithm can significantly reduce the computational complexity of motion estimation compared with the JM15.1 reference software, with a negligible decrease in peak signal-to-noise ratio and a slight increase in bit rate. Our algorithm also outperforms existing methods in terms of its low complexity and high coding quality.
On Using Adaptive Binary Search Trees to Enhance Self Organizing Maps
NASA Astrophysics Data System (ADS)
Astudillo, César A.; Oommen, B. John
We present a strategy by which a Self-Organizing Map (SOM) with an underlying Binary Search Tree (BST) structure can be adaptively re-structured using conditional rotations. These rotations on the nodes of the tree are local and are performed in constant time, guaranteeing a decrease in the Weighted Path Length (WPL) of the entire tree. As a result, the algorithm, referred to as the Tree-based Topology-Oriented SOM with Conditional Rotations (TTO-CONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution, and additionally, the neighborhood properties of the neurons suit the best BST that represents the data.
Sadjadi, Firooz A
2006-08-01
An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.
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
Zhu, Hongjian
2016-12-12
Seamless phase II/III clinical trials have attracted increasing attention recently. They mainly use Bayesian response adaptive randomization (RAR) designs. There has been little research into seamless clinical trials using frequentist RAR designs because of the difficulty in performing valid statistical inference following this procedure. The well-designed frequentist RAR designs can target theoretically optimal allocation proportions, and they have explicit asymptotic results. In this paper, we study the asymptotic properties of frequentist RAR designs with adjusted target allocation proportions, and investigate statistical inference for this procedure. The properties of the proposed design provide an important theoretical foundation for advanced seamless clinical trials. Our numerical studies demonstrate that the design is ethical and efficient.
Gibson, Bradley S.; Kronenberger, William G.; Gondoli, Dawn M.; Johnson, Ann C.; Morrissey, Rebecca A.; Steeger, Christine M.
2012-01-01
There has been growing interest in using adaptive training interventions such as Cogmed-RM to increase the capacity of working memory (WM), but this intervention may not be optimally designed. For instance, Cogmed-RM can target the primary memory (PM) component of WM capacity, but not the secondary memory (SM) component. The present study hypothesized that Cogmed-RM does not target SM capacity because the simple span exercises it uses may not cause a sufficient amount of information to be lost from PM during training. To investigate, we randomly assigned participants to either a standard (simple span; N = 31) or a modified (complex span; N = 30) training condition. The main findings showed that SM capacity did not improve, even in the modified training condition. Hence, the potency of span-based WM interventions cannot be increased simply by converting simple span exercises into complex span exercises. PMID:23066524
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
2006-01-01
Objectives: The Alzheimer's Disease Anti-inflammatory Prevention Trial (ADAPT) was designed to evaluate the conventional NSAID naproxen sodium and the selective COX-2 inhibitor celecoxib for primary prevention of Alzheimer's dementia (AD). On 17 December 2004, after the Adenoma Prevention with Celecoxib (APC) trial reported increased cardiovascular risks with celecoxib, the ADAPT Steering Committee suspended treatment and enrollment. This paper reports on cardiovascular and cerebrovascular events in ADAPT. Design: ADAPT is a randomized, placebo-controlled, parallel chemoprevention trial with 1–46 mo of follow-up. Setting: The trial was conducted at six field sites in the United States: Baltimore, Maryland; Boston, Massachusetts; Rochester, New York; Seattle, Washington; Sun City, Arizona; and Tampa, Florida. Participants: The 2,528 participants were aged 70 y and older with a family history of AD. Interventions: Study treatments were celecoxib (200 mg b.i.d.), naproxen sodium (220 mg b.i.d.), and placebo. Outcome measures: Outcome measures were deaths, along with nonfatal myocardial infarction (MI), stroke, congestive heart failure (CHF), transient ischemic attack (TIA), and antihypertensive treatment recorded from structured interviews at scheduled intervals. Cox proportional hazards regression was used to analyze these events individually and in several composites. Results: Counts (with 3-y incidence) of participants who experienced cardiovascular or cerebrovascular death, MI, stroke, CHF, or TIA in the celecoxib-, naproxen-, and placebo-treated groups were 28/717 (5.54%), 40/713 (8.25%), and 37/1070 (5.68%), respectively. This yielded a hazard ratio (95% confidence interval [CI]) for celecoxib of 1.10 (0.67–1.79) and for naproxen of 1.63 (1.04–2.55). Antihypertensive treatment was initiated in 160/440 (47.43%), 147/427 (45.00%), and 164/644 (34.08%). This yielded hazard ratios (CIs) of 1.56 for celecoxib (1.26–1.94) and 1.40 for naproxen (1.12–1
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.
Nowacki, Amy S; Zhao, Wenle; Palesch, Yuko Y
2015-01-12
Response-adaptive randomization (RAR) offers clinical investigators benefit by modifying the treatment allocation probabilities to optimize the ethical, operational, or statistical performance of the trial. Delayed primary outcomes and their effect on RAR have been studied in the literature; however, the incorporation of surrogate outcomes has not been fully addressed. We explore the benefits and limitations of surrogate outcome utilization in RAR in the context of acute stroke clinical trials. We propose a novel surrogate-primary (S-P) replacement algorithm where a patient's surrogate outcome is used in the RAR algorithm only until their primary outcome becomes available to replace it. Computer simulations investigate the effect of both the delay in obtaining the primary outcome and the underlying surrogate and primary outcome distributional discrepancies on complete randomization, standard RAR and the S-P replacement algorithm methods. Results show that when the primary outcome is delayed, the S-P replacement algorithm reduces the variability of the treatment allocation probabilities and achieves stabilization sooner. Additionally, the S-P replacement algorithm benefit proved to be robust in that it preserved power and reduced the expected number of failures across a variety of scenarios.
CR-Calculus and adaptive array theory applied to MIMO random vibration control tests
NASA Astrophysics Data System (ADS)
Musella, U.; Manzato, S.; Peeters, B.; Guillaume, P.
2016-09-01
Performing Multiple-Input Multiple-Output (MIMO) tests to reproduce the vibration environment in a user-defined number of control points of a unit under test is necessary in applications where a realistic environment replication has to be achieved. MIMO tests require vibration control strategies to calculate the required drive signal vector that gives an acceptable replication of the target. This target is a (complex) vector with magnitude and phase information at the control points for MIMO Sine Control tests while in MIMO Random Control tests, in the most general case, the target is a complete spectral density matrix. The idea behind this work is to tailor a MIMO random vibration control approach that can be generalized to other MIMO tests, e.g. MIMO Sine and MIMO Time Waveform Replication. In this work the approach is to use gradient-based procedures over the complex space, applying the so called CR-Calculus and the adaptive array theory. With this approach it is possible to better control the process performances allowing the step-by-step Jacobian Matrix update. The theoretical bases behind the work are followed by an application of the developed method to a two-exciter two-axis system and by performance comparisons with standard methods.
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.
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.
Lin, Yunzhi; Zhu, Ming; Su, Zheng
2015-11-01
Randomization is fundamental to the design and conduct of clinical trials. Simple randomization ensures independence among subject treatment assignments and prevents potential selection biases, yet it does not guarantee balance in covariate distributions across treatment groups. Ensuring balance in important prognostic covariates across treatment groups is desirable for many reasons. A broad class of randomization methods for achieving balance are reviewed in this paper; these include block randomization, stratified randomization, minimization, and dynamic hierarchical randomization. Practical considerations arising from experience with using the techniques are described. A review of randomization methods used in practice in recent randomized clinical trials is also provided.
ERIC Educational Resources Information Center
Poslawsky, Irina E; Naber, Fabiënne BA; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H
2015-01-01
In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child…
Adaptive Algebraic Multigrid for Finite Element Elliptic Equations with Random Coefficients
Kalchev, D
2012-04-02
This thesis presents a two-grid algorithm based on Smoothed Aggregation Spectral Element Agglomeration Algebraic Multigrid (SA-{rho}AMGe) combined with adaptation. The aim is to build an efficient solver for the linear systems arising from discretization of second-order elliptic partial differential equations (PDEs) with stochastic coefficients. Examples include PDEs that model subsurface flow with random permeability field. During a Markov Chain Monte Carlo (MCMC) simulation process, that draws PDE coefficient samples from a certain distribution, the PDE coefficients change, hence the resulting linear systems to be solved change. At every such step the system (discretized PDE) needs to be solved and the computed solution used to evaluate some functional(s) of interest that then determine if the coefficient sample is acceptable or not. The MCMC process is hence computationally intensive and requires the solvers used to be efficient and fast. This fact that at every step of MCMC the resulting linear system changes, makes an already existing solver built for the old problem perhaps not as efficient for the problem corresponding to the new sampled coefficient. This motivates the main goal of our study, namely, to adapt an already existing solver to handle the problem (with changed coefficient) with the objective to achieve this goal to be faster and more efficient than building a completely new solver from scratch. Our approach utilizes the local element matrices (for the problem with changed coefficients) to build local problems associated with constructed by the method agglomerated elements (a set of subdomains that cover the given computational domain). We solve a generalized eigenproblem for each set in a subspace spanned by the previous local coarse space (used for the old solver) and a vector, component of the error, that the old solver cannot handle. A portion of the spectrum of these local eigen-problems (corresponding to eigenvalues close to zero) form the
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.
NASA Astrophysics Data System (ADS)
Chen, Hung-Ming; Chen, Po-Hung; Lin, Cheng-Tso; Liu, Ching-Chung
2012-11-01
An efficient algorithm named modified directional gradient descent searches to enhance the directional gradient descent search (DGDS) algorithm is presented to reduce computations. A modified search pattern with an adaptive threshold for early termination is applied to DGDS to avoid meaningless calculation after the searching point is good enough. A statistical analysis of best motion vector distribution is analyzed to decide the modified search pattern. Then a statistical model based on the characteristics of the block distortion information of the previous coded frame helps the early termination parameters selection, and a trade-off between the video quality and the computational complexity can be obtained. The simulation results show the proposed algorithm provides significant improvement in reducing the motion estimation (ME) by 17.81% of the average search points and 20% of ME time saving compared to the fast DGDS algorithm implemented in H.264/AVC JM 18.2 reference software according to different types of sequences, while maintaining a similar bit rate without losing picture quality.
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.
Kalchev, D.; Ketelsen, C.; Vassilevski, P. S.
2013-11-07
Our paper proposes an adaptive strategy for reusing a previously constructed coarse space by algebraic multigrid to construct a two-level solver for a problem with nearby characteristics. Furthermore, a main target application is the solution of the linear problems that appear throughout a sequence of Markov chain Monte Carlo simulations of subsurface flow with uncertain permeability field. We demonstrate the efficacy of the method with extensive set of numerical experiments.
Burger, Kyle S
2017-03-01
Background: Current obesity theories suggest that the repeated intake of highly palatable high-sugar foods causes adaptions in the striatum, parietal lobe, and prefrontal and visual cortices in the brain that may serve to perpetuate consumption in a feed-forward manner. However, the data for humans are cross-sectional and observational, leaving little ability to determine the temporal precedence of repeated consumption on brain response.Objective: We tested the impact of regular sugar-sweetened beverage intake on brain and behavioral responses to beverage stimuli.Design: We performed an experiment with 20 healthy-weight individuals who were randomly assigned to consume 1 of 2 sugar-sweetened beverages daily for 21 d, underwent 2 functional MRI sessions, and completed behavioral and explicit hedonic assessments.Results: Consistent with preclinical experiments, daily beverage consumption resulted in decreases in dorsal striatal response during receipt of the consumed beverage (r = -0.46) and decreased ventromedial prefrontal response during logo-elicited anticipation (r = -0.44). This decrease in the prefrontal response correlated with increases in behavioral disinhibition toward the logo of the consumed beverage (r = 0.54; P = 0.02). Daily beverage consumption also increased precuneus response to both juice logos compared with a tasteless control (r = 0.45), suggesting a more generalized effect toward beverage cues. Last, the repeated consumption of 1 beverage resulted in an explicit hedonic devaluation of a similar nonconsumed beverage (P < 0.001).Conclusions: Analogous to previous reports, these initial results provide convergent data for a role of regular sugar-sweetened beverage intake in altering neurobehavioral responses to the regularly consumed beverage that may also extend to other beverage stimuli. Future research is required to provide evidence of replication in a larger sample and to establish whether the neurobehavioral adaptations observed herein are
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.
Benchmark tests and spin adaptation for the particle-particle random phase approximation.
Yang, Yang; van Aggelen, Helen; Steinmann, Stephan N; Peng, Degao; 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(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)
Rukolaine, Sergey A.
2015-01-01
A technique of the shape optimization of radiant enclosures with specular-diffuse surfaces is proposed. The shape optimization problem is formulated as an operator equation of the first kind with respect to a surface to be optimized. The operator equation is reduced to a minimization problem for a least-squares objective shape functional. The minimization problem is solved by a combination of the pure random (or blind) search (the simplest stochastic minimization method) and the conjugate gradient method. The random search is used to find a starting point for the gradient method. The latter needs the gradient of the objective functional. The shape gradient of the objective functional is derived by means of the shape sensitivity analysis and the adjoint problem method. Eventually, the shape gradient is obtained as a result of solving the direct and adjoint problems. If a surface to be optimized is given by a finite number of parameters, then the objective functional becomes a function in a finite-dimensional space and the shape gradient becomes an ordinary gradient. Numerical examples of the shape optimization of "two-dimensional" radiant enclosures with polyhedral specular or specular-diffuse surfaces are given.
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…
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.
Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva
2017-03-01
In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method.
NASA Astrophysics Data System (ADS)
Bong, Chin Wei; Yoong Lam, Hong; Tajudin Khader, Ahamad; Kamarulzaman, Hamzah
2012-03-01
This article proposes a multi-objective clustering ensemble method for medical image segmentation. The proposed method is called adaptive multi-objective archive-based hybrid scatter search (AMAHSS). It utilizes fuzzy clustering with optimization of three fitness functions: global fuzzy compactness of the clusters, fuzzy separation and symmetry distance-based cluster validity index. The AMAHSS enables the search strategy to explore intensively the search space with high-quality solutions and to move to unexplored search space when necessary. The best single solution is processed using the metaclustering algorithm. The proposed framework is designed to segment lung computed tomography images for candidate nodule detection. This candidate nodule will then be classified as cancerous or non-cancerous. The authors validate the method with standard k-means, fuzzy c-means and the multi-objective genetic algorithm with different postprocessing methods for the final solution. The results obtained from the benchmark experiment indicate that the method achieves up to 90% of the positive predictive rate.
Wavelength control of random polymer fiber laser based on adaptive disorder.
Hu, Zhijia; Gao, Pengfei; Xie, Kang; Liang, Yunyun; Jiang, Haiming
2014-12-15
We demonstrate the realization of two different kinds of random polymer optical fiber lasers to control the random lasing wavelength by changing the disorder of polymer optical fibers (POFs). One is a long-range disorder POF based on copolymer refractive-index inhomogeneity, and the other is a short-range disorder POF based on polyhedral oligomeric silsesquioxanes scattering. By end pumped both disorder POFs, the coherent random lasing for both is observed. Meanwhile, the random lasing wavelength of the short-range disorder POF because of a small scattering mean-free path has been found to be blue shifted with respect to the long-range disorder POF, which will give a way to control the random lasing wavelength.
Heng, Henry H
2016-07-15
Big-data-omics have promised the success of precision medicine. However, most common diseases belong to adaptive systems where the precision is all but difficult to achieve. In this commentary, I propose a heterogeneity-mediated cellular adaptive model to search for the general model of diseases, which also illustrates why in most non-infectious non-Mendelian diseases the involvement of cellular evolution is less predictable when gene profiles are used. This synthesis is based on the following new observations/concepts: 1) the gene only codes "parts inheritance" while the genome codes "system inheritance" or the entire blueprint; 2) the nature of somatic genetic coding is fuzzy rather than precise, and genetic alterations are not just the results of genetic error but are in fact generated from internal adaptive mechanisms in response to environmental dynamics; 3) stress-response is less specific within cellular evolutionary context when compared to known biochemical specificities; and 4) most medical interventions have their unavoidable uncertainties and often can function as negative harmful stresses as trade-offs. The acknowledgment of diseases as adaptive systems calls for the action to integrate genome- (not simply individual gene-) mediated cellular evolution into molecular medicine.
NASA Astrophysics Data System (ADS)
Lang, Jun; Hao, Zhengchao
2014-01-01
In this paper, we first propose the discrete multi-parameter fractional random transform (DMPFRNT), which can make the spectrum distributed randomly and uniformly. Then we introduce this new spectrum transform into the image fusion field and present a new approach for the remote sensing image fusion, which utilizes both adaptive pulse coupled neural network (PCNN) and the discrete multi-parameter fractional random transform in order to meet the requirements of both high spatial resolution and low spectral distortion. In the proposed scheme, the multi-spectral (MS) and panchromatic (Pan) images are converted into the discrete multi-parameter fractional random transform domains, respectively. In DMPFRNT spectrum domain, high amplitude spectrum (HAS) and low amplitude spectrum (LAS) components carry different informations of original images. We take full advantage of the synchronization pulse issuance characteristics of PCNN to extract the HAS and LAS components properly, and give us the PCNN ignition mapping images which can be used to determine the fusion parameters. In the fusion process, local standard deviation of the amplitude spectrum is chosen as the link strength of pulse coupled neural network. Numerical simulations are performed to demonstrate that the proposed method is more reliable and superior than several existing methods based on Hue Saturation Intensity representation, Principal Component Analysis, the discrete fractional random transform etc.
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-07-12
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.
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
NASA Astrophysics Data System (ADS)
Žeželj, M.; Stanković, I.
2016-10-01
Random networks of as-grown single-walled carbon nanotubes (CNTs) contain both metallic (m-CNTs) and semiconducting (s-CNTs) nanotubes in an approximate ratio of 1:2, which leads to a trade-off between on-conductance and the on/off ratio. We demonstrate how this design problem can be solved with a realistic numerical approach. We determine the CNT density, length, and channel dimensions under which CNT thin-film transistors simultaneously attain on-conductance higher than 1 μS and an on/off ratio higher than 104. The fact that asymmetric systems have more pronounced finite-size scaling behavior than symmetric systems allows us additional design freedom. A realization probability of the desired characteristics higher than 99% is obtained for the channels with aspect ratio {L}{{CH}}/{W}{{CH}}\\lt 1.2 and normalized size {L}{{CH}}{W}{{CH}}/{l}{{CNT}}2\\gt 250 when the CNT length is {l}{{CNT}}=4-20 μ {{m}} and the normalized density of CNTs is close to the value where the probability of percolation through only s-CNT pathways reaches its maximum.
Hemmelmayr, Vera C; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-12-01
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.
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
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.
Wang, Jiexin; Uchibe, Eiji; Doya, Kenji
2017-01-01
EM-based policy search methods estimate a lower bound of the expected return from the histories of episodes and iteratively update the policy parameters using the maximum of a lower bound of expected return, which makes gradient calculation and learning rate tuning unnecessary. Previous algorithms like Policy learning by Weighting Exploration with the Returns, Fitness Expectation Maximization, and EM-based Policy Hyperparameter Exploration implemented the mechanisms to discard useless low-return episodes either implicitly or using a fixed baseline determined by the experimenter. In this paper, we propose an adaptive baseline method to discard worse samples from the reward history and examine different baselines, including the mean, and multiples of SDs from the mean. The simulation results of benchmark tasks of pendulum swing up and cart-pole balancing, and standing up and balancing of a two-wheeled smartphone robot showed improved performances. We further implemented the adaptive baseline with mean in our two-wheeled smartphone robot hardware to test its performance in the standing up and balancing task, and a view-based approaching task. Our results showed that with adaptive baseline, the method outperformed the previous algorithms and achieved faster, and more precise behaviors at a higher successful rate. PMID:28167910
2013-10-01
Randomized Controlled Trial PRINCIPAL INVESTIGATOR: Henry W. Mahncke, Ph.D. CONTRACTING ORGANIZATION: Brain Plasticity, Inc...WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Brain Plasticity Inc. AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT...TERMS traumatic brain injury, tbi, concussion, persistent post-concussive symptoms, cognition, cognitive function, cognitive rehabilitation
2012-10-01
Veterans: A Randomized Controlled Trial PRINCIPAL INVESTIGATOR: Henry W. Mahncke, Ph.D. CONTRACTING ORGANIZATION: Brain Plasticity...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Brain Plasticity Inc., San Francisco, CA 94105 ES) 8. PERFORMING ORGANIZATION REPORT...SUBJECT TERMS traumatic brain injury, tbi, concussion, persistent post-concussive symptoms, cognition, cognitive function, cognitive rehabilitation
Practical high-order adaptive optics systems for extrasolar planet searches
NASA Astrophysics Data System (ADS)
Macintosh, Bruce A.; Olivier, Scot S.; Bauman, Brian J.; Brase, James M.; Carr, Emily; Carrano, Carmen J.; Gavel, Donald T.; Max, Claire E.; Patience, Jennifer
2002-02-01
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 109 - Jupiter is a billion times fainter than the sun. Current adaptive optics systems can only achieve contrast levels of 106, but so-called extreme adaptive optics systems with 104 -105 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 r0 (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.
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.
SEEK-TIME IMPROVEMENT IN A RANDOM-ACCESS FILE BY APPLICATION OF AN ADAPTIVE ELEMENT
An Adaline (adaptive linear neuron) can be trained to distinguish between sets of inputs. In general, the quantized output is used. This report...investigates the usefulness of the analog output of Adaline for measuring the frequency of occurrence of a number of different events. Each event is more...or less arbitrarily associated with a pattern and it is shown that the degree to which Adaline has been trained to recognize any one of these patterns
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.
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
Hao, Xiang; Martin-Rouault, Laure; Cui, Meng
2014-01-01
Controlling the propagation of electromagnetic waves is important to a broad range of applications. Recent advances in controlling wave propagation in random scattering media have enabled optical focusing and imaging inside random scattering media. In this work, we propose and demonstrate a new method to deliver optical power more efficiently through scattering media. Drastically different from the random matrix characterization approach, our method can rapidly establish high efficiency communication channels using just a few measurements, regardless of the number of optical modes, and provides a practical and robust solution to boost the signal levels in optical or short wave communications. We experimentally demonstrated analog and digital signal transmission through highly scattering media with greatly improved performance. Besides scattering, our method can also reduce the loss of signal due to absorption. Experimentally, we observed that our method forced light to go around absorbers, leading to even higher signal improvement than in the case of purely scattering media. Interestingly, the resulting signal improvement is highly directional, which provides a new means against eavesdropping. PMID:25070592
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
Campana, Gianluca; Camilleri, Rebecca; Moret, Beatrice; Ghin, Filippo; Pavan, Andrea
2016-01-01
Transcranial random noise stimulation (tRNS) is a recent neuro-modulation technique whose effects at both behavioural and neural level are still debated. Here we employed the well-known phenomenon of motion after-effect (MAE) in order to investigate the effects of high- vs. low-frequency tRNS on motion adaptation and recovery. Participants were asked to estimate the MAE duration following prolonged adaptation (20 s) to a complex moving pattern, while being stimulated with either sham or tRNS across different blocks. Different groups were administered with either high- or low-frequency tRNS. Stimulation sites were either bilateral human MT complex (hMT+) or frontal areas. The results showed that, whereas no effects on MAE duration were induced by stimulating frontal areas, when applied to the bilateral hMT+, high-frequency tRNS caused a significant decrease in MAE duration whereas low-frequency tRNS caused a significant corresponding increase in MAE duration. These findings indicate that high- and low-frequency tRNS have opposed effects on the adaptation-dependent unbalance between neurons tuned to opposite motion directions, and thus on neuronal excitability. PMID:27934947
Rath, J J; Veluvolu, K C; Defoort, M
2014-01-01
The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system.
Rath, J. J.; Veluvolu, K. C.; Defoort, M.
2014-01-01
The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system. PMID:24683321
Kording, Konrad P.; Hargrove, Levi J.; Sensinger, Jonathon W.
2017-01-01
The objective of this study was to understand how people adapt to errors when using a myoelectric control interface. We compared adaptation across 1) non-amputee subjects using joint angle, joint torque, and myoelectric control interfaces, and 2) amputee subjects using myoelectric control interfaces with residual and intact limbs (five total control interface conditions). We measured trial-by-trial adaptation to self-generated errors and random perturbations during a virtual, single degree-of-freedom task with two levels of feedback uncertainty, and evaluated adaptation by fitting a hierarchical Kalman filter model. We have two main results. First, adaptation to random perturbations was similar across all control interfaces, whereas adaptation to self-generated errors differed. These patterns matched predictions of our model, which was fit to each control interface by changing the process noise parameter that represented system variability. Second, in amputee subjects, we found similar adaptation rates and error levels between residual and intact limbs. These results link prosthesis control to broader areas of motor learning and adaptation and provide a useful model of adaptation with myoelectric control. The model of adaptation will help us understand and solve prosthesis control challenges, such as providing additional sensory feedback. PMID:28301512
Cermak, Sharon A; Stein Duker, Leah I; Williams, Marian E; Dawson, Michael E; Lane, Christianne J; Polido, José C
2015-09-01
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 3-4 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.
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
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.
Wei, Yan; Wang, Xiaolin; Liu, Jingfang; Nememan, Ilya; Singh, Amoolya H; Weiss, Howie; Levin, Bruce R
2011-03-08
Why is motility so common in bacteria? An obvious answer to this ecological and evolutionary question is that in almost all habitats, bacteria need to go someplace and particularly in the direction of food. Although the machinery required for motility and chemotaxis (acquiring and processing the information needed to direct movement toward nutrients) are functionally coupled in contemporary bacteria, they are coded for by different sets of genes. Moreover, information that resources are more abundant elsewhere in a habitat would be of no value to a bacterium unless it already had the means to get there. Thus, motility must have evolved before chemotaxis, and bacteria with flagella and other machinery for propulsion in random directions must have an advantage over bacteria relegated to moving at the whim of external forces alone. However, what are the selection pressures responsible for the evolution and maintenance of undirected motility in bacteria? Here we use a combination of mathematical modeling and experiments with Escherichia coli to generate and test a parsimonious and ecologically general hypothesis for the existence of undirected motility in bacteria: it enables bacteria to move away from each other and thereby obtain greater individual shares of resources in physically structured environments. The results of our experiments not only support this hypothesis, but are quantitatively and qualitatively consistent with the predictions of our model.
Human tracking in thermal images using adaptive particle filters with online random forest learning
NASA Astrophysics Data System (ADS)
Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal
2013-11-01
This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.
Mahalati, Reza Nasiri; Askarov, Daulet; Wilde, Jeffrey P; Kahn, Joseph M
2012-06-18
We develop a method for synthesis of a desired intensity profile at the output of a multimode fiber (MMF) with random mode coupling by controlling the input field distribution using a spatial light modulator (SLM) whose complex reflectance is piecewise constant over a set of disjoint blocks. Depending on the application, the desired intensity profile may be known or unknown a priori. We pose the problem as optimization of an objective function quantifying, and derive a theoretical lower bound on the achievable objective function. We present an adaptive sequential coordinate ascent (SCA) algorithm for controlling the SLM, which does not require characterizing the full transfer characteristic of the MMF, and which converges to near the lower bound after one pass over the SLM blocks. This algorithm is faster than optimizations based on genetic algorithms or random assignment of SLM phases. We present simulated and experimental results applying the algorithm to forming spots of light at a MMF output, and describe how the algorithm can be applied to imaging.
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
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
Selvan, S Easter; Borckmans, Pierre B; Chattopadhyay, A; Absil, P-A
2013-09-01
It is seemingly paradoxical to the classical definition of the independent component analysis (ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this letter concerns a framework to extract quasi-uncorrelated sources with finite supports by optimizing a range-based contrast function under unit-norm constraints (to handle the inherent scaling indeterminacy of ICA) but without orthogonality constraints. Albeit the appealing contrast properties of the range-based function (e.g., the absence of mixing local optima), the function is not differentiable everywhere. Unfortunately, there is a dearth of literature on derivative-free optimizers that effectively handle such a nonsmooth yet promising contrast function. This is the compelling reason for the design of a nonsmooth optimization algorithm on a manifold of matrices having unit-norm columns with the following objectives: to ascertain convergence to a Clarke stationary point of the contrast function and adhere to the necessary unit-norm constraints more naturally. The proposed nonsmooth optimization algorithm crucially relies on the design and analysis of an extension of the mesh adaptive direct search (MADS) method to handle locally Lipschitz objective functions defined on the sphere. The applicability of the algorithm in the ICA domain is demonstrated with simulations involving natural, face, aerial, and texture images.
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
2015-01-01
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 six-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 six 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
ERIC Educational Resources Information Center
Raudenbush, Stephen W.
2009-01-01
Fixed effects models are often useful in longitudinal studies when the goal is to assess the impact of teacher or school characteristics on student learning. In this article, I introduce an alternative procedure: adaptive centering with random effects. I show that this procedure can replicate the fixed effects analysis while offering several…
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.
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.
Christopher, Mary M.; Pereira, Jacqueline L.; Brigmon, Robin L.
1992-01-01
An automated method for measuring beta-hydroxybutyrate was adapted to the Ciba-Corning 550 Express trade mark random access analyzer. The assay was based on a kinetic reaction utilizing hydroxybutyrate-dehydrogenase. Beta-hydroxybutyrate concentration (mmol/L) was calculated ratiometrically using a 1.0 mmol/l standard. Canine serum, plasma, and urine were used without prior deproteinization and only a 30-microliter sample was required. The method demonstrated good linearity between 0 to 2 mmol/l of beta-hydroxybutyrate. Analytical recovery (accuracy) within these concentrations ranged from 85.8 to 113.3%. Both within-run and day-to-day precision were determined, as was specificity of the assay in the presence of a variety of interfering substances. The automated assay was rapid and economical, with reagent stability maintained for at least 2 weeks at 4 degrees C. This assay can readily be applied toward the assessment of ketoacidosis in dogs, and with further validation, other species.
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.
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.
Rotundo, Mario P.; Whittall, Jonathan P.; Scribbans, Trisha D.; Graham, Ryan B.; Gurd, Brendon J.
2016-01-01
The current study examined the adaptive response to both endurance (END) and sprint interval training (SIT) in a group of twenty-one recreationally active adults. All participants completed three weeks (four days/ week) of both END (30 minutes at ~65% VO2peak work rate (WR) and SIT (eight, 20-second intervals at ~170% VO2peak WR separated by 10 seconds of active rest) following a randomized crossover study design with a three-month washout period between training interventions. While a main effect of training was observed for VO2peak, lactate threshold, and submaximal heart rate (HR), considerable variability was observed in the individual responses to both END and SIT. No significant positive relationships were observed between END and SIT for individual changes in any variable. Non-responses were determined using two times the typical error (TE) of measurement for VO2peak (0.107 L/min), lactate threshold (15.7 W), and submaximal HR (10.7bpm). Non-responders in VO2peak, lactate threshold, and submaximal HR were observed following both END and SIT, however, the individual patterns of response differed following END and SIT. Interestingly, all individuals responded in at least one variable when exposed to both END and SIT. These results suggest that the individual response to exercise training is highly variable following different training protocols and that the incidence of non-response to exercise training may be reduced by changing the training stimulus for non-responders to three weeks of END or SIT. PMID:27936084
NASA Astrophysics Data System (ADS)
Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong
2014-09-01
In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.
De Voogd, E L; Wiers, R W; Salemink, E
2017-05-01
Anxiety and depression, which are highly prevalent in adolescence, are both characterized by a negative attentional bias. As Attentional Bias Modification (ABM) can reduce such a bias, and might also affect emotional reactivity, it could be a promising early intervention. However, a growing number of studies also report comparable improvements in both active and placebo groups. The current study investigated the effects of eight online sessions of visual search (VS) ABM compared to both a VS placebo-training and a no-training control group in adolescents with heightened symptoms of anxiety and/or depression (n = 108). Attention bias, interpretation bias, and stress-reactivity were assessed pre- and post-training. Primary outcomes of anxiety and depressive symptoms, and secondary measures of emotional resilience were assessed pre- and post-training and at three and six months follow-up. Results revealed that VS training reduced attentional bias compared to both control groups, with stronger effects for participants who completed more training sessions. Irrespective of training condition, an overall reduction in symptoms of anxiety and depression and an increase in emotional resilience were observed up to six months later. The training was evaluated relatively negatively. Results suggest that online ABM as employed in the current study has no added value as an early intervention in adolescents with heightened symptoms.
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.
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…
2009-01-01
Background Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer-approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion Our results show the utility of the
NASA Astrophysics Data System (ADS)
Liao, Qinzhuo; Zhang, Dongxiao; Tchelepi, Hamdi
2017-02-01
A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod-Patterson-Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.
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.
Prinsen, E C; Nederhand, M J; Sveinsdóttir, H S; Prins, M R; van der Meer, F; Koopman, H F J M; Rietman, J S
2017-01-01
Previously conducted trials comparing the gait pattern of individuals with a transfemoral amputation using a user-adaptive and a non-microprocessor-controlled prosthetic knee (NMPK) found mixed and conflicting results. Few trials, however, have compared user-adaptive to non-adaptive prosthetic knees across different walking speeds. Because of the ability of variable damping, the effect of user-adaptive knees might be more pronounced at lower or higher walking speeds. Our aim was to compare the Rheo Knee II (a microprocessor-controlled prosthetic knee) with NMPKs across varying walking speeds. In addition, we studied compensatory mechanisms associated with non-optimal prosthetic knee kinematics, such as intact ankle vaulting and vertical acceleration of the pelvis. Nine persons with a transfemoral amputation or knee disarticulation were included and measured with their own NMPK and with the Rheo Knee II. Measurements were performed at three walking speeds: preferred walking speed, 70% preferred walking speed and 115% preferred walking speed. No differences on peak prosthetic knee flexion during swing were found between prosthetic knee conditions. In addition, prosthetic knee flexion increased significantly with walking speed for both prosthetic knee conditions. At 70% preferred walking speed we found that vaulting of the intact ankle was significantly decreased while walking with the Rheo Knee II compared to the NMPK condition (P=0.028). We did not find differences in peak vertical acceleration of the pelvis during initial and mid-swing of the prosthetic leg. In conclusion, comparison of walking with the Rheo Knee II to walking with a NMPK across different walking speeds showed limited differences in gait parameters.
Muratori, Pietro; Bertacchi, Iacopo; Giuli, Consuelo; Nocentini, Annalaura; Lochman, John E
2016-09-24
Behavioral problems in schools can cause serious harm to the emotional and social well-being of students and limit their ability to achieve their full academic potential. A prior pilot study on the universal application of Coping Power showed a significant decrease in the hyperactivity behaviors of five classes. The next step was to test whether Coping Power Universal could be successfully implemented by teachers in a variety of Italian schools. The sample involved 40 third- and fourth-grade classes (901 students) from public schools located in three Italian cities. Twenty classes were randomly assigned to Coping Power Universal, and 20 classes were randomly assigned to the control group, which received the strictly standard academic curriculum of Italian elementary schools. At each assessment period, the teachers completed the Strengths and Difficulties Questionnaire. The findings showed a significant reduction in hyperactive and inattention behaviors and conduct problems and emotional symptoms in the intervention classes compared with the control classes. This study suggests that Coping Power model can be delivered in school settings at both universal and targeted prevention levels and that in this multi-tiered prevention model, teachers can learn a set of intervention skills which can be delivered with flexibility, thus reducing some of the complexity and costs of schools using multiple interventions.
NASA Astrophysics Data System (ADS)
Tian, Yu-Kun; Zhou, Hui; Chen, Han-Ming; Zou, Ya-Ming; Guan, Shou-Jun
2013-12-01
Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber-Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.
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).
SEARCHING FOR BINARY Y DWARFS WITH THE GEMINI MULTI-CONJUGATE ADAPTIVE OPTICS SYSTEM (GeMS)
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., 10{sup 42} erg) are consistent with those observed in previous studies of hotter ultra-cool dwarfs.
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.
Adaptive Highlighting of Links to Assist Surfing on the Internet
2002-01-01
in about 5 to 10 steps, or less. Keywords: Internet, search, intelligent crawler, reinforcement learning , adaptivity, information filtering 1...into the value estimation algorithm to be described below. 2.5 Adaptation 2.5.1 On-line reinforcement learning (RL) RL is the state-of-the-art method...window update, dotted line: reinforcement learning . User switched weights randomly in every 50 steps. In the moving window update experiment the
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.
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.
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
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
Tanjasiri, Sora Park; Weiss, Jie W.; Santos, Lola; Flores, Peter; Flores, Preciosa; DeGuzman Lacsamana, Jasmine; Paige, Ciara; Mouttapa, Michele; Quitugua, Lourdes; Taito, Peniamina; May, Vanessa Tui’one; Tupua, Marina; Vaikona, Elenoa; Vaivao, Dorothy; Vunileva, Isileli
2016-01-01
Background Pacific Islanders (PIs) experience high cervical cancer rates in the United States. Stage of diagnosis is also later for PIs than non-Hispanic Whites. The Pap test is severely underutilized among PIs: only 71% of Asian American and Pacific Islander women age 25 years or older received a Pap test within the last 3 years (U.S. average, 82%). Community-based participatory research (CBPR) is increasingly seen as an essential approach in designing and conducting culturally relevant and appropriate studies that reduce cancer incidence and other health disparities among minority and other medically underserved populations. Purpose The purpose of this article is to describe the lessons learned thus far regarding the identification, recruitment, and retention of PI community organizations and members into a CBPR-informed, randomized, community trial promoting Pap testing. Methods This 5-year study used CBPR to develop and test the efficacy of a social support intervention for Chamorro, Samoan, and Tongan women to increase Pap testing in southern California. Eligible women were between the ages of 21 and 65, and married or in a long-term relationship with a man for at least 5 years. Women and their husbands or significant others received a 2-hour, culturally tailored workshop that include a group activity, information on Pap testing, a video, and corresponding materials. Comparison participants received a brochure about Pap testing. Three waves of data are collected from all participants: pretest (before workshop or brochure), posttest 1 (immediately after workshop or brochure), and posttest 2 (6 months follow-up). Results Of the 76 organizations approached to participate in the study, 67 (88.2%) eventually agreed to participate. Thus far, 473 women and 419 men completed the study pretest, post-test, education, and 6-month follow-up. Only 242 women and 204 men of the eligible participants have completed the follow-up survey (63.5% of women and 60.5% of men
Parameter Estimation of Nonlinear Systems by Dynamic Cuckoo Search.
Liao, Qixiang; Zhou, Shudao; Shi, Hanqing; Shi, Weilai
2017-04-01
In order to address with the problem of the traditional or improved cuckoo search (CS) algorithm, we propose a dynamic adaptive cuckoo search with crossover operator (DACS-CO) algorithm. Normally, the parameters of the CS algorithm are kept constant or adapted by empirical equation that may result in decreasing the efficiency of the algorithm. In order to solve the problem, a feedback control scheme of algorithm parameters is adopted in cuckoo search; Rechenberg's 1/5 criterion, combined with a learning strategy, is used to evaluate the evolution process. In addition, there are no information exchanges between individuals for cuckoo search algorithm. To promote the search progress and overcome premature convergence, the multiple-point random crossover operator is merged into the CS algorithm to exchange information between individuals and improve the diversification and intensification of the population. The performance of the proposed hybrid algorithm is investigated through different nonlinear systems, with the numerical results demonstrating that the method can estimate parameters accurately and efficiently. Finally, we compare the results with the standard CS algorithm, orthogonal learning cuckoo search algorithm (OLCS), an adaptive and simulated annealing operation with the cuckoo search algorithm (ACS-SA), a genetic algorithm (GA), a particle swarm optimization algorithm (PSO), and a genetic simulated annealing algorithm (GA-SA). Our simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
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.
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…
André, Marc P E; Girinsky, Théodore; Federico, Massimo; Reman, Oumédaly; Fortpied, Catherine; Gotti, Manuel; Casasnovas, Olivier; Brice, Pauline; van der Maazen, Richard; Re, Alessandro; Edeline, Véronique; Fermé, Christophe; van Imhoff, Gustaaf; Merli, Francesco; Bouabdallah, Réda; Sebban, Catherine; Specht, Lena; Stamatoullas, Aspasia; Delarue, Richard; Fiaccadori, Valeria; Bellei, Monica; Raveloarivahy, Tiana; Versari, Annibale; Hutchings, Martin; Meignan, Michel; Raemaekers, John
2017-03-14
Purpose Patients who receive combined modality treatment for stage I and II Hodgkin lymphoma (HL) have an excellent outcome. Early response evaluation with positron emission tomography (PET) scan may improve selection of patients who need reduced or more intensive treatments. Methods We performed a randomized trial to evaluate treatment adaptation on the basis of early PET (ePET) after two cycles of doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) in previously untreated-according to European Organisation for Research and Treatment of Cancer criteria favorable (F) and unfavorable (U)-stage I and II HL. The standard arm consisted of ABVD followed by involved-node radiotherapy (INRT), regardless of ePET result. In the experimental arm, ePET-negative patients received ABVD only (noninferiority design), whereas ePET-positive patients switched to two cycles of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (BEACOPPesc) and INRT (superiority design). Primary end point was progression-free survival (PFS). Results Of 1,950 randomly assigned patients, 1,925 received an ePET-361 patients (18.8%) were positive. In ePET-positive patients, 5-year PFS improved from 77.4% for standard ABVD + INRT to 90.6% for intensification to BEACOPPesc + INRT (hazard ratio [HR], 0.42; 95% CI, 0.23 to 0.74; P = .002). In ePET-negative patients, 5-year PFS rates in the F group were 99.0% versus 87.1% (HR, 15.8; 95% CI, 3.8 to 66.1) in favor of ABVD + INRT; the U group, 92.1% versus 89.6% (HR, 1.45; 95% CI, 0.8 to 2.5) in favor of ABVD + INRT. For both F and U groups, noninferiority of ABVD only compared with combined modality treatment could not be demonstrated. Conclusion In stage I and II HL, PET response after two cycles of ABVD allows for early treatment adaptation. When ePET is positive after two cycles of ABVD, switching to BEACOPPesc + INRT significantly improved 5-year PFS. In ePET-negative patients, noninferiority of ABVD only
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
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.
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
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.
Scaling laws of marine predator search behaviour.
Sims, David W; Southall, Emily J; Humphries, Nicolas E; Hays, Graeme C; Bradshaw, Corey J A; Pitchford, Jonathan W; James, Alex; Ahmed, Mohammed Z; Brierley, Andrew S; Hindell, Mark A; Morritt, David; Musyl, Michael K; Righton, David; Shepard, Emily L C; Wearmouth, Victoria J; Wilson, Rory P; Witt, Matthew J; Metcalfe, Julian D
2008-02-28
Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. Lévy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators-sharks, bony fishes, sea turtles and penguins-exhibit Lévy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions.
2006-08-01
theater distribution problem and find excellent solutions. This research utilizes advanced tabu search techniques, including reactive tabu search and...5.4.2 Within Cycle Swap (WCS) Move Neighborhood.............................. 102 5.4.3 Complete Route Insert ( CRI ) Move Neighborhood...Fractional Factorial Design........................................... 128 6.3 An Excel – VBA based LPDPTW Problem Generator
Holland's SDS Applied to Chinese College Students: A Revisit to Cross-Culture Adaptation
ERIC Educational Resources Information Center
Kong, Jin; Xu, Yonghong Jade; Zhang, Hao
2016-01-01
In this study, data collected from 875 college freshman and sophomore students enrolled in a 4-year university in central China are used to examine the applicability and validity of a Chinese version of Holland's Self-Directed Search (SDS) that was adapted in the 1990s. The total sample was randomly divided into two groups. Data from the first…
Da Boit, Mariasole; Sibson, Rachael; Sivasubramaniam, Selvaraj; Meakin, Judith R; Greig, Carolyn A; Aspden, Richard M; Thies, Frank; Jeromson, Stewart; Hamilton, D Lee; Speakman, John R; Hambly, Catherine; Mangoni, Arduino A; Preston, Thomas
2017-01-01
Background: Resistance exercise increases muscle mass and function in older adults, but responses are attenuated compared with younger people. Data suggest that long-chain n–3 polyunsaturated fatty acids (PUFAs) may enhance adaptations to resistance exercise in older women. To our knowledge, this possibility has not been investigated in men. Objective: We sought to determine the effects of long-chain n–3 PUFA supplementation on resistance exercise training–induced increases in muscle mass and function and whether these effects differ between older men and women. Design: Fifty men and women [men: n = 27, mean ± SD age: 70.6 ± 4.5 y, mean ± SD body mass index (BMI; in kg/m2): 25.6 ± 4.2; women: n = 23, mean ± SD age: 70.7 ± 3.3 y, mean ± SD BMI: 25.3 ± 4.7] were randomly assigned to either long-chain n–3 PUFA (n = 23; 3 g fish oil/d) or placebo (n = 27; 3 g safflower oil/d) and participated in lower-limb resistance exercise training twice weekly for 18 wk. Muscle size, strength, and quality (strength per unit muscle area), functional abilities, and circulating metabolic and inflammatory markers were measured before and after the intervention. Results: Maximal isometric torque increased after exercise training to a greater (P < 0.05) extent in the long-chain n–3 PUFA group than in the placebo group in women, with no differences (P > 0.05) between groups in men. In both sexes, the effect of exercise training on maximal isokinetic torque at 30, 90, and 240° s−1, 4-m walk time, chair-rise time, muscle anatomic cross-sectional area, and muscle fat did not differ (P > 0.05) between groups. There was a greater (P < 0.05) increase in muscle quality in women after exercise training in the long-chain n–3 PUFA group than in the placebo group, with no such differences in men (P > 0.05). Long-chain n–3 PUFAs resulted in a greater decrease (P < 0.05) than the placebo in plasma triglyceride concentrations in both sexes, with no differences (P > 0.05) in
Improving Search Algorithms by Using Intelligent Coordinates
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar
2004-01-01
We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.
School Locker Searches and the Fourth Amendment.
ERIC Educational Resources Information Center
Bjorklun, Eugene C.
1995-01-01
Because school lockers are potential hiding places for weapons and drugs, some schools are eliminating them. Searching student lockers on a random basis raises legal questions. Examines the legality of random locker searches based upon the guidelines for student searches set forth by the Supreme Court in "New Jersey v. T.L.O." and lower…
2008-05-01
militaires sont en grande partie appuyés par des techno- logies de fusion de données et de gestion de ressources . Le C2 naval militaire doit faire...technologies de fusion de données et de gestion des ressources . La Section des systèmes d’aide à la décision (SAD), à Recherche et développement...données adaptative et de gestion des ressources . L’objectif du présent travail est de définir des fonctions de fusion de données adaptive et de
2006-12-01
tinuously as one moves away from the origin (Figure 1). Because such a search is both strategically optimal and locally random, we will refer to it as SOLR ...approximating the inverted cup with a solid composed of n piled slabs. The resulting detection proba- bility will, of course, be smaller than the SOLR ...total effort density in the annulus between Ri−1 and Ri (Figure 2). The total Figure 1. The inverted SOLR cup has the greatest search effort density at
... this page: https://medlineplus.gov/cloud.html Search Cloud To use the sharing features on this page, ... chest pa and lateral Share the MedlinePlus search cloud with your users by embedding our search cloud ...
ERIC Educational Resources Information Center
Rama, Irene; Kontu, Elina
2012-01-01
The purpose of this article is to introduce a research design, which aims to find useful pedagogical adaptations for teaching pupils with autism. Autism is a behavioural syndrome characterised by disabilities and dysfunctions in interaction and communication, which is why it is interesting to explore educational processes particularly from an…
A hybrid search algorithm for swarm robots searching in an unknown environment.
Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao
2014-01-01
This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.
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…
Heim, Eva; Chowdhary, Neerja; Maercker, Andreas; Albanese, Emiliano
2016-01-01
Background Cultural adaptation of mental health care interventions is key, particularly when there is little or no therapist interaction. There is little published information on the methods of adaptation of bibliotherapy and e-mental health interventions. Objective To systematically search for evidence of the effectiveness of minimally guided interventions for the treatment of common mental disorders among culturally diverse people with common mental disorders; to analyze the extent and effects of cultural adaptation of minimally guided interventions for the treatment of common mental disorders. Methods We searched Embase, PubMed, the Cochrane Library, and PsycINFO for randomized controlled trials that tested the efficacy of minimally guided or self-help interventions for depression or anxiety among culturally diverse populations. We calculated pooled standardized mean differences using a random-effects model. In addition, we administered a questionnaire to the authors of primary studies to assess the cultural adaptation methods used in the included primary studies. We entered this information into a meta-regression to investigate effects of the extent of adaptation on intervention efficacy. Results We included eight randomized controlled trials (RCTs) out of the 4911 potentially eligible records identified by the search: four on e-mental health and four on bibliotherapy. The extent of cultural adaptation varied across the studies, with language translation and use of metaphors being the most frequently applied elements of adaptation. The pooled standardized mean difference for primary outcome measures of depression and anxiety was -0.81 (95% CI -0.10 to -0.62). Higher cultural adaptation scores were significantly associated with greater effect sizes (P=.04). Conclusions Our results support the results of previous systematic reviews on the cultural adaptation of face-to-face interventions: the extent of cultural adaptation has an effect on intervention efficacy
ERIC Educational Resources Information Center
Silverman, Linda Kreger, Ed.
1994-01-01
Talent searches are discussed in this journal theme issue, with two feature articles and several recurring columns. "Talent Search: A Driving Force in Gifted Education," by Paula Olszewski-Kubilius, defines what a talent search is, how the Talent Search was developed by Dr. Julian Stanley at Johns Hopkins University in Maryland, the…
Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets
NASA Astrophysics Data System (ADS)
Toft, I. E.; Bagnall, A. J.
This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.
Akhmadeeva, L R; Setchenkova, N M; Magzhanov, R V; Abdrashitova, E V; Bulgakova, A Z
2010-01-01
The effectiveness of dynamic transcutaneous electrostimulation was compared to its imitation in patients with low back pain. Patients were randomized into two groups: 21 patients were treated with transcutaneous electrostimulation and 21 patients received placebo. Patients had one session of electrostimulation (20 minutes) daily during 7-10 days. Pain was assessed by the Visual Analogous scale (VAS) daily. The Oswestry Low Back Pain Scale, the Beck Depression scale and the Spilberger-Khanin Anxiety test were used as well before and after the treatment. The significant improvement on the VAS (p=0,048) and the Oswestry scale (p=0,047) was found in the main group compared to the placebo one. No side-effects of transcutaneous electrostimulation were observed.
Jalilian, Babak; Einarsson, Halldór Bjarki; Vorup-Jensen, Thomas
2012-01-01
Multiple sclerosis is a disease of the central nervous system, resulting in the demyelination of neurons, causing mild to severe symptoms. Several anti-inflammatory treatments now play a significant role in ameliorating the disease. Glatiramer acetate (GA) is a formulation of random polypeptide copolymers for the treatment of relapsing-remitting MS by limiting the frequency of attacks. While evidence suggests the influence of GA on inflammatory responses, the targeted molecular mechanisms remain poorly understood. Here, we review the multiple pharmacological modes-of-actions of glatiramer acetate in treatment of multiple sclerosis. We discuss in particular a newly discovered interaction between the leukocyte-expressed integrin αMβ2 (also called Mac-1, complement receptor 3, or CD11b/CD18) and perspectives on the GA co-polymers as an influence on the function of the innate immune system. PMID:23203082
ERIC Educational Resources Information Center
Kenney, Linda Chion
2003-01-01
Will the stealth superintendent hunt in Cincinnati become tomorrow's standard approach? Search consultants and superintendents offer their views on how far confidentiality should go. Also includes a search firm's process for shielding identities and a confidentiality pledge. (MLF)
ERIC Educational Resources Information Center
Zirkel, Perry A.
2000-01-01
In a federal case involving a vice-principal's pat-down search of middle-school students in a cafeteria (for a missing pizza knife), the court upheld the search, saying it was relatively unintrusive and met "TLO's" reasonable-suspicion standards. Principals need reasonable justification for searching a group. (Contains 18 references.)…
Ginsberg, M.L.
1996-12-31
We introduce a new form of game search called partition search that incorporates dependency analysis, allowing substantial reductions in the portion of the tree that needs to be expanded. Both theoretical results and experimental data are presented. For the game of bridge, partition search provides approximately as much of an improvement over existing methods as {alpha}-{beta} pruning provides over minimax.
Precision and Recall in Title Keyword Searches.
ERIC Educational Resources Information Center
McJunkin, Monica Cahill
This study examines precision and recall for title and keyword searches performed in the "FirstSearch" WorldCat database when keywords are used with and without adjacency of terms specified. A random sample of 68 titles in economics were searched in the OCLC (Online Computer Library Center) Online Union Catalog in order to obtain their…
IIR algorithms for adaptive line enhancement
David, R.A.; Stearns, S.D.; Elliott, G.R.; Etter, D.M.
1983-01-01
We introduce a simple IIR structure for the adaptive line enhancer. Two algorithms based on gradient-search techniques are presented for adapting the structure. Results from experiments which utilized real data as well as computer simulations are provided.
Imanishi, Masatoshi; Saito, Yuriko
2014-01-01
We present the results of infrared K- (2.2 μm) and L'-band (3.8 μm) high-spatial-resolution (<0.''2) imaging observations of nearby gas- and dust-rich infrared luminous merging galaxies, assisted by the adaptive optics system on the Subaru 8.2 m telescope. We investigate the presence and frequency of red K – L' compact sources, which are sensitive indicators of active galactic nuclei (AGNs), including AGNs that are deeply buried in gas and dust. We observed 29 merging systems and confirmed at least one AGN in all but one system. However, luminous dual AGNs were detected in only four of the 29 systems (∼14%), despite our method's being sensitive to buried AGNs. For multiple nuclei sources, we compared the estimated AGN luminosities with supermassive black hole (SMBH) masses inferred from large-aperture K-band stellar emission photometry in individual nuclei. We found that mass accretion rates onto SMBHs are significantly different among multiple SMBHs, such that larger-mass SMBHs generally show higher mass accretion rates when normalized to SMBH mass. Our results suggest that non-synchronous mass accretion onto SMBHs in gas- and dust-rich infrared luminous merging galaxies hampers the observational detection of kiloparsec-scale multiple active SMBHs. This could explain the significantly smaller detection fraction of kiloparsec-scale dual AGNs when compared with the number expected from simple theoretical predictions. Our results also indicate that mass accretion onto SMBHs is dominated by local conditions, rather than by global galaxy properties, reinforcing the importance of observations to our understanding of how multiple SMBHs are activated and acquire mass in gas- and dust-rich merging galaxies.
Leoutsakos, Jeannie-Marie S.; Muthen, Bengt O.; Breitner, John C.S.; Lyketsos, Constantine G.
2011-01-01
Objective We examined effects of non-steroidal anti-inflammatory drugs (NSAID) on cognitive decline as a function of phase of pre-clinical Alzheimer’s disease (AD). Methods Given recent findings that cognitive decline accelerates as clinical diagnosis is approached, we used rate of decline as a proxy for phase of pre-clinical Alzheimer’s disease. We fit growth mixture models of Modified Mini-Mental State Examination (3MS) trajectories with data from 2,388 participants in the Alzheimer’s Disease Anti-inflammatory Prevention Trial (ADAPT), and included class-specific effects of naproxen and celecoxib. Results We identified 3 classes: “no-decline”, “slow-decline”, and “fast-decline”, and examined effects of celecoxib and naproxen on linear slope and rate of change by class. Inclusion of quadratic terms improved fit of the model (−2 log likelihood difference: 369.23; p<0.001), but resulted in reversal of effects over time. Over four years, participants in the slow-decline class on placebo typically lost 6.6 3MS points, while those on naproxen lost 3.1 points (p-value for difference: 0.19). Participants in the fast-decline class on placebo typically lost 11.2 points, but those on celecoxib first declined and then gained points (p-value for difference from placebo: 0.04), while those on naproxen showed a typical decline of 24.9 points (p-value for difference from placebo: <0.0001). Conclusions Our results appeared statistically robust, but provided some unexpected contrasts in effects of different treatments at different times. Naproxen may attenuate cognitive decline in slow decliners while accelerating decline in fast decliners. Celecoxib appeared to have similar effects at first but then to attenuate change in fast decliners. PMID:21560159
Schättin, Alexandra; Arner, Rendel; Gennaro, Federico; de Bruin, Eling D.
2016-01-01
During aging, the prefrontal cortex (PFC) undergoes age-dependent neuronal changes influencing cognitive and motor functions. Motor-learning interventions are hypothesized to ameliorate motor and cognitive deficits in older adults. Especially, video game-based physical exercise might have the potential to train motor in combination with cognitive abilities in older adults. The aim of this study was to compare conventional balance training with video game-based physical exercise, a so-called exergame, on the relative power (RP) of electroencephalographic (EEG) frequencies over the PFC, executive function (EF), and gait performance. Twenty-seven participants (mean age 79.2 ± 7.3 years) were randomly assigned to one of two groups. All participants completed 24 trainings including three times a 30 min session/week. The EEG measurements showed that theta RP significantly decreased in favor of the exergame group [L(14) = 6.23, p = 0.007]. Comparing pre- vs. post-test, EFs improved both within the exergame (working memory: z = −2.28, p = 0.021; divided attention auditory: z = −2.51, p = 0.009; divided attention visual: z = −2.06, p = 0.040; go/no-go: z = −2.55, p = 0.008; set-shifting: z = −2.90, p = 0.002) and within the balance group (set-shifting: z = −2.04, p = 0.042). Moreover, spatio-temporal gait parameters primarily improved within the exergame group under dual-task conditions (speed normal walking: z = −2.90, p = 0.002; speed fast walking: z = −2.97, p = 0.001; cadence normal walking: z = −2.97, p = 0.001; stride length fast walking: z = −2.69, p = 0.005) and within the balance group under single-task conditions (speed normal walking: z = −2.54, p = 0.009; speed fast walking: z = −1.98, p = 0.049; cadence normal walking: z = −2.79, p = 0.003). These results indicate that exergame training as well as balance training positively influence prefrontal cortex activity and/or function in varying proportion. PMID:27932975
ERIC Educational Resources Information Center
Haskin, David
1997-01-01
Compares six leading Web search engines (AltaVista, Excite, HotBot, Infoseek, Lycos, and Northern Light), looking at the breadth of their coverage, accuracy, and ease of use, and finds a clear favorite of the six. Includes tips that can improve search results. (AEF)
Moran, Robert F.; McKay, David; Pickard, Chris J.; Berry, Andrew J.; Griffin, John M.
2016-01-01
The structural chemistry of materials containing low levels of nonstoichiometric hydrogen is difficult to determine, and producing structural models is challenging where hydrogen has no fixed crystallographic site. Here we demonstrate a computational approach employing ab initio random structure searching (AIRSS) to generate a series of candidate structures for hydrous wadsleyite (β-Mg2SiO4 with 1.6 wt% H2O), a high-pressure mineral proposed as a repository for water in the Earth's transition zone. Aligning with previous experimental work, we solely consider models with Mg3 (over Mg1, Mg2 or Si) vacancies. We adapt the AIRSS method by starting with anhydrous wadsleyite, removing a single Mg2+ and randomly placing two H+ in a unit cell model, generating 819 candidate structures. 103 geometries were then subjected to more accurate optimisation under periodic DFT. Using this approach, we find the most favourable hydration mechanism involves protonation of two O1 sites around the Mg3 vacancy. The formation of silanol groups on O3 or O4 sites (with loss of stable O1–H hydroxyls) coincides with an increase in total enthalpy. Importantly, the approach we employ allows observables such as NMR parameters to be computed for each structure. We consider hydrous wadsleyite (∼1.6 wt%) to be dominated by protonated O1 sites, with O3/O4–H silanol groups present as defects, a model that maps well onto experimental studies at higher levels of hydration (J. M. Griffin et al., Chem. Sci., 2013, 4, 1523). The AIRSS approach adopted herein provides the crucial link between atomic-scale structure and experimental studies. PMID:27020937
Design for an Adaptive Library Catalog.
ERIC Educational Resources Information Center
Buckland, Michael K.; And Others
1992-01-01
Describes OASIS, a prototype adaptive online catalog implemented as a front end to the University of California MELVYL catalog. Topics addressed include the concept of adaptive retrieval systems, strategic search commands, feedback, prototyping using a front-end, the problem of excessive retrieval, commands to limit or increase search results, and…
Coelho, V N; Coelho, I M; Souza, M J F; Oliveira, T A; Cota, L P; Haddad, M N; Mladenovic, N; Silva, R C P; Guimarães, F G
2016-01-01
This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different [Formula: see text]-Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.
Self-correcting random number generator
Humble, Travis S.; Pooser, Raphael C.
2016-09-06
A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, to provide a random number according to one or more performance criteria.
Foraging search: Prototypical intelligence
NASA Astrophysics Data System (ADS)
Mobus, George
2000-05-01
We think because we eat. Or as Descartes might have said, on a little more reflection, "I need to eat, therefore I think." Animals that forage for a living repeatedly face the problem of searching for a sparsely distributed resource in a vast space. Furthermore, the resource may occur sporadically and episodically under conditions of true uncertainty (nonstationary, complex and non-linear dynamics). I assert that this problem is the canonical problem solved by intelligence. It's solution is the basis for the evolution of more advanced intelligence in which the space of search includes that of concepts (objects and relations) encoded in cortical structures. In humans the conscious experience of searching through concept space we call thinking. The foraging search model is based upon a higher-order autopoeitic system (the forager) employing anticipatory processing to enhance its success at finding food while avoiding becoming food or having accidents in a hostile world. I present a semi-formal description of the general foraging search problem and an approach to its solution. The latter is a brain-like structure employing dynamically adaptive neurons. A physical robot, MAVRIC, embodies some principles of foraging. It learns cues that lead to improvements in finding targets in a dynamic and nonstationary environment. This capability is based on a unique learning mechanism that encodes causal relations in the neural-like processing element. An argument is advanced that searching for resources in the physical world, as per the foraging model, is a prototype for generalized search for conceptual resources as when we think. A problem represents a conceptual disturbance in a homeostatic sense. The finding of a solution restores the homeostatic balance. The establishment of links between conceptual cues and solutions (resources) and the later use of those cues to think through to solutions of quasi-isomorphic problems is, essentially, foraging for ideas. It is a quite
28 CFR 511.15 - When searches will be conducted.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 2 2011-07-01 2011-07-01 false When searches will be conducted. 511.15... ADMINISTRATION GENERAL MANAGEMENT POLICY Searching and Detaining or Arresting Non-Inmates § 511.15 When searches will be conducted. You and your belongings may be searched, either randomly or based on...
Evolutionary pattern search algorithms
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimental analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.
Searching with the Google Search Appliance (GSA)
Guidance and search help resource listing examples of common queries that can be used in the Google Search Appliance search request, including examples of special characters, or query term seperators that Google Search Appliance recognizes.
Begin: Online Database Searching Now!
ERIC Educational Resources Information Center
Lodish, Erica K.
1986-01-01
Because of the increasing importance of online databases, school library media specialists are encouraged to introduce students to online searching. Four books that would help media specialists gain a basic background are reviewed and it is noted that although they are very technical, they can be adapted to individual needs. (EM)
Reidys, C.M.
1996-06-01
A mapping in random-structures is defined on the vertices of a generalized hypercube Q{sub {alpha}}{sup n}. A random-structure will consist of (1) a random contact graph and (2) a family of relations imposed on adjacent vertices. The vertex set of a random contact graph will be the set of all coordinates of a vertex P {element_of} Q{sub {alpha}}{sup n}. Its edge will be the union of the edge sets of two random graphs. The first is a random 1-regular graph on 2m vertices (coordinates) and the second is a random graph G{sub p} with p = c{sub 2}/n on all n vertices (coordinates). The structure of the random contact graphs will be investigated and it will be shown that for certain values of m, c{sub 2} the mapping in random-structures allows to search by the set of random-structures. This is applied to mappings in RNA-secondary structures. Also, the results on random-structures might be helpful for designing 3D-folding algorithms for RNA.
NASA Astrophysics Data System (ADS)
Knepper, Margaret M.; Fox, Kevin L.; Frieder, Ophir
Information overload is now a reality. We no longer worry about obtaining a sufficient volume of data; we now are concerned with sifting and understanding the massive volumes of data available to us. To do so, we developed an integrated information processing toolkit that provides the user with a variety of ways to view their information. The views include keyword search results, a domain specific ranking system that allows for adaptively capturing topic vocabularies to customize and focus the search results, navigation pages for browsing, and a geospatial and temporal component to visualize results in time and space, and provide “what if” scenario playing. Integrating the information from different tools and sources gives the user additional information and another way to analyze the data. An example of the integration is illustrated on reports of the avian influenza (bird flu).
ERIC Educational Resources Information Center
Flournoy, Nancy
Designs for sequential sampling procedures that adapt to cumulative information are discussed. A familiar illustration is the play-the-winner rule in which there are two treatments; after a random start, the same treatment is continued as long as each successive subject registers a success. When a failure occurs, the other treatment is used until…
Kepler, Christopher K
2017-04-01
An understanding of randomization is important both for study design and to assist medical professionals in evaluating the medical literature. Simple randomization can be done through a variety of techniques, but carries a risk of unequal distribution of subjects into treatment groups. Block randomization can be used to overcome this limitation by ensuring that small subgroups are distributed evenly between treatment groups. Finally, techniques can be used to evenly distribute subjects between treatment groups while accounting for confounding variables, so as to not skew results when there is a high index of suspicion that a particular variable will influence outcome.
Search and Seizure in the Schools
ERIC Educational Resources Information Center
Staros, Kari; Williams, Charles F.
2007-01-01
The Fourth Amendment to the U.S. Constitution protects the people of the United States from unreasonable searches and seizures. On first reading, these protections seem clearly defined. The amendment was meant to protect Americans from the kinds of random searches and seizures that the colonists experienced under British colonial rule. Under…
NASA Astrophysics Data System (ADS)
Sikivie, Pierre
The following sections are included: * INTRODUCTION TO AXION PHYSICS * THE COSMOLOGICAL AXION ENERGY DENSITY * The contribution from initial vacuum misalignment * The contribution from cosmic axion strings * THE CAVITY DETECTOR OF GALACTIC HALO AXIONS * THE PHASE SPACE STRUCTURE OF COLD DARK MATTER HALOS * TELESCOPE SEARCH FOR THE 2γ DECAY OF RELIC AXIONS * A SOLAR AXION DETECTOR * ACKNOWLEDGEMENT * REFERENCES
NASA Astrophysics Data System (ADS)
ajansen; kwhitefoot; panteltje1; edprochak; sudhakar, the
2014-07-01
In reply to the physicsworld.com news story “How to make a quantum random-number generator from a mobile phone” (16 May, http://ow.ly/xFiYc, see also p5), which describes a way of delivering random numbers by counting the number of photons that impinge on each of the individual pixels in the camera of a Nokia N9 smartphone.
Clinician Search Behaviors May Be Influenced by Search Engine Design
Coiera, Enrico; Zrimec, Tatjana; Compton, Paul
2010-01-01
Background Searching the Web for documents using information retrieval systems plays an important part in clinicians’ practice of evidence-based medicine. While much research focuses on the design of methods to retrieve documents, there has been little examination of the way different search engine capabilities influence clinician search behaviors. Objectives Previous studies have shown that use of task-based search engines allows for faster searches with no loss of decision accuracy compared with resource-based engines. We hypothesized that changes in search behaviors may explain these differences. Methods In all, 75 clinicians (44 doctors and 31 clinical nurse consultants) were randomized to use either a resource-based or a task-based version of a clinical information retrieval system to answer questions about 8 clinical scenarios in a controlled setting in a university computer laboratory. Clinicians using the resource-based system could select 1 of 6 resources, such as PubMed; clinicians using the task-based system could select 1 of 6 clinical tasks, such as diagnosis. Clinicians in both systems could reformulate search queries. System logs unobtrusively capturing clinicians’ interactions with the systems were coded and analyzed for clinicians’ search actions and query reformulation strategies. Results The most frequent search action of clinicians using the resource-based system was to explore a new resource with the same query, that is, these clinicians exhibited a “breadth-first” search behaviour. Of 1398 search actions, clinicians using the resource-based system conducted 401 (28.7%, 95% confidence interval [CI] 26.37-31.11) in this way. In contrast, the majority of clinicians using the task-based system exhibited a “depth-first” search behavior in which they reformulated query keywords while keeping to the same task profiles. Of 585 search actions conducted by clinicians using the task-based system, 379 (64.8%, 95% CI 60.83-68.55) were
Adaptive photoacoustic imaging quality optimization with EMD and reconstruction
NASA Astrophysics Data System (ADS)
Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.
2016-10-01
Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.
The Adaptive Analysis of Visual Cognition using Genetic Algorithms
Cook, Robert G.; Qadri, Muhammad A. J.
2014-01-01
Two experiments used a novel, open-ended, and adaptive test procedure to examine visual cognition in animals. Using a genetic algorithm, a pigeon was tested repeatedly from a variety of different initial conditions for its solution to an intermediate brightness search task. On each trial, the animal had to accurately locate and peck a target element of intermediate brightness from among a variable number of surrounding darker and lighter distractor elements. Displays were generated from six parametric variables, or genes (distractor number, element size, shape, spacing, target brightness, distractor brightness). Display composition changed over time, or evolved, as a function of the bird’s differential accuracy within the population of values for each gene. Testing three randomized initial conditions and one set of controlled initial conditions, element size and number of distractors were identified as the most important factors controlling search accuracy, with distractor brightness, element shape, and spacing making secondary contributions. The resulting changes in this multidimensional stimulus space suggested the existence of a set of conditions that the bird repeatedly converged upon regardless of initial conditions. This psychological “attractor” represents the cumulative action of the cognitive operations used by the pigeon in solving and performing this search task. The results are discussed regarding their implications for visual cognition in pigeons and the usefulness of adaptive, subject-driven experimentation for investigating human and animal cognition more generally. PMID:24000905
Peters, Krisztian
2009-11-01
We present the status and prospects of Higgs searches at the Tevatron and the LHC. Results from the Tevatron are using up to 5 fb{sup -} of data collected with the CDF and D0 detectors. The major contributing processes include associated production (WH {yields} l{nu}bb, ZH {yields} {nu}{nu}bb, ZH {yields} llbb) and gluon fusion (gg {yields} H {yields} WW{sup (*)}). Improvements across the full mass range resulting from the larger data sets, improved analyses techniques and increased signal acceptance are discussed. Recent results exclude the SM Higgs boson in a mass range of 160 < m{sub H} < 170 GeV. Searches for the neutral MSSM Higgs boson in the region 90 < m{sub A} < 200 GeV exclude tan {beta} values down to 30 for several benchmark scenarios.
Chhun, Nok; Cleland, Charles M; Crespo-Fierro, Michele; Parés-Avila, José A; Lizcano, John A; Shedlin, Michele G; Johnston, Barbara E; Sharp, Victoria L
2016-01-01
Background Human immunodeficiency virus (HIV) disease in the United States disproportionately affects minorities, including Latinos. Barriers including language are associated with lower antiretroviral therapy (ART) adherence seen among Latinos, yet ART and interventions for clinic visit adherence are rarely developed or delivered in Spanish. Objective The aim was to adapt a computer-based counseling tool, demonstrated to reduce HIV-1 viral load and sexual risk transmission in a population of English-speaking adults, for use during routine clinical visits for an HIV-positive Spanish-speaking population (CARE+ Spanish); the Technology Acceptance Model (TAM) was the theoretical framework guiding program development. Methods A longitudinal randomized controlled trial was conducted from June 4, 2010 to March 29, 2012. Participants were recruited from a comprehensive HIV treatment center comprising three clinics in New York City. Eligibility criteria were (1) adults (age ≥18 years), (2) Latino birth or ancestry, (3) speaks Spanish (mono- or multilingual), and (4) on antiretrovirals. Linear and generalized mixed linear effects models were used to analyze primary outcomes, which included ART adherence, sexual transmission risk behaviors, and HIV-1 viral loads. Exit interviews were offered to purposively selected intervention participants to explore cultural acceptability of the tool among participants, and focus groups explored the acceptability and system efficiency issues among clinic providers, using the TAM framework. Results A total of 494 Spanish-speaking HIV clinic attendees were enrolled and randomly assigned to the intervention (arm A: n=253) or risk assessment-only control (arm B, n=241) group and followed up at 3-month intervals for one year. Gender distribution was 296 (68.4%) male, 110 (25.4%) female, and 10 (2.3%) transgender. By study end, 433 of 494 (87.7%) participants were retained. Although intervention participants had reduced viral loads, increased
Webster, Michael A.
2015-01-01
Sensory systems continuously mold themselves to the widely varying contexts in which they must operate. Studies of these adaptations have played a long and central role in vision science. In part this is because the specific adaptations remain a powerful tool for dissecting vision, by exposing the mechanisms that are adapting. That is, “if it adapts, it's there.” Many insights about vision have come from using adaptation in this way, as a method. A second important trend has been the realization that the processes of adaptation are themselves essential to how vision works, and thus are likely to operate at all levels. That is, “if it's there, it adapts.” This has focused interest on the mechanisms of adaptation as the target rather than the probe. Together both approaches have led to an emerging insight of adaptation as a fundamental and ubiquitous coding strategy impacting all aspects of how we see. PMID:26858985
Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive managem...
NASA Technical Reports Server (NTRS)
Messaro. Semma; Harrison, Phillip
2010-01-01
Ares I Zonal Random vibration environments due to acoustic impingement and combustion processes are develop for liftoff, ascent and reentry. Random Vibration test criteria for Ares I Upper Stage pyrotechnic components are developed by enveloping the applicable zonal environments where each component is located. Random vibration tests will be conducted to assure that these components will survive and function appropriately after exposure to the expected vibration environments. Methodology: Random Vibration test criteria for Ares I Upper Stage pyrotechnic components were desired that would envelope all the applicable environments where each component was located. Applicable Ares I Vehicle drawings and design information needed to be assessed to determine the location(s) for each component on the Ares I Upper Stage. Design and test criteria needed to be developed by plotting and enveloping the applicable environments using Microsoft Excel Spreadsheet Software and documenting them in a report Using Microsoft Word Processing Software. Conclusion: Random vibration liftoff, ascent, and green run design & test criteria for the Upper Stage Pyrotechnic Components were developed by using Microsoft Excel to envelope zonal environments applicable to each component. Results were transferred from Excel into a report using Microsoft Word. After the report is reviewed and edited by my mentor it will be submitted for publication as an attachment to a memorandum. Pyrotechnic component designers will extract criteria from my report for incorporation into the design and test specifications for components. Eventually the hardware will be tested to the environments I developed to assure that the components will survive and function appropriately after exposure to the expected vibration environments.
Adaptive spatial sampling of contaminated soil
Cox, L.A. Jr.
1999-12-01
Suppose that a residential neighborhood may have been contaminated by a nearby abandoned hazardous waste site. The suspected contamination consists of elevated soil concentrations o chemicals that are also found in the absence of site-related contamination. How should a risk manager decide which residential properties to sample and which ones to clean? This paper introduces an adaptive spatial sampling approach which uses initial observations to guide subsequent search. Unlike some recent model-based spatial data analysis methods, it does not require any specific statistical model for the spatial distribution of hazards, but instead constructs an increasingly accurate nonparametric approximation to it as sampling proceeds. Possible cost-effective sampling and cleanup decision rules are described by decision parameters such as the number of randomly selected locations used to initialize the process, the number of highest-concentration locations searched around, the number of samples taken at each location, a stopping rule, and a remediation action threshold. These decision parameters are optimized by simulating the performance of each decision rule. The simulation is performed using the data collected so far to impute multiple probably values of unknown soil concentration distributions during each simulation run.
Web Search Engines: Search Syntax and Features.
ERIC Educational Resources Information Center
Ojala, Marydee
2002-01-01
Presents a chart that explains the search syntax, features, and commands used by the 12 most widely used general Web search engines. Discusses Web standardization, expanded types of content searched, size of databases, and search engines that include both simple and advanced versions. (LRW)
NASA Astrophysics Data System (ADS)
Tapiero, Charles S.; Vallois, Pierre
2016-11-01
The premise of this paper is that a fractional probability distribution is based on fractional operators and the fractional (Hurst) index used that alters the classical setting of random variables. For example, a random variable defined by its density function might not have a fractional density function defined in its conventional sense. Practically, it implies that a distribution's granularity defined by a fractional kernel may have properties that differ due to the fractional index used and the fractional calculus applied to define it. The purpose of this paper is to consider an application of fractional calculus to define the fractional density function of a random variable. In addition, we provide and prove a number of results, defining the functional forms of these distributions as well as their existence. In particular, we define fractional probability distributions for increasing and decreasing functions that are right continuous. Examples are used to motivate the usefulness of a statistical approach to fractional calculus and its application to economic and financial problems. In conclusion, this paper is a preliminary attempt to construct statistical fractional models. Due to the breadth and the extent of such problems, this paper may be considered as an initial attempt to do so.
Efficient search of multiple types of targets
NASA Astrophysics Data System (ADS)
Wosniack, M. E.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.
2015-12-01
Random searches often take place in fragmented landscapes. Also, in many instances like animal foraging, significant benefits to the searcher arise from visits to a large diversity of patches with a well-balanced distribution of targets found. Up to date, such aspects have been widely ignored in the usual single-objective analysis of search efficiency, in which one seeks to maximize just the number of targets found per distance traversed. Here we address the problem of determining the best strategies for the random search when these multiple-objective factors play a key role in the process. We consider a figure of merit (efficiency function), which properly "scores" the mentioned tasks. By considering random walk searchers with a power-law asymptotic Lévy distribution of step lengths, p (ℓ ) ˜ℓ-μ , with 1 <μ ≤3 , we show that the standard optimal strategy with μopt≈2 no longer holds universally. Instead, optimal searches with enhanced superdiffusivity emerge, including values as low as μopt≈1.3 (i.e., tending to the ballistic limit). For the general theory of random search optimization, our findings emphasize the necessity to correctly characterize the multitude of aims in any concrete metric to compare among possible candidates to efficient strategies. In the context of animal foraging, our results might explain some empirical data pointing to stronger superdiffusion (μ <2 ) in the search behavior of different animal species, conceivably associated to multiple goals to be achieved in fragmented landscapes.
Theory of continuum random walks and application to chemotaxis
NASA Astrophysics Data System (ADS)
Schnitzer, Mark J.
1993-10-01
We formulate the general theory of random walks in continuum, essential for treating a collision rate which depends smoothly upon direction of motion. We also consider a smooth probability distribution of correlations between the directions of motion before and after collisions, as well as orientational Brownian motion between collisions. These features lead to an effective Smoluchowski equation. Such random walks involving an infinite number of distinct directions of motion cannot be treated on a lattice, which permits only a finite number of directions of motion, nor by Langevin methods, which make no reference to individual collisions. The effective Smoluchowski equation enables a description of the biased random walk of the bacterium Escherichia coli during chemotaxis, its search for food. The chemotactic responses of cells which perform temporal comparisons of the concentration of a chemical attractant are predicted to be strongly positive, whereas those of cells which measure averages of the ambient attractant concentration are predicted to be negative. The former prediction explains the observed behavior of wild-type (naturally occurring) cells; however, the latter behavior has yet to be observed, even in cells defective in adaption.
Signatures of active and passive optimized Lévy searching in jellyfish.
Reynolds, Andy M
2014-10-06
Some of the strongest empirical support for Lévy search theory has come from telemetry data for the dive patterns of marine predators (sharks, bony fishes, sea turtles and penguins). The dive patterns of the unusually large jellyfish Rhizostoma octopus do, however, sit outside of current Lévy search theory which predicts that a single search strategy is optimal. When searching the water column, the movement patterns of these jellyfish change over time. Movement bouts can be approximated by a variety of Lévy and Brownian (exponential) walks. The adaptive value of this variation is not known. On some occasions movement pattern data are consistent with the jellyfish prospecting away from a preferred depth, not finding an improvement in conditions elsewhere and so returning to their original depth. This 'bounce' behaviour also sits outside of current Lévy walk search theory. Here, it is shown that the jellyfish movement patterns are consistent with their using optimized 'fast simulated annealing'--a novel kind of Lévy walk search pattern--to locate the maximum prey concentration in the water column and/or to locate the strongest of many olfactory trails emanating from more distant prey. Fast simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a large search space. This new finding shows that the notion of active optimized Lévy walk searching is not limited to the search for randomly and sparsely distributed resources, as previously thought, but can be extended to embrace other scenarios, including that of the jellyfish R. octopus. In the presence of convective currents, it could become energetically favourable to search the water column by riding the convective currents. Here, it is shown that these passive movements can be represented accurately by Lévy walks of the type occasionally seen in R. octopus. This result vividly illustrates that Lévy walks are not necessarily
Signatures of active and passive optimized Lévy searching in jellyfish
Reynolds, Andy M.
2014-01-01
Some of the strongest empirical support for Lévy search theory has come from telemetry data for the dive patterns of marine predators (sharks, bony fishes, sea turtles and penguins). The dive patterns of the unusually large jellyfish Rhizostoma octopus do, however, sit outside of current Lévy search theory which predicts that a single search strategy is optimal. When searching the water column, the movement patterns of these jellyfish change over time. Movement bouts can be approximated by a variety of Lévy and Brownian (exponential) walks. The adaptive value of this variation is not known. On some occasions movement pattern data are consistent with the jellyfish prospecting away from a preferred depth, not finding an improvement in conditions elsewhere and so returning to their original depth. This ‘bounce’ behaviour also sits outside of current Lévy walk search theory. Here, it is shown that the jellyfish movement patterns are consistent with their using optimized ‘fast simulated annealing’—a novel kind of Lévy walk search pattern—to locate the maximum prey concentration in the water column and/or to locate the strongest of many olfactory trails emanating from more distant prey. Fast simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a large search space. This new finding shows that the notion of active optimized Lévy walk searching is not limited to the search for randomly and sparsely distributed resources, as previously thought, but can be extended to embrace other scenarios, including that of the jellyfish R. octopus. In the presence of convective currents, it could become energetically favourable to search the water column by riding the convective currents. Here, it is shown that these passive movements can be represented accurately by Lévy walks of the type occasionally seen in R. octopus. This result vividly illustrates that Lévy walks are not
Intermittent search process and teleportation.
Bénichou, O; Moreau, M; Suet, P-H; Voituriez, R
2007-06-21
The authors study an intermittent search process combining diffusion and "teleportation" phases in a d-dimensional spherical continuous system and in a regular lattice. The searcher alternates diffusive phases, during which targets can be discovered, and fast phases (teleportation) which randomly relocate the searcher, but do not allow for target detection. The authors show that this alternation can be favorable for minimizing the time of first discovery, and that this time can be optimized by a convenient choice of the mean waiting times of each motion phase. The optimal search strategy is explicitly derived in the continuous case and in the lattice case. Arguments are given to show that much more general intermittent motions do provide optimal search strategies in d dimensions. These results can be useful in the context of heterogeneous catalysis or in various biological examples of transport through membrane pores.
NASA Astrophysics Data System (ADS)
Malyshev, V. A.
1998-04-01
Contents § 1. Definitions1.1. Grammars1.2. Random grammars and L-systems1.3. Semigroup representations § 2. Infinite string dynamics2.1. Cluster expansion2.2. Cluster dynamics2.3. Local observer § 3. Large time behaviour: small perturbations3.1. Invariant measures3.2. Classification § 4. Large time behaviour: context free case4.1. Invariant measures for grammars4.2. L-systems4.3. Fractal correlation functions4.4. Measures on languages Bibliography
NASA Astrophysics Data System (ADS)
Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang
2016-09-01
Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.
Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang
2016-01-01
Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests. PMID:27666514
True Randomness from Big Data.
Papakonstantinou, Periklis A; Woodruff, David P; Yang, Guang
2016-09-26
Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.
Adaptive building skin structures
NASA Astrophysics Data System (ADS)
Del Grosso, A. E.; Basso, P.
2010-12-01
The concept of adaptive and morphing structures has gained considerable attention in the recent years in many fields of engineering. In civil engineering very few practical applications are reported to date however. Non-conventional structural concepts like deployable, inflatable and morphing structures may indeed provide innovative solutions to some of the problems that the construction industry is being called to face. To give some examples, searches for low-energy consumption or even energy-harvesting green buildings are amongst such problems. This paper first presents a review of the above problems and technologies, which shows how the solution to these problems requires a multidisciplinary approach, involving the integration of architectural and engineering disciplines. The discussion continues with the presentation of a possible application of two adaptive and dynamically morphing structures which are proposed for the realization of an acoustic envelope. The core of the two applications is the use of a novel optimization process which leads the search for optimal solutions by means of an evolutionary technique while the compatibility of the resulting configurations of the adaptive envelope is ensured by the virtual force density method.
Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.
2008-01-01
Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485
Lévy-taxis: a novel search strategy for finding odor plumes in turbulent flow-dominated environments
NASA Astrophysics Data System (ADS)
Pasternak, Zohar; Bartumeus, Frederic; Grasso, Frank W.
2009-10-01
Locating chemical plumes in aquatic or terrestrial environments is important for many economic, conservation, security and health related human activities. The localization process is composed mainly of two phases: finding the chemical plume and then tracking it to its source. Plume tracking has been the subject of considerable study whereas plume finding has received little attention. We address here the latter issue, where the searching agent must find the plume in a region often many times larger than the plume and devoid of the relevant chemical cues. The probability of detecting the plume not only depends on the movements of the searching agent but also on the fluid mechanical regime, shaping plume intermittency in space and time; this is a basic, general problem when exploring for ephemeral resources (e.g. moving and/or concealing targets). Here we present a bio-inspired search strategy named Lévy-taxis that, under certain conditions, located odor plumes significantly faster and with a better success rate than other search strategies such as Lévy walks (LW), correlated random walks (CRW) and systematic zig-zag. These results are based on computer simulations which contain, for the first time ever, digitalized real-world water flow and chemical plume instead of their theoretical model approximations. Combining elements of LW and CRW, Lévy-taxis is particularly efficient for searching in flow-dominated environments: it adaptively controls the stochastic search pattern using environmental information (i.e. flow) that is available throughout the course of the search and shows correlation with the source providing the cues. This strategy finds natural application in real-world search missions, both by humans and autonomous robots, since it accomodates the stochastic nature of chemical mixing in turbulent flows. In addition, it may prove useful in the field of behavioral ecology, explaining and predicting the movement patterns of various animals searching for
When Gravity Fails: Local Search Topology
NASA Technical Reports Server (NTRS)
Frank, Jeremy; Cheeseman, Peter; Stutz, John; Lau, Sonie (Technical Monitor)
1997-01-01
Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called {\\em plateau moves), dominate the time spent in local search. We analyze and characterize {\\em plateaus) for three different classes of randomly generated Boolean Satisfiability problems. We identify several interesting features of plateaus that impact the performance of local search algorithms. We show that local minima tend to be small but occasionally may be very large. We also show that local minima can be escaped without unsatisfying a large number of clauses, but that systematically searching for an escape route may be computationally expensive if the local minimum is large. We show that plateaus with exits, called benches, tend to be much larger than minima, and that some benches have very few exit states which local search can use to escape. We show that the solutions (i.e. global minima) of randomly generated problem instances form clusters, which behave similarly to local minima. We revisit several enhancements of local search algorithms and explain their performance in light of our results. Finally we discuss strategies for creating the next generation of local search algorithms.
Is random access memory random?
NASA Technical Reports Server (NTRS)
Denning, P. J.
1986-01-01
Most software is contructed on the assumption that the programs and data are stored in random access memory (RAM). Physical limitations on the relative speeds of processor and memory elements lead to a variety of memory organizations that match processor addressing rate with memory service rate. These include interleaved and cached memory. A very high fraction of a processor's address requests can be satified from the cache without reference to the main memory. The cache requests information from main memory in blocks that can be transferred at the full memory speed. Programmers who organize algorithms for locality can realize the highest performance from these computers.
NASA Astrophysics Data System (ADS)
Kinzig, Ann P.
2015-03-01
This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.
Adaptive clinical trial designs in oncology
Zang, Yong; Lee, J. Jack
2015-01-01
Adaptive designs have become popular in clinical trial and drug development. Unlike traditional trial designs, adaptive designs use accumulating data to modify the ongoing trial without undermining the integrity and validity of the trial. As a result, adaptive designs provide a flexible and effective way to conduct clinical trials. The designs have potential advantages of improving the study power, reducing sample size and total cost, treating more patients with more effective treatments, identifying efficacious drugs for specific subgroups of patients based on their biomarker profiles, and shortening the time for drug development. In this article, we review adaptive designs commonly used in clinical trials and investigate several aspects of the designs, including the dose-finding scheme, interim analysis, adaptive randomization, biomarker-guided randomization, and seamless designs. For illustration, we provide examples of real trials conducted with adaptive designs. We also discuss practical issues from the perspective of using adaptive designs in oncology trials. PMID:25811018
ERIC Educational Resources Information Center
Bell, Suzanne S.
1997-01-01
Provides strategies for effective Internet searches. Categorizes queries into four types and describes tools: subject lists; indexes/directories; keyword search engines; Usenet newsgroups; and special purpose search tools. Discusses the importance of deciphering information and adjusting to changes. (AEF)
Mak, Chi H; Pham, Phuong; Afif, Samir A; Goodman, Myron F
2015-09-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C→U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.
Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.
2015-01-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C → U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics. PMID:26465508
NASA Astrophysics Data System (ADS)
Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.
2015-09-01
Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C →U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.
Ringed Seal Search for Global Optimization via a Sensitive Search Model.
Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar
2016-01-01
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global
Ringed Seal Search for Global Optimization via a Sensitive Search Model
Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar
2016-01-01
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global
Searching the Scholarly Literature Made Easier
NASA Astrophysics Data System (ADS)
Eichhorn, G.
2006-11-01
The ADS provides a search system for over 4.8 million records in Astronomy, Solar Physics, Planetary Sciences, and Physics/Geosciences and 3.3 million scanned pages of the scholarly literature, including the entire journal "Solar Physics". In order to improve access to the ADS and to make searching easier, we allow Google to index the information in the ADS. Since many scientists use Google as their general search system, it makes it easier to also search the scientific literature that the ADS cover. HOWEVER, please be aware that Google does not index all the abstracts in the ADS. Their system crawls the ADS, but may miss some abstracts on a random basis. We therefore recommend for detailed searches to continue using the ADS search system directly. Since a one-field search system like Google seems to be popular, the ADS have developed such an interface to the ADS as well. The new interface allows you to specify word and author searches in one input field. Author names are detected automatically in the input. Years and year ranges are detected as well. This new interface is available on the ADS homepage or at: http://adsabs.harvard.edu/basic_search.html
ERIC Educational Resources Information Center
Exceptional Parent, 1987
1987-01-01
Suggestions are presented for helping disabled individuals learn to use or adapt toothbrushes for proper dental care. A directory lists dental health instructional materials available from various organizations. (CB)
Entropy Crises in Glasses and Random Heteropolymers.
Wolynes, Peter G
1997-01-01
The concept of random first order transitions with configurational entropy crises provides a theoretical framework for understanding the glass transition. This paper discusses such transitions in exactly solvable spin glass models and in globular random heteropolymers and their relation to glass transitions in molecular fluids and polymers. The Vogel-Fulcher law is shown to be related to the search time through the energy landscape of an "entropic droplet."
NASA Astrophysics Data System (ADS)
Vrugt, J. A.
2007-12-01
Markov chain Monte Carlo (MCMC) methods are widely used in fields ranging from physics and chemistry, to finance, economics and statistical inference for estimating the average properties of complex systems. The convergence rate of MCMC schemes is often observed, however to be disturbingly low, limiting its practical use in many applications. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves. Here we show that significant improvements to the efficiency of MCMC algorithms can be made by using a self-adaptive Differential Evolution search strategy within a population-based evolutionary framework. This scheme differs fundamentally from existing MCMC algorithms, in that trial jumps are simply a fixed multiple of the difference of randomly chosen members of the population using various genetic operators that are adaptively updated during the search. In addition, the algorithm includes randomized subspace sampling to further improve convergence and acceptance rate. Detailed balance and ergodicity of the algorithm are proved, and hydrologic examples show that the proposed method significantly enhances the efficiency and applicability of MCMC simulations to complex, multi-modal search problems.
NASA Astrophysics Data System (ADS)
Vodniza, Alberto Quijano; Pereira, M. Rojas; Lopez, J. P.
2007-12-01
The event of the variable stars by eclipse occurs owing to the rotation of at least two stars around its center of mass and it's relatively easy to detect because of the large size of the bodies that are involved on it. But in the case of the exoplanets the eclipse that originates is very small, because the variation of the luminous intensity generated is very little on the whole. However, with photometric techniques of high precision, it is possible to detect those passages. Also, there exist astrometrical methods quite complicated for an amateur, so the one we will employ at the Astronomical Observatory of the University of Nariño (COLOMBIA) and which better adapts to our equipment and capacity is the photometric method. Through differential photometry, we will analyze first variable stars weaker than tenth magnitude so we can acquire enough experience on determining stellar passages and then begin a systematic search for exoplanets, in which case photometry must have an accuracy of the order of thousandths of magnitude. We have already made trials with some variable stars, like the GCVS FZ ORIONIS and the results are quite good, because the accuracy is of the hundredths order of magnitude, but in order to search exoplanets, photometry must have a resolution in the order of few thousandths of magnitude. First of all we'll test our methodology with stars that have already been established as to hold planets so then we'll start the research seeking after possible exoplanets around other stars. On the poster it'll be explained the scientific methodology.
Online Database Searching Workbook.
ERIC Educational Resources Information Center
Littlejohn, Alice C.; Parker, Joan M.
Designed primarily for use by first-time searchers, this workbook provides an overview of online searching. Following a brief introduction which defines online searching, databases, and database producers, five steps in carrying out a successful search are described: (1) identifying the main concepts of the search statement; (2) selecting a…
Search Alternatives and Beyond
ERIC Educational Resources Information Center
Bell, Steven J.
2006-01-01
Internet search has become a routine computing activity, with regular visits to a search engine--usually Google--the norm for most people. The vast majority of searchers, as recent studies of Internet search behavior reveal, search only in the most basic of ways and fail to avail themselves of options that could easily and effortlessly improve…
Multimedia Web Searching Trends.
ERIC Educational Resources Information Center
Ozmutlu, Seda; Spink, Amanda; Ozmutlu, H. Cenk
2002-01-01
Examines and compares multimedia Web searching by Excite and FAST search engine users in 2001. Highlights include audio and video queries; time spent on searches; terms per query; ranking of the most frequently used terms; and differences in Web search behaviors of U.S. and European Web users. (Author/LRW)
Visual search in virtual environments
NASA Astrophysics Data System (ADS)
Stark, Lawrence W.; Ezumi, Koji; Nguyen, Tho; Paul, R.; Tharp, Gregory K.; Yamashita, H. I.
1992-08-01
A key task in virtual environments is visual search. To obtain quantitative measures of human performance and documentation of visual search strategies, we have used three experimental arrangements--eye, head, and mouse control of viewing windows--by exploiting various combinations of helmet-mounted-displays, graphics workstations, and eye movement tracking facilities. We contrast two different categories of viewing strategies: one, for 2D pictures with large numbers of targets and clutter scattered randomly; the other for quasi-natural 3D scenes with targets and non-targets placed in realistic, sensible positions. Different searching behaviors emerge from these contrasting search conditions, reflecting different visual and perceptual modes. A regular 'searchpattern' is a systematic, repetitive, idiosyncratic sequence of movements carrying the eye to cover the entire 2D scene. Irregular 'searchpatterns' take advantages of wide windows and the wide human visual lobe; here, hierarchical detection and recognition is performed with the appropriate capabilities of the 'two visual systems'. The 'searchpath', also efficient, repetitive and idiosyncratic, provides only a small set of fixations to check continually the smaller number of targets in the naturalistic 3D scene; likely, searchpaths are driven by top-down spatial models. If the viewed object is known and able to be named, then an hypothesized, top-down cognitive model drives active looking in the 'scanpath' mode, again continually checking important subfeatures of the object. Spatial models for searchpaths may be primitive predecessors, in the evolutionary history of animals, of cognitive models for scanpaths.
Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua
2014-01-01
This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.
Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua
2014-01-01
This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341
Genetic-Algorithm Tool For Search And Optimization
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven
1995-01-01
SPLICER computer program used to solve search and optimization problems. Genetic algorithms adaptive search procedures (i.e., problem-solving methods) based loosely on processes of natural selection and Darwinian "survival of fittest." Algorithms apply genetically inspired operators to populations of potential solutions in iterative fashion, creating new populations while searching for optimal or nearly optimal solution to problem at hand. Written in Think C.
Human visual search: a two state process
NASA Astrophysics Data System (ADS)
Cartier, Joan F.; Hsu, David H.
1995-05-01
In searching a field of view for an object of interest, observers appear to alternate between two states: wandering (rapid saccades) and examining (focusing on an attractive region). This observation is made based on eye tracker measurements and is consistent with the model proposed by J. F. Nicoll, which describes search as a competition between points of interest for the observer's attention. In this paper search is represented as a random process -- a random walk in which the observers exist in one of two states until they quit: they are either searching or wandering around looking for a point of interest. When wandering, the observers skip rapidly from point to point. When examining, they move more slowly, because detection discrimination requires additional or different thought processes. An interesting consequence of the two state approach is that the random walk must have two time constants -- the time constant for fast (wandering) movements and a different time constant for slow (examining) movements. We describe a technique which can be used to separate raw eye tracker data collected in a search experiment into the wandering and examining states. Then we postulate the relationship of the probability of wandering (or examining) to the attractiveness of the image. We use a clutter metric to estimate the relative attractiveness of the target and the competing clutter. We find that the clutter metric predicts fairly well the time spent in the two states.
Global search algorithm for optimal control
NASA Technical Reports Server (NTRS)
Brocker, D. H.; Kavanaugh, W. P.; Stewart, E. C.
1970-01-01
Random-search algorithm employs local and global properties to solve two-point boundary value problem in Pontryagin maximum principle for either fixed or variable end-time problems. Mixed boundary value problem is transformed to an initial value problem. Mapping between initial and terminal values utilizes hybrid computer.
Hybrid foraging search: Searching for multiple instances of multiple types of target.
Wolfe, Jeremy M; Aizenman, Avigael M; Boettcher, Sage E P; Cain, Matthew S
2016-02-01
This paper introduces the "hybrid foraging" paradigm. In typical visual search tasks, observers search for one instance of one target among distractors. In hybrid search, observers search through visual displays for one instance of any of several types of target held in memory. In foraging search, observers collect multiple instances of a single target type from visual displays. Combining these paradigms, in hybrid foraging tasks observers search visual displays for multiple instances of any of several types of target (as might be the case in searching the kitchen for dinner ingredients or an X-ray for different pathologies). In the present experiment, observers held 8-64 target objects in memory. They viewed displays of 60-105 randomly moving photographs of objects and used the computer mouse to collect multiple targets before choosing to move to the next display. Rather than selecting at random among available targets, observers tended to collect items in runs of one target type. Reaction time (RT) data indicate searching again for the same item is more efficient than searching for any other targets, held in memory. Observers were trying to maximize collection rate. As a result, and consistent with optimal foraging theory, they tended to leave 25-33% of targets uncollected when moving to the next screen/patch. The pattern of RTs shows that while observers were collecting a target item, they had already begun searching memory and the visual display for additional targets, making the hybrid foraging task a useful way to investigate the interaction of visual and memory search.
Hybrid foraging search: Searching for multiple instances of multiple types of target
Wolfe, Jeremy M.; Aizenman, Avigael M.; Boettcher, Sage E.P.; Cain, Matthew S.
2016-01-01
This paper introduces the “hybrid foraging” paradigm. In typical visual search tasks, observers search for one instance of one target among distractors. In hybrid search, observers search through visual displays for one instance of any of several types of target held in memory. In foraging search, observers collect multiple instances of a single target type from visual displays. Combining these paradigms, in hybrid foraging tasks observers search visual displays for multiple instances of any of several types of target (as might be the case in searching the kitchen for dinner ingredients or an X-ray for different pathologies). In the present experiment, observers held 8–64 targets objects in memory. They viewed displays of 60–105 randomly moving photographs of objects and used the computer mouse to collect multiple targets before choosing to move to the next display. Rather than selecting at random among available targets, observers tended to collect items in runs of one target type. Reaction time (RT) data indicate searching again for the same item is more efficient than searching for any other targets, held in memory. Observers were trying to maximize collection rate. As a result, and consistent with optimal foraging theory, they tended to leave 25–33% of targets uncollected when moving to the next screen/patch. The pattern of RTs shows that while observers were collecting a target item, they had already begun searching memory and the visual display for additional targets, making the hybrid foraging task a useful way to investigate the interaction of visual and memory search. PMID:26731644
Allen, Craig R.; Garmestani, Ahjond S.
2015-01-01
Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive management has explicit structure, including a careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. The process is iterative, and serves to reduce uncertainty, build knowledge and improve management over time in a goal-oriented and structured process.
Mason, Malcolm D; Clarke, Noel W; James, Nicholas D; Dearnaley, David P; Spears, Melissa R; Ritchie, Alastair W S; Attard, Gerhardt; Cross, William; Jones, Rob J; Parker, Christopher C; Russell, J Martin; Thalmann, George N; Schiavone, Francesca; Cassoly, Estelle; Matheson, David; Millman, Robin; Rentsch, Cyrill A; Barber, Jim; Gilson, Clare; Ibrahim, Azman; Logue, John; Lydon, Anna; Nikapota, Ashok D; O'Sullivan, Joe M; Porfiri, Emilio; Protheroe, Andrew; Srihari, Narayanan Nair; Tsang, David; Wagstaff, John; Wallace, Jan; Walmsley, Catherine; Parmar, Mahesh K B; Sydes, Matthew R
2017-03-13
Purpose Systemic Therapy for Advanced or Metastatic Prostate Cancer: Evaluation of Drug Efficacy is a randomized controlled trial using a multiarm, multistage, platform design. It recruits men with high-risk, locally advanced or metastatic prostate cancer who were initiating long-term hormone therapy. We report survival data for two celecoxib (Cel)-containing comparisons, which stopped accrual early at interim analysis on the basis of failure-free survival. Patients and Methods Standard of care (SOC) was hormone therapy continuously (metastatic) or for ≥ 2 years (nonmetastatic); prostate (± pelvic node) radiotherapy was encouraged for men without metastases. Cel 400 mg was administered twice a day for 1 year. Zoledronic acid (ZA) 4 mg was administered for six 3-weekly cycles, then 4-weekly for 2 years. Stratified random assignment allocated patients 2:1:1 to SOC (control), SOC + Cel, or SOC + ZA + Cel. The primary outcome measure was all-cause mortality. Results were analyzed with Cox proportional hazards and flexible parametric models adjusted for stratification factors. Results A total of 1,245 men were randomly assigned (Oct 2005 to April 2011). Groups were balanced: median age, 65 years; 61% metastatic, 14% N+/X M0, 25% N0M0; 94% newly diagnosed; median prostate-specific antigen, 66 ng/mL. Median follow-up was 69 months. Grade 3 to 5 adverse events were seen in 36% SOC-only, 33% SOC + Cel, and 32% SOC + ZA + Cel patients. There were 303 control arm deaths (83% prostate cancer), and median survival was 66 months. Compared with SOC, the adjusted hazard ratio was 0.98 (95% CI, 0.80 to 1.20; P = .847; median survival, 70 months) for SOC + Cel and 0.86 (95% CI, 0.70 to 1.05; P =.130; median survival, 76 months) for SOC + ZA + Cel. Preplanned subgroup analyses in men with metastatic disease showed a hazard ratio of 0.78 (95% CI, 0.62 to 0.98; P = .033) for SOC + ZA + Cel. Conclusion These data show no overall evidence of improved survival with Cel. Preplanned
Randomized selection on the GPU
Monroe, Laura Marie; Wendelberger, Joanne R; Michalak, Sarah E
2011-01-13
We implement here a fast and memory-sparing probabilistic top N selection algorithm on the GPU. To our knowledge, this is the first direct selection in the literature for the GPU. The algorithm proceeds via a probabilistic-guess-and-chcck process searching for the Nth element. It always gives a correct result and always terminates. The use of randomization reduces the amount of data that needs heavy processing, and so reduces the average time required for the algorithm. Probabilistic Las Vegas algorithms of this kind are a form of stochastic optimization and can be well suited to more general parallel processors with limited amounts of fast memory.
Bremer, P. -T.
2014-08-26
ADAPT is a topological analysis code that allow to compute local threshold, in particular relevance based thresholds for features defined in scalar fields. The initial target application is vortex detection but the software is more generally applicable to all threshold based feature definitions.
Adaptation of adaptive optics systems.
NASA Astrophysics Data System (ADS)
Xin, Yu; Zhao, Dazun; Li, Chen
1997-10-01
In the paper, a concept of an adaptation of adaptive optical system (AAOS) is proposed. The AAOS has certain real time optimization ability against the variation of the brightness of detected objects m, atmospheric coherence length rO and atmospheric time constant τ by means of changing subaperture number and diameter, dynamic range, and system's temporal response. The necessity of AAOS using a Hartmann-Shack wavefront sensor and some technical approaches are discussed. Scheme and simulation of an AAOS with variable subaperture ability by use of both hardware and software are presented as an example of the system.
Quantum search algorithms on a regular lattice
Hein, Birgit; Tanner, Gregor
2010-07-15
Quantum algorithms for searching for one or more marked items on a d-dimensional lattice provide an extension of Grover's search algorithm including a spatial component. We demonstrate that these lattice search algorithms can be viewed in terms of the level dynamics near an avoided crossing of a one-parameter family of quantum random walks. We give approximations for both the level splitting at the avoided crossing and the effectively two-dimensional subspace of the full Hilbert space spanning the level crossing. This makes it possible to give the leading order behavior for the search time and the localization probability in the limit of large lattice size including the leading order coefficients. For d=2 and d=3, these coefficients are calculated explicitly. Closed form expressions are given for higher dimensions.
Are outcome-adaptive allocation trials ethical?
Hey, Spencer Phillips; Kimmelman, Jonathan
2015-04-01
Randomization is firmly established as a cornerstone of clinical trial methodology. Yet, the ethics of randomization continues to generate controversy. The default, and most efficient, allocation scheme randomizes patients equally (1:1) across all arms of study. However, many randomized trials are using outcome-adaptive allocation schemes, which dynamically adjust the allocation ratio in favor of the better performing treatment arm. Advocates of outcome-adaptive allocation contend that it better accommodates clinical equipoise and promotes informed consent, since such trials limit patient-subject exposure to sub-optimal care. In this essay, we argue that this purported ethical advantage of outcome-adaptive allocation does not stand up to careful scrutiny in the setting of two-armed studies and/or early-phase research.
Mathematical physics: Search research
NASA Astrophysics Data System (ADS)
Shlesinger, Michael F.
2006-09-01
How does one best search for non-replenishable targets at unknown positions? An optimized search strategy could be applied to situations as diverse as animal foraging and time-sensitive rescue missions.
Adaptive optics imaging of the retina
Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha
2014-01-01
Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified. PMID:24492503
Adaptive optics imaging of the retina.
Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha
2014-01-01
Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified.
2008-07-02
solution of certain problems for which the communication needs do not dominate. A similar situation prevails in the quantum world. Quantum teleportation and...REPORT Quantum Search and Beyond 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Ten years ago, the quantum search algorithm was designed to provide a way...P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS quantum searching - partial quantum searching, fixed-point quantum
NASA Astrophysics Data System (ADS)
Qureshi, S. U. H.
1985-09-01
Theoretical work which has been effective in improving data transmission by telephone and radio links using adaptive equalization (AE) techniques is reviewed. AE has been applied to reducing the temporal dispersion effects, such as intersymbol interference, caused by the channel accessed. Attention is given to the Nyquist telegraph transmission theory, least mean square error adaptive filtering and the theory and structure of linear receive and transmit filters for reducing error. Optimum nonlinear receiver structures are discussed in terms of optimality criteria as a function of error probability. A suboptimum receiver structure is explored in the form of a decision-feedback equalizer. Consideration is also given to quadrature amplitude modulation and transversal equalization for receivers.
NASA Technical Reports Server (NTRS)
Hacker, Scott C. (Inventor); Dean, Richard J. (Inventor); Burge, Scott W. (Inventor); Dartez, Toby W. (Inventor)
2007-01-01
An adapter for installing a connector to a terminal post, wherein the connector is attached to a cable, is presented. In an embodiment, the adapter is comprised of an elongated collet member having a longitudinal axis comprised of a first collet member end, a second collet member end, an outer collet member surface, and an inner collet member surface. The inner collet member surface at the first collet member end is used to engage the connector. The outer collet member surface at the first collet member end is tapered for a predetermined first length at a predetermined taper angle. The collet includes a longitudinal slot that extends along the longitudinal axis initiating at the first collet member end for a predetermined second length. The first collet member end is formed of a predetermined number of sections segregated by a predetermined number of channels and the longitudinal slot.
Adaptive Dynamic Bayesian Networks
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
Adaptive Sampling in Hierarchical Simulation
Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R
2007-07-09
We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.
Curating the Web: Building a Google Custom Search Engine for the Arts
ERIC Educational Resources Information Center
Hennesy, Cody; Bowman, John
2008-01-01
Google's first foray onto the web made search simple and results relevant. With its Co-op platform, Google has taken another step toward dramatically increasing the relevancy of search results, further adapting the World Wide Web to local needs. Google Custom Search Engine, a tool on the Co-op platform, puts one in control of his or her own search…
Watson, B.L.; Aeby, I.
1980-08-26
An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.
ERIC Educational Resources Information Center
Cooper, Rosie
2011-01-01
Lou Marinoff's article, "Inside a Search," discusses the issues college search committees face in the pursuit of qualified faculty members that will be a good fit for their institutions. More often than not, faculty searches are more complex and challenging than the featured article suggests. The economic downturn facing the nation has resulted in…
ERIC Educational Resources Information Center
Meadow, Charles T.; Cochrane, Pauline (Atherton)
Intended to teach the principles of interactive bibliographic searching to those with little or no prior experience, this textbook explains the basic elements of online information retrieval and compares the major database search systems. Its chapters address (1) relevant definitions and vocabulary; (2) the conceptual facets of database searching,…
NASA Astrophysics Data System (ADS)
Barton, P.
1987-04-01
The basic principles of adaptive antennas are outlined in terms of the Wiener-Hopf expression for maximizing signal to noise ratio in an arbitrary noise environment; the analogy with generalized matched filter theory provides a useful aid to understanding. For many applications, there is insufficient information to achieve the above solution and thus non-optimum constrained null steering algorithms are also described, together with a summary of methods for preventing wanted signals being nulled by the adaptive system. The three generic approaches to adaptive weight control are discussed; correlation steepest descent, weight perturbation and direct solutions based on sample matrix conversion. The tradeoffs between hardware complexity and performance in terms of null depth and convergence rate are outlined. The sidelobe cancellor technique is described. Performance variation with jammer power and angular distribution is summarized and the key performance limitations identified. The configuration and performance characteristics of both multiple beam and phase scan array antennas are covered, with a brief discussion of performance factors.
Random template placement and prior information
NASA Astrophysics Data System (ADS)
Röver, Christian
2010-05-01
In signal detection problems, one is usually faced with the task of searching a parameter space for peaks in the likelihood function which indicate the presence of a signal. Random searches have proven to be very efficient as well as easy to implement, compared e.g. to searches along regular grids in parameter space. Knowledge of the parameterised shape of the signal searched for adds structure to the parameter space, i.e., there are usually regions requiring to be densely searched while in other regions a coarser search is sufficient. On the other hand, prior information identifies the regions in which a search will actually be promising or may likely be in vain. Defining specific figures of merit allows one to combine both template metric and prior distribution and devise optimal sampling schemes over the parameter space. We show an example related to the gravitational wave signal from a binary inspiral event. Here the template metric and prior information are particularly contradictory, since signals from low-mass systems tolerate the least mismatch in parameter space while high-mass systems are far more likely, as they imply a greater signal-to-noise ratio (SNR) and hence are detectable to greater distances. The derived sampling strategy is implemented in a Markov chain Monte Carlo (MCMC) algorithm where it improves convergence.
An efficient cuckoo search algorithm for numerical function optimization
NASA Astrophysics Data System (ADS)
Ong, Pauline; Zainuddin, Zarita
2013-04-01
Cuckoo search algorithm which reproduces the breeding strategy of the best known brood parasitic bird, the cuckoos has demonstrated its superiority in obtaining the global solution for numerical optimization problems. However, the involvement of fixed step approach in its exploration and exploitation behavior might slow down the search process considerably. In this regards, an improved cuckoo search algorithm with adaptive step size adjustment is introduced and its feasibility on a variety of benchmarks is validated. The obtained results show that the proposed scheme outperforms the standard cuckoo search algorithm in terms of convergence characteristic while preserving the fascinating features of the original method.
Adaptive noise cancellation based on beehive pattern evolutionary digital filter
NASA Astrophysics Data System (ADS)
Zhou, Xiaojun; Shao, Yimin
2014-01-01
Evolutionary digital filtering (EDF) exhibits the advantage of avoiding the local optimum problem by using cloning and mating searching rules in an adaptive noise cancellation system. However, convergence performance is restricted by the large population of individuals and the low level of information communication among them. The special beehive structure enables the individuals on neighbour beehive nodes to communicate with each other and thus enhance the information spread and random search ability of the algorithm. By introducing the beehive pattern evolutionary rules into the original EDF, this paper proposes an improved beehive pattern evolutionary digital filter (BP-EDF) to overcome the defects of the original EDF. In the proposed algorithm, a new evolutionary rule which combines competing cloning, complete cloning and assistance mating methods is constructed to enable the individuals distributed on the beehive to communicate with their neighbours. Simulation results are used to demonstrate the improved performance of the proposed algorithm in terms of convergence speed to the global optimum compared with the original methods. Experimental results also verify the effectiveness of the proposed algorithm in extracting feature signals that are contaminated by significant amounts of noise during the fault diagnosis task.
A directed search for extraterrestrial laser signals.
Betz, A
1986-01-01
This paper analyzes the technical feasibility of interstellar communication at infrared frequencies, both in its own right and in comparison with communication at radio frequencies. The analysis considers both the practical and fundamental limits affecting communication over interstellar distances and concludes that for specified transmitter and receiver locations communications at infrared and radio frequencies can be equally effective. On this basis a search for extraterrestrial signals at infrared wavelengths is equally as valid as any planned microwave effort. Work is now in progress to adapt a 10 micrometers heterodyne spectrometer to search for CO2 laser signals from 200 nearby stars.
A directed search for extraterrestrial laser signals
NASA Technical Reports Server (NTRS)
Betz, A.
1986-01-01
This paper analyzes the technical feasibility of interstellar communication at infrared frequencies, both in its own right and in comparison with communication at radio frequencies. The analysis considers both the practical and fundamental limits affecting communication over interstellar distances and concludes that for specified transmitter and receiver locations communications at infrared and radio frequencies can be equally effective. On this basis a search for extraterrestrial signals at infrared wavelengths is equally as valid as any planned microwave effort. Work is now in progress to adapt a 10 micrometers heterodyne spectrometer to search for CO2 laser signals from 200 nearby stars.
NASA Technical Reports Server (NTRS)
Prinzel, Lawrence J., III; Kaber, David B.
2006-01-01
This report presents a review of literature on approaches to adaptive and adaptable task/function allocation and adaptive interface technologies for effective human management of complex systems that are likely to be issues for the Next Generation Air Transportation System, and a focus of research under the Aviation Safety Program, Integrated Intelligent Flight Deck Project. Contemporary literature retrieved from an online database search is summarized and integrated. The major topics include the effects of delegation-type, adaptable automation on human performance, workload and situation awareness, the effectiveness of various automation invocation philosophies and strategies to function allocation in adaptive systems, and the role of user modeling in adaptive interface design and the performance implications of adaptive interface technology.
Random broadcast on random geometric graphs
Bradonjic, Milan; Elsasser, Robert; Friedrich, Tobias
2009-01-01
In this work, we consider the random broadcast time on random geometric graphs (RGGs). The classic random broadcast model, also known as push algorithm, is defined as: starting with one informed node, in each succeeding round every informed node chooses one of its neighbors uniformly at random and informs it. We consider the random broadcast time on RGGs, when with high probability: (i) RGG is connected, (ii) when there exists the giant component in RGG. We show that the random broadcast time is bounded by {Omicron}({radical} n + diam(component)), where diam(component) is a diameter of the entire graph, or the giant component, for the regimes (i), or (ii), respectively. In other words, for both regimes, we derive the broadcast time to be {Theta}(diam(G)), which is asymptotically optimal.
GeoSearcher: GeoSpatial Ranking of Search Engine Results.
ERIC Educational Resources Information Center
Watters, Carolyn; Amoudi, Ghada
2002-01-01
Discusses search engines and describes a prototype system that provides dynamic ranking of search engine results for geospatial queries based on the URL of the host site. Evaluates this approach using user queries and random Web pages, making a contribution to Web retrieval by providing an alternative ranking order for search engine results.…
How random is a random vector?
Eliazar, Iddo
2015-12-15
Over 80 years ago Samuel Wilks proposed that the “generalized variance” of a random vector is the determinant of its covariance matrix. To date, the notion and use of the generalized variance is confined only to very specific niches in statistics. In this paper we establish that the “Wilks standard deviation” –the square root of the generalized variance–is indeed the standard deviation of a random vector. We further establish that the “uncorrelation index” –a derivative of the Wilks standard deviation–is a measure of the overall correlation between the components of a random vector. Both the Wilks standard deviation and the uncorrelation index are, respectively, special cases of two general notions that we introduce: “randomness measures” and “independence indices” of random vectors. In turn, these general notions give rise to “randomness diagrams”—tangible planar visualizations that answer the question: How random is a random vector? The notion of “independence indices” yields a novel measure of correlation for Lévy laws. In general, the concepts and results presented in this paper are applicable to any field of science and engineering with random-vectors empirical data.
[Advanced online search techniques and dedicated search engines for physicians].
Nahum, Yoav
2008-02-01
In recent years search engines have become an essential tool in the work of physicians. This article will review advanced search techniques from the world of information specialists, as well as some advanced search engine operators that may help physicians improve their online search capabilities, and maximize the yield of their searches. This article also reviews popular dedicated scientific and biomedical literature search engines.
University Students' Online Information Searching Strategies in Different Search Contexts
ERIC Educational Resources Information Center
Tsai, Meng-Jung; Liang, Jyh-Chong; Hou, Huei-Tse; Tsai, Chin-Chung
2012-01-01
This study investigates the role of search context played in university students' online information searching strategies. A total of 304 university students in Taiwan were surveyed with questionnaires in which two search contexts were defined as searching for learning, and searching for daily life information. Students' online search strategies…
Searching the clinical fitness landscape.
Eppstein, Margaret J; Horbar, Jeffrey D; Buzas, Jeffrey S; Kauffman, Stuart A
2012-01-01
Widespread unexplained variations in clinical practices and patient outcomes suggest major opportunities for improving the quality and safety of medical care. However, there is little consensus regarding how to best identify and disseminate healthcare improvements and a dearth of theory to guide the debate. Many consider multicenter randomized controlled trials to be the gold standard of evidence-based medicine, although results are often inconclusive or may not be generally applicable due to differences in the contexts within which care is provided. Increasingly, others advocate the use "quality improvement collaboratives", in which multi-institutional teams share information to identify potentially better practices that are subsequently evaluated in the local contexts of specific institutions, but there is concern that such collaborative learning approaches lack the statistical rigor of randomized trials. Using an agent-based model, we show how and why a collaborative learning approach almost invariably leads to greater improvements in expected patient outcomes than more traditional approaches in searching simulated clinical fitness landscapes. This is due to a combination of greater statistical power and more context-dependent evaluation of treatments, especially in complex terrains where some combinations of practices may interact in affecting outcomes. The results of our simulations are consistent with observed limitations of randomized controlled trials and provide important insights into probable reasons for effectiveness of quality improvement collaboratives in the complex socio-technical environments of healthcare institutions. Our approach illustrates how modeling the evolution of medical practice as search on a clinical fitness landscape can aid in identifying and understanding strategies for improving the quality and safety of medical care.
Adaptive Firefly Algorithm: Parameter Analysis and its Application
Shen, Hong-Bin
2014-01-01
As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm — adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem — protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise. PMID:25397812
Adaptive firefly algorithm: parameter analysis and its application.
Cheung, Ngaam J; Ding, Xue-Ming; Shen, Hong-Bin
2014-01-01
As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm - adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a gray coefficient enhancing fireflies to share difference information from attractive ones efficiently; and (3) five different dynamic strategies for the randomization parameter. Promising selections of parameters in the strategies are analyzed to guarantee the efficient performance of AdaFa. AdaFa is validated over widely used benchmark functions, and the numerical experiments and statistical tests yield useful conclusions on the strategies and the parameter selections affecting the performance of AdaFa. When applied to the real-world problem - protein tertiary structure prediction, the results demonstrated improved variants can rebuild the tertiary structure with the average root mean square deviation less than 0.4Å and 1.5Å from the native constrains with noise free and 10% Gaussian white noise.
Directed random walk with random restarts: The Sisyphus random walk
NASA Astrophysics Data System (ADS)
Montero, Miquel; Villarroel, Javier
2016-09-01
In this paper we consider a particular version of the random walk with restarts: random reset events which suddenly bring the system to the starting value. We analyze its relevant statistical properties, like the transition probability, and show how an equilibrium state appears. Formulas for the first-passage time, high-water marks, and other extreme statistics are also derived; we consider counting problems naturally associated with the system. Finally we indicate feasible generalizations useful for interpreting different physical effects.
Directed random walk with random restarts: The Sisyphus random walk.
Montero, Miquel; Villarroel, Javier
2016-09-01
In this paper we consider a particular version of the random walk with restarts: random reset events which suddenly bring the system to the starting value. We analyze its relevant statistical properties, like the transition probability, and show how an equilibrium state appears. Formulas for the first-passage time, high-water marks, and other extreme statistics are also derived; we consider counting problems naturally associated with the system. Finally we indicate feasible generalizations useful for interpreting different physical effects.
Strategies for Computerized Adaptive Grading Testing.
ERIC Educational Resources Information Center
Xiao, Beiling
1999-01-01
Evaluated three strategies for assigning examinees to grading categories in computerized adaptive testing. The expected a posteriori-based method had more correct classifications in the middle range of grade levels and more errors for the extremes than the golden section search grading test and the Z-score grading test. (SLD)
Demystifying the Search Button
McKeever, Liam; Nguyen, Van; Peterson, Sarah J.; Gomez-Perez, Sandra
2015-01-01
A thorough review of the literature is the basis of all research and evidence-based practice. A gold-standard efficient and exhaustive search strategy is needed to ensure all relevant citations have been captured and that the search performed is reproducible. The PubMed database comprises both the MEDLINE and non-MEDLINE databases. MEDLINE-based search strategies are robust but capture only 89% of the total available citations in PubMed. The remaining 11% include the most recent and possibly relevant citations but are only searchable through less efficient techniques. An effective search strategy must employ both the MEDLINE and the non-MEDLINE portion of PubMed to ensure all studies have been identified. The robust MEDLINE search strategies are used for the MEDLINE portion of the search. Usage of the less robust strategies is then efficiently confined to search only the remaining 11% of PubMed citations that have not been indexed for MEDLINE. The current article offers step-by-step instructions for building such a search exploring methods for the discovery of medical subject heading (MeSH) terms to search MEDLINE, text-based methods for exploring the non-MEDLINE database, information on the limitations of convenience algorithms such as the “related citations feature,” the strengths and pitfalls associated with commonly used filters, the proper usage of Boolean operators to organize a master search strategy, and instructions for automating that search through “MyNCBI” to receive search query updates by email as new citations become available. PMID:26129895
Search Space Characterization for a Telescope Scheduling Application
NASA Technical Reports Server (NTRS)
Bresina, John; Drummond, Mark; Swanson, Keith; Friedland, Peter (Technical Monitor)
1994-01-01
This paper presents a technique for statistically characterizing a search space and demonstrates the use of this technique within a practical telescope scheduling application. The characterization provides the following: (i) an estimate of the search space size, (ii) a scaling technique for multi-attribute objective functions and search heuristics, (iii) a "quality density function" for schedules in a search space, (iv) a measure of a scheduler's performance, and (v) support for constructing and tuning search heuristics. This paper describes the random sampling algorithm used to construct this characterization and explains how it can be used to produce this information. As an example, we include a comparative analysis of an heuristic dispatch scheduler and a look-ahead scheduler that performs greedy search.
Effective trapping of random walkers in complex networks
NASA Astrophysics Data System (ADS)
Hwang, S.; Lee, D.-S.; Kahng, B.
2012-04-01
Exploring the World Wide Web has become one of the key issues in information science, specifically in view of its application to the PageRank-like algorithms used in search engines. The random walk approach has been employed to study such a problem. The probability of return to the origin (RTO) of random walks is inversely related to how information can be accessed during random surfing. We find analytically that the RTO probability for a given starting node shows a crossover from a slow to a fast decay behavior with time and the crossover time increases with the degree of the starting node. We remark that the RTO probability becomes almost constant in the early-time regime as the degree exponent approaches two. This result indicates that a random surfer can be effectively trapped at the hub and supports the necessity of the random jump strategy empirically used in the Google's search engine.
Spectroscopy with Random and Displaced Random Ensembles
NASA Astrophysics Data System (ADS)
Velázquez, V.; Zuker, A. P.
2002-02-01
Because of the time reversal invariance of the angular momentum operator J2, the average energies and variances at fixed J for random two-body Hamiltonians exhibit odd-even- J staggering that may be especially strong for J = 0. It is shown that upon ensemble averaging over random runs, this behavior is reflected in the yrast states. Displaced (attractive) random ensembles lead to rotational spectra with strongly enhanced B(E2) transitions for a certain class of model spaces. It is explained how to generalize these results to other forms of collectivity.
Whitley, L. Darrell; Howe, Adele E.; Watson, Jean-Paul
2004-09-01
Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features that influence problem difficulty. We consider these questions in the context of the job-shop scheduling problem (JSP), a domain where tabu search algorithms have been shown to be remarkably effective. Previously, we demonstrated that the mean distance between random local optima and the nearest optimal solution is highly correlated with problem difficulty for a well-known tabu search algorithm for the JSP introduced by Taillard. In this paper, we discuss various shortcomings of this measure and develop a new model of problem difficulty that corrects these deficiencies. We show that Taillard's algorithm can be modeled with high fidelity as a simple variant of a straightforward random walk. The random walk model accounts for nearly all of the variability in the cost required to locate both optimal and sub-optimal solutions to random JSPs, and provides an explanation for differences in the difficulty of random versus structured JSPs. Finally, we discuss and empirically substantiate two novel predictions regarding tabu search algorithm behavior. First, the method for constructing the initial solution is highly unlikely to impact the performance of tabu search. Second, tabu tenure should be selected to be as small as possible while simultaneously avoiding search stagnation; values larger than necessary lead to significant degradations in performance.
Caroline Müllenbroich, M; McGhee, Ewan J; Wright, Amanda J; Anderson, Kurt I; Mathieson, Keith
2014-01-01
We have developed a nonlinear adaptive optics microscope utilizing a deformable membrane mirror (DMM) and demonstrated its use in compensating for system- and sample-induced aberrations. The optimum shape of the DMM was determined with a random search algorithm optimizing on either two photon fluorescence or second harmonic signals as merit factors. We present here several strategies to overcome photobleaching issues associated with lengthy optimization routines by adapting the search algorithm and the experimental methodology. Optimizations were performed on extrinsic fluorescent dyes, fluorescent beads loaded into organotypic tissue cultures and the intrinsic second harmonic signal of these cultures. We validate the approach of using these preoptimized mirror shapes to compile a robust look-up table that can be applied for imaging over several days and through a variety of tissues. In this way, the photon exposure to the fluorescent cells under investigation is limited to imaging. Using our look-up table approach, we show signal intensity improvement factors ranging from 1.7 to 4.1 in organotypic tissue cultures and freshly excised mouse tissue. Imaging zebrafish in vivo, we demonstrate signal improvement by a factor of 2. This methodology is easily reproducible and could be applied to many photon starved experiments, for example fluorescent life time imaging, or when photobleaching is a concern.
Randomness in quantum mechanics - nature's ultimate cryptogram?
NASA Astrophysics Data System (ADS)
Erber, T.; Putterman, S.
1985-11-01
The possibility that a single atom irradiated by coherent light will be equivalent to an infinite computer with regard to its ability to generate random numbers is addressed. A search for unexpected patterns of order by crypt analysis of the telegraph signal generated by the on/off time of the atom's fluorescence is described. The results will provide new experimental tests of the fundamental principles of quantum theory.
On Gaussian random supergravity
NASA Astrophysics Data System (ADS)
Bachlechner, Thomas C.
2014-04-01
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial Kähler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a numerical study of high dimensional random fields. Using these novel tools, we find that the vast majority of metastable critical points in N dimensional random supergravities are either approximately supersymmetric with | F| ≪ M susy or supersymmetric. Such approximately supersymmetric points are dynamical attractors in the landscape and the probability that a randomly chosen critical point is metastable scales as log( P ) ∝ - N. We argue that random supergravities lead to potentially interesting inflationary dynamics.
How Users Search the Library from a Single Search Box
ERIC Educational Resources Information Center
Lown, Cory; Sierra, Tito; Boyer, Josh
2013-01-01
Academic libraries are turning increasingly to unified search solutions to simplify search and discovery of library resources. Unfortunately, very little research has been published on library user search behavior in single search box environments. This study examines how users search a large public university library using a prominent, single…
Computerized Literature Searching: An Orientation for the Search Requestor.
ERIC Educational Resources Information Center
Fabiano, Emily
Developed to orient the information seeker to the computerized literature search process, this guide provides background information that will help the user facilitate the search interview and the formation of a search topic, enabling him or her to focus on personal search needs and not on the fundamentals of online searching. Major purposes for…
Citation Searching: Search Smarter & Find More
ERIC Educational Resources Information Center
Hammond, Chelsea C.; Brown, Stephanie Willen
2008-01-01
The staff at University of Connecticut are participating in Elsevier's Student Ambassador Program (SAmP) in which graduate students train their peers on "citation searching" research using Scopus and Web of Science, two tremendous citation databases. They are in the fourth semester of these training programs, and they are wildly successful: They…
NASA Technical Reports Server (NTRS)
Lynnes, Chris
2014-01-01
Three current search engines are queried for ozone data at the GES DISC. The results range from sub-optimal to counter-intuitive. We propose a method to fix dataset search by implementing a robust relevancy ranking scheme. The relevancy ranking scheme is based on several heuristics culled from more than 20 years of helping users select datasets.
ERIC Educational Resources Information Center
Maxfield, Sandy, Ed.; Kabus, Karl, Ed.
This document is a guide to the use of Quick Search, a library service that provides access to more than 100 databases which contain references to journal articles and other research materials through two commercial systems--BRS After/Dark and DIALOG's Knowledge Index. The guide is divided into five sections: (1) Using Quick Search; (2) The…
Lokutsievskiy, Lev V
2011-05-31
This paper is concerned with the optimal search of an object at rest with unknown exact position in the n-dimensional space. A necessary condition for optimality of a trajectory is obtained. An explicit form of a differential equation for an optimal trajectory is found while searching over R-strongly convex sets. An existence theorem is also established. Bibliography: 8 titles.
ERIC Educational Resources Information Center
Gunn, Holly
2005-01-01
Although there are many news search engines on the Web, finding the news items one wants can be challenging. Choosing appropriate search terms is one of the biggest challenges. Unless one has seen the article that one is seeking, it is often difficult to select words that were used in the headline or text of the article. The limited archives of…
ERIC Educational Resources Information Center
Tenopir, Carol
2004-01-01
Only the most dedicated super-searchers are motivated to learn and control command systems, like DialogClassic, that rely on the user to input complex search strategies. Infrequent searchers and most end users choose interfaces that do some of the work for them and make the search process appear easy. However, the easier a good interface seems to…
NASA Technical Reports Server (NTRS)
Newman, Doug; Silva, Sam; Mitchell, Andrew
2016-01-01
We will present an overview of our OpenSearch efforts over the past 6 months. We will discuss our Best Practices and those of CEOS concentrating on the compatibility issues between the two. We will also discuss the state of earth data OpenSearch implementations and their adherence to the standards, extensions and best practices available.
Search for Gravitational Waves
NASA Astrophysics Data System (ADS)
Tsubono, K.
The current status of the experimental search for gravitational waves is reviewed here. The emphasis is on the Japanese TAMA project. We started operation of the TAMA300 laser interferometric detector in 1999, and are now collecting and analyzing observational data to search for gravitational wave signals.
Origins of Coordinate Searching.
ERIC Educational Resources Information Center
Kilgour, Frederick G.
1997-01-01
Reviews the origins of post-coordinate searching and emphasizes that the focal point should be on the searcher, not on the item being indexed. Highlights include the history of the term information retrieval; edge notched punch cards; the "peek-a-boo" system; the Uniterm system; and using computers to search for information. (LRW)
A simplified method for random vibration analysis of structures with random parameters
NASA Astrophysics Data System (ADS)
Ghienne, Martin; Blanzé, Claude
2016-09-01
Piezoelectric patches with adapted electrical circuits or viscoelastic dissipative materials are two solutions particularly adapted to reduce vibration of light structures. To accurately design these solutions, it is necessary to describe precisely the dynamical behaviour of the structure. It may quickly become computationally intensive to describe robustly this behaviour for a structure with nonlinear phenomena, such as contact or friction for bolted structures, and uncertain variations of its parameters. The aim of this work is to propose a non-intrusive reduced stochastic method to characterize robustly the vibrational response of a structure with random parameters. Our goal is to characterize the eigenspace of linear systems with dynamic properties considered as random variables. This method is based on a separation of random aspects from deterministic aspects and allows us to estimate the first central moments of each random eigenfrequency with a single deterministic finite elements computation. The method is applied to a frame with several Young's moduli modeled as random variables. This example could be expanded to a bolted structure including piezoelectric devices. The method needs to be enhanced when random eigenvalues are closely spaced. An indicator with no additional computational cost is proposed to characterize the ’’proximity” of two random eigenvalues.
NASA Astrophysics Data System (ADS)
Jenkins, D. N.
2012-09-01
The Canadian Astronomy Data Centre's (CADC) Advanced Search web application is a modern search tool to access data across the CADC archives. It allows searching in different units, and is well averse in wild card characters and numeric operations. Search results are displayed in a sortable and filterable manner allowing quick and accurate access to downloadable data. The Advanced Search interface makes extremely good use of the Astronomical Data Query Language (ADQL) to scour the Common Archive Observation Model (CAOM) Table Access Protocol (TAP) query service and the vast CADC Archive Data (AD) storage system. A new tabular view of the query form and the results data makes it easy to view the query, then return to the query form to make further changes, or, alternatively, filter the data from the paginated table. Results are displayed using a rich, open-source, JavaScript-based VOTable viewer called voview.
Intermittent search strategies
NASA Astrophysics Data System (ADS)
Bénichou, O.; Loverdo, C.; Moreau, M.; Voituriez, R.
2011-01-01
This review examines intermittent target search strategies, which combine phases of slow motion, allowing the searcher to detect the target, and phases of fast motion during which targets cannot be detected. It is first shown that intermittent search strategies are actually widely observed at various scales. At the macroscopic scale, this is, for example, the case of animals looking for food; at the microscopic scale, intermittent transport patterns are involved in a reaction pathway of DNA-binding proteins as well as in intracellular transport. Second, generic stochastic models are introduced, which show that intermittent strategies are efficient strategies that enable the minimization of search time. This suggests that the intrinsic efficiency of intermittent search strategies could justify their frequent observation in nature. Last, beyond these modeling aspects, it is proposed that intermittent strategies could also be used in a broader context to design and accelerate search processes.
Needle Federated Search Engine
2009-12-01
The Idaho National Laboratory (INL) has combined a number of technologies, tools, and resources to accomplish a new means of federating search results. The resulting product is a search engine called Needle, an open-source-based tool that the INL uses internally for researching across a wide variety of information repositories. Needle has a flexible search interface that allows end users to point at any available data source. A user can select multiple sources such as commercial databases (Web of Science, Engineering Index), external resources (WorldCat, Google Scholar), and internal corporate resources (email, document management system, library collections) in a single interface with one search query. In the future, INL hopes to offer this open-source engine to the public. This session will outline the development processes for making Needles search interface and simplifying the federation of internal and external data sources.
Adaptive evolution of molecular phenotypes
NASA Astrophysics Data System (ADS)
Held, Torsten; Nourmohammad, Armita; Lässig, Michael
2014-09-01
Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak.
Adaptive Behavior for Mobile Robots
NASA Technical Reports Server (NTRS)
Huntsberger, Terrance
2009-01-01
The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.
Hentschel random access tracking system HSG 84.30
NASA Astrophysics Data System (ADS)
Zamzow, Heinz
1990-08-01
The development of the Random Access Tracking System was initiated at the University of Muenster, Department of Orthopaedic Physiology by Dr. Theysohn. This system is a real-time high-speed and high-resolution multi-point tracking system. The moving objects are identified with retro-reflective markers which are illuminated by halogen spotlights placed around the camera lens. The video interface generates deflection signals which are fed to unique Random Access Cameras manufactured by Hamamatsu Corporation. These signals perform high speed window scanning and can sample up to 7,500 markers per second. Under certain circumstances this can be increased to 15,000 markers per second. From 1 to 126 markers can be detected in a line scan search mode. Window size may be varied in steps from 0.5% to 4.0% of the field of view. Using a small window it is possible to obtain 1 part in 32,768 in each direction of the field of view. The raw data are reduced to 2-D centroids of the targets. On-line data storage and display are possible using an industry-standard ATPC with DMA interface. Real-time feed-back is also possible. The video interface provides for off-line 3-D reconstructions using the data from two or more synchronized cameras. The system can be adapted to meet the needs of particular applications by modifying sample-rate, data transfer rate, and the number and the dimensions of the windows.
Chen, Ying-ping; Chen, Chao-Hong
2010-01-01
An adaptive discretization method, called split-on-demand (SoD), enables estimation of distribution algorithms (EDAs) for discrete variables to solve continuous optimization problems. SoD randomly splits a continuous interval if the number of search points within the interval exceeds a threshold, which is decreased at every iteration. After the split operation, the nonempty intervals are assigned integer codes, and the search points are discretized accordingly. As an example of using SoD with EDAs, the integration of SoD and the extended compact genetic algorithm (ECGA) is presented and numerically examined. In this integration, we adopt a local search mechanism as an optional component of our back end optimization engine. As a result, the proposed framework can be considered as a memetic algorithm, and SoD can potentially be applied to other memetic algorithms. The numerical experiments consist of two parts: (1) a set of benchmark functions on which ECGA with SoD and ECGA with two well-known discretization methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH) are compared; (2) a real-world application, the economic dispatch problem, on which ECGA with SoD is compared to other methods. The experimental results indicate that SoD is a better discretization method to work with ECGA. Moreover, ECGA with SoD works quite well on the economic dispatch problem and delivers solutions better than the best known results obtained by other methods in existence.
Sarkar, Kanchan; Bhattacharyya, S P
2013-08-21
We propose and implement a simple adaptive heuristic to optimize the geometries of clusters of point charges or ions with the ability to find the global minimum energy configurations. The approach uses random mutations of a single string encoding the geometry and accepts moves that decrease the energy. Mutation probability and mutation intensity are allowed to evolve adaptively on the basis of continuous evaluation of past explorations. The resulting algorithm has been called Completely Adaptive Random Mutation Hill Climbing method. We have implemented this method to search through the complex potential energy landscapes of parabolically confined 3D classical Coulomb clusters of hundreds or thousands of charges--usually found in high frequency discharge plasmas. The energy per particle (EN∕N) and its first and second differences, structural features, distribution of the oscillation frequencies of normal modes, etc., are analyzed as functions of confinement strength and the number of charges in the system. Certain magic numbers are identified. In order to test the feasibility of the algorithm in cluster geometry optimization on more complex energy landscapes, we have applied the algorithm for optimizing the geometries of MgO clusters, described by Coulomb-Born-Mayer potential and finding global minimum of some Lennard-Jones clusters. The convergence behavior of the algorithm compares favorably with those of other existing global optimizers.
NASA Astrophysics Data System (ADS)
Sarkar, Kanchan; Bhattacharyya, S. P.
2013-08-01
We propose and implement a simple adaptive heuristic to optimize the geometries of clusters of point charges or ions with the ability to find the global minimum energy configurations. The approach uses random mutations of a single string encoding the geometry and accepts moves that decrease the energy. Mutation probability and mutation intensity are allowed to evolve adaptively on the basis of continuous evaluation of past explorations. The resulting algorithm has been called Completely Adaptive Random Mutation Hill Climbing method. We have implemented this method to search through the complex potential energy landscapes of parabolically confined 3D classical Coulomb clusters of hundreds or thousands of charges—usually found in high frequency discharge plasmas. The energy per particle (EN/N) and its first and second differences, structural features, distribution of the oscillation frequencies of normal modes, etc., are analyzed as functions of confinement strength and the number of charges in the system. Certain magic numbers are identified. In order to test the feasibility of the algorithm in cluster geometry optimization on more complex energy landscapes, we have applied the algorithm for optimizing the geometries of MgO clusters, described by Coulomb-Born-Mayer potential and finding global minimum of some Lennard-Jones clusters. The convergence behavior of the algorithm compares favorably with those of other existing global optimizers.
Classification of adaptive memetic algorithms: a comparative study.
Ong, Yew-Soon; Lim, Meng-Hiot; Zhu, Ning; Wong, Kok-Wai
2006-02-01
Adaptation of parameters and operators represents one of the recent most important and promising areas of research in evolutionary computations; it is a form of designing self-configuring algorithms that acclimatize to suit the problem in hand. Here, our interests are on a recent breed of hybrid evolutionary algorithms typically known as adaptive memetic algorithms (MAs). One unique feature of adaptive MAs is the choice of local search methods or memes and recent studies have shown that this choice significantly affects the performances of problem searches. In this paper, we present a classification of memes adaptation in adaptive MAs on the basis of the mechanism used and the level of historical knowledge on the memes employed. Then the asymptotic convergence properties of the adaptive MAs considered are analyzed according to the classification. Subsequently, empirical studies on representatives of adaptive MAs for different type-level meme adaptations using continuous benchmark problems indicate that global-level adaptive MAs exhibit better search performances. Finally we conclude with some promising research directions in the area.
Custom Search Engines: Tools & Tips
ERIC Educational Resources Information Center
Notess, Greg R.
2008-01-01
Few have the resources to build a Google or Yahoo! from scratch. Yet anyone can build a search engine based on a subset of the large search engines' databases. Use Google Custom Search Engine or Yahoo! Search Builder or any of the other similar programs to create a vertical search engine targeting sites of interest to users. The basic steps to…
Mesh Adaptive Direct Search Methods for Constrained Nonsmooth Optimization
2012-02-24
presence will extend our collaboration circle to mechanical engineering researchers. • We have initiated a new collaboration with A.D. Pelton from chemi...Published: 1. A.E. Gheribi, C. Audet, S. Le Digabel, E. Blisle, C.W. Bale and A. D. Pelton . Calculating optimal conditions for alloy and process...Gheribi, C. Robelin, S. Le Digabel, C. Audet and A.D. Pelton . Calculating All Local Minima on Liquidus Surfaces Using the FactSage Software and Databases
Quantum random number generation
Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing
2016-06-28
Quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.
Quantum random number generation
Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; ...
2016-06-28
Quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a highmore » speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less
Quantum random number generation
NASA Astrophysics Data System (ADS)
Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Qi, Bing; Zhang, Zhen
2016-06-01
Quantum physics can be exploited to generate true random numbers, which have important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness—coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. On the basis of the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a high speed by properly modelling the devices. The second category is self-testing QRNG, in which verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category that provides a tradeoff between the trustworthiness on the device and the random number generation speed.
Adaptive evolution of Mediterranean pines.
Grivet, Delphine; Climent, José; Zabal-Aguirre, Mario; Neale, David B; Vendramin, Giovanni G; González-Martínez, Santiago C
2013-09-01
Mediterranean pines represent an extremely heterogeneous assembly. Although they have evolved under similar environmental conditions, they diversified long ago, ca. 10 Mya, and present distinct biogeographic and demographic histories. Therefore, it is of special interest to understand whether and to what extent they have developed specific strategies of adaptive evolution through time and space. To explore evolutionary patterns, the Mediterranean pines' phylogeny was first reconstructed analyzing a new set of 21 low-copy nuclear genes with multilocus Bayesian tree reconstruction methods. Secondly, a phylogenetic approach was used to search for footprints of natural selection and to examine the evolution of multiple phenotypic traits. We identified two genes (involved in pines' defense and stress responses) that have likely played a role in the adaptation of Mediterranean pines to their environment. Moreover, few life-history traits showed historical or evolutionary adaptive convergence in Mediterranean lineages, while patterns of character evolution revealed various evolutionary trade-offs linking growth-development, reproduction and fire-related traits. Assessing the evolutionary path of important life-history traits, as well as the genomic basis of adaptive variation is central to understanding the past evolutionary success of Mediterranean pines and their future response to environmental changes.
Competitive Facility Location with Fuzzy Random Demands
NASA Astrophysics Data System (ADS)
Uno, Takeshi; Katagiri, Hideki; Kato, Kosuke
2010-10-01
This paper proposes a new location problem of competitive facilities, e.g. shops, with uncertainty and vagueness including demands for the facilities in a plane. By representing the demands for facilities as fuzzy random variables, the location problem can be formulated as a fuzzy random programming problem. For solving the fuzzy random programming problem, first the α-level sets for fuzzy numbers are used for transforming it to a stochastic programming problem, and secondly, by using their expectations and variances, it can be reformulated to a deterministic programming problem. After showing that one of their optimal solutions can be found by solving 0-1 programming problems, their solution method is proposed by improving the tabu search algorithm with strategic oscillation. The efficiency of the proposed method is shown by applying it to numerical examples of the facility location problems.
Improving Search Engine Reliability
NASA Astrophysics Data System (ADS)
Pruthi, Jyoti; Kumar, Ela
2010-11-01
Search engines on the Internet are used daily to access and find information. While these services are providing an easy way to find information globally, they are also suffering from artificially created false results. This paper describes two techniques that are being used to manipulate the search engines: spam pages (used to achieve higher rankings on the result page) and cloaking (used to feed falsified data into search engines). This paper also describes two proposed methods to fight this kind of misuse, algorithms for both of the formerly mentioned cases of spamdexing.
Correspondence: Searching sequence space
Youvan, D.C.
1995-08-01
This correspondence debates the efficiency and application of genetic algorithms (GAs) to search protein sequence space. The important experimental point is that such sparse searches utilize physically realistic syntheses. In this regard, all GA-based technologies are very similar; they {open_quotes}learn{close_quotes} from their initial sparse search and then generate interesting new proteins within a few iterations. Which GA-based technology is best? That probably depends on the protein and the specific engineering goal. Given the fact that the field of combinatorial chemistry is still in its infancy, it is probably wise to consider all of the proven mutagenesis methods. 19 refs.
NASA Astrophysics Data System (ADS)
Kipping, D. M.
2011-12-01
With exoplanet detections becoming routine, astronomers are now vying to characterise these alien worlds. As well as detecting the atmospheres of these exoplanets, part of the characterisation process will undoubtedly involve the search for extrasolar moons. In this work, we explore the motivations for searching for exomoons, review some of the previously proposed detection techniques and finally introduce transit duration variation (TDV) as a proposed search method. We find that these techniques could easily detect Earth-mass exomoons with current instruments and potentially down to Galilean mass moons with future space missions like Kepler.
ReSEARCH: A Requirements Search Engine
2008-04-23
formally specify the meaning and domain of their requirements. Our goal in the research presented here is to address these concerns by designing a...synonymous. auto engine bonnet tyres lorry boot car emissions hood make model trunk make hidden Markov model emissions normalize Synonymy Problem Polysemy ...links as well • attempts to identify topic clusters related to search • find experts within these topics to “seed” the rank of some websites as
Unbiased structural search of small copper clusters within DFT
NASA Astrophysics Data System (ADS)
Cogollo-Olivo, Beatriz H.; Seriani, Nicola; Montoya, Javier A.
2015-11-01
The atomic structure of small Cu clusters with 3-6 atoms has been investigated by density functional theory and random search algorithm. New metastable structures have been found that lie merely tens of meV/atom above the corresponding ground state, and could therefore be present at thermodynamic equilibrium at room temperature or slightly above. Moreover, we show that the previously proposed linear configuration for Cu3 is in fact a local maximum of the energy. Finally, we argue that the random search algorithm also provides qualitative information about the attraction basin of each structure in the energy landscape.
Optimal search strategies on complex multi-linked networks
Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco
2015-01-01
In this paper we consider the problem of optimal search strategies on multi-linked networks, i.e. graphs whose nodes are endowed with several independent sets of links. We focus preliminarily on agents randomly hopping along the links of a graph, with the additional possibility of performing non-local hops to randomly chosen nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network. We then generalize our results to multi-linked networks with an arbitrary number of mutually interfering link sets. PMID:25950716
Navigability of interconnected networks under random failures
De Domenico, Manlio; Solé-Ribalta, Albert; Gómez, Sergio; Arenas, Alex
2014-01-01
Assessing the navigability of interconnected networks (transporting information, people, or goods) under eventual random failures is of utmost importance to design and protect critical infrastructures. Random walks are a good proxy to determine this navigability, specifically the coverage time of random walks, which is a measure of the dynamical functionality of the network. Here, we introduce the theoretical tools required to describe random walks in interconnected networks accounting for structure and dynamics inherent to real systems. We develop an analytical approach for the covering time of random walks in interconnected networks and compare it with extensive Monte Carlo simulations. Generally speaking, interconnected networks are more resilient to random failures than their individual layers per se, and we are able to quantify this effect. As an application––which we illustrate by considering the public transport of London––we show how the efficiency in exploring the multiplex critically depends on layers’ topology, interconnection strengths, and walk strategy. Our findings are corroborated by data-driven simulations, where the empirical distribution of check-ins and checks-out is considered and passengers travel along fastest paths in a network affected by real disruptions. These findings are fundamental for further development of searching and navigability strategies in real interconnected systems. PMID:24912174
LAHS: A novel harmony search algorithm based on learning automata
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin
2013-12-01
This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.
Randomization methods in emergency setting trials: a descriptive review
Moe‐Byrne, Thirimon; Oddie, Sam; McGuire, William
2015-01-01
Background Quasi‐randomization might expedite recruitment into trials in emergency care settings but may also introduce selection bias. Methods We searched the Cochrane Library and other databases for systematic reviews of interventions in emergency medicine or urgent care settings. We assessed selection bias (baseline imbalances) in prognostic indicators between treatment groups in trials using true randomization versus trials using quasi‐randomization. Results Seven reviews contained 16 trials that used true randomization and 11 that used quasi‐randomization. Baseline group imbalance was identified in four trials using true randomization (25%) and in two quasi‐randomized trials (18%). Of the four truly randomized trials with imbalance, three concealed treatment allocation adequately. Clinical heterogeneity and poor reporting limited the assessment of trial recruitment outcomes. Conclusions We did not find strong or consistent evidence that quasi‐randomization is associated with selection bias more often than true randomization. High risk of bias judgements for quasi‐randomized emergency studies should therefore not be assumed in systematic reviews. Clinical heterogeneity across trials within reviews, coupled with limited availability of relevant trial accrual data, meant it was not possible to adequately explore the possibility that true randomization might result in slower trial recruitment rates, or the recruitment of less representative populations. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. PMID:26333419
Second Graders Learn Animal Adaptations through Form and Function Analogy Object Boxes
ERIC Educational Resources Information Center
Rule, Audrey C.; Baldwin, Samantha; Schell, Robert
2008-01-01
This study examined the use of form and function analogy object boxes to teach second graders (n = 21) animal adaptations. The study used a pretest-posttest design to examine animal adaptation content learned through focused analogy activities as compared with reading and Internet searches for information about adaptations of animals followed by…
Tuning of patient-specific deformable models using an adaptive evolutionary optimization strategy.
Vidal, Franck P; Villard, Pierre-Frédéric; Lutton, Evelyne
2012-10-01
We present and analyze the behavior of an evolutionary algorithm designed to estimate the parameters of a complex organ behavior model. The model is adaptable to account for patient's specificities. The aim is to finely tune the model to be accurately adapted to various real patient datasets. It can then be embedded, for example, in high fidelity simulations of the human physiology. We present here an application focused on respiration modeling. The algorithm is automatic and adaptive. A compound fitness function has been designed to take into account for various quantities that have to be minimized. The algorithm efficiency is experimentally analyzed on several real test cases: 1) three patient datasets have been acquired with the "breath hold" protocol, and 2) two datasets corresponds to 4-D CT scans. Its performance is compared with two traditional methods (downhill simplex and conjugate gradient descent): a random search and a basic real-valued genetic algorithm. The results show that our evolutionary scheme provides more significantly stable and accurate results.
Searching Sociological Abstracts.
ERIC Educational Resources Information Center
Kerbel, Sandra Sandor
1981-01-01
Describes the scope, content, and retrieval characteristics of Sociological Abstracts, an online database of literature in the social sciences. Sample searches are displayed, and the strengths and weaknesses of the database are summarized. (FM)
Automated search for supernovae
Kare, J.T.
1984-11-15
This thesis describes the design, development, and testing of a search system for supernovae, based on the use of current computer and detector technology. This search uses a computer-controlled telescope and charge coupled device (CCD) detector to collect images of hundreds of galaxies per night of observation, and a dedicated minicomputer to process these images in real time. The system is now collecting test images of up to several hundred fields per night, with a sensitivity corresponding to a limiting magnitude (visual) of 17. At full speed and sensitivity, the search will examine some 6000 galaxies every three nights, with a limiting magnitude of 18 or fainter, yielding roughly two supernovae per week (assuming one supernova per galaxy per 50 years) at 5 to 50 percent of maximum light. An additional 500 nearby galaxies will be searched every night, to locate about 10 supernovae per year at one or two percent of maximum light, within hours of the initial explosion.
... Cancer Programs Trauma Centers Education Institutes Breast Centers Bariatric Surgery Centers ACS NSQIP Hospitals Search Member Services Member ... Invoices Quality and Safety Conference Bariatrics Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program Metabolic and Bariatric ...
Costs and benefits to industry of online literature searches
NASA Technical Reports Server (NTRS)
Jensen, R. J.; Asbury, H. O.; King, R. G.
1980-01-01
A description is given of a client survey conducted by the NASA Industrial Application Center, U.S.C., examining user-identified dollar costs and benefits of an online computerized literature search. Telephone interviews were conducted on a random sample of clients using a Denver Research Institute questionnaire. Of the total 159 clients surveyed, over 53% identified dollar benefits. A direct relationship between client dollars invested and benefits derived from the search was shown. The ratio of dollar benefit to investment dollar averaged 2.9 to 1. Precise data on the end user's evaluation of the dollar value of an information search are presented.
Quantum random number generators
NASA Astrophysics Data System (ADS)
Herrero-Collantes, Miguel; Garcia-Escartin, Juan Carlos
2017-01-01
Random numbers are a fundamental resource in science and engineering with important applications in simulation and cryptography. The inherent randomness at the core of quantum mechanics makes quantum systems a perfect source of entropy. Quantum random number generation is one of the most mature quantum technologies with many alternative generation methods. This review discusses the different technologies in quantum random number generation from the early devices based on radioactive decay to the multiple ways to use the quantum states of light to gather entropy from a quantum origin. Randomness extraction and amplification and the notable possibility of generating trusted random numbers even with untrusted hardware using device-independent generation protocols are also discussed.
Random forests for genomic data analysis.
Chen, Xi; Ishwaran, Hemant
2012-06-01
Random forests (RF) is a popular tree-based ensemble machine learning tool that is highly data adaptive, applies to "large p, small n" problems, and is able to account for correlation as well as interactions among features. This makes RF particularly appealing for high-dimensional genomic data analysis. In this article, we systematically review the applications and recent progresses of RF for genomic data, including prediction and classification, variable selection, pathway analysis, genetic association and epistasis detection, and unsupervised learning.
NASA Astrophysics Data System (ADS)
Gurau, Razvan
2016-09-01
This article is preface to the SIGMA special issue ''Tensor Models, Formalism and Applications'', http://www.emis.de/journals/SIGMA/Tensor_Models.html. The issue is a collection of eight excellent, up to date reviews on random tensor models. The reviews combine pedagogical introductions meant for a general audience with presentations of the most recent developments in the field. This preface aims to give a condensed panoramic overview of random tensors as the natural generalization of random matrices to higher dimensions.
Russian Doll Search for solving Constraint Optimization problems
Verfaillie, G.; Lemaitre, M.
1996-12-31
If the Constraint Satisfaction framework has been extended to deal with Constraint Optimization problems, it appears that optimization is far more complex than satisfaction. One of the causes of the inefficiency of complete tree search methods, like Depth First Branch and Bound, lies in the poor quality of the lower bound on the global valuation of a partial assignment, even when using Forward Checking techniques. In this paper, we introduce the Russian Doll Search algorithm which replaces one search by n successive searches on nested subproblems (n being the number of problem variables), records the results of each search and uses them later, when solving larger subproblems, in order to improve the lower bound on the global valuation of any partial assignment. On small random problems and on large real scheduling problems, this algorithm yields surprisingly good results, which greatly improve as the problems get more constrained and the bandwidth of the used variable ordering diminishes.
Data Bus Adapts to Changing Traffic Level
NASA Technical Reports Server (NTRS)
Lew, Eugene; Deruiter, John; Varga, Mike
1987-01-01
Access becomes timed when collisions threaten. Two-mode scheme used to grant terminals access to data bus. Causes bus to alternate between random accessibility and controlled accessibility to optimize performance and adapt to changing data-traffic conditions. Bus is part of 100-Mb/s optical-fiber packet data system.
The importance of search strategy for finding targets in open terrain.
Riggs, Charlotte A; Cornes, Katherine; Godwin, Hayward J; Liversedge, Simon P; Guest, Richard; Donnelly, Nick
2017-01-01
A number of real-world search tasks (i.e. police search, detection of improvised explosive devices (IEDs)) require searchers to search exhaustively across open ground. In the present study, we simulated this problem by asking individuals (Experiments 1a and 1b) and dyads (Experiment 2) to search for coin targets pseudo-randomly located in a bounded area of open grassland terrain. In Experiment 1a, accuracy, search time, and the route used to search an area were measured. Participants tended to use an 'S'-shaped pattern with a common width of search lane. Increased accuracy was associated with slower, but also variable, search speed, though only when participants moved along the length (as opposed to across the width) of the search area. Experiment 1b varied the number of targets available within the bounded search area and in doing so varied target prevalence and density. The results confirmed that the route taken in Experiment 1a generalizes across variations in target prevalence/density. In Experiment 2, accuracy, search time, and the search strategy used by dyads was measured. While dyads were more accurate than individuals, dyads that opted to conduct two independent searches were more accurate than those who opted to split the search space. The implications of these results for individuals and dyads when searching for targets in open space are discussed.
NASA Astrophysics Data System (ADS)
Newman, D. J.; Mitchell, A. E.
2015-12-01
At AGU 2014, NASA EOSDIS demonstrated a case-study of an OpenSearch framework for Earth science data discovery. That framework leverages the IDN and CWIC OpenSearch API implementations to provide seamless discovery of data through the 'two-step' discovery process as outlined by the Federation for Earth Sciences (ESIP) OpenSearch Best Practices. But how would an Earth Scientist leverage this framework and what are the benefits? Using a client that understands the OpenSearch specification and, for further clarity, the various best practices and extensions, a scientist can discovery a plethora of data not normally accessible either by traditional methods (NASA Earth Data Search, Reverb, etc) or direct methods (going to the source of the data) We will demonstrate, via the CWICSmart web client, how an earth scientist can access regional data on a regional phenomena in a uniform and aggregated manner. We will demonstrate how an earth scientist can 'globalize' their discovery. You want to find local data on 'sea surface temperature of the Indian Ocean'? We can help you with that. 'European meteorological data'? Yes. 'Brazilian rainforest satellite imagery'? That too. CWIC allows you to get earth science data in a uniform fashion from a large number of disparate, world-wide agencies. This is what we mean by Global OpenSearch.
NASA Technical Reports Server (NTRS)
Albornoz, Caleb Ronald
2012-01-01
Thousands of millions of documents are stored and updated daily in the World Wide Web. Most of the information is not efficiently organized to build knowledge from the stored data. Nowadays, search engines are mainly used by users who rely on their skills to look for the information needed. This paper presents different techniques search engine users can apply in Google Search to improve the relevancy of search results. According to the Pew Research Center, the average person spends eight hours a month searching for the right information. For instance, a company that employs 1000 employees wastes $2.5 million dollars on looking for nonexistent and/or not found information. The cost is very high because decisions are made based on the information that is readily available to use. Whenever the information necessary to formulate an argument is not available or found, poor decisions may be made and mistakes will be more likely to occur. Also, the survey indicates that only 56% of Google users feel confident with their current search skills. Moreover, just 76% of the information that is available on the Internet is accurate.
Duffy, Steven; de Kock, Shelley; Misso, Kate; Noake, Caro; Ross, Janine; Stirk, Lisa
2016-01-01
Objective The research investigated whether conducting a supplementary search of PubMed in addition to the main MEDLINE (Ovid) search for a systematic review is worthwhile and to ascertain whether this PubMed search can be conducted quickly and if it retrieves unique, recently published, and ahead-of-print studies that are subsequently considered for inclusion in the final systematic review. Methods Searches of PubMed were conducted after MEDLINE (Ovid) and MEDLINE In-Process (Ovid) searches had been completed for seven recent reviews. The searches were limited to records not in MEDLINE or MEDLINE In-Process (Ovid). Results Additional unique records were identified for all of the investigated reviews. Search strategies were adapted quickly to run in PubMed, and reviewer screening of the results was not time consuming. For each of the investigated reviews, studies were ordered for full screening; in six cases, studies retrieved from the supplementary PubMed searches were included in the final systematic review. Conclusion Supplementary searching of PubMed for studies unavailable elsewhere is worthwhile and improves the currency of the systematic reviews. PMID:27822154
Randomized SUSAN edge detector
NASA Astrophysics Data System (ADS)
Qu, Zhi-Guo; Wang, Ping; Gao, Ying-Hui; Wang, Peng
2011-11-01
A speed up technique for the SUSAN edge detector based on random sampling is proposed. Instead of sliding the mask pixel by pixel on an image as the SUSAN edge detector does, the proposed scheme places the mask randomly on pixels to find edges in the image; we hereby name it randomized SUSAN edge detector (R-SUSAN). Specifically, the R-SUSAN edge detector adopts three approaches in the framework of random sampling to accelerate a SUSAN edge detector: procedure integration of response computation and nonmaxima suppression, reduction of unnecessary processing for obvious nonedge pixels, and early termination. Experimental results demonstrate the effectiveness of the proposed method.
Random Packing and Random Covering Sequences.
1988-03-24
obtained by appeain~g to a result due to Marsaglia [39, and de Finetti [8]. Their result states that if (XI. X2 .. X,) is a random point on the simplex {X E...to sequeil~ coverage problems. J. App). Prob. 11. 281-293. [81 de Finetti . B. (1964). Alcune ossevazioni in tema de "suddivisione casuale." Giornale I
Genetic evolutionary taboo search for optimal marker placement in infrared patient setup.
Riboldi, M; Baroni, G; Spadea, M F; Tagaste, B; Garibaldi, C; Cambria, R; Orecchia, R; Pedotti, A
2007-10-07
In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths
NASA Astrophysics Data System (ADS)
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [http://www.cs.ubc.ca/~hoos/5/benchm.html]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Adaptive Image Denoising by Mixture Adaptation
NASA Astrophysics Data System (ADS)
Luo, Enming; Chan, Stanley H.; Nguyen, Truong Q.
2016-10-01
We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the Expectation-Maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad-hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper: First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. Experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.
Adaptive Image Denoising by Mixture Adaptation.
Luo, Enming; Chan, Stanley H; Nguyen, Truong Q
2016-10-01
We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the expectation-maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper. First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. The experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.
The orientation period: essential for new registered nurses' adaptation.
Ashton, Kathleen S
2015-04-01
The purpose of this research study was to explore adaptation in new registered nurses using the Roy adaptation model as the guiding conceptual framework. This quantitative study employed a random sampling of new nurses in the state of North Carolina. Personal attributes of the new registered nurses and characteristics of their work setting were modeled with four measures considered suitable proxies for adaptation. Being in a formal orientation period significantly supported the new nurses' overall adaptation. This may represent the benefit of social support, including education, which seems to facilitate adaptation.
Children's Search Engines from an Information Search Process Perspective.
ERIC Educational Resources Information Center
Broch, Elana
2000-01-01
Describes cognitive and affective characteristics of children and teenagers that may affect their Web searching behavior. Reviews literature on children's searching in online public access catalogs (OPACs) and using digital libraries. Profiles two Web search engines. Discusses some of the difficulties children have searching the Web, in the…
ERIC Educational Resources Information Center
Simms, Leonard J.; Clark, Lee Anna
2005-01-01
This is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With…
Enhancing Student Motivation and Learning within Adaptive Tutors
ERIC Educational Resources Information Center
Ostrow, Korinn S.
2015-01-01
My research is rooted in improving K-12 educational practice using motivational facets made possible through adaptive tutoring systems. In an attempt to isolate best practices within the science of learning, I conduct randomized controlled trials within ASSISTments, an online adaptive tutoring system that provides assistance and assessment to…
Distinct perceptual rhythms for feature and conjunction searches
Dugué, Laura; Xue, Alice M.; Carrasco, Marisa
2017-01-01
Feature and conjunction searches are widely used to study attentional deployment. However, the spatiotemporal behavior of attention integration in these tasks remains under debate. Are multiple search stimuli processed in parallel or sequentially? Does sampling of visual information and attentional deployment differ between these two types of search? If so, how? We used an innovative methodology to estimate the distribution of attention on a single-trial basis for feature and conjunction searches. Observers performed feature- and conjunction-search tasks. They had to detect and discriminate a tilted low-spatial-frequency grating among three low-spatial-frequency vertical gratings (feature search) or low-spatial-frequency vertical gratings and high-spatial-frequency tilted gratings (conjunction search). After a variable delay, two probes were flashed at random locations. Performance in reporting the probes was used to infer attentional deployment to those locations. By solving a second-degree equation, we determined the probability of probe report at the most (P1) and least (P2) attended locations on a given trial. Were P1 and P2 equal, we would conclude that attention had been uniformly distributed across all four locations. Otherwise, we would conclude that visual information sampling and attentional deployment had been nonuniformly distributed. Our results show that processing was nonuniformly distributed across the four locations in both searches, and was modulated periodically over time at ∼5 Hz for the conjunction search and ∼12 Hz for the feature search. We argue that the former corresponds to the periodicity of attentional deployment during the search, whereas the latter corresponds to ongoing sampling of visual information. Because different locations were not simultaneously processed, this study rules out a strict parallel model for both search types. PMID:28362897
Searching CA Condensates, On-Line and Batch.
ERIC Educational Resources Information Center
Kaminecki, Ronald M.; And Others
Batch mode processing is compared, using cost-effectiveness, with on-line processing for computer-aided searching of chemical abstracts. Consideration for time, need, coverage, and adaptability are found to be the criteria by which a searcher selects a method, and sometimes both methods are used. There is a tradeoff between batch mode's slower…
Software Searches for Better Spacecraft-Navigation Models
NASA Technical Reports Server (NTRS)
Ely, Todd; Crossley, William
2003-01-01
ADAPT is a computer program that searches for better mathematical models for spacecraft navigation. The task of tuning trajectory-determination models for interplanetary navigation is complex, requiring an intensive search of multiple dynamical and nondynamical models that yield trajectory solutions with minimal errors. By automating the search, ADAPT eases the task of human analysts and enables them to consider wider ranges of potential solutions. ADAPT uses genetic algorithms to search a range of relevant parameters in a user-selected design space to arrive at values for those parameters that best fit the measured spacecraft-tracking data. The user s guide for ADAPT reviews the theoretical basis of the program and presents two example applications. One example is that of selecting a solar-radiation model for the Mars Pathfinder (MPF) mission using MPF tracking data and an extended Kalman filter from prior spacecraft-navigation software. The second example is of the use of tracking data from the Stardust spacecraft mission combined with a pseudo-epoch-state batch filter and an empirical small-forces model to find improved impulse models for use during Stardust attitude adjustments.
Search by Fuzzy Inference in a Children's Dictionary
ERIC Educational Resources Information Center
St-Jacques, Claude; Barriere, Caroline
2005-01-01
This research aims at promoting the usage of an online children's dictionary within a context of reading comprehension and vocabulary acquisition. Inspired by document retrieval approaches developed in the area of information retrieval (IR) research, we adapt a particular IR strategy, based on fuzzy logic, to a search in the electronic dictionary.…
Searching for Sustainability in an Encroaching and Transforming Environment
2004-08-23
number. 1. REPORT DATE 01 AUG 2004 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Searching for Sustainability in an...adaptation 8-23-04 OASA (I&E) 40Sustain the Mission — Secure the Future Sustainability Strategies • Dematerialization –Use less (reduce consumption) –Waste
Quantum random number generator
Pooser, Raphael C.
2016-05-10
A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.
Randomness: Quantum versus classical
NASA Astrophysics Data System (ADS)
Khrennikov, Andrei
2016-05-01
Recent tremendous development of quantum information theory has led to a number of quantum technological projects, e.g. quantum random generators. This development had stimulated a new wave of interest in quantum foundations. One of the most intriguing problems of quantum foundations is the elaboration of a consistent and commonly accepted interpretation of a quantum state. Closely related problem is the clarification of the notion of quantum randomness and its interrelation with classical randomness. In this short review, we shall discuss basics of classical theory of randomness (which by itself is very complex and characterized by diversity of approaches) and compare it with irreducible quantum randomness. We also discuss briefly “digital philosophy”, its role in physics (classical and quantum) and its coupling to the information interpretation of quantum mechanics (QM).
Zivkovic, L.
2011-07-01
In this article results from supersymmetry searches at D0 and CDF are reported. Searches for third generation squarks, searches for gauginos, and searches for models with R-parity violation are described. As no signs of supersymmetry for these models are observed, the most stringent limits to date are presented.
Product Searching with Shopping Bots.
ERIC Educational Resources Information Center
Rowley, Jennifer
2000-01-01
Using trial searches for three best-selling books, this study examined the search facilities offered by shopping bots, which support consumers with the product search and identification stage in e-shopping. Findings indicate that effectiveness of bots not only depends upon search facilities but also upon product coverage, and other added value…
Wang, Dayong; Otto, Charles; Jain, Anil K
2016-06-20
rsons of interest among the billions of shared photos on these websites. Despite significant progress in face recognition, searching a large collection of unconstrained face images remains a difficult problem. To address this challenge, we propose a face search system which combines a fast search procedure, coupled with a state-of-the-art commercial off the shelf (COTS) matcher, in a cascaded framework. Given a probe face, we first filter the large gallery of photos to find the top-k most similar faces using features learned by a convolutional neural network. The k retrieved candidates are re-ranked by combining similarities based on deep features and those output by the COTS matcher. We evaluate the proposed face search system on a gallery containing 80 million web-downloaded face images. Experimental results demonstrate that while the deep features perform worse than the COTS matcher on a mugshot dataset (93.7% vs. 98.6% TAR@FAR of 0.01%), fusing the deep features with the COTS matcher improves the overall performance (99.5% TAR@FAR of 0.01%). This shows that the learned deep features provide complementary information over representations used in state-of-the-art face matchers. On the unconstrained face image benchmarks, the performance of the learned deep features is competitive with reported accuracies. LFW database: 98.20% accuracy under the standard protocol and 88.03% TAR@FAR of 0.1% under the BLUFR protocol; IJB-A benchmark: 51.0% TAR@FAR of 0.1% (verification), rank 1 retrieval of 82.2% (closed-set search), 61.5% FNIR@FAR of 1% (open-set search). The proposed face search system offers an excellent trade-off between accuracy and scalability on galleries with millions of images. Additionally, in a face search experiment involving photos of the Tsarnaev brothers, convicted of the Boston Marathon bombing, the proposed cascade face search system could find the younger brother's (Dzhokhar Tsarnaev) photo at rank 1 in 1 second on a 5M gallery and at rank 8 in 7
Autonomous Byte Stream Randomizer
NASA Technical Reports Server (NTRS)
Paloulian, George K.; Woo, Simon S.; Chow, Edward T.
2013-01-01
Net-centric networking environments are often faced with limited resources and must utilize bandwidth as efficiently as possible. In networking environments that span wide areas, the data transmission has to be efficient without any redundant or exuberant metadata. The Autonomous Byte Stream Randomizer software provides an extra level of security on top of existing data encryption methods. Randomizing the data s byte stream adds an extra layer to existing data protection methods, thus making it harder for an attacker to decrypt protected data. Based on a generated crypto-graphically secure random seed, a random sequence of numbers is used to intelligently and efficiently swap the organization of bytes in data using the unbiased and memory-efficient in-place Fisher-Yates shuffle method. Swapping bytes and reorganizing the crucial structure of the byte data renders the data file unreadable and leaves the data in a deconstructed state. This deconstruction adds an extra level of security requiring the byte stream to be reconstructed with the random seed in order to be readable. Once the data byte stream has been randomized, the software enables the data to be distributed to N nodes in an environment. Each piece of the data in randomized and distributed form is a separate entity unreadable on its own right, but when combined with all N pieces, is able to be reconstructed back to one. Reconstruction requires possession of the key used for randomizing the bytes, leading to the generation of the same cryptographically secure random sequence of numbers used to randomize the data. This software is a cornerstone capability possessing the ability to generate the same cryptographically secure sequence on different machines and time intervals, thus allowing this software to be used more heavily in net-centric environments where data transfer bandwidth is limited.
Contrast adaptation in the Limulus lateral eye
Valtcheva, Tchoudomira M.
2015-01-01
Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether this mechanism operates in horseshoe crab eyes, one of the best-understood neural networks in the animal kingdom. The spike trains of optic nerve fibers were recorded in response to light stimuli modulated randomly in time and delivered to single ommatidia or the whole eye. We found that the retina adapts to both the mean luminance and contrast of a white-noise stimulus, that luminance- and contrast-adaptive processes are largely independent, and that they originate within an ommatidium. Network interactions are not involved. A published computer model that simulates existing knowledge of the horseshoe crab eye did not show contrast adaptation, suggesting that a heretofore unknown mechanism may underlie the phenomenon. This mechanism does not appear to reside in photoreceptors because white-noise analysis of electroretinogram recordings did not show contrast adaptation. The likely site of origin is therefore the spike discharge mechanism of optic nerve fibers. The finding of contrast adaption in a retinal network as simple as the horseshoe crab eye underscores the broader importance of this image processing strategy to vision. PMID:26445869
Salient Distractors Can Induce Saccade Adaptation
Khan, Afsheen; McFadden, Sally A.; Wallman, Josh
2014-01-01
When saccadic eye movements consistently fail to land on their intended target, saccade accuracy is maintained by gradually adapting the movement size of successive saccades. The proposed error signal for saccade adaptation has been based on the distance between where the eye lands and the visual target (retinal error). We studied whether the error signal could alternatively be based on the distance between the predicted and actual locus of attention after the saccade. Unlike conventional adaptation experiments that surreptitiously displace the target once a saccade is initiated towards it, we instead attempted to draw attention away from the target by briefly presenting salient distractor images on one side of the target after the saccade. To test whether less salient, more predictable distractors would induce less adaptation, we separately used fixed random noise distractors. We found that both visual attention distractors were able to induce a small degree of downward saccade adaptation but significantly more to the more salient distractors. As in conventional adaptation experiments, upward adaptation was less effective and salient distractors did not significantly increase amplitudes. We conclude that the locus of attention after the saccade can act as an error signal for saccade adaptation. PMID:24876947
Cross-correlation search for periodic gravitational waves
Dhurandhar, Sanjeev; Mukhopadhyay, Himan; Krishnan, Badri; Whelan, John T.
2008-04-15
In this paper we study the use of cross correlations between multiple gravitational wave (GW) data streams for detecting long-lived periodic signals. Cross-correlation searches between data from multiple detectors have traditionally been used to search for stochastic GW signals, but recently they have also been used in directed searches for periodic GWs. Here we further adapt the cross-correlation statistic for periodic GW searches by taking into account both the nonstationarity and the long-term-phase coherence of the signal. We study the statistical properties and sensitivity of this search and its relation to existing periodic wave searches, and describe the precise way in which the cross-correlation statistic interpolates between semicoherent and fully coherent methods. Depending on the maximum duration over which we wish to preserve phase coherence, the cross-correlation statistic can be tuned to go from a standard cross-correlation statistic using data from distinct detectors, to the semicoherent time-frequency methods with increasing coherent time baselines, and all the way to a full coherent search. This leads to a unified framework for studying periodic wave searches and can be used to make informed trade-offs between computational cost, sensitivity, and robustness against signal uncertainties.
Habituation of visual adaptation
Dong, Xue; Gao, Yi; Lv, Lili; Bao, Min
2016-01-01
Our sensory system adjusts its function driven by both shorter-term (e.g. adaptation) and longer-term (e.g. learning) experiences. Most past adaptation literature focuses on short-term adaptation. Only recently researchers have begun to investigate how adaptation changes over a span of days. This question is important, since in real life many environmental changes stretch over multiple days or longer. However, the answer to the question remains largely unclear. Here we addressed this issue by tracking perceptual bias (also known as aftereffect) induced by motion or contrast adaptation across multiple daily adaptation sessions. Aftereffects were measured every day after adaptation, which corresponded to the degree of adaptation on each day. For passively viewed adapters, repeated adaptation attenuated aftereffects. Once adapters were presented with an attentional task, aftereffects could either reduce for easy tasks, or initially show an increase followed by a later decrease for demanding tasks. Quantitative analysis of the decay rates in contrast adaptation showed that repeated exposure of the adapter appeared to be equivalent to adaptation to a weaker stimulus. These results suggest that both attention and a non-attentional habituation-like mechanism jointly determine how adaptation develops across multiple daily sessions. PMID:26739917
Forward estimation for game-tree search
Zhang, Weixiong
1996-12-31
It is known that bounds on the minimax values of nodes in a game tree can be used to reduce the computational complexity of minimax search for two-player games. We describe a very simple method to estimate bounds on the minimax values of interior nodes of a game tree, and use the bounds to improve minimax search. The new algorithm, called forward estimation, does not require additional domain knowledge other than a static node evaluation function, and has small constant overhead per node expansion. We also propose a variation of forward estimation, which provides a tradeoff between computational complexity and decision quality. Our experimental results show that forward estimation outperforms alpha-beta pruning on random game trees and the game of Othello.
Weems, Carl F.
2014-01-01
more positive and adaptive memories. In addition, the results suggest that future research could focus on the longer-term benefits of DCS on attention and ways to capitalize on attention-enhancing therapies. ClinicalTrials.gov registry: Effect of D-cycloserine on Treatment of Posttraumatic Stress Disorder (PTSD) in Youth, #NCT01157416, http://clinicaltrials.gov/ct2/results?term=NCT01157416&Search=Search, and D-cycloserine Adjunctive Treatment for Posttraumatic Stress Disorder (PTSD) in Adolescents, #NCT01157429, http://clinicaltrials.gov/ct2/results?term=NCT01157429&Search=Search. PMID:24506079
Optimal fractional order PID design via Tabu Search based algorithm.
Ateş, Abdullah; Yeroglu, Celaleddin
2016-01-01
This paper presents an optimization method based on the Tabu Search Algorithm (TSA) to design a Fractional-Order Proportional-Integral-Derivative (FOPID) controller. All parameter computations of the FOPID employ random initial conditions, using the proposed optimization method. Illustrative examples demonstrate the performance of the proposed FOPID controller design method.
Riggs, Thomas; Walts, Adrienne; Perry, Nicolas; Bickle, Laura; Lynch, Jennifer N.; Myers, Amy; Flynn, Joanne; Linderman, Jennifer J.; Miller, Mark J.; Kirschner, Denise E.
2008-01-01
Generating adaptive immunity after infection or immunization requires physical interactions within a lymph node (LN) T-zone between antigen-bearing dendritic cells (DCs) that arrive from peripheral tissues and rare cognate T cells entering via high endothelial venules (HEVs). This interaction results in activation of cognate T cells, expansion of that T cell lineage and their exit from the LN T zone via efferent lymphatics (ELs). How antigen-specific T cells locate DCs within this complex environment is controversial, and both random T cell migration and chemotaxis have been proposed. We developed an agent-based computational model of a LN that captures many features of T cell and DC dynamics observed by two-photon microscopy. Our simulations matched in vivo two-photon microscopy data regarding T cell speed, short-term directional persistence of motion and cell motility. We also obtained in vivo data regarding density of T cells and DCs within a LN and matched our model environment to measurements of the distance from HEVs to ELs. We used our model to compare chemotaxis with random motion and showed that chemotaxis increased total number of T cell DC contacts, but decreased unique contacts, producing fewer activated T cells. Our results suggest that, within a LN T-zone, a random search strategy is optimal for a rare cognate T cell to find its DC match and maximize production of activated T cells. PMID:18068193
Search for Gluonic Excitations
Eugenio, Paul
2007-10-26
Studies of meson spectra via strong decays provide insight regarding QCD at the confinement scale. These studies have led to phenomenological models for QCD such as the constituent quark model. However, QCD allows for a much richer spectrum of meson states which include extra states such as exotics, hybrids, multi-quarks, and glueballs. First discussion of the status of exotic meson searches is given followed by a discussion of plans at Jefferson Lab to double the energy of the machine to 12 GeV, which will allow us to access photoproduction of mesons in search for gluonic excited states.
Search for Gluonic Excitations
Paul Eugenio
2007-10-01
Studies of meson spectra via strong decays provide insight regarding QCD at the confinement scale. These studies have led to phenomenological models for QCD such as the constituent quark model. However, QCD allows for a much richer spectrum of meson states which include extra states such as exotics, hybrids, multi-quarks, and glueballs. First discussion of the status of exotic meson searches is given followed by a discussion of plans at Jefferson Lab to double the energy of the machine to 12 GeV, which will allow us to access photoproduction of mesons in search for gluonic excited states.
NASA Astrophysics Data System (ADS)
Yager, Robert E.
Visits to six school districts which were identified by the National Science Teachers Association's Search for Excellence program were made during 1983 by teams of 17 researchers. The reports were analyzed in search for common characteristics that can explain the requirements necessary for excellent science programs. The results indicate that creative ideas, administrative and community involvement, local ownership and pride, and well-developed in-service programs and implementation strategies are vital. Exceptional teachers with boundless energies also seem to exist where exemplary science programs are found.
Elser, V.; Rankenburg, I.; Thibault, P.
2007-01-01
In many problems that require extensive searching, the solution can be described as satisfying two competing constraints, where satisfying each independently does not pose a challenge. As an alternative to tree-based and stochastic searching, for these problems we propose using an iterated map built from the projections to the two constraint sets. Algorithms of this kind have been the method of choice in a large variety of signal-processing applications; we show here that the scope of these algorithms is surprisingly broad, with applications as diverse as protein folding and Sudoku. PMID:17202267
Toki, W.
1997-06-01
In these Summer School lectures, the author reviews the results of recent glueball searches. He begins with a brief review of glueball phenomenology and meson spectroscopy, including a discussion of resonance behavior. The results on the f{sub o}(1500) and f{sub J}(1700) resonances from proton-antiproton experiments and radiative J/{Psi} decays are discussed. Finally, {pi}{pi} and {eta}{pi} studies from D{sub s} decays and exotic meson searches are reviewed. 46 refs., 40 figs.
Critically damped quantum search.
Mizel, Ari
2009-04-17
Although measurement and unitary processes can accomplish any quantum evolution in principle, thinking in terms of dissipation and damping can be powerful. We propose a modification of Grover's algorithm in which the idea of damping plays a natural role. Remarkably, we find that there is a critical damping value that divides between the quantum O(sqrt[N]) and classical O(N) search regimes. In addition, by allowing the damping to vary in a fashion we describe, one obtains a fixed-point quantum search algorithm in which ignorance of the number of targets increases the number of oracle queries only by a factor of 1.5.
An adaptive contextual quantum language model
NASA Astrophysics Data System (ADS)
Li, Jingfei; Zhang, Peng; Song, Dawei; Hou, Yuexian
2016-08-01
User interactions in search system represent a rich source of implicit knowledge about the user's cognitive state and information need that continuously evolves over time. Despite massive efforts that have been made to exploiting and incorporating this implicit knowledge in information retrieval, it is still a challenge to effectively capture the term dependencies and the user's dynamic information need (reflected by query modifications) in the context of user interaction. To tackle these issues, motivated by the recent Quantum Language Model (QLM), we develop a QLM based retrieval model for session search, which naturally incorporates the complex term dependencies occurring in user's historical queries and clicked documents with density matrices. In order to capture the dynamic information within users' search session, we propose a density matrix transformation framework and further develop an adaptive QLM ranking model. Extensive comparative experiments show the effectiveness of our session quantum language models.
Navigation by anomalous random walks on complex networks
Weng, Tongfeng; Zhang, Jie; Khajehnejad, Moein; Small, Michael; Zheng, Rui; Hui, Pan
2016-01-01
Anomalous random walks having long-range jumps are a critical branch of dynamical processes on networks, which can model a number of search and transport processes. However, traditional measurements based on mean first passage time are not useful as they fail to characterize the cost associated with each jump. Here we introduce a new concept of mean first traverse distance (MFTD) to characterize anomalous random walks that represents the expected traverse distance taken by walkers searching from source node to target node, and we provide a procedure for calculating the MFTD between two nodes. We use Lévy walks on networks as an example, and demonstrate that the proposed approach can unravel the interplay between diffusion dynamics of Lévy walks and the underlying network structure. Moreover, applying our framework to the famous PageRank search, we show how to inform the optimality of the PageRank search. The framework for analyzing anomalous random walks on complex networks offers a useful new paradigm to understand the dynamics of anomalous diffusion processes, and provides a unified scheme to characterize search and transport processes on networks. PMID:27876855
Navigation by anomalous random walks on complex networks
NASA Astrophysics Data System (ADS)
Weng, Tongfeng; Zhang, Jie; Khajehnejad, Moein; Small, Michael; Zheng, Rui; Hui, Pan
2016-11-01
Anomalous random walks having long-range jumps are a critical branch of dynamical processes on networks, which can model a number of search and transport processes. However, traditional measurements based on mean first passage time are not useful as they fail to characterize the cost associated with each jump. Here we introduce a new concept of mean first traverse distance (MFTD) to characterize anomalous random walks that represents the expected traverse distance taken by walkers searching from source node to target node, and we provide a procedure for calculating the MFTD between two nodes. We use Lévy walks on networks as an example, and demonstrate that the proposed approach can unravel the interplay between diffusion dynamics of Lévy walks and the underlying network structure. Moreover, applying our framework to the famous PageRank search, we show how to inform the optimality of the PageRank search. The framework for analyzing anomalous random walks on complex networks offers a useful new paradigm to understand the dynamics of anomalous diffusion processes, and provides a unified scheme to characterize search and transport processes on networks.
NASA Astrophysics Data System (ADS)
Shivakiran Bhaktha, B. N.; Bachelard, Nicolas; Noblin, Xavier; Sebbah, Patrick
2012-10-01
Random lasing is reported in a dye-circulated structured polymeric microfluidic channel. The role of disorder, which results from limited accuracy of photolithographic process, is demonstrated by the variation of the emission spectrum with local-pump position and by the extreme sensitivity to a local perturbation of the structure. Thresholds comparable to those of conventional microfluidic lasers are achieved, without the hurdle of state-of-the-art cavity fabrication. Potential applications of optofluidic random lasers for on-chip sensors are discussed. Introduction of random lasers in the field of optofluidics is a promising alternative to on-chip laser integration with light and fluidic functionalities.
Randomization Methods in Emergency Setting Trials: A Descriptive Review
ERIC Educational Resources Information Center
Corbett, Mark Stephen; Moe-Byrne, Thirimon; Oddie, Sam; McGuire, William
2016-01-01
Background: Quasi-randomization might expedite recruitment into trials in emergency care settings but may also introduce selection bias. Methods: We searched the Cochrane Library and other databases for systematic reviews of interventions in emergency medicine or urgent care settings. We assessed selection bias (baseline imbalances) in prognostic…
Recent advances in the dark adaptation investigations
Yang, Guo-Qing; Chen, Tao; Tao, Ye; Zhang, Zuo-Ming
2015-01-01
Dark adaptation is a highly sensitive neural function and may be the first symptom of many status including the physiologic and pathologic entity, suggesting that it could be instrumental for diagnose. However, shortcomings such as the lack of standardized parameters, the long duration of examination, and subjective randomness would substantially impede the use of dark adaptation in clinical work. In this review we summarize the recent research about the dark adaptation, including two visual cycles-canonical and cone-specific visual cycle, affecting factors and the methods for measuring dark adaptation. In the opinions of authors, intensive investigations are needed to be done for the widely use of this significant visual function in clinic. PMID:26682182
Technology and Teaching: Searching under Cups for Clues about Memory--An Online Demonstration
ERIC Educational Resources Information Center
Kahan, Todd A.; Mathis, Katherine M.
2007-01-01
An online demonstration, designed to enhance comprehension of Sternberg's (1966) short-term memory scanning task, involved rapidly searching under virtual cups for a ball. We randomly assigned students to 1 of 3 groups, all of whom read the same textbook description of Sternberg's work: A demonstration group used 3 search methods to look for balls…
What Do the Public Search for on the Catalogue of the State Library of Victoria?
ERIC Educational Resources Information Center
Waller, Vivienne
2009-01-01
This study examines what the public search for in the catalogue of the State Library of Victoria (SLV). As well as indicating the type of content being accessed, this gives an indication of what catalogue users expect of the State Library collection. A content analysis was undertaken of a random, stratified sample of 4,000 search queries typed in…
Central and Peripheral Vision Loss Differentially Affects Contextual Cueing in Visual Search
ERIC Educational Resources Information Center
Geringswald, Franziska; Pollmann, Stefan
2015-01-01
Visual search for targets in repeated displays is more efficient than search for the same targets in random distractor layouts. Previous work has shown that this contextual cueing is severely impaired under central vision loss. Here, we investigated whether central vision loss, simulated with gaze-contingent displays, prevents the incidental…
Adaptive multiconfigurational wave functions
Evangelista, Francesco A.
2014-03-28
A method is suggested to build simple multiconfigurational wave functions specified uniquely by an energy cutoff Λ. These are constructed from a model space containing determinants with energy relative to that of the most stable determinant no greater than Λ. The resulting Λ-CI wave function is adaptive, being able to represent both single-reference and multireference electronic states. We also consider a more compact wave function parameterization (Λ+SD-CI), which is based on a small Λ-CI reference and adds a selection of all the singly and doubly excited determinants generated from it. We report two heuristic algorithms to build Λ-CI wave functions. The first is based on an approximate prescreening of the full configuration interaction space, while the second performs a breadth-first search coupled with pruning. The Λ-CI and Λ+SD-CI approaches are used to compute the dissociation curve of N{sub 2} and the potential energy curves for the first three singlet states of C{sub 2}. Special attention is paid to the issue of energy discontinuities caused by changes in the size of the Λ-CI wave function along the potential energy curve. This problem is shown to be solvable by smoothing the matrix elements of the Hamiltonian. Our last example, involving the Cu{sub 2}O{sub 2}{sup 2+} core, illustrates an alternative use of the Λ-CI method: as a tool to both estimate the multireference character of a wave function and to create a compact model space to be used in subsequent high-level multireference coupled cluster computations.
Benefits and Harms of Sick Leave: Lack of Randomized, Controlled Trials
ERIC Educational Resources Information Center
Axelsson, Inge; Marnetoft, Sven-Uno
2010-01-01
The aim of this study was to try to identify those randomized controlled trials that compare sick leave with no sick leave or a different duration or degree of sick leave. A comprehensive, systematic, electronic search of Clinical Evidence, the Cochrane Library and PubMed, and a manual search of the Campbell Library and a journal supplement was…
Expressing Adaptation Strategies Using Adaptation Patterns
ERIC Educational Resources Information Center
Zemirline, N.; Bourda, Y.; Reynaud, C.
2012-01-01
Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition…
A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing
NASA Technical Reports Server (NTRS)
Takaki, Mitsuo; Cavalcanti, Diego; Gheyi, Rohit; Iyoda, Juliano; dAmorim, Marcelo; Prudencio, Ricardo
2009-01-01
The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compare the effectiveness of a symbolic solver (CVC3), a random solver, three hybrid solvers (i.e., mix of random and symbolic), and two heuristic search solvers. We evaluate the solvers on two benchmarks: one consisting of manually generated constraints and another generated with a concolic execution of 8 subjects. In addition to fully decidable constraints, the benchmarks include constraints with non-linear integer arithmetic, integer modulo and division, bitwise arithmetic, and floating-point arithmetic. As expected symbolic solving (in particular, CVC3) subsumes the other solvers for the concolic execution of subjects that only generate decidable constraints. For the remaining subjects the solvers are complementary.
Fenimore, E.E.
1980-08-22
A hexagonally shaped quasi-random no-two-holes touching grid collimator. The quasi-random array grid collimator eliminates contamination from small angle off-axis rays by using a no-two-holes-touching pattern which simultaneously provides for a self-supporting array increasng throughput by elimination of a substrate. The presentation invention also provides maximum throughput using hexagonally shaped holes in a hexagonal lattice pattern for diffraction limited applications. Mosaicking is also disclosed for reducing fabrication effort.
Roemmich, Ryan T; Hack, Nawaz; Akbar, Umer; Hass, Chris J
2014-07-15
Persons with Parkinson's disease (PD) are characterized by multifactorial gait deficits, though the factors which influence the abilities of persons with PD to adapt and store new gait patterns are unclear. The purpose of this study was to investigate the effects of dopaminergic therapy on the abilities of persons with PD to adapt and store gait parameters during split-belt treadmill (SBT) walking. Ten participants with idiopathic PD who were being treated with stable doses of orally-administered dopaminergic therapy participated. All participants performed two randomized testing sessions on separate days: once while optimally-medicated (ON meds) and once after 12-h withdrawal from dopaminergic medication (OFF meds). During each session, locomotor adaptation was investigated as the participants walked on a SBT for 10 min while the belts moved at a 2:1 speed ratio. We assessed locomotor adaptive learning by quantifying: (1) aftereffects during de-adaptation (once the belts returned to tied speeds immediately following SBT walking) and (2) savings during re-adaptation (as the participants repeated the same SBT walking task after washout of aftereffects following the initial SBT task). The withholding of dopaminergic medication diminished step length aftereffects significantly during de-adaptation. However, both locomotor adaptation and savings were unaffected by levodopa. These findings suggest that dopaminergic pathways influence aftereffect storage but do not influence locomotor adaptation or savings within a single session of SBT walking. It appears important that persons with PD should be optimally-medicated if walking on the SBT as gait rehabilitation.
NASA Astrophysics Data System (ADS)
Baudis, Laura
2006-01-01
More than 90% of matter in the Universe could be composed of heavy particles, which were non-relativistic, or 'cold', when they froze-out from the primordial soup. I will review current searches for these hypothetical particles, both via interactions with nuclei in deep underground detectors, and via the observation of their annihilation products in the Sun, galactic halo and galactic center.
NASA Astrophysics Data System (ADS)
Baudis, Laura
More than 90% of matter in the Universe could be composed of heavy particles, which were non-relativistic, or 'cold', when they froze-out from the primordial soup. I will review current searches for these hypothetical particles, both via interactions with nuclei in deep underground detectors, and via the observation of their annihilation products in the Sun, galactic halo and galactic center.
Evaluation of Online Searches.
ERIC Educational Resources Information Center
Blood, Richard W.
Based on an analysis of online search evaluation forms collected from all types of U.S. libraries, and a pilot test of a draft evaluation form in selected federal research libraries, this report presents the work of the American Library Association's (ALA's) Machine-Assisted Reference Section (MARS) Committee on Measurement and Evaluation. The…
1946-10-23
It is frequently desired to find the best search plan to detect a given target, in the sense of that plan of a given total track length which gives...the maximum probability of detection. It is usually impossible to find an analytic solution to this problem. The usual method of attack is to construct
The Pulsar Search Collaboratory
ERIC Educational Resources Information Center
Rosen, R.; Heatherly, S.; McLaughlin, M. A.; Kondratiev, V. I.; Boyles, J. R.; Wilson, M.; Lorimer, D. R.; Lynch, R.; Ransom, S.
2010-01-01
The Pulsar Search Collaboratory (PSC) (NSF #0737641) is a joint project between the National Radio Astronomy Observatory and West Virginia University designed to interest high school students in science, technology, engineering, and mathematics related career paths by helping them to conduct authentic scientific research. The 3 year PSC program,…
ERIC Educational Resources Information Center
Lager, Mark A.
This paper focuses on techniques for retrieval used in information sciences and in World Wide Web search engines. The purpose of reference service and information science is to provide useful information in response to a query. The two metrics of recall and precision serve to express information retrieval performance. There are two major…
The Search Consultant's Obligations.
ERIC Educational Resources Information Center
Underwood, Kenneth
1994-01-01
The superintendent search consultant is employed by the board of education and must always act in the board's best interest. Boards want consultants to be friendly and courteous, provide information, and foster an aura of good feeling with candidates and the board. Candidates should receive accurate information, selection criteria briefings,…
Next Generation Search Interfaces
NASA Astrophysics Data System (ADS)
Roby, W.; Wu, X.; Ly, L.; Goldina, T.
2015-09-01
Astronomers are constantly looking for easier ways to access multiple data sets. While much effort is spent on VO, little thought is given to the types of User Interfaces we need to effectively search this sort of data. For instance, an astronomer might need to search Spitzer, WISE, and 2MASS catalogs and images then see the results presented together in one UI. Moving seamlessly between data sets is key to presenting integrated results. Results need to be viewed using first class, web based, integrated FITS viewers, XY Plots, and advanced table display tools. These components should be able to handle very large datasets. To make a powerful Web based UI that can manage and present multiple searches to the user requires taking advantage of many HTML5 features. AJAX is used to start searches and present results. Push notifications (Server Sent Events) monitor background jobs. Canvas is required for advanced result displays. Lesser known CSS3 technologies makes it all flow seamlessly together. At IPAC, we have been developing our Firefly toolkit for several years. We are now using it to solve this multiple data set, multiple queries, and integrated presentation problem to create a powerful research experience. Firefly was created in IRSA, the NASA/IPAC Infrared Science Archive (http://irsa.ipac.caltech.edu). Firefly is the core for applications serving many project archives, including Spitzer, Planck, WISE, PTF, LSST and others. It is also used in IRSA's new Finder Chart and catalog and image displays.
ERIC Educational Resources Information Center
Hill, Paul; MacArthur, Stacey; Read, Nick
2014-01-01
Effective Internet search skills are essential with the continually increasing amount of information available on the Web. Extension personnel are required to find information to answer client questions and to conduct research on programs. Unfortunately, many lack the skills necessary to effectively navigate the Internet and locate needed…
Searches Conducted for Engineers.
ERIC Educational Resources Information Center
Lorenz, Patricia
This paper reports an industrial information specialist's experience in performing online searches for engineers and surveys the databases used. Engineers seeking assistance fall into three categories: (1) those who recognize the value of online retrieval; (2) referrals by colleagues; and (3) those who do not seek help. As more successful searches…
NASA Astrophysics Data System (ADS)
Tuts, P. M.; Franzini, P.; Youssef, S.; Zhao, T.; Kaarsberg, T. M.; Lee-Franzini, J.; Lovelock, D. M. J.; Narain, M.; Sontz, S.; Schamberger, R. D.; Willins, J.; Yanagisawa, C.
1987-03-01
A study of radiative decays from 400 000 ϒ (9460)'s in the partially upgraded CUSB detector is presented. We find evidence against the existence of gluinos of mass 0 6(GeV/c2)
W. Orejudos
2002-10-25
Results of searches performed by CDF and D0 are presented. Most of the results are based on data taken during the 1994-95 data taking period (Run I), but some preliminary results from the current data taking period (Run II) are included.
ERIC Educational Resources Information Center
Fattal, Laura Felleman
2004-01-01
Practical and academic, the interrelationship of the visual and performing arts opens unique frontiers to aesthetic pioneers. Divergent in aim from the historic search for similar tonalities between the Synchronists and Stravinsky or atonal musicians of the 1950s-70s and minimalist painters and sculptors, the present use of the visual arts as a…
1975-03-01
57-65. 10. Kadane, Joseph B., (1968). "Discrete Search and the Neyman-Pearson Lemma", Journal of Mathematical Analysis and Applications 22, 156- 171...11. Kadane, Joseph B., (1969). "Quiz Sitow Problems", Journal of Mathematical Analysis and Applications 27, 609-623. 12. Kadane, Joseph B., (1971
Mikesell, Charles R.
1978-01-01
A device is provided for reducing internal reflections from the tire of an ultrasonic search wheel probe or from within the material being examined. The device includes a liner with an anechoic chamber within which is an ultrasonic transducer. The liner is positioned within the wheel and includes an aperture through which the ultrasonic sound from the transducer is directed.
NASA Astrophysics Data System (ADS)
Holt, P. J.; Poblocki, M.
2017-01-01
We provide a design for a low cost orientable search coil that can be used to investigate the variation of magnetic flux with angle. This experiment is one of the required practical activities in the current A level physics specification for the AQA examination board in the UK. We demonstrate its performance and suggest other suitable investigations that can be undertaken.
Careers Booklet. Project SEARCH.
ERIC Educational Resources Information Center
Heart of the Earth Survival School, Minneapolis, MN.
Developed by the staff of Project SEARCH, this booklet is designed to assist American Indian adults of the Minneapolis-St. Paul area in an exploration of careers. As noted by the introduction, it may also be of interest to Indian high school students, college students, and others who are looking for ideas about the kinds of careers available. The…
Contreras, M.; The CDF Collaboration
1991-10-01
We review top quark searches carried out at CDF with data collected during the 1988--1989 Collider Run. The latest analyses give a lower limit on the top quark mass of 91 GeV/c{sup 2} at the 95% confidence level, assuming Standard Model decays. 8 refs., 6 figs., 1 tab.
Norms of Random Submatrices and Sparse Approximation
2008-07-28
usual Hilbert space operator norm; the `1 to `2 operator norm ‖·‖1→2 computes the maximum `2 norm of a column; and ‖·‖max returns the maximum absolute...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining...the spectral norm of a random column submatrix. Its proof is analogous with that of Theorem 3.2 but relies on a sharp noncommutative Khintchine
Competitive Facility Location with Random Demands
NASA Astrophysics Data System (ADS)
Uno, Takeshi; Katagiri, Hideki; Kato, Kosuke
2009-10-01
This paper proposes a new location problem of competitive facilities, e.g. shops and stores, with uncertain demands in the plane. By representing the demands for facilities as random variables, the location problem is formulated to a stochastic programming problem, and for finding its solution, three deterministic programming problems: expectation maximizing problem, probability maximizing problem, and satisfying level maximizing problem are considered. After showing that one of their optimal solutions can be found by solving 0-1 programming problems, their solution method is proposed by improving the tabu search algorithm with strategic vibration. Efficiency of the solution method is shown by applying to numerical examples of the facility location problems.
Race, Self-Selection, and the Job Search Process1
Pager, Devah; Pedulla, David S.
2015-01-01
While existing research has documented persistent barriers facing African American job seekers, far less research has questioned how job seekers respond to this reality. Do minorities self-select into particular segments of the labor market to avoid discrimination? Such questions have remained unanswered due to the lack of data available on the positions to which job seekers apply. Drawing on two original datasets with application-specific information, we find little evidence that blacks target or avoid particular job types. Rather, blacks cast a wider net in their search than similarly situated whites, including a greater range of occupational categories and characteristics in their pool of job applications. Finally, we show that perceptions of discrimination are associated with increased search breadth, suggesting that broad search among African Americans represents an adaptation to labor market discrimination. Together these findings provide novel evidence on the role of race and self-selection in the job search process. PMID:26046224
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-22
... Employment and Training Administration Comment Request for Information Collection for ETA 9162, Random Audit... collection of data about Random Audit of Claimants in the Emergency Unemployment Compensation Program of 2008... is intended to provide data describing random audits of the work search provision of Public Law...
Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.
Notarnicola, Ippolito; Petrucci, Cristina; De Jesus Barbosa, Maria Rosimar; Giorgi, Fabio; Stievano, Alessandro; Rocco, Gennaro; Lancia, Loreto
2017-02-08
This study aimed to analyze the concept of "complex adaptive systems." The construct is still nebulous in the literature, and a further explanation of the idea is needed to have a shared knowledge of it. A concept analysis was conducted utilizing Rodgers evolutionary method. The inclusive years of bibliographic search started from 2005 to 2015. The search was conducted at PubMed©, CINAHL© 2017 John Wiley & Sons Australia, Ltd Nursing is a complex adaptive system, and the nursing profession in practice exhibits complex adaptive system characteristics. Complexity science through complex adaptive systems provides new ways of seeing and understanding the mechanisms that underpin the nursing profession.
Piehowski, Paul D.; Petyuk, Vladislav A.; Sandoval, John D.; Burnum, Kristin E.; Kiebel, Gary R.; Monroe, Matthew E.; Anderson, Gordon A.; Camp, David G.; Smith, Richard D.
2013-03-01
For bottom-up proteomics there are a wide variety of database searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection - referred to as STEPS - utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.
"Compressing liquid": an efficient global minima search strategy for clusters.
Zhou, R L; Zhao, L Y; Pan, B C
2009-07-21
In this paper we present a new global search strategy named as "compressing liquid" for atomic clusters. In this strategy, a random fragment of liquid structure is adopted as a starting geometry, followed by iterative operations of "compressing" and Monte Carlo adjustment of the atom positions plus structural optimization. It exhibits fair efficiency when it is applied to seeking the global minima of Lennard-Jones clusters. We also employed it to search the low-lying candidates of medium silicon clusters Si(n)(n=40-60), where the global search is absent. We found the best candidates for most sizes. More importantly, we obtained non-fullerene-based structures for some sized clusters, which were not found from the endohedral-fullerene strategy. These results indicate that the "compressing-liquid" method is highly efficient for global minima search of clusters.
Combining local search and backtracking techniques for constraint satisfaction
Zhang, Jian; Zhang, Hantao
1996-12-31
Backtracking techniques are well-known traditional methods for solving many constraint satisfaction problems (CSPs) including the satisfiability (SAT) problem in the propositional logic. In recent years, it has been reported that local search techniques are very effective in solving some large-scale instances of the SAT problem. In this research, we combine the backtracking and local search techniques into a single method for solving SAT and CSPs. When setting a parameter of the method to either of its two extreme values, we obtain the ordinary backtracking procedure or the local search procedure. For some problems, if the parameter takes values in the middle of the two extremes, the new method is much more effective than either backtracking or local search. We tested the method with classical problems like the n-Queens and random SAT instances, as well as some difficult problems from finite mathematics. In particular, using the new method, we solved four open problems in design theory.
Statistical patterns of visual search for hidden objects
Credidio, Heitor F.; Teixeira, Elisângela N.; Reis, Saulo D. S.; Moreira, André A.; Andrade Jr, José S.
2012-01-01
The movement of the eyes has been the subject of intensive research as a way to elucidate inner mechanisms of cognitive processes. A cognitive task that is rather frequent in our daily life is the visual search for hidden objects. Here we investigate through eye-tracking experiments the statistical properties associated with the search of target images embedded in a landscape of distractors. Specifically, our results show that the twofold process of eye movement, composed of sequences of fixations (small steps) intercalated by saccades (longer jumps), displays characteristic statistical signatures. While the saccadic jumps follow a log-normal distribution of distances, which is typical of multiplicative processes, the lengths of the smaller steps in the fixation trajectories are consistent with a power-law distribution. Moreover, the present analysis reveals a clear transition between a directional serial search to an isotropic random movement as the difficulty level of the searching task is increased. PMID:23226829
Towards Motivation-Based Adaptation of Difficulty in E-Learning Programs
ERIC Educational Resources Information Center
Endler, Anke; Rey, Gunter Daniel; Butz, Martin V.
2012-01-01
The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of…
Wright, Amanda J; Burns, David; Patterson, Brett A; Poland, Simon P; Valentine, Gareth J; Girkin, John M
2005-05-01
We report on the introduction of active optical elements into confocal and multiphoton microscopes in order to reduce the sample-induced aberration. Using a flexible membrane mirror as the active element, the beam entering the rear of the microscope objective is altered to produce the smallest point spread function once it is brought to a focus inside the sample. The conventional approach to adaptive optics, commonly used in astronomy, is to utilise a wavefront sensor to determine the required mirror shape. We have developed a technique that uses optimisation algorithms to improve the returned signal without the use of a wavefront sensor. We have investigated a number of possible optimisation methods, covering hill climbing, genetic algorithms, and more random search methods. The system has demonstrated a significant enhancement in the axial resolution of a confocal microscope when imaging at depth within a sample. We discuss the trade-offs of the various approaches adopted, comparing speed with resolution enhancement.
Randomly stopped sums: models and psychological applications
Smithson, Michael; Shou, Yiyun
2014-01-01
This paper describes an approach to modeling the sums of a continuous random variable over a number of measurement occasions when the number of occasions also is a random variable. A typical example is summing the amounts of time spent attending to pieces of information in an information search task leading to a decision to obtain the total time taken to decide. Although there is a large literature on randomly stopped sums in financial statistics, it is largely absent from psychology. The paper begins with the standard modeling approaches used in financial statistics, and then extends them in two ways. First, the randomly stopped sums are modeled as “life distributions” such as the gamma or log-normal distribution. A simulation study investigates Type I error rate accuracy and power for gamma and log-normal versions of this model. Second, a Bayesian hierarchical approach is used for constructing an appropriate general linear model of the sums. Model diagnostics are discussed, and three illustrations are presented from real datasets. PMID:25426090
A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.
Mao, Wei; Lan, Heng-You; Li, Hao-Ru
2016-01-01
As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions.
A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps
Mao, Wei; Li, Hao-ru
2016-01-01
As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426
... Tools Español You Are Here: Home → Search Tips URL of this page: https://medlineplus.gov/searchtips.html ... site by adding 'site:' and the domain or URL to your search words. For example, if you ...
Adaptive evolutionary artificial neural networks for pattern classification.
Oong, Tatt Hee; Isa, Nor Ashidi Mat
2011-11-01
This paper presents a new evolutionary approach called the hybrid evolutionary artificial neural network (HEANN) for simultaneously evolving an artificial neural networks (ANNs) topology and weights. Evolutionary algorithms (EAs) with strong global search capabilities are likely to provide the most promising region. However, they are less efficient in fine-tuning the search space locally. HEANN emphasizes the balancing of the global search and local search for the evolutionary process by adapting the mutation probability and the step size of the weight perturbation. This is distinguishable from most previous studies that incorporate EA to search for network topology and gradient learning for weight updating. Four benchmark functions were used to test the evolutionary framework of HEANN. In addition, HEANN was tested on seven classification benchmark problems from the UCI machine learning repository. Experimental results show the superior performance of HEANN in fine-tuning the network complexity within a small number of generations while preserving the generalization capability compared with other algorithms.