Pearl, J.
1983-01-01
This work is comprised of articles which are representative of current research on search and heuristics. The general theme is the quest for understanding the workings of heuristic knowledge; how it is acquired, stored and used by people, how it can be represented and utilized by machines and what makes one heuristic succeed where others fail. Topics covered include the following: search and reasoning in problem solving; theory formation by heuristic search; the nature of heuristics II: background and examples; Eurisko: a program that learns new heuristics and domain concepts; the nature of heuristics III: program design and results; searching for an optimal path in a tree with random costs; search rearrangement backtracking and polynomial average time; consistent-labeling problems and their algorithms: expected-complexities and theory-based heuristics; general branch and bound formulation for understanding and synthesizing and/or tree search procedures; a minimax algorithm better than alpha-beta. yes and no; and pathology on game trees revisited, and an alternative to minimaxing.
Heuristic method for searches on large data-sets organised using network models
NASA Astrophysics Data System (ADS)
Ruiz-Fernández, D.; Quintana-Pacheco, Y.
2016-05-01
Searches on large data-sets have become an important issue in recent years. An alternative, which has achieved good results, is the use of methods relying on data mining techniques, such as cluster-based retrieval. This paper proposes a heuristic search that is based on an organisational model that reflects similarity relationships among data elements. The search is guided by using quality estimators of model nodes, which are obtained by the progressive evaluation of the given target function for the elements associated with each node. The results of the experiments confirm the effectiveness of the proposed algorithm. High-quality solutions are obtained evaluating a relatively small percentage of elements in the data-sets.
Properties of heuristic search strategies
NASA Technical Reports Server (NTRS)
Vanderbrug, G. J.
1973-01-01
A directed graph is used to model the search space of a state space representation with single input operators, an AND/OR is used for problem reduction representations, and a theorem proving graph is used for state space representations with multiple input operators. These three graph models and heuristic strategies for searching them are surveyed. The completeness, admissibility, and optimality properties of search strategies which use the evaluation function f = (1 - omega)g = omega(h) are presented and interpreted using a representation of the search process in the plane. The use of multiple output operators to imply dependent successors, and thus obtain a formalism which includes all three types of representations, is discussed.
Ferland, J.; Fleurent, C.
1994-12-31
Using object-oriented design and the C++ programming language, generic operators are developed for tabu search and genetic algorithms. These operators are used for the graph coloring, maximum clique and satisfiability problems. The availability of all methods for each problem permits to consider hybrid schemes.
A Graph Search Heuristic for Shortest Distance Paths
Chow, E
2005-03-24
This paper presents a heuristic for guiding A* search for finding the shortest distance path between two vertices in a connected, undirected, and explicitly stored graph. The heuristic requires a small amount of data to be stored at each vertex. The heuristic has application to quickly detecting relationships between two vertices in a large information or knowledge network. We compare the performance of this heuristic with breadth-first search on graphs with various topological properties. The results show that one or more orders of magnitude improvement in the number of vertices expanded is possible for large graphs, including Poisson random graphs.
Automated discovery of local search heuristics for satisfiability testing.
Fukunaga, Alex S
2008-01-01
The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey. PMID:18386995
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1988-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
A heuristic method for reactive power planning
Mantovani, J.R.S.
1996-02-01
An approach for solving reactive power planning problems is presented, which is based on binary search techniques and the use of a special heuristic to obtain a discrete solution. Two versions were developed, one to run on conventional (sequential) computers and the other to run on a distributed memory (hypercube) machine. This latter parallel processing version employs an asynchronous programming model. Once the set of candidate bases has been defined, the program gives the location and size of the reactive sources needed (if any) in keeping with operating and security constraints.
A comparison of heuristic search algorithms for molecular docking.
Westhead, D R; Clark, D E; Murray, C W
1997-05-01
This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone. PMID:9263849
Symbolic Heuristic Search for Factored Markov Decision Processes
NASA Technical Reports Server (NTRS)
Morris, Robert (Technical Monitor); Feng, Zheng-Zhu; Hansen, Eric A.
2003-01-01
We describe a planning algorithm that integrates two approaches to solving Markov decision processes with large state spaces. State abstraction is used to avoid evaluating states individually. Forward search from a start state, guided by an admissible heuristic, is used to avoid evaluating all states. We combine these two approaches in a novel way that exploits symbolic model-checking techniques and demonstrates their usefulness for decision-theoretic planning.
Minimizing conflicts: A heuristic repair method for constraint-satisfaction and scheduling problems
NASA Technical Reports Server (NTRS)
Minton, Steve; Johnston, Mark; Philips, Andrew; Laird, Phil
1992-01-01
This paper describes a simple heuristic approach to solving large-scale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value-ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. We demonstrate empirically that on the n-queens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. We also describe a scheduling application where the approach has been used successfully. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be most effective.
A Library of Local Search Heuristics for the Vehicle Routing Problem
Groer, Christopher S; Golden, Bruce; Edward, Wasil
2010-01-01
The vehicle routing problem (VRP) is a difficult and well-studied combinatorial optimization problem. Real-world instances of the VRP can contain hundreds and even thousands of customer locations and can involve many complicating constraints, necessitating the use of heuristic methods. We present a software library of local search heuristics that allow one to quickly generate good solutions to VRP instances. The code has a logical, object-oriented design and uses efficient data structures to store and modify solutions. The core of the library is the implementation of seven local search operators that share a similar interface and are designed to be extended to handle additional options with minimal code change. The code is well-documented, is straightforward to compile, and is freely available for download at http://sites.google.com/site/vrphlibrary/ . The distribution of the code contains several applications that can be used to generate solutions to instances of the capacitated VRP.
Worst-case analysis of self-organizing sequential search heuristics
Bentley, J.L.; McGeoch, C.C.
1983-03-01
The performance of sequential search can be enhanced by the use of heuristics that move elements closer to the front of the list as they are found. Previous analyses have characterized the performance of such heuristics probabilitically. In this paper we show that the heuristics can also be analyzed in the worst-case sense, and that the relative merit of the heuristics under this analysis is different than in the probabilistic analyses. Simulations show that the relative merit of the heuristics on real data is closer to that of the new worst-case analyses rather than that of the previous probabilistic analyses.
Geometry optimization of bimetallic clusters using an efficient heuristic method
NASA Astrophysics Data System (ADS)
Lai, Xiangjing; Xu, Ruchu; Huang, Wenqi
2011-10-01
In this paper, an efficient heuristic algorithm for geometry optimization of bimetallic clusters is proposed. The algorithm is mainly composed of three ingredients: the monotonic basin-hopping method with guided perturbation (MBH-GP), surface optimization method, and iterated local search (ILS) method, where MBH-GP and surface optimization method are used to optimize the geometric structure of a cluster, and the ILS method is used to search the optimal homotop for a fixed geometric structure. The proposed method is applied to Cu38-nAun (0 ≤ n ≤ 38), Ag55-nAun (0 ≤ n ≤ 55), and Cu55-nAun (0 ≤ n ≤ 55) clusters modeled by the many-body Gupta potential. Comparison with the results reported in the literature indicates that the present method is highly efficient and a number of new putative global minima missed in the previous papers are found. The present method should be a promising tool for the theoretical determination of ground-state structure of bimetallic clusters. Additionally, some key elements and properties of the present method are also analyzed.
NASA Astrophysics Data System (ADS)
Kato, Tomohiro; Hasegawa, Mikio
Chaotic dynamics has been shown to be effective in improving the performance of combinatorial optimization algorithms. In this paper, the performance of chaotic dynamics in the asymmetric traveling salesman problem (ATSP) is investigated by introducing three types of heuristic solution update methods. Numerical simulation has been carried out to compare its performance with simulated annealing and tabu search; thus, the effectiveness of the approach using chaotic dynamics for driving heuristic methods has been shown. The chaotic method is also evaluated in the case of a combinatorial optimization problem in the real world, which can be solved by the same heuristic operation as that for the ATSP. We apply the chaotic method to the DNA fragment assembly problem, which involves building a DNA sequence from several hundred fragments obtained by the genome sequencer. Our simulation results show that the proposed algorithm using chaotic dynamics in a block shift operation exhibits the best performance for the DNA fragment assembly problem.
Divergence of Scientific Heuristic Method and Direct Algebraic Instruction
ERIC Educational Resources Information Center
Calucag, Lina S.
2016-01-01
This is an experimental study, made used of the non-randomized experimental and control groups, pretest-posttest designs. The experimental and control groups were two separate intact classes in Algebra. For a period of twelve sessions, the experimental group was subjected to the scientific heuristic method, but the control group instead was given…
Heuristic-based tabu search algorithm for folding two-dimensional AB off-lattice model proteins.
Liu, Jingfa; Sun, Yuanyuan; Li, Gang; Song, Beibei; Huang, Weibo
2013-12-01
The protein structure prediction problem is a classical NP hard problem in bioinformatics. The lack of an effective global optimization method is the key obstacle in solving this problem. As one of the global optimization algorithms, tabu search (TS) algorithm has been successfully applied in many optimization problems. We define the new neighborhood conformation, tabu object and acceptance criteria of current conformation based on the original TS algorithm and put forward an improved TS algorithm. By integrating the heuristic initialization mechanism, the heuristic conformation updating mechanism, and the gradient method into the improved TS algorithm, a heuristic-based tabu search (HTS) algorithm is presented for predicting the two-dimensional (2D) protein folding structure in AB off-lattice model which consists of hydrophobic (A) and hydrophilic (B) monomers. The tabu search minimization leads to the basins of local minima, near which a local search mechanism is then proposed to further search for lower-energy conformations. To test the performance of the proposed algorithm, experiments are performed on four Fibonacci sequences and two real protein sequences. The experimental results show that the proposed algorithm has found the lowest-energy conformations so far for three shorter Fibonacci sequences and renewed the results for the longest one, as well as two real protein sequences, demonstrating that the HTS algorithm is quite promising in finding the ground states for AB off-lattice model proteins. PMID:24077543
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
Designing safe job rotation schedules using optimization and heuristic search.
Carnahan, B J; Redfern, M S; Norman, B
2000-04-01
Job rotation is one method that is sometimes used to reduce exposure to strenuous materials handling; however, developing effective rotation schedules can be complex in even moderate sized facilities. The purpose of this research is to develop methods of incorporating safety criteria into scheduling algorithms to produce job rotation schedules that reduce the potential for injury. Integer programming and a genetic algorithm were used to construct job rotation schedules. Schedules were comprised of lifting tasks whose potential for causing injury was assessed with the Job Severity Index. Each method was used to design four job rotation schedules that met specified safety criteria in a working environment where the object weight, horizontal distance and repetition rate varied over time. Each rotation was assigned to a specific gender/lifting capacity group. Five versions of the integer programming search method were applied to this problem. Each version generated one job rotation schedule. The genetic algorithm model was able to create a population of 437 feasible solutions to the rotation problem. Utilizing cluster analysis, a rule set was derived from the genetic algorithm generated solutions. These rules provided guidelines for designing safe job rotation schedules without the use of a computer. The advantages and limitations of these approaches in developing administrative controls for the prevention of back injury are discussed. PMID:10801086
An extended abstract: A heuristic repair method for constraint-satisfaction and scheduling problems
NASA Technical Reports Server (NTRS)
Minton, Steven; Johnston, Mark D.; Philips, Andrew B.; Laird, Philip
1992-01-01
The work described in this paper was inspired by a surprisingly effective neural network developed for scheduling astronomical observations on the Hubble Space Telescope. Our heuristic constraint satisfaction problem (CSP) method was distilled from an analysis of the network. In the process of carrying out the analysis, we discovered that the effectiveness of the network has little to do with its connectionist implementation. Furthermore, the ideas employed in the network can be implemented very efficiently within a symbolic CSP framework. The symbolic implementation is extremely simple. It also has the advantage that several different search strategies can be employed, although we have found that hill-climbing methods are particularly well-suited for the applications that we have investigated. We begin the paper with a brief review of the neural network. Following this, we describe our symbolic method for heuristic repair.
Tuning Parameters in Heuristics by Using Design of Experiments Methods
NASA Technical Reports Server (NTRS)
Arin, Arif; Rabadi, Ghaith; Unal, Resit
2010-01-01
With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.
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.
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. PMID:26129639
NASA Astrophysics Data System (ADS)
Frenken, Koen
2001-06-01
The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
Scatter search heuristic for least-cost design of water distribution networks
NASA Astrophysics Data System (ADS)
Lin, Min-Der; Liu, Yu-Hsin; Liu, Gee-Fon; Chu, Chien-Wei
2007-10-01
The optimization problems of water distribution networks are complex, multi-modal and discrete-variable problems that cannot be easily solved with conventional optimization algorithms. Heuristic algorithms such as genetic algorithms, simulated annealing, tabu search and ant colony optimization have been extensively employed over the last decade. This article proposed an optimization procedure based on the scatter search (SS) framework, which is also a heuristic algorithm, to obtain the least-cost designs of three well-known looped water distribution networks (two-loop, Hanoi and New York networks). The computational results obtained with the three benchmark instances indicate that SS is able to find solutions comparable to those provided by some of the most competitive algorithms published in the literature.
A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model
NASA Astrophysics Data System (ADS)
Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban
We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.
Parameter Identification of Robot Manipulators: A Heuristic Particle Swarm Search Approach
Yan, Danping; Lu, Yongzhong; Levy, David
2015-01-01
Parameter identification of robot manipulators is an indispensable pivotal process of achieving accurate dynamic robot models. Since these kinetic models are highly nonlinear, it is not easy to tackle the matter of identifying their parameters. To solve the difficulty effectively, we herewith present an intelligent approach, namely, a heuristic particle swarm optimization (PSO) algorithm, which we call the elitist learning strategy (ELS) and proportional integral derivative (PID) controller hybridized PSO approach (ELPIDSO). A specified PID controller is designed to improve particles’ local and global positions information together with ELS. Parameter identification of robot manipulators is conducted for performance evaluation of our proposed approach. Experimental results clearly indicate the following findings: Compared with standard PSO (SPSO) algorithm, ELPIDSO has improved a lot. It not only enhances the diversity of the swarm, but also features better search effectiveness and efficiency in solving practical optimization problems. Accordingly, ELPIDSO is superior to least squares (LS) method, genetic algorithm (GA), and SPSO algorithm in estimating the parameters of the kinetic models of robot manipulators. PMID:26039090
Parameter identification of robot manipulators: a heuristic particle swarm search approach.
Yan, Danping; Lu, Yongzhong; Levy, David
2015-01-01
Parameter identification of robot manipulators is an indispensable pivotal process of achieving accurate dynamic robot models. Since these kinetic models are highly nonlinear, it is not easy to tackle the matter of identifying their parameters. To solve the difficulty effectively, we herewith present an intelligent approach, namely, a heuristic particle swarm optimization (PSO) algorithm, which we call the elitist learning strategy (ELS) and proportional integral derivative (PID) controller hybridized PSO approach (ELPIDSO). A specified PID controller is designed to improve particles' local and global positions information together with ELS. Parameter identification of robot manipulators is conducted for performance evaluation of our proposed approach. Experimental results clearly indicate the following findings: Compared with standard PSO (SPSO) algorithm, ELPIDSO has improved a lot. It not only enhances the diversity of the swarm, but also features better search effectiveness and efficiency in solving practical optimization problems. Accordingly, ELPIDSO is superior to least squares (LS) method, genetic algorithm (GA), and SPSO algorithm in estimating the parameters of the kinetic models of robot manipulators. PMID:26039090
Heuristic search in robot configuration space using variable metric
NASA Technical Reports Server (NTRS)
Verwer, Ben J. H.
1987-01-01
A method to generate obstacle free trajectories for both mobile robots and linked robots is proposed. The approach generates the shortest paths in a configuration space. The metric in the configuration space can be adjusted to obtain a tradeoff between safety and velocity by imposing extra costs on paths near obstacles.
Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.
Lin, Lanny; Goodrich, Michael A
2014-12-01
During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal. PMID:24691199
Mignon, David; Simonson, Thomas
2016-07-15
Computational protein design depends on an energy function and an algorithm to search the sequence/conformation space. We compare three stochastic search algorithms: a heuristic, Monte Carlo (MC), and a Replica Exchange Monte Carlo method (REMC). The heuristic performs a steepest-descent minimization starting from thousands of random starting points. The methods are applied to nine test proteins from three structural families, with a fixed backbone structure, a molecular mechanics energy function, and with 1, 5, 10, 20, 30, or all amino acids allowed to mutate. Results are compared to an exact, "Cost Function Network" method that identifies the global minimum energy conformation (GMEC) in favorable cases. The designed sequences accurately reproduce experimental sequences in the hydrophobic core. The heuristic and REMC agree closely and reproduce the GMEC when it is known, with a few exceptions. Plain MC performs well for most cases, occasionally departing from the GMEC by 3-4 kcal/mol. With REMC, the diversity of the sequences sampled agrees with exact enumeration where the latter is possible: up to 2 kcal/mol above the GMEC. Beyond, room temperature replicas sample sequences up to 10 kcal/mol above the GMEC, providing thermal averages and a solution to the inverse protein folding problem. © 2016 Wiley Periodicals, Inc. PMID:27197555
Parsing heuristic and forward search in first-graders' game-play behavior.
Paz, Luciano; Goldin, Andrea P; Diuk, Carlos; Sigman, Mariano
2015-07-01
Seventy-three children between 6 and 7 years of age were presented with a problem having ambiguous subgoal ordering. Performance in this task showed reliable fingerprints: (a) a non-monotonic dependence of performance as a function of the distance between the beginning and the end-states of the problem, (b) very high levels of performance when the first move was correct, and (c) states in which accuracy of the first move was significantly below chance. These features are consistent with a non-Markov planning agent, with an inherently inertial decision process, and that uses heuristics and partial problem knowledge to plan its actions. We applied a statistical framework to fit and test the quality of a proposed planning model (Monte Carlo Tree Search). Our framework allows us to parse out independent contributions to problem-solving based on the construction of the value function and on general mechanisms of the search process in the tree of solutions. We show that the latter are correlated with children's performance on an independent measure of planning, while the former is highly domain specific. PMID:25302559
Heuristic Search for Planning with Different Forced Goal-Ordering Constraints
Zhang, Weiming; Cui, Jing; Zhu, Cheng; Huang, Jincai; Liu, Zhong
2013-01-01
Planning with forced goal-ordering (FGO) constraints has been proposed many times over the years, but there are still major difficulties in realizing these FGOs in plan generation. In certain planning domains, all the FGOs exist in the initial state. No matter which approach is adopted to achieve a subgoal, all the subgoals should be achieved in a given sequence from the initial state. Otherwise, the planning may arrive at a deadlock. For some other planning domains, there is no FGO in the initial state. However, FGO may occur during the planning process if certain subgoal is achieved by an inappropriate approach. This paper contributes to illustrate that it is the excludable constraints among the goal achievement operations (GAO) of different subgoals that introduce the FGOs into the planning problem, and planning with FGO is still a challenge for the heuristic search based planners. Then, a novel multistep forward search algorithm is proposed which can solve the planning problem with different FGOs efficiently. PMID:23935443
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
Development of a core collection for ramie by heuristic search based on SSR markers
Luan, Ming-Bao; Zou, Zi-Zheng; Zhu, Juan-Juan; Wang, Xiao-Fei; Xu, Ying; Ma, Qing-Hua; Sun, Zhi-Min; Chen, Jian-Hua
2014-01-01
There are more than 2000 ramie germplasms in the National Ramie Germplasm Nursery affiliated with the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Science, China. As it is difficult to perform effective conservation, management, evaluation, and utilization of redundant genetic resources, it is necessary to construct a core collection by using molecular markers. In this study, a core collection of ramie consisting of 22 germplasms was constructed from 108 accessions by heuristic search based on 21 Simple Sequence Repeat (SSR) marker combinations. The results showed that there is a poor relationship between the core collection and the geographic distribution. The number of amplification bands for the core collection was the same as that for the entire collection. Shannon's index for three of the SSR primers (14%) and Nei's index for nine of the SSR primers (19%) were lower in the core collection than in the entire collection. The true core collection had wider genetic diversity compared with the random core collection. Collectively, the core collection constructed in this study is reliable and represents the genetic diversity of all the 108 accessions. PMID:26019563
Perturbation method for probabilistic search for the traveling salesperson problem
NASA Astrophysics Data System (ADS)
Cohoon, James P.; Karro, John E.; Martin, Worthy N.; Niebel, William D.; Nagel, Klaus
1998-10-01
The Traveling Salesperson Problem (TSP), is an MP-complete combinatorial optimization problem of substantial importance in many scheduling applications. Here we show the viability of SPAN, a hybrid approach to solving the TSP that incorporates a perturbation method applied to a classic heuristic in the overall context of a probabilistic search control strategy. In particular, the heuristic for the TSP is based on the minimal spanning tree of the city locations, the perturbation method is a simple modification of the city locations, and the control strategy is a genetic algorithm (GA). The crucial concept here is that the perturbation of the problem allows variant solutions to be generated by the heuristic and applied to the original problem, thus providing the GA with capabilities for both exploration in its search process. We demonstrate that SPAN outperforms, with regard to solution quality, one of the best GA system reported in the literature.
QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm.
Bao, Ying; Lei, Weimin; Zhang, Wei; Zhan, Yuzhuo
2016-01-01
At present, to realize or improve the quality of experience (QoE) is a major goal for network media transmission service, and QoE evaluation is the basis for adjusting the transmission control mechanism. Therefore, a kind of QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm is proposed in this paper, which is concentrated on service score calculation at the server side. The server side collects network transmission quality of service (QoS) parameter, node location data, and user expectation value from client feedback information. Then it manages the historical data in database through the "big data" process mode, and predicts user score according to heuristic rules. On this basis, it completes fuzzy clustering analysis, and generates service QoE score and management message, which will be finally fed back to clients. Besides, this paper mainly discussed service evaluation generative rules, heuristic evaluation rules and fuzzy clustering analysis methods, and presents service-based QoE evaluation processes. The simulation experiments have verified the effectiveness of QoE collaborative evaluation method based on fuzzy clustering heuristic rules. PMID:27398281
Ronald L. Boring; David I. Gertman; Jeffrey C. Joe; Julie L. Marble
2005-09-01
An ongoing issue within human-computer interaction (HCI) is the need for simplified or “discount” methods. The current economic slowdown has necessitated innovative methods that are results driven and cost effective. The myriad methods of design and usability are currently being cost-justified, and new techniques are actively being explored that meet current budgets and needs. Recent efforts in human reliability analysis (HRA) are highlighted by the ten-year development of the Standardized Plant Analysis Risk HRA (SPAR-H) method. The SPAR-H method has been used primarily for determining humancentered risk at nuclear power plants. The SPAR-H method, however, shares task analysis underpinnings with HCI. Despite this methodological overlap, there is currently no HRA approach deployed in heuristic usability evaluation. This paper presents an extension of the existing SPAR-H method to be used as part of heuristic usability evaluation in HCI.
BinAligner: a heuristic method to align biological networks.
Yang, Jialiang; Li, Jun; Grünewald, Stefan; Wan, Xiu-Feng
2013-01-01
The advances in high throughput omics technologies have made it possible to characterize molecular interactions within and across various species. Alignments and comparison of molecular networks across species will help detect orthologs and conserved functional modules and provide insights on the evolutionary relationships of the compared species. However, such analyses are not trivial due to the complexity of network and high computational cost. Here we develop a mixture of global and local algorithm, BinAligner, for network alignments. Based on the hypotheses that the similarity between two vertices across networks would be context dependent and that the information from the edges and the structures of subnetworks can be more informative than vertices alone, two scoring schema, 1-neighborhood subnetwork and graphlet, were introduced to derive the scoring matrices between networks, besides the commonly used scoring scheme from vertices. Then the alignment problem is formulated as an assignment problem, which is solved by the combinatorial optimization algorithm, such as the Hungarian method. The proposed algorithm was applied and validated in aligning the protein-protein interaction network of Kaposi's sarcoma associated herpesvirus (KSHV) and that of varicella zoster virus (VZV). Interestingly, we identified several putative functional orthologous proteins with similar functions but very low sequence similarity between the two viruses. For example, KSHV open reading frame 56 (ORF56) and VZV ORF55 are helicase-primase subunits with sequence identity 14.6%, and KSHV ORF75 and VZV ORF44 are tegument proteins with sequence identity 15.3%. These functional pairs can not be identified if one restricts the alignment into orthologous protein pairs. In addition, BinAligner identified a conserved pathway between two viruses, which consists of 7 orthologous protein pairs and these proteins are connected by conserved links. This pathway might be crucial for virus packing and
Utilization of Tabu search heuristic rules in sampling-based motion planning
NASA Astrophysics Data System (ADS)
Khaksar, Weria; Hong, Tang Sai; Sahari, Khairul Salleh Mohamed; Khaksar, Mansoor
2015-05-01
Path planning in unknown environments is one of the most challenging research areas in robotics. In this class of path planning, the robot acquires the information from its sensory system. Sampling-based path planning is one of the famous approaches with low memory and computational requirements that has been studied by many researchers during the past few decades. We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. The Tabu search component of the proposed method guides the sampling to find the samples in the most promising areas and makes the sampling procedure more intelligent. The simulation results show the efficient performance of the proposed approach in different types of environments. We also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, PRM, RRT and the Visibility Graph. The comparison results support the claim of superiority of the proposed algorithm.
Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement
Siswantoro, Joko; Idrus, Bahari
2014-01-01
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method. PMID:24892069
Extraction of microcracks in rock images based on heuristic graph searching and application
NASA Astrophysics Data System (ADS)
Luo, Zhihua; Zhu, Zhende; Ruan, Huaining; Shi, Chong
2015-12-01
In this paper, we propose a new method, based on a graph searching technique, for microcrack extraction from scanning electron microscopic images of rocks. This method mainly focuses on how to detect the crack and extract it, and then quantify some basic geometrical features. The crack can be detected automatically with the aid of two endpoints of the crack. The algorithm involves the following process: the A* graph searching technique is first used to find a path throughout the crack region, defined by the initial two endpoints; the pixels of the path will be used as the seeds for the region growing method to restore the primary crack area; then, an automatic filling holes' operation is used to remove the possible holes in the region growing result; the medial axis and distance transformation of the crack area are acquired, and then the final crack is rebuilt by painting disks along a medial axis without branches. The crack result is separated without interaction. In the remaining parts, the crack features are quantified, such as the length, width, angle and area, and error analysis shows that the error percentage of the proposed approach reduces to a low level with actual width increases, and results of some example images are illustrated. The algorithm is efficient and can also be used for image detection of other linear structural objects.
Pérez-Losada, Marcos; Bond-Buckup, Georgina; Jara, Carlos G; Crandall, Keith A
2004-10-01
Recently new heuristic genetic algorithms such as Treefinder and MetaGA have been developed to search for optimal trees in a maximum likelihood (ML) framework. In this study we combined these methods with other standard heuristic approaches such as ML and maximum parsimony hill-climbing searches and Bayesian inference coupled with Markov chain Monte Carlo techniques under homogeneous and mixed models of evolution to conduct an extensive phylogenetic analysis of the most abundant and widely distributed southern South American freshwater"crab,"the Aegla(Anomura: Aeglidae). A total of 167 samples representing 64 Aegla species and subspecies were sequenced for one nuclear (28S rDNA) and four mitochondrial (12S and 16S rDNA, COI, and COII) genes (5352 bp total). Additionally, six other anomuran species from the genera Munida,Pachycheles, and Uroptychus(Galatheoidea), Lithodes(Paguroidea), and Lomis(Lomisoidea) and the nuclear 18S rDNA gene (1964 bp) were included in preliminary analyses for rooting the Aegla tree. Nonsignificantly different phylogenetic hypotheses resulted from all the different heuristic methods used here, although the best scored topologies found under the ML hill-climbing, Bayesian, and MetaGA approaches showed considerably better likelihood scores (Delta> 54) than those found under the MP and Treefinder approaches. Our trees provided strong support for most of the recognized Aegla species except for A. cholchol,A. jarai,A. parana,A. marginata, A. platensis, and A. franciscana, which may actually represent multiple species. Geographically, the Aegla group was divided into a basal western clade (21 species and subspecies) composed of two subclades with overlapping distributions, and a more recent central-eastern clade (43 species) composed of three subclades with fairly well-recognized distributions. This result supports the Pacific-Origin Hypothesis postulated for the group; alternative hypotheses of Atlantic or multiple origins were significantly
Heuristic-biased stochastic sampling
Bresina, J.L.
1996-12-31
This paper presents a search technique for scheduling problems, called Heuristic-Biased Stochastic Sampling (HBSS). The underlying assumption behind the HBSS approach is that strictly adhering to a search heuristic often does not yield the best solution and, therefore, exploration off the heuristic path can prove fruitful. Within the HBSS approach, the balance between heuristic adherence and exploration can be controlled according to the confidence one has in the heuristic. By varying this balance, encoded as a bias function, the HBSS approach encompasses a family of search algorithms of which greedy search and completely random search are extreme members. We present empirical results from an application of HBSS to the realworld problem of observation scheduling. These results show that with the proper bias function, it can be easy to outperform greedy search.
Job-shop scheduling with a combination of evolutionary and heuristic methods
NASA Astrophysics Data System (ADS)
Patkai, Bela; Torvinen, Seppo
1999-08-01
Since almost all of the scheduling problems are NP-hard-- cannot be solved in polynomial time--those companies that need a realistic scheduling system face serious limitations of available methods for finding an optimal schedule, especially if the given environment requires adaptation to dynamic variations. Exact methods do find an optimal schedule, but the size of the problem they can solve is very limited, excluding this way the required scalability. The solution presented in this paper is a simple, multi-pass heuristic method, which aims to avoid the limitations of other well-known formulations. Even though the dispatching rules are fast and provide near-optimal solutions in most cases, they are severely limited in efficiency--especially in case the schedule builder satisfies a significant number of constraints. That is the main motivation for adding a simplified genetic algorithm to the dispatching rules, which--due to its stochastic nature--belongs to heuristic, too. The scheduling problem is of a middle size Finnish factory, throughout the investigations their up-to-date manufacturing data has been used for the sake of realistic calculations.
NASA Astrophysics Data System (ADS)
Najafi, Amir Abbas; Pourahmadi, Zahra
2016-04-01
Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.
Archer, Charles J.; Blocksome, Michael A.; Heidelberger, Philip; Kumar, Sameer; Parker, Jeffrey J.; Ratterman, Joseph D.
2011-06-07
Methods, compute nodes, and computer program products are provided for heuristic status polling of a component in a computing system. Embodiments include receiving, by a polling module from a requesting application, a status request requesting status of a component; determining, by the polling module, whether an activity history for the component satisfies heuristic polling criteria; polling, by the polling module, the component for status if the activity history for the component satisfies the heuristic polling criteria; and not polling, by the polling module, the component for status if the activity history for the component does not satisfy the heuristic criteria.
NASA Astrophysics Data System (ADS)
Hada, Akio; Soga, Kenichi; Liu, Ruoshui; Wassell, Ian J.
2012-04-01
In this paper, we study a design method for minimizing the total cost of a wireless sensor network (WSN) used for health monitoring of railway structures. First, we present the problem, that is to simultaneously determine the number of relays and their deployment locations, the transmission power level for each sensor and relay, and the routes for transferring sensor data to a gateway using multi-hop wireless communication. Second, we formulate this task as a mathematical programming problem, and to solve this problem, we propose a near optimal algorithm based on the Lagrangian heuristic method. Finally, we verify the effectiveness of our algorithm through computational experiments carried out using data acquired from a real WSN used for railway structural health monitoring.
Iterative-deepening heuristic search for optimal and semi-optimal resource allocation
NASA Technical Reports Server (NTRS)
Bridges, Susan M.; Johannes, James D.
1987-01-01
It is demonstrated that when iterative-deepening A asterisk (IDA asterisk) is applied to one type of resource allocation problem, it uses far less storage than A asterisk, but opens far more nodes and thus has unacceptable time complexity. This is shown to be due, at least in part, to the low-valued effective branching factor that is a characteristic of problems with real-valued cost functions. The semi-optimal, epsilon-admissible IDA asterisk sub epsilon search algorithm that the authors described was shown to open fewer nodes than both A asterisk and IDA asterisk with storage complexity proportional to the depth of the search tree.
Managing Heuristics as a Method of Inquiry in Autobiographical Graphic Design Theses
ERIC Educational Resources Information Center
Ings, Welby
2011-01-01
This article draws on case studies undertaken in postgraduate research at AUT University, Auckland. It seeks to address a number of issues related to heuristic inquiries employed by graphic design students who use autobiographical approaches when developing research-based theses. For this type of thesis, heuristics as a system of inquiry may…
NASA Astrophysics Data System (ADS)
Ayvaz, M. Tamer
2007-11-01
This study proposes an inverse solution algorithm through which both the aquifer parameters and the zone structure of these parameters can be determined based on a given set of observations on piezometric heads. In the zone structure identification problem fuzzy c-means ( FCM) clustering method is used. The association of the zone structure with the transmissivity distribution is accomplished through an optimization model. The meta-heuristic harmony search ( HS) algorithm, which is conceptualized using the musical process of searching for a perfect state of harmony, is used as an optimization technique. The optimum parameter zone structure is identified based on three criteria which are the residual error, parameter uncertainty, and structure discrimination. A numerical example given in the literature is solved to demonstrate the performance of the proposed algorithm. Also, a sensitivity analysis is performed to test the performance of the HS algorithm for different sets of solution parameters. Results indicate that the proposed solution algorithm is an effective way in the simultaneous identification of aquifer parameters and their corresponding zone structures.
Using tree diversity to compare phylogenetic heuristics
Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L
2009-01-01
Background Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Results Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Conclusion Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees—especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest. PMID:19426451
A heuristic method for consumable resource allocation in multi-class dynamic PERT networks
NASA Astrophysics Data System (ADS)
Yaghoubi, Saeed; Noori, Siamak; Mazdeh, Mohammad Mahdavi
2013-06-01
This investigation presents a heuristic method for consumable resource allocation problem in multi-class dynamic Project Evaluation and Review Technique (PERT) networks, where new projects from different classes (types) arrive to system according to independent Poisson processes with different arrival rates. Each activity of any project is operated at a devoted service station located in a node of the network with exponential distribution according to its class. Indeed, each project arrives to the first service station and continues its routing according to precedence network of its class. Such system can be represented as a queuing network, while the discipline of queues is first come, first served. On the basis of presented method, a multi-class system is decomposed into several single-class dynamic PERT networks, whereas each class is considered separately as a minisystem. In modeling of single-class dynamic PERT network, we use Markov process and a multi-objective model investigated by Azaron and Tavakkoli-Moghaddam in 2007. Then, after obtaining the resources allocated to service stations in every minisystem, the final resources allocated to activities are calculated by the proposed method.
SP-100 shield design automation process using expert system and heuristic search techniques
NASA Astrophysics Data System (ADS)
Marcille, Thomas F.; Protsik, Robert; Deane, Nelson A.; Hoover, Darryl G.
1993-01-01
The SP-100 shield subsystem design process has been modified to utilize the GE Corporate Reserch and Development program, ENGINEOUS (Tong 1990). ENGINEOUS is a software system that automates the use of Computer Aided Engineering (CAE) analysis programs in the engineering design process. The shield subsystem design process incorporates a nuclear subsystems design and performance code, a two-dimensional neutral particle transport code, several input processors and two general purpose neutronic output processors. Coupling these programs within ENGINEOUS provides automatic transition paths between applications, with no source code modifications. ENGINEOUS captures human design knowledge, as well as information about the specific CAE applications and stores this information in knowledge base files. The knowledge base information is used by the ENGINEOUS expert system to drive knowledge directed and knowledge supplemented search modules to find an optimum shield design for a given reactor definition, ensuring that specified constraints are satisfied. Alternate designs, not accommodated in the optimization design rules, can readily be explored through the use of a parametric study capability.
Recursive heuristic classification
NASA Technical Reports Server (NTRS)
Wilkins, David C.
1994-01-01
The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.
NASA Astrophysics Data System (ADS)
Bashiri, Mahdi; Karimi, Hossein
2012-07-01
Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and particle swarm optimization as meta-heuristic methods for the QAP. This research is dedicated to compare the relative percentage deviation of these solution qualities from the best known solution which is introduced in QAPLIB. Furthermore, a tuning method is applied for meta-heuristic parameters. Results indicate that TS is the best in 31%of QAPs, and the IFLS method, which is in the literature, is the best in 58 % of QAPs; these two methods are the same in 11 % of test problems. Also, TS has a better computational time among heuristic and meta-heuristic methods.
A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices
ERIC Educational Resources Information Center
Brusco, Michael; Steinley, Douglas
2011-01-01
Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where…
Heuristic decision making in medicine
Marewski, Julian N.; Gigerenzer, Gerd
2012-01-01
Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care. PMID:22577307
NASA Astrophysics Data System (ADS)
Kumar, Shailendra; Sharma, Rajiv Kumar
2015-12-01
Over the last four decades of research, numerous cell formation algorithms have been developed and tested, still this research remains of interest to this day. Appropriate manufacturing cells formation is the first step in designing a cellular manufacturing system. In cellular manufacturing, consideration to manufacturing flexibility and production-related data is vital for cell formation. The consideration to this realistic data makes cell formation problem very complex and tedious. It leads to the invention and implementation of highly advanced and complex cell formation methods. In this paper an effort has been made to develop a simple and easy to understand/implement manufacturing cell formation heuristic procedure with considerations to the number of production and manufacturing flexibility-related parameters. The heuristic minimizes inter-cellular movement cost/time. Further, the proposed heuristic is modified for the application of principal component analysis and Taguchi's method. Numerical example is explained to illustrate the approach. A refinement in the results is observed with adoption of principal component analysis and Taguchi's method.
The Impact of Using the Heuristic Teaching Method on Jordanian Mathematics Students
ERIC Educational Resources Information Center
Al-Fayez, Mona Qutefan; Jubran, Sereen Mousa
2012-01-01
This study investigates the impact of using the heuristic teaching approach for teaching mathematics to tenth grade students in Jordan. The researchers followed the equivalent pre/post T test two group designs. To achieve the goal of the study, a pre/post- test was constructed to measure student achievement in mathematics. The sample for this…
Heuristics as a Basis for Assessing Creative Potential: Measures, Methods, and Contingencies
ERIC Educational Resources Information Center
Vessey, William B.; Mumford, Michael D.
2012-01-01
Studies of creative thinking skills have generally measured a single aspect of creativity, divergent thinking. A number of other processes involved in creative thought have been identified. Effective execution of these processes is held to depend on the strategies applied in process execution, or heuristics. In this article, we review prior…
Twilight of the Slogans: A Heuristic Investigation of Linguistic Memes Using Mixed Methods
ERIC Educational Resources Information Center
Duffy, Curt Paul
2013-01-01
Slogans, or linguistic memes, are short, memorable phrases that are present in commercial, political, and everyday discourse. Slogans propagate similarly to other memes, or cultural units, through an evolutionary mechanism first proposed by Dawkins (1976). Heuristic inquiry, as presented by Moustakas (1990), provided a template from which to…
The min-conflicts heuristic: Experimental and theoretical results
NASA Technical Reports Server (NTRS)
Minton, Steven; Philips, Andrew B.; Johnston, Mark D.; Laird, Philip
1991-01-01
This paper describes a simple heuristic method for solving large-scale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching through the space of possible repairs. The search is guided by an ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. We demonstrate empirically that the method performs orders of magnitude better than traditional backtracking techniques on certain standard problems. For example, the one million queens problem can be solved rapidly using our approach. We also describe practical scheduling applications where the method has been successfully applied. A theoretical analysis is presented to explain why the method works so well on certain types of problems and to predict when it is likely to be most effective.
Meta-heuristic algorithms as tools for hydrological science
NASA Astrophysics Data System (ADS)
Yoo, Do Guen; Kim, Joong Hoon
2014-12-01
In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.
NASA Astrophysics Data System (ADS)
Shibata, Kazuaki; Horio, Yoshihiko; Aihara, Kazuyuki
The quadratic assignment problem (QAP) is one of the NP-hard combinatorial optimization problems. An exponential chaotic tabu search using a 2-opt algorithm driven by chaotic neuro-dynamics has been proposed as one heuristic method for solving QAPs. In this paper we first propose a new local search, the double-assignment method, suitable for the exponential chaotic tabu search, which adopts features of the Lin-Kernighan algorithm. We then introduce chaotic neuro-dynamics into the double-assignment method to propose a novel exponential chaotic tabu search. We further improve the proposed exponential chaotic tabu search with the double-assignment method by enhancing the effect of chaotic neuro-dynamics.
Heuristic Learning and Programmed Learning
ERIC Educational Resources Information Center
Okon, Wincenty
1969-01-01
Flexibility in the application of instructional methods is the best approach to a teaching situation. Insofar as possible, a combination of traditional learning methods with heuristic (problem solving) and programed ones should be used. (CK)
A parallel graph coloring heuristic
Jones, M.T.; Plassmann, P.E. )
1993-05-01
The problem of computing good graph colorings arises in many diverse applications, such as in the estimation of sparse Jacobians and in the development of efficient, parallel iterative methods for solving sparse linear systems. This paper presents an asynchronous graph coloring heuristic well suited to distributed memory parallel computers. Experimental results obtained on an Intel iPSC/860 are presented, which demonstrate that, for graphs arising from finite element applications, the heuristic exhibits scalable performance and generates colorings usually within three or four colors of the best-known linear time sequential heuristics. For bounded degree graphs, it is shown that the expected running time of the heuristic under the P-Ram computation model is bounded by EO(log(n)/log log(n)). This bound is an improvement over the previously known best upper bound for the expected running time of a random heuristic for the graph coloring problem.
2015-01-01
Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377
Maktabdar Oghaz, Mahdi; Maarof, Mohd Aizaini; Zainal, Anazida; Rohani, Mohd Foad; Yaghoubyan, S Hadi
2015-01-01
Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377
Sabar, Nasser R; Ayob, Masri; Kendall, Graham; Qu, Rong
2015-02-01
Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite. PMID:24951713
A System for Automatically Generating Scheduling Heuristics
NASA Technical Reports Server (NTRS)
Morris, Robert
1996-01-01
The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.
Applications of Meta-heuristics to Power and Energy Fields
NASA Astrophysics Data System (ADS)
Fukuyama, Yoshikazu
Considering deregulation in power systems and the energy conservation law, power and energy systems require more cost and energy reduction for system planning, operation, and control. Optimization techniques such as linear and nonlinear programming techniques have been utilized as one of the methods for realization of the reduction. Recently, meta-heuristics such as genetic algorithm, simulated annealing, tabu search, and particle swarm optimization have been paid attention as other options for realization of the reduction. In power and energy society, we had one technical committee and one special issue on applications of meta-heuristics for power system. Moreover, panel sessions and tutorials have been held in IEEE and IFAC. This paper presents applications of meta-heuristics to power and energy fields from the practical application point of view.
Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul
2015-01-01
In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858
ERIC Educational Resources Information Center
Bell, C. L. M.; Jones, K. P.
1980-01-01
Explains, with supporting figures and flowcharts of programing logic, two search strategies introduced to the MORPHS System since 1976: one that employs the normal Boolean operators in strings without bracketing or in the form of marked steps, and one that treats a string of keywords as a compound word. (Author/JD)
Heuristics for chemical compound matching.
Hattori, Masahiro; Okuno, Yasushi; Goto, Susumu; Kanehisa, Minoru
2003-01-01
We have developed an efficient algorithm for comparing two chemical compounds, where the chemical structure is treated as a 2D graph consisting of atoms as vertices and covalent bonds as edges. Based on the concept of functional groups in chemistry, 68 atom types (vertex types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection of biochemically meaningful features. Maximal common subgraphs of two graphs can be found by searching for maximal cliques in the association graph, and we have introduced heuristics to accelerate the clique finding. Our heuristic procedure is controlled by some adjustable parameters. Here we applied our procedure to the latest KEGG/LIGAND database with different sets of parameters, and demonstrated the correlation of parameters in our algorithm with the distribution of similarity scores and/or the execution time. Finally, we showed the effectiveness of our heuristics for compound pairs along metabolic pathways. PMID:15706529
Pattern Search Methods for Linearly Constrained Minimization
NASA Technical Reports Server (NTRS)
Lewis, Robert Michael; Torczon, Virginia
1998-01-01
We extend pattern search methods to linearly constrained minimization. We develop a general class of feasible point pattern search algorithms and prove global convergence to a Karush-Kuhn-Tucker point. As in the case of unconstrained minimization, pattern search methods for linearly constrained problems accomplish this without explicit recourse to the gradient or the directional derivative. Key to the analysis of the algorithms is the way in which the local search patterns conform to the geometry of the boundary of the feasible region.
Search systems and computer-implemented search methods
Payne, Deborah A.; Burtner, Edwin R.; Bohn, Shawn J.; Hampton, Shawn D.; Gillen, David S.; Henry, Michael J.
2015-12-22
Search systems and computer-implemented search methods are described. In one aspect, a search system includes a communications interface configured to access a plurality of data items of a collection, wherein the data items include a plurality of image objects individually comprising image data utilized to generate an image of the respective data item. The search system may include processing circuitry coupled with the communications interface and configured to process the image data of the data items of the collection to identify a plurality of image content facets which are indicative of image content contained within the images and to associate the image objects with the image content facets and a display coupled with the processing circuitry and configured to depict the image objects associated with the image content facets.
NASA Technical Reports Server (NTRS)
Wheeler, Ward C.
2003-01-01
A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.
Wheeler, Ward C
2003-06-01
A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. PMID:12901383
A Meta-heuristic Approach for Variants of VRP in Terms of Generalized Saving Method
NASA Astrophysics Data System (ADS)
Shimizu, Yoshiaki
Global logistic design is becoming a keen interest to provide an essential infrastructure associated with modern societal provision. For examples, we can designate green and/or robust logistics in transportation systems, smart grids in electricity utilization systems, and qualified service in delivery systems, and so on. As a key technology for such deployments, we engaged in practical vehicle routing problem on a basis of the conventional saving method. This paper extends such idea and gives a general framework available for various real-world applications. It can cover not only delivery problems but also two kind of pick-up problems, i.e., straight and drop-by routings. Moreover, multi-depot problem is considered by a hybrid approach with graph algorithm and its solution method is realized in a hierarchical manner. Numerical experiments have been taken place to validate effectiveness of the proposed method.
Paging Doctor Google! Heuristics vs. technology
Jhaveri, Kenar D
2013-01-01
The most dramatic development in medical decision-making technology has been the advent of the Internet. This has had an impact not only on clinicians, but has also become an important resource for patients who often approach their doctors with medical information they have obtained from the Internet. Increasingly, medical students, residents and attending physicians have been using the Internet as a tool for diagnosing and treating disease. Internet-based resources that are available take various forms, including informational websites, online journals and textbooks, and social media. Search engines such as Google have been increasingly used to help in making diagnoses of disease entities. Do these search methods fare better than experienced heuristic methods? In a small study, we examined the comparative role of heuristics versus the 'Google' mode of thinking. Internal medicine residents were asked to “google” key words to come up with a diagnosis. Their results were compared to experienced nephrology faculty and fellows in training using heuristics and no additional help of internet. Overall, with the aid of Google, the novices (internal medicine residents) correctly diagnosed renal diseases less often than the experts (the attendings) but with the same frequency as the intermediates (nephrology fellows). However, in a subgroup analysis of both common diseases and rare diseases, the novices correctly diagnosed renal diseases less often than the experts but more often than the intermediates in each analysis. The novices correctly diagnosed renal diseases with the same frequency as nephrology fellows in training. PMID:24627777
Paging Doctor Google! Heuristics vs. technology.
Jhaveri, Kenar D; Schrier, Peter B; Mattana, Joseph
2013-01-01
The most dramatic development in medical decision-making technology has been the advent of the Internet. This has had an impact not only on clinicians, but has also become an important resource for patients who often approach their doctors with medical information they have obtained from the Internet. Increasingly, medical students, residents and attending physicians have been using the Internet as a tool for diagnosing and treating disease. Internet-based resources that are available take various forms, including informational websites, online journals and textbooks, and social media. Search engines such as Google have been increasingly used to help in making diagnoses of disease entities. Do these search methods fare better than experienced heuristic methods? In a small study, we examined the comparative role of heuristics versus the 'Google' mode of thinking. Internal medicine residents were asked to "google" key words to come up with a diagnosis. Their results were compared to experienced nephrology faculty and fellows in training using heuristics and no additional help of internet. Overall, with the aid of Google, the novices (internal medicine residents) correctly diagnosed renal diseases less often than the experts (the attendings) but with the same frequency as the intermediates (nephrology fellows). However, in a subgroup analysis of both common diseases and rare diseases, the novices correctly diagnosed renal diseases less often than the experts but more often than the intermediates in each analysis. The novices correctly diagnosed renal diseases with the same frequency as nephrology fellows in training. PMID:24627777
ERIC Educational Resources Information Center
Maxwell, Joseph A.
2011-01-01
In this article, the author challenges the validity and usefulness of the concept of "paradigm," as this term has been used in the social sciences generally, and specifically in the debates over research methods. He emphasizes that in criticizing what he sees as the misuse of the paradigm concept, he is not arguing for dismissing or ignoring…
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.
Formal and heuristic system decomposition methods in multidisciplinary synthesis. Ph.D. Thesis, 1991
NASA Technical Reports Server (NTRS)
Bloebaum, Christina L.
1991-01-01
The multidisciplinary interactions which exist in large scale engineering design problems provide a unique set of difficulties. These difficulties are associated primarily with unwieldy numbers of design variables and constraints, and with the interdependencies of the discipline analysis modules. Such obstacles require design techniques which account for the inherent disciplinary couplings in the analyses and optimizations. The objective of this work was to develop an efficient holistic design synthesis methodology that takes advantage of the synergistic nature of integrated design. A general decomposition approach for optimization of large engineering systems is presented. The method is particularly applicable for multidisciplinary design problems which are characterized by closely coupled interactions among discipline analyses. The advantage of subsystem modularity allows for implementation of specialized methods for analysis and optimization, computational efficiency, and the ability to incorporate human intervention and decision making in the form of an expert systems capability. The resulting approach is not a method applicable to only a specific situation, but rather, a methodology which can be used for a large class of engineering design problems in which the system is non-hierarchic in nature.
Automatic Generation of Heuristics for Scheduling
NASA Technical Reports Server (NTRS)
Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.
1997-01-01
This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
NASA Astrophysics Data System (ADS)
Blais-Stevens, A.; Behnia, P.
2016-02-01
This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC), by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect, surficial geology, plan curvature, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high-resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g. 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.
Method for Loss Minimum Re-configuration Problem of Distribution System by Tabu Search
NASA Astrophysics Data System (ADS)
Mishima, Yuji; Nara, Koichi; Satoh, Taiji; Ito, Takamitsu; Kaneda, Hirotoshi
This paper proposes a loss minimum reconfiguration method by Tabu Search for open loop radial distribution system with distributed generators. The problem is to find the optimal normal open sectionalizing switch positions which minimize the total distribution line losses subjected to the line/transformer capacity constraints and voltage constraint. Generally, the problem is mathematically formulated as a complex combinatorial optimization problem or mixed integer programming problem, and is solved by using mathematical programming method, heuristic algorithm, intelligent method, etc. However, satisfactory algorithm for power companies has not yet been attained both in computational burden and solution accuracy. Thus, in this paper, the authors propose a method to solve the above problem by using Tabu Search (TS) method. Reverse power flow caused by distributed generators can be included in the solution algorithm. TS is one of meta-heuristic algorithms, and sometimes evaluated to be better compared with Genetic Algorithm (GA) or Simulated Annealing (SA) from viewpoints of both computational speed and solution accuracy. In order to evaluate the validity and efficiency of the algorithm, several numerical examples are shown in this paper.
ERIC Educational Resources Information Center
Barak, Moshe
2013-01-01
This paper presents the outcomes of teaching an inventive problem-solving course in junior high schools in an attempt to deal with the current relative neglect of fostering students' creativity and problem-solving capabilities in traditional schooling. The method involves carrying out systematic manipulation with attributes, functions and…
Prediction-based dynamic load-sharing heuristics
NASA Technical Reports Server (NTRS)
Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.
1993-01-01
The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.
Multiobjective Tabu Search method used in chemistry
NASA Astrophysics Data System (ADS)
Rusu, T.; Bulacovschi, V.
The use of a combined artificial intelligence method in macromolecular chemistry design is described. This method implies a Back-Propagation (BP) Neural Network, modified for two-dimensional input data and for a system composed of a genetic algorithm extended by a Tabu Search operator used to incorporate high-level chemical knowledge: thermodynamic polymer properties.
Job Search Methods: Internet versus Traditional.
ERIC Educational Resources Information Center
Kuhn, Peter; Skuterud, Mikal
2000-01-01
In 1998, 15 percent of unemployed job seekers used the Internet to seek jobs, as did half of all job seekers with online access from home. Internet search rates exceeded those of traditional methods, but Internet job seekers were more likely to use traditional methods as well. Unemployed blacks and Hispanics used the Internet least in job…
Learning process mapping heuristics under stochastic sampling overheads
NASA Technical Reports Server (NTRS)
Ieumwananonthachai, Arthur; Wah, Benjamin W.
1991-01-01
A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.
SEARCHING FOR RAPID METHODS IN ENVIRONMENTAL BACTERIOLOGY
The search for rapid methods in sanitary bacteriology is more urgent today than ever before because of increased necessity for processing poorer quality source waters and controlling quality of sewage effluent discharges. Selection of criteria for rapid tests involving either mod...
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Heuristic Evaluation of E-Learning Courses: A Comparative Analysis of Two E-Learning Heuristic Sets
ERIC Educational Resources Information Center
Zaharias, Panagiotis; Koutsabasis, Panayiotis
2012-01-01
Purpose: The purpose of this paper is to discuss heuristic evaluation as a method for evaluating e-learning courses and applications and more specifically to investigate the applicability and empirical use of two customized e-learning heuristic protocols. Design/methodology/approach: Two representative e-learning heuristic protocols were chosen…
Solving systems of inequalities and equalities by a nonmonotone hybrid tabu search method
NASA Astrophysics Data System (ADS)
Ramadas, Gisela C. V.; Fernandes, Edite M. G. P.
2012-09-01
This paper presents a derivative-free nonmonotone hybrid tabu search to compute a solution of overdetermined systems of inequalities and equalities through the global optimization of an appropriate merit function. The proposed algorithm combines global and local searches aiming to reduce computational effort. Preliminary numerical results show the effectiveness of the combined heuristic.
Trends in Job Search Methods, 1970-92.
ERIC Educational Resources Information Center
Ports, Michelle Harrison
1993-01-01
Updates the existing research on job search behaviors and analyzes trends in job search behavior since the 1970s. Tables show data on search methods by age, sex, race, Hispanic origin, type of work sought, and reason for unemployment. (JOW)
Heuristic Inquiry: A Personal Journey of Acculturation and Identity Reconstruction
ERIC Educational Resources Information Center
Djuraskovic, Ivana; Arthur, Nancy
2010-01-01
Heuristic methodology attempts to discover the nature and meaning of phenomenon through internal self-search, exploration, and discovery. Heuristic methodology encourages the researcher to explore and pursue the creative journey that begins inside one's being and ultimately uncovers its direction and meaning through internal discovery (Douglass &…
Hermawati, Setia; Lawson, Glyn
2016-09-01
Heuristics evaluation is frequently employed to evaluate usability. While general heuristics are suitable to evaluate most user interfaces, there is still a need to establish heuristics for specific domains to ensure that their specific usability issues are identified. This paper presents a comprehensive review of 70 studies related to usability heuristics for specific domains. The aim of this paper is to review the processes that were applied to establish heuristics in specific domains and identify gaps in order to provide recommendations for future research and area of improvements. The most urgent issue found is the deficiency of validation effort following heuristics proposition and the lack of robustness and rigour of validation method adopted. Whether domain specific heuristics perform better or worse than general ones is inconclusive due to lack of validation quality and clarity on how to assess the effectiveness of heuristics for specific domains. The lack of validation quality also affects effort in improving existing heuristics for specific domain as their weaknesses are not addressed. PMID:27184309
Method of searching for neutron clusters
NASA Astrophysics Data System (ADS)
Dudkin, G. N.; Garapatskii, A. A.; Padalko, V. N.
2014-10-01
A new method of searching for neutron clusters (multineutrons) composed of neutrons bound by nuclear forces has been introduced and implemented. The method is based on the search for daughter nuclei that emerge at the nuclei cluster decay of 252Cf to neutron clusters. The effect of long-time build-up of daughter nuclei with a high atomic number and long half-life was utilized. The results are interpreted as evidence of the cluster decay of 252Cf to daughter nucleus 232U (half-life of T1/2= 68.9 years). The emergence of 232U is attributed to emission of neutron clusters consisting of eight neutrons - octaneutrons. The emission probability of octaneutrons against α-decay probability of 252Cf is defined equal to λC/λα=1.74×10-6.
Harmony Search Method: Theory and Applications
Gao, X. Z.; Govindasamy, V.; Xu, H.; Wang, X.; Zenger, K.
2015-01-01
The Harmony Search (HS) method is an emerging metaheuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory and applications of the HS algorithm are first described and reviewed. Several typical variants of the original HS are next briefly explained. As an example of case study, a modified HS method inspired by the idea of Pareto-dominance-based ranking is also presented. It is further applied to handle a practical wind generator optimal design problem. PMID:25945083
NASA Technical Reports Server (NTRS)
Syed, S. A.; Chiappetta, L. M.
1985-01-01
A methodological evaluation for two-finite differencing schemes for computer-aided gas turbine design is presented. The two computational schemes include; a Bounded Skewed Finite Differencing Scheme (BSUDS); and a Quadratic Upwind Differencing Scheme (QSDS). In the evaluation, the derivations of the schemes were incorporated into two-dimensional and three-dimensional versions of the Teaching Axisymmetric Characteristics Heuristically (TEACH) computer code. Assessments were made according to performance criteria for the solution of problems of turbulent, laminar, and coannular turbulent flow. The specific performance criteria used in the evaluation were simplicity, accuracy, and computational economy. It is found that the BSUDS scheme performed better with respect to the criteria than the QUDS. Some of the reasons for the more successful performance BSUDS are discussed.
NASA Astrophysics Data System (ADS)
Mugunthan, P.; Shoemaker, C. A.; Regis, R. G.
2003-12-01
Heuristics and function approximation optimization methods were applied in calibrating biological and biokinetic parameters for a computationally expensive groundwater bioremediation model for engineered reductive dechlorination of chlorinated ethenes. Multi-species groundwater bioremediation models that use monod type kinetics are often not amenable to traditional derivative based optimization due to stiff biokinetic equations. The performance of three heuristic methods, Stochastic Greedy Search (GS), Real Genetic Algorithm (RGA), Derandomized Evolution Strategy (DES), and, Function Approximation Optimization based on Radial Basis Function (FA-RBF) were compared on three-dimensional hypothetical and field problems. GS was implemented so as to perform a more global search. Optimization results on hypothetical problem indicated that FA-RBF performed statistically significantly better than heuristic based evolutionary algorithms at a 10% significance level. Further, this particular implementation of GS performed well and proved superior to RGA. These heuristic methods and FA-RBF, with the exception of RGA, were applied to calibrate biological and biokinetic parameters using treatability test data for enhanced bioremediation at a Naval Air Station in Alameda Point, CA. All three methods performed well and identified similar solutions. The approximate simulation times for the hypothetical and real problems were 7 min and 2.5 hours respectively. Calibration of such computationally expensive models by heuristic and function approximation methods appears promising.
Fluency Heuristic: A Model of How the Mind Exploits a By-Product of Information Retrieval
ERIC Educational Resources Information Center
Hertwig, Ralph; Herzog, Stefan M.; Schooler, Lael J.; Reimer, Torsten
2008-01-01
Boundedly rational heuristics for inference can be surprisingly accurate and frugal for several reasons. They can exploit environmental structures, co-opt complex capacities, and elude effortful search by exploiting information that automatically arrives on the mental stage. The fluency heuristic is a prime example of a heuristic that makes the…
Computational Experiments with the RAVE Heuristic
NASA Astrophysics Data System (ADS)
Tom, David; Müller, Martin
The Monte-Carlo tree search algorithm Upper Confidence bounds applied to Trees (UCT) has become extremely popular in computer games research. The Rapid Action Value Estimation (RAVE) heuristic is a strong estimator that often improves the performance of UCT-based algorithms. However, there are situations where RAVE misleads the search whereas pure UCT search can find the correct solution. Two games, the simple abstract game Sum of Switches (SOS) and the game of Go, are used to study the behavior of the RAVE heuristic. In SOS, RAVE updates are manipulated to mimic game situations where RAVE misleads the search. Such false RAVE updates are used to create RAVE overestimates and underestimates. A study of the distributions of mean and RAVE values reveals great differences between Go and SOS. While the RAVE-max update rule is able to correct extreme cases of RAVE underestimation, it is not effective in closer to practical settings and in Go.
Pitfalls in Teaching Judgment Heuristics
ERIC Educational Resources Information Center
Shepperd, James A.; Koch, Erika J.
2005-01-01
Demonstrations of judgment heuristics typically focus on how heuristics can lead to poor judgments. However, exclusive focus on the negative consequences of heuristics can prove problematic. We illustrate the problem with the representativeness heuristic and present a study (N = 45) that examined how examples influence understanding of the…
ConfGen: a conformational search method for efficient generation of bioactive conformers.
Watts, K Shawn; Dalal, Pranav; Murphy, Robert B; Sherman, Woody; Friesner, Rich A; Shelley, John C
2010-04-26
We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reasonable amount of computer time. The method combines physics-based force field calculations with empirically derived heuristics designed to achieve efficient searching and prioritization of the ligand's conformational space. While many parameter settings are supported, four modes spanning a range of speed and quality trades-offs are defined and characterized. The validation set used to test the method is composed of ligands from 667 crystal structures covering a broad array of target and ligand classes. With the fastest mode, ConfGen uses an average of 0.5 s per ligand and generates only 14.3 conformers per ligand, at least one of which lies within 2.0 A root-mean-squared deviation of the crystal structure for 96% of the ligands. The most computationally intensive mode raises this recovery rate to 99%, while taking 8 s per ligand. Combining multiple search modes to "fill-in" holes in the conformation space or energy minimizing using an all-atom force field each lead to improvements in the recovery rates at higher resolutions. Overall, ConfGen is at least as good as competing programs at high resolution and demonstrates higher efficiency at resolutions sufficient for many downstream applications, such as pharmacophore modeling. PMID:20373803
NASA Astrophysics Data System (ADS)
Lee, T. S.; Yoon, S.; Jeong, C.
2012-12-01
The primary purpose of frequency analysis in hydrology is to estimate the magnitude of an event with a given frequency of occurrence. The precision of frequency analysis depends on the selection of an appropriate probability distribution model (PDM) and parameter estimation techniques. A number of PDMs have been developed to describe the probability distribution of the hydrological variables. For each of the developed PDMs, estimated parameters are provided based on alternative estimation techniques, such as the method of moments (MOM), probability weighted moments (PWM), linear function of ranked observations (L-moments), and maximum likelihood (ML). Generally, the results using ML are more reliable than the other methods. However, the ML technique is more laborious than the other methods because an iterative numerical solution, such as the Newton-Raphson method, must be used for the parameter estimation of PDMs. In the meantime, meta-heuristic approaches have been developed to solve various engineering optimization problems (e.g., linear and stochastic, dynamic, nonlinear). These approaches include genetic algorithms, ant colony optimization, simulated annealing, tabu searches, and evolutionary computation methods. Meta-heuristic approaches use a stochastic random search instead of a gradient search so that intricate derivative information is unnecessary. Therefore, the meta-heuristic approaches have been shown to be a useful strategy to solve optimization problems in hydrology. A number of studies focus on using meta-heuristic approaches for estimation of hydrological variables with parameter estimation of PDMs. Applied meta-heuristic approaches offer reliable solutions but use more computation time than derivative-based methods. Therefore, the purpose of this study is to enhance the meta-heuristic approach for the parameter estimation of PDMs by using a recently developed algorithm known as a harmony search (HS). The performance of the HS is compared to the
Intelligent process mapping through systematic improvement of heuristics
NASA Technical Reports Server (NTRS)
Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.
1992-01-01
The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.
Multiobjective hyper heuristic scheme for system design and optimization
NASA Astrophysics Data System (ADS)
Rafique, Amer Farhan
2012-11-01
As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.
Li, Yu-qin; Si, Hong-zong; Xiao, Yu-liang; Liu, Cai-hong; Xia, Cheng-cai; Li, Ke; Qi, Yong-xiu
2009-05-01
Quantitative structure-property relationships (QSPR) were developed to predict the pK(a) values of sulfa drugs via heuristic method (HM) and gene expression programming (GEP). The descriptors of 31 sulfa drugs were calculated by the software CODESSA, which can calculate constitutional, topological, geometrical, electrostatic, and quantum chemical descriptors. HM was also used for the preselection of 4 appropriate molecular descriptors. Linear and nonlinear QSPR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R) of 0.90 and 0.95. The two QSPR models are tseful in predicting pK(a) during the discovery of new drugs and providing theory information for studying the new drugs. PMID:19618723
Visual tracking method based on cuckoo search algorithm
NASA Astrophysics Data System (ADS)
Gao, Ming-Liang; Yin, Li-Ju; Zou, Guo-Feng; Li, Hai-Tao; Liu, Wei
2015-07-01
Cuckoo search (CS) is a new meta-heuristic optimization algorithm that is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. It has been found to be efficient in solving global optimization problems. An application of CS is presented to solve the visual tracking problem. The relationship between optimization and visual tracking is comparatively studied and the parameters' sensitivity and adjustment of CS in the tracking system are experimentally studied. To demonstrate the tracking ability of a CS-based tracker, a comparative study of tracking accuracy and speed of the CS-based tracker with six "state-of-art" trackers, namely, particle filter, meanshift, PSO, ensemble tracker, fragments tracker, and compressive tracker are presented. Comparative results show that the CS-based tracker outperforms the other trackers.
A framework for structured quantum search
NASA Astrophysics Data System (ADS)
Hogg, Tad
1998-09-01
A quantum algorithm for general combinatorial search that uses the underlying structure of the search space to increase the probability of finding a solution is presented. This algorithm shows how coherent quantum systems can be matched to the underlying structure of abstract search spaces. The algorithm is evaluated empirically with a variety of search problems, and shown to be particularly effective for searches with many constraints. Furthermore, the algorithm provides a simple framework for utilizing search heuristics. It also exhibits the same phase transition in search difficulty as found for sophisticated classical search methods, indicating that it is effectively using the problem structure.
Parallel Heuristics for Scalable Community Detection
Lu, Howard; Kalyanaraman, Anantharaman; Halappanavar, Mahantesh; Choudhury, Sutanay
2014-05-17
Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability to problems that can be solved on desktops. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose multiple heuristics that are designed to break the sequential barrier. Our heuristics are agnostic to the underlying parallel architecture. For evaluation purposes, we implemented our heuristics on shared memory (OpenMP) and distributed memory (MapReduce-MPI) machines, and tested them over real world graphs derived from multiple application domains (internet, biological, natural language processing). Experimental results demonstrate the ability of our heuristics to converge to high modularity solutions comparable to those output by the serial algorithm in nearly the same number of iterations, while also drastically reducing time to solution.
The use of geoscience methods for terrestrial forensic searches
NASA Astrophysics Data System (ADS)
Pringle, J. K.; Ruffell, A.; Jervis, J. R.; Donnelly, L.; McKinley, J.; Hansen, J.; Morgan, R.; Pirrie, D.; Harrison, M.
2012-08-01
Geoscience methods are increasingly being utilised in criminal, environmental and humanitarian forensic investigations, and the use of such methods is supported by a growing body of experimental and theoretical research. Geoscience search techniques can complement traditional methodologies in the search for buried objects, including clandestine graves, weapons, explosives, drugs, illegal weapons, hazardous waste and vehicles. This paper details recent advances in search and detection methods, with case studies and reviews. Relevant examples are given, together with a generalised workflow for search and suggested detection technique(s) table. Forensic geoscience techniques are continuing to rapidly evolve to assist search investigators to detect hitherto difficult to locate forensic targets.
Cuckoo search epistasis: a new method for exploring significant genetic interactions.
Aflakparast, M; Salimi, H; Gerami, A; Dubé, M-P; Visweswaran, S; Masoudi-Nejad, A
2014-06-01
The advent of high-throughput sequencing technology has resulted in the ability to measure millions of single-nucleotide polymorphisms (SNPs) from thousands of individuals. Although these high-dimensional data have paved the way for better understanding of the genetic architecture of common diseases, they have also given rise to challenges in developing computational methods for learning epistatic relationships among genetic markers. We propose a new method, named cuckoo search epistasis (CSE) for identifying significant epistatic interactions in population-based association studies with a case-control design. This method combines a computationally efficient Bayesian scoring function with an evolutionary-based heuristic search algorithm, and can be efficiently applied to high-dimensional genome-wide SNP data. The experimental results from synthetic data sets show that CSE outperforms existing methods including multifactorial dimensionality reduction and Bayesian epistasis association mapping. In addition, on a real genome-wide data set related to Alzheimer's disease, CSE identified SNPs that are consistent with previously reported results, and show the utility of CSE for application to genome-wide data. PMID:24549111
An intelligent method for geographic Web search
NASA Astrophysics Data System (ADS)
Mei, Kun; Yuan, Ying
2008-10-01
While the electronically available information in the World-Wide Web is explosively growing and thus increasing, the difficulty to find relevant information is also increasing for search engine user. In this paper we discuss how to constrain web queries geographically. A number of search queries are associated with geographical locations, either explicitly or implicitly. Accurately and effectively detecting the locations where search queries are truly about has huge potential impact on increasing search relevance, bringing better targeted search results, and improving search user satisfaction. Our approach focus on both in the way geographic information is extracted from the web and, as far as we can tell, in the way it is integrated into query processing. This paper gives an overview of a spatially aware search engine for semantic querying of web document. It also illustrates algorithms for extracting location from web documents and query requests using the location ontologies to encode and reason about formal semantics of geographic web search. Based on a real-world scenario of tourism guide search, the application of our approach shows that the geographic information retrieval can be efficiently supported.
Exhaustive search system and method using space-filling curves
Spires, Shannon V.
2003-10-21
A search system and method for one agent or for multiple agents using a space-filling curve provides a way to control one or more agents to cover an area of any space of any dimensionality using an exhaustive search pattern. An example of the space-filling curve is a Hilbert curve. The search area can be a physical geography, a cyberspace search area, or an area searchable by computing resources. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace.
NASA Astrophysics Data System (ADS)
Lightfoot, J.; Wyrowski, F.; Muders, D.; Boone, F.; Davis, L.; Shepherd, D.; Wilson, C.
2006-07-01
The ALMA (Atacama Large Millimeter Array) Pipeline Heuristics system is being developed to automatically reduce data taken with the standard observing modes. The goal is to make ALMA user-friendly to astronomers who are not experts in radio interferometry. The Pipeline Heuristics system must capture the expert knowledge required to provide data products that can be used without further processing. Observing modes to be processed by the system include single field interferometry, mosaics and single dish `on-the-fly' maps, and combinations of these modes. The data will be produced by the main ALMA array, the ALMA Compact Array (ACA) and single dish antennas. The Pipeline Heuristics system is being developed as a set of Python scripts. For interferometry these use as data processing engines the CASA/AIPS++ libraries and their bindings as CORBA objects within the ALMA Common Software (ACS). Initial development has used VLA and Plateau de Bure data sets to build and test a heuristic script capable of reducing single field data. In this paper we describe the reduction datapath and the algorithms used at each stage. Test results are presented. The path for future development is outlined.
Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.
Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique
2016-01-01
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems. PMID:26949383
Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems
Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique
2016-01-01
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems. PMID:26949383
A quantum heuristic algorithm for the traveling salesman problem
NASA Astrophysics Data System (ADS)
Bang, Jeongho; Ryu, Junghee; Lee, Changhyoup; Yoo, Seokwon; Lim, James; Lee, Jinhyoung
2012-12-01
We propose a quantum heuristic algorithm to solve the traveling salesman problem by generalizing the Grover search. Sufficient conditions are derived to greatly enhance the probability of finding the tours with the cheapest costs reaching almost to unity. These conditions are characterized by the statistical properties of tour costs and are shown to be automatically satisfied in the large-number limit of cities. In particular for a continuous distribution of the tours along the cost, we show that the quantum heuristic algorithm exhibits a quadratic speedup compared to its classical heuristic algorithm.
A Heuristic Approach for International Crude Oil Transportation Scheduling Problems
NASA Astrophysics Data System (ADS)
Yin, Sisi; Nishi, Tatsushi; Izuno, Tsukasa
In this paper, we propose a heuristic algorithm to solve a practical ship scheduling problem for international crude oil transportation. The problem is considered as a vehicle routing problem with split deliveries. The objective of this paper is to find an optimal assignment of tankers, a sequence of visiting and loading volume simultaneously in order to minimize the total distance satisfying the capacity of tankers. A savings-based meta-heuristic algorithm with lot sizing parameters and volume assignment heuristic is developed. The proposed method is applied to solve a case study with real data. Computational results demonstrate the effectiveness of the heuristic algorithm compared with that of human operators.
Heuristics for multiextremal optimization on a hyperrectangle: Some experiments
Hendrix, E.; Roosma, J.
1994-12-31
The problem of finding the best point of a multiextremal oracle function on a hyperrectangle given a budget of (relatively expensive) function evaluations, is considered. Global optimization can be seen as combining covering actions and local searches. The combination can be adapted during the search depending on the roughness, number of optima found. Various heuristics are formulated and outcomes of experiments are shown.
Searching for Data: Swarming Agent Method
NASA Astrophysics Data System (ADS)
Caputo, D. P.; Dolan, R.
2012-07-01
As our ability to produce data grows our ability to examine and find the useful portions of large data sets must grow as well. We present an efficient, agent based search algorithm, based on the behavior of schooling fish in the presence of predators, designed to search and/or map very large data sets. Our algorithm, which belongs to the artificial life family of algorithms, attempts to leverage swarm intelligence against the difficulty of finding valuable data within a sea of data. The agents search the data space based on a small set of simple rules which produces emergent behavior and results in an efficient and flexible algorithm, while at the same time resisting many of the short comings of other artificial life algorithms.
A novel method of wide searching scope and fast searching speed for image block matching
NASA Astrophysics Data System (ADS)
Yu, Fei; Li, Chao; Mei, Qiang; Lin, Zhe
2015-10-01
When the image matching method is used for motion estimation, the performance parameters like searching scope, searching speed, accuracy and robustness of the method normally are significant and need enhancement. In this paper, a novel method of block matching containing the wide range image block matching strategy and the strategy of multi-start points and parallel searching are presented. In the wide range matching strategy, the size of template block and searching block are same. And the average value of cumulative results by pixels in calculation is taken to ensure matching parameters can accurately represent the matching degree. In the strategy of multi-start points and parallel searching, the way of choosing starting points evenly is presented based on the characteristic of the block matching search, and the adaptive conditions and adaptive schedule is established based on the searching region. In the processing of iteration, the new strategy can not only adapt to the solution that lead the objective to the correct direction, but also adapt to the solution that have a little offset comparing with the objective. Therefore the multi-start points and parallel searching algorithm can be easy to keep from the trap of local minima effectively. The image processing system based on the DSP chip of TMS320C6415 is used to make the experiment for the video image stabilization. The results of experiment show that, the application of two methods can improve the range of motion estimation and reduce the searching computation.
Inferring heuristic classification hierarchies from natural language input
NASA Technical Reports Server (NTRS)
Hull, Richard; Gomez, Fernando
1993-01-01
A methodology for inferring hierarchies representing heuristic knowledge about the check out, control, and monitoring sub-system (CCMS) of the space shuttle launch processing system from natural language input is explained. Our method identifies failures explicitly and implicitly described in natural language by domain experts and uses those descriptions to recommend classifications for inclusion in the experts' heuristic hierarchies.
A screened automated structural search with semiempirical methods
NASA Astrophysics Data System (ADS)
Ota, Yukihiro; Ruiz-Barragan, Sergi; Machida, Masahiko; Shiga, Motoyuki
2016-03-01
We developed an interface program between a program suite for an automated search of chemical reaction pathways, GRRM, and a program package of semiempirical methods, MOPAC. A two-step structural search is proposed as an application of this interface program. A screening test is first performed by semiempirical calculations. Subsequently, a reoptimization procedure is done by ab initio or density functional calculations. We apply this approach to ion adsorption on cellulose. The computational efficiency is also shown for a GRRM search. The interface program is suitable for the structural search of large molecular systems for which semiempirical methods are applicable.
NASA Astrophysics Data System (ADS)
Aungkulanon, P.; Luangpaiboon, P.
2010-10-01
Nowadays, the engineering problem systems are large and complicated. An effective finite sequence of instructions for solving these problems can be categorised into optimisation and meta-heuristic algorithms. Though the best decision variable levels from some sets of available alternatives cannot be done, meta-heuristics is an alternative for experience-based techniques that rapidly help in problem solving, learning and discovery in the hope of obtaining a more efficient or more robust procedure. All meta-heuristics provide auxiliary procedures in terms of their own tooled box functions. It has been shown that the effectiveness of all meta-heuristics depends almost exclusively on these auxiliary functions. In fact, the auxiliary procedure from one can be implemented into other meta-heuristics. Well-known meta-heuristics of harmony search (HSA) and shuffled frog-leaping algorithms (SFLA) are compared with their hybridisations. HSA is used to produce a near optimal solution under a consideration of the perfect state of harmony of the improvisation process of musicians. A meta-heuristic of the SFLA, based on a population, is a cooperative search metaphor inspired by natural memetics. It includes elements of local search and global information exchange. This study presents solution procedures via constrained and unconstrained problems with different natures of single and multi peak surfaces including a curved ridge surface. Both meta-heuristics are modified via variable neighbourhood search method (VNSM) philosophy including a modified simplex method (MSM). The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The results show that the variant of HSA with VNSM and MSM seems to be better in terms of the mean and variance of design points and yields.
Emami, F.; Hatami, M.; Keshavarz, A. R.; Jafari, A. H.
2009-08-13
Using a combination of Runge-Kutta and Jacobi iterative method, we could solve the nonlinear Schroedinger equation describing the pulse propagation in FBGs. By decomposing the electric field to forward and backward components in fiber Bragg grating and utilizing the Fourier series analysis technique, the boundary value problem of a set of coupled equations governing the pulse propagation in FBG changes to an initial condition coupled equations which can be solved by simple Runge-Kutta method.
Job Search Methods. ERIC Digest No. 121.
ERIC Educational Resources Information Center
Wagner, Judith O.
Steps in preparing and conducting a job search include the following: (1) developing a resume; (2) locating prospective employers; (3) applying for the job; (4) interviewing; and (5) following through. The two types of resumes are the chronological and the functional. Most application forms require some basic information: name, address, and…
Heuristics for scheduling Earth observing satellites
NASA Astrophysics Data System (ADS)
Wolfe, William J.; Sorensen, Stephen E.
1999-09-01
This paper describes several methods for assigning tasks to Earth Observing Systems Satellites (EOS). We present empirical results for three heuristics, called: Priority Dispatch (PD), Look Ahead (LA), and Genetic Algorithm (GA). These heuristics progress from simple to complex, from less accurate to more accurate, and from fast to slow. We present empirical results as applied to the Window-Constrained Packing problem (WCP). The WCP is a simplified version of the EOS scheduling problem. We discuss the problem of having more than one optimization criteria. We will also discuss the relationship between the WCP and the more traditional Knapsack and Weighted Early/Tardy problems.
Application of heuristic optimization in aircraft design
NASA Astrophysics Data System (ADS)
Hu, Zhenning
Genetic algorithms and the related heuristic optimization strategies are introduced and their applications in the aircraft design are developed. Generally speaking, genetic algorithms belong to non-deterministic direct search methods, which are most powerful in finding optimum or near-optimum solutions of a very complex system where a little priori knowledge is known. Therefore they have a wide application in aerospace systems. Two major aircraft optimal design projects are illustrated in this dissertation. The first is the application of material optimization of aligned fiber laminate composites in the presence of stress concentrations. After a large number of tests on laminates with different layers, genetic algorithms find an alignment pattern in a certain range for the Boeing Co. specified material. The second project is the application of piezoelectric actuator placement on a generic tail skins to reduce the 2nd mode vibration caused by buffet, which is part of a Boeing project to control the buffet effect on aircraft. In this project, genetic algorithms are closely involved with vibration analysis and finite element analysis. Actuator optimization strategies are first tested on the theoretical beam models to gain experience, and then the generic tail model is applied. Genetic algorithms achieve a great success in optimizing up to 888 actuator parameters on the tail skins.
2011-01-01
Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These
AN EVALUATION OF A METHOD FOR IMPROVING SEARCH STRATEGIES IN A COORDINATE SEARCHING SYSTEM.
ERIC Educational Resources Information Center
HEWER, DAVID J.
SEARCH STRATEGIES WHICH CAN BE CONTINUOUSLY MODIFIED WERE DEVELOPED FOR COORDINATE SEARCHING SYSTEMS. USING THE FILES OF THE NASA TECHNOLOGY UTILIZATION PROGRAM AT THE KNOWLEDGE AVAILABILITY SYSTEMS CENTER, UNIVERSITY OF PITTSBURGH, A STUDY WAS CONDUCTED OF THE RETRIEVAL OF RELEVANT DOCUMENTS BY BOTH MANUAL AND MACHINE METHODS FOR FIVE QUESTIONS…
Automating the packing heuristic design process with genetic programming.
Burke, Edmund K; Hyde, Matthew R; Kendall, Graham; Woodward, John
2012-01-01
The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains. PMID:21609273
Searching method through biased random walks on complex networks.
Lee, Sungmin; Yook, Soon-Hyung; Kim, Yup
2009-07-01
Information search is closely related to the first-passage property of diffusing particle. The physical properties of diffusing particle is affected by the topological structure of the underlying network. Thus, the interplay between dynamical process and network topology is important to study information search on complex networks. Designing an efficient method has been one of main interests in information search. Both reducing the network traffic and decreasing the searching time have been two essential factors for designing efficient method. Here we propose an efficient method based on biased random walks. Numerical simulations show that the average searching time of the suggested model is more efficient than other well-known models. For a practical interest, we demonstrate how the suggested model can be applied to the peer-to-peer system. PMID:19658839
Real-time earthquake monitoring using a search engine method
NASA Astrophysics Data System (ADS)
Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong
2014-12-01
When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake’s parameters in <1 s after receiving the long-period surface wave data.
Real-time earthquake monitoring using a search engine method
Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong
2014-01-01
When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake’s parameters in <1 s after receiving the long-period surface wave data. PMID:25472861
Real-time earthquake monitoring using a search engine method.
Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong
2014-01-01
When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake's parameters in <1 s after receiving the long-period surface wave data. PMID:25472861
Heuristic Classification. Technical Report Number 12.
ERIC Educational Resources Information Center
Clancey, William J.
A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…
Structural Functionalism as a Heuristic Device.
ERIC Educational Resources Information Center
Chilcott, John H.
1998-01-01
Argues that structural functionalism as a method for conducting fieldwork and as a format for the analysis of ethnographic data remains a powerful model, one that is easily understood by professional educators. As a heuristic device, functionalist theory can help in the solution of a problem that is otherwise incapable of theoretical…
Heuristic Presentations: The Role of Structuring.
ERIC Educational Resources Information Center
Leron, Uri
1985-01-01
Discusses insufficiency of the linear method and some informal practices (or heuristics) used by expositors in trying to alleviate it. Uses the Cantor-Bernstein theorem to illustrate the linear proof, structuring, and the structure proof. Argues that the informal practices considered be consistently applied to the presentation of pivots and…
Heuristic reusable dynamic programming: efficient updates of local sequence alignment.
Hong, Changjin; Tewfik, Ahmed H
2009-01-01
Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm. PMID:19875856
Method and system for efficiently searching an encoded vector index
Bui, Thuan Quang; Egan, Randy Lynn; Kathmann, Kevin James
2001-09-04
Method and system aspects for efficiently searching an encoded vector index are provided. The aspects include the translation of a search query into a candidate bitmap, and the mapping of data from the candidate bitmap into a search result bitmap according to entry values in the encoded vector index. Further, the translation includes the setting of a bit in the candidate bitmap for each entry in a symbol table that corresponds to candidate of the search query. Also included in the mapping is the identification of a bit value in the candidate bitmap pointed to by an entry in an encoded vector.
Job Search as Goal-Directed Behavior: Objectives and Methods
ERIC Educational Resources Information Center
Van Hoye, Greet; Saks, Alan M.
2008-01-01
This study investigated the relationship between job search objectives (finding a new job/turnover, staying aware of job alternatives, developing a professional network, and obtaining leverage against an employer) and job search methods (looking at job ads, visiting job sites, networking, contacting employment agencies, contacting employers, and…
Methods for Measuring Search Engine Performance over Time.
ERIC Educational Resources Information Center
Bar-Ilan, Judit
2002-01-01
Introduces methods for evaluating Web search engine performance over a time period. Describes the necessary setup for such studies, illustrates the use of these measures through a specific example, and recommends the use of the measures as a guideline for testing and improving search engine functionality. (Author/LRW)
An Efficient Substring Search Method by Using Delayed Keyword Extraction.
ERIC Educational Resources Information Center
Okada, Makoto; Ando, Kazuaki; Lee, Samuel Sangkon; Hayashi, Yoshitaka; Aoe, Jun-ichi
2001-01-01
Discusses information retrieval systems and extracting appropriate keywords from documents and proposes an effective substring search method by extending a pattern matching machine for multi-keywords called delayed keyword extraction (DKE). Also proposes a construction algorithm of the retrieval structure for speeding up the substring search.…
Obtaining Maxwell's equations heuristically
NASA Astrophysics Data System (ADS)
Diener, Gerhard; Weissbarth, Jürgen; Grossmann, Frank; Schmidt, Rüdiger
2013-02-01
Starting from the experimental fact that a moving charge experiences the Lorentz force and applying the fundamental principles of simplicity (first order derivatives only) and linearity (superposition principle), we show that the structure of the microscopic Maxwell equations for the electromagnetic fields can be deduced heuristically by using the transformation properties of the fields under space inversion and time reversal. Using the experimental facts of charge conservation and that electromagnetic waves propagate with the speed of light, together with Galilean invariance of the Lorentz force, allows us to finalize Maxwell's equations and to introduce arbitrary electrodynamics units naturally.
Bidirectional citation searching to completion: an exploration of literature searching methods.
Hinde, Sebastian; Spackman, Eldon
2015-01-01
Literature reviews underpin the majority of research projects in the health sciences, and yet relatively little analysis has been published as to the most appropriate method to identify relevant literature, outside of specialist information journals. The method of applying keyword search queries to bibliographic databases using Boolean logic dominates literature reviews due to its easy application to the major online databases. However, it is recognised increasingly as being problematic where the research question cannot be clearly defined or requires an element of exploration, due to its reliance on author's use of titling and keywords and is unable to identify topics other than those defined in the search query. This paper discusses the relative merits of a systematic citation searching approach as both an alternative and a concurrent method to keyword searching. A method of citation searching, both forwards and backwards, which is iterated to form a closed loop solution, is discussed. An illustrative example is presented of both methods, applying them to the topic of the UK National Institute for Health and Care Excellence (NICE) cost-effectiveness threshold. The case study finds the citation searching approach dominates the traditional keyword searching approach, finding 76 papers of relevance, including all 15 found by the alternative approach. Conceptually, and in the example presented, it is demonstrated that the proposed method can represent a dominant strategy to the more traditional approach in some situations, highlighting that, wherever possible, it is preferential to employ multiple methods of searching. However, it is clear that a better understanding is required as to how we can most efficiently search the ever-growing sea of literature. PMID:25145803
Automated Detection of Heuristics and Biases among Pathologists in a Computer-Based System
ERIC Educational Resources Information Center
Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia
2013-01-01
The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to…
Accelerated Profile HMM Searches
Eddy, Sean R.
2011-01-01
Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the “multiple segment Viterbi” (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call “sparse rescaling”. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches. PMID:22039361
Reexamining Our Bias against Heuristics
ERIC Educational Resources Information Center
McLaughlin, Kevin; Eva, Kevin W.; Norman, Geoff R.
2014-01-01
Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources…
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.
Morris, Graham P; Simonov, Alexandr N; Mashkina, Elena A; Bordas, Rafel; Gillow, Kathryn; Baker, Ruth E; Gavaghan, David J; Bond, Alan M
2013-12-17
Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6](3-/4-) process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered parameters in all forms of data analysis encompass E(0) (reversible potential), k(0) (heterogeneous charge transfer rate constant at E(0)), α (charge transfer coefficient), Ru (uncompensated resistance), and Cdl (double layer capacitance). The automated method of analysis employed time domain optimization and Bayesian statistics. This and all other methods assumed the Butler-Volmer model applies for electron transfer kinetics, planar diffusion for mass transport, Ohm's Law for Ru, and a potential-independent Cdl model. Heuristic approaches utilize combinations of Fourier Transform filtering, sensitivity analysis, and simplex-based forms of optimization applied to resolved AC harmonics and rely on experimenter experience to assist in experiment-theory comparisons. Remarkable consistency of parameter evaluation was achieved, although the fully automated time domain method provided consistently higher α values than those based on frequency domain data analysis. The origin of this difference is that the implemented fully automated method requires a perfect model for the double layer capacitance. In contrast, the importance of imperfections in the double layer model is minimized when analysis is performed in the frequency domain. Substantial variation in k(0) values was found by analysis of the 10 data sets for this highly surface-sensitive pathologically variable [Fe(CN)6](3-/4-) process, but remarkably, all fit the quasi-reversible model satisfactorily. PMID:24160752
A constrained optimization algorithm based on the simplex search method
NASA Astrophysics Data System (ADS)
Mehta, Vivek Kumar; Dasgupta, Bhaskar
2012-05-01
In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency.
ERIC Educational Resources Information Center
Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank
2011-01-01
Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…
Kim, H.; Ko, Y.S.; Jung, K.H. )
1992-07-01
In this paper, an expert system is developed to provide a quick and best strategy of load transfer for the power system operator. This load transferring problem is then constrained by the firm and normal capacities of a bank, the fault history of a bank, and the feeder priorities. Heuristic rules which are obtained from a substation operator and both DDC (Distribution Dispatch Center) and DDC (Distribution Control Center) engineers, are incorporated in an expert system to improve the solution procedure. Furthermore, the structural rules based on the bus topology are also generated to reduce the number of switching required to reallocate the load from the busbar connected to the faulted bank to the other sections. This expert system is implemented in Prolog, and the best-first search method is adopted. To solve the combinatorial problem, list processing and recursive programming techniques are used. We also employ the pattern matching mechanism to trace the feeder connectivity.
Remarks on search methods for stable, massive, elementary particles
NASA Astrophysics Data System (ADS)
Perl, Martin L.
2001-11-01
This paper was presented at the 69th birthday celebration of Professor Eugene Commins, honoring his research achievements. These remarks are about the experimental techniques used in the search for new stable, massive particles, particles at least as massive as the electron. A variety of experimental methods such as accelerator experiments, cosmic ray studies, searches for halo particles in the galaxy and searches for exotic particles in bulk matter are described. A summary is presented of the measured limits on the existence of new stable, massive particle. .
Method and System for Object Recognition Search
NASA Technical Reports Server (NTRS)
Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)
2012-01-01
A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.
A Tabu Search WSN Deployment Method for Monitoring Geographically Irregular Distributed Events.
Aitsaadi, Nadjib; Achir, Nadjib; Boussetta, Khaled; Pujolle, Guy
2009-01-01
In this paper, we address the Wireless Sensor Network (WSN) deployment issue. We assume that the observed area is characterized by the geographical irregularity of the sensed events. Formally, we consider that each point in the deployment area is associated a differentiated detection probability threshold, which must be satisfied by our deployment method. Our resulting WSN deployment problem is formulated as a Multi-Objectives Optimization problem, which seeks to reduce the gap between the generated events detection probabilities and the required thresholds while minimizing the number of deployed sensors. To overcome the computational complexity of an exact resolution, we propose an original pseudo-random approach based on the Tabu Search heuristic. Simulations show that our proposal achieves better performances than several other approaches proposed in the literature. In the last part of this paper, we generalize the deployment problem by including the wireless communication network connectivity constraint. Thus, we extend our proposal to ensure that the resulting WSN topology is connected even if a sensor communication range takes small values. PMID:22573977
The Convolution Method in Neutrino Physics Searches
Tsakstara, V.; Kosmas, T. S.; Chasioti, V. C.; Divari, P. C.; Sinatkas, J.
2007-12-26
We concentrate on the convolution method used in nuclear and astro-nuclear physics studies and, in particular, in the investigation of the nuclear response of various neutrino detection targets to the energy-spectra of specific neutrino sources. Since the reaction cross sections of the neutrinos with nuclear detectors employed in experiments are extremely small, very fine and fast convolution techniques are required. Furthermore, sophisticated de-convolution methods are also needed whenever a comparison between calculated unfolded cross sections and existing convoluted results is necessary.
Minimization search method for data inversion
NASA Technical Reports Server (NTRS)
Fymat, A. L.
1975-01-01
Technique has been developed for determining values of selected subsets of independent variables in mathematical formulations. Required computation time increases with first power of the number of variables. This is in contrast with classical minimization methods for which computational time increases with third power of the number of variables.
A flexible transition state searching method for atmospheric reaction systems
NASA Astrophysics Data System (ADS)
Lin, Xiao-Xiao; Liu, Yi-Rong; Huang, Teng; Chen, Jiao; Jiang, Shuai; Huang, Wei
2015-04-01
The precise and rapid exploration of transition states (TSs) is a major challenge when studying atmospheric reactions due to their complexity. In this work, a Monte Carlo Transition State Search Method (MCTSSM), which integrates Monte Carlo sampling technique with transition state optimization methods using an efficient computer script, has been developed for transition state searches. The efficiency and the potential application in atmospheric reactions of this method have been demonstrated by three types of test suits related to the reactions of atmospheric volatile organic compounds (VOCs): (1) OH addition, (2) OH hydrogen-abstraction, and (3) the other reactive group (e.g. Cl, O3, NO3), especially for the reaction of β-pinene-sCI (stabilized Criegee Intermediates) with water. It was shown that the application of this method with effective restricted parameters has greatly simplified the time-consuming and tedious manual search procedure for transition state (TS) of the bimolecular reaction systems.
A Flexible Transition State Searching Method for Atmospheric Reaction Systems
Lin, Xiao-Xiao; Liu, Yi-Rong; Huang, Teng; Chen, Jiao; Jiang, Shuai; Huang, Wei
2015-04-01
The precise and rapid exploration of transition states (TSs) is a major challenge when studying atmospheric reactions due to their complexity. In this work, a Monte Carlo Transition State Search Method (MCTSSM), which integrates Monte Carlo sampling technique with transition state optimization methods using an efficient computer script, has been developed for transition state searches. The efficiency and the potential application in atmospheric reactions of this method have been demonstrated by three types of test suits related to the reactions of atmospheric volatile organic compounds (VOCs): (1) OH addition, (2) OH hydrogen-abstraction, and (3) the other reactive group (e.g. Cl, O3, NO3), especially for the reaction of β-pinene-sCI (stabilized Criegee Intermediates) with water. It was shown that the application of this method with effective restricted parameters has greatly simplified the time-consuming and tedious manual search procedure for transition state (TS) of the bimolecular reaction systems.
Heuristic dynamic complexity coding
NASA Astrophysics Data System (ADS)
Škorupa, Jozef; Slowack, Jürgen; Mys, Stefaan; Lambert, Peter; Van de Walle, Rik
2008-04-01
Distributed video coding is a new video coding paradigm that shifts the computational intensive motion estimation from encoder to decoder. This results in a lightweight encoder and a complex decoder, as opposed to the predictive video coding scheme (e.g., MPEG-X and H.26X) with a complex encoder and a lightweight decoder. Both schemas, however, do not have the ability to adapt to varying complexity constraints imposed by encoder and decoder, which is an essential ability for applications targeting a wide range of devices with different complexity constraints or applications with temporary variable complexity constraints. Moreover, the effect of complexity adaptation on the overall compression performance is of great importance and has not yet been investigated. To address this need, we have developed a video coding system with the possibility to adapt itself to complexity constraints by dynamically sharing the motion estimation computations between both components. On this system we have studied the effect of the complexity distribution on the compression performance. This paper describes how motion estimation can be shared using heuristic dynamic complexity and how distribution of complexity affects the overall compression performance of the system. The results show that the complexity can indeed be shared between encoder and decoder in an efficient way at acceptable rate-distortion performance.
System, Method and Apparatus for Conducting a Keyterm Search
NASA Technical Reports Server (NTRS)
McGreevy, Michael W. (Inventor)
2004-01-01
A keyterm search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more keyterms. Next, a gleaning model of the query is created. The gleaning model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.
System, method and apparatus for conducting a keyterm search
NASA Technical Reports Server (NTRS)
McGreevy, Michael W. (Inventor)
2004-01-01
A keyterm search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more keyterms. Next, a gleaning model of the query is created. The gleaning model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.
System, method and apparatus for conducting a phrase search
NASA Technical Reports Server (NTRS)
McGreevy, Michael W. (Inventor)
2004-01-01
A phrase search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more sequences of terms. Next, a relational model of the query is created. The relational model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.
Reliable Transition State Searches Integrated with the Growing String Method.
Zimmerman, Paul
2013-07-01
The growing string method (GSM) is highly useful for locating reaction paths connecting two molecular intermediates. GSM has often been used in a two-step procedure to locate exact transition states (TS), where GSM creates a quality initial structure for a local TS search. This procedure and others like it, however, do not always converge to the desired transition state because the local search is sensitive to the quality of the initial guess. This article describes an integrated technique for simultaneous reaction path and exact transition state search. This is achieved by implementing an eigenvector following optimization algorithm in internal coordinates with Hessian update techniques. After partial convergence of the string, an exact saddle point search begins under the constraint that the maximized eigenmode of the TS node Hessian has significant overlap with the string tangent near the TS. Subsequent optimization maintains connectivity of the string to the TS as well as locks in the TS direction, all but eliminating the possibility that the local search leads to the wrong TS. To verify the robustness of this approach, reaction paths and TSs are found for a benchmark set of more than 100 elementary reactions. PMID:26583985
Heuristic Programming of Educational - Research Activity
NASA Astrophysics Data System (ADS)
Stoev, Alexey
HEURISTIC PROGRAMMING OF EDUCATIONAL - RESEARCH ACTIVITY OF THE STUDENTS OF ASTRONOMY AT PUBLIC ASTRONOMICAL OBSERVATORIES A.Stoev Yu. Gagarin Public Astronomical Observatory Stara Zagora Bulgaria Seeking for optimal conditions of the students’ investigation skills development is exceptionally actual task in Astronomy school at Public astronomical observatory. The didactic plan of its solving is connected with a realization of the concept of the problematic approach in astronomical education. In addition different means of astronomical educative activity organization are used depending on the didactic task. In some cases they are algorithmic but in others - mainly heuristic. Educational - research skills are defined as skills of scientific method use in the conditions of seeking for educational problem solving the astronomical educational - research task. The influence of the system of heuristic programming didactic means on the process of teaching and the use of system of didactic means for out of the school education on astronomy aimed mainly to this activity rule are analyzed. In conclusion the process of optimization of the didactic conditions for students’ self-organization during the individual or collective completion of the educational - research astronomical tasks at the transition from secondary to high education.
The Use of Resistivity Methods in Terrestrial Forensic Searches
NASA Astrophysics Data System (ADS)
Wolf, R. C.; Raisuddin, I.; Bank, C.
2013-12-01
The increasing use of near-surface geophysical methods in forensic searches has demonstrated the need for further studies to identify the ideal physical, environmental and temporal settings for each geophysical method. Previous studies using resistivity methods have shown promising results, but additional work is required to more accurately interpret and analyze survey findings. The Ontario Provincial Police's UCRT (Urban Search and Rescue; Chemical, Biolgical, Radiological, Nuclear and Explosives; Response Team) is collaborating with the University of Toronto and two additional universities in a multi-year study investigating the applications of near-surface geophysical methods to terrestrial forensic searches. In the summer of 2012, on a test site near Bolton, Ontario, the OPP buried weapons, drums and pigs (naked, tarped, and clothed) to simulate clandestine graves and caches. Our study aims to conduct repeat surveys using an IRIS Syscal Junior with 48 electrode switching system resistivity-meter. These surveys will monitor changes in resistivity reflecting decomposition of the object since burial, and identify the strengths and weaknesses of resistivity when used in a rural, clandestine burial setting. Our initial findings indicate the usefulness of this method, as prominent resistivity changes have been observed. We anticipate our results will help to assist law enforcement agencies in determining the type of resistivity results to expect based on time since burial, depth of burial and state of dress of the body.
Climate adaptation heuristics and the science/policy divide
Preston, Benjamin L.; Mustelin, Johanna; Maloney, Megan C.
2013-09-05
The adaptation science enterprise has expanded rapidly in recent years, presumably in response to growth in demand for knowledge that can facilitate adaptation policy and practice. However, evidence suggests such investments in adaptation science have not necessarily translated into adaptation implementation. One potential constraint on adaptation may be the underlying heuristics that are used as the foundation for both adaptation research and practice. In this paper, we explore the adaptation academic literature with the objective of identifying adaptation heuristics, assessing the extent to which they have become entrenched within the adaptation discourse, and discussing potential weaknesses in their framing that could undermine adaptation efforts. This investigation is supported by a multi-method analysis that includes both a quantitative content analysis of the adaptation literature that evidences the use of adaptation heuristics and a qualitative analysis of the implications of such heuristics for enhancing or hindering the implementation of adaptation. Results demonstrate that a number of heuristic devices are commonly used in both the peer-reviewed adaptation literature as well as within grey literature designed to inform adaptation practitioners. Furthermore, the apparent lack of critical reflection upon the robustness of these heuristics for diverse contexts may contribute to potential cognitive bias with respect to the framing of adaptation by both researchers and practitioners. Finally, we discuss this phenomenon by drawing upon heuristic-analytic theory, which has explanatory utility in understanding both the origins of such heuristics as well as the measures that can be pursued toward the co-generation of more robust approaches to adaptation problem-solving.
Climate adaptation heuristics and the science/policy divide
Preston, Benjamin L.; Mustelin, Johanna; Maloney, Megan C.
2013-09-05
The adaptation science enterprise has expanded rapidly in recent years, presumably in response to growth in demand for knowledge that can facilitate adaptation policy and practice. However, evidence suggests such investments in adaptation science have not necessarily translated into adaptation implementation. One potential constraint on adaptation may be the underlying heuristics that are used as the foundation for both adaptation research and practice. In this paper, we explore the adaptation academic literature with the objective of identifying adaptation heuristics, assessing the extent to which they have become entrenched within the adaptation discourse, and discussing potential weaknesses in their framing thatmore » could undermine adaptation efforts. This investigation is supported by a multi-method analysis that includes both a quantitative content analysis of the adaptation literature that evidences the use of adaptation heuristics and a qualitative analysis of the implications of such heuristics for enhancing or hindering the implementation of adaptation. Results demonstrate that a number of heuristic devices are commonly used in both the peer-reviewed adaptation literature as well as within grey literature designed to inform adaptation practitioners. Furthermore, the apparent lack of critical reflection upon the robustness of these heuristics for diverse contexts may contribute to potential cognitive bias with respect to the framing of adaptation by both researchers and practitioners. Finally, we discuss this phenomenon by drawing upon heuristic-analytic theory, which has explanatory utility in understanding both the origins of such heuristics as well as the measures that can be pursued toward the co-generation of more robust approaches to adaptation problem-solving.« less
Generating effective project scheduling heuristics by abstraction and reconstitution
NASA Technical Reports Server (NTRS)
Janakiraman, Bhaskar; Prieditis, Armand
1992-01-01
A project scheduling problem consists of a finite set of jobs, each with fixed integer duration, requiring one or more resources such as personnel or equipment, and each subject to a set of precedence relations, which specify allowable job orderings, and a set of mutual exclusion relations, which specify jobs that cannot overlap. No job can be interrupted once started. The objective is to minimize project duration. This objective arises in nearly every large construction project--from software to hardware to buildings. Because such project scheduling problems are NP-hard, they are typically solved by branch-and-bound algorithms. In these algorithms, lower-bound duration estimates (admissible heuristics) are used to improve efficiency. One way to obtain an admissible heuristic is to remove (abstract) all resources and mutual exclusion constraints and then obtain the minimal project duration for the abstracted problem; this minimal duration is the admissible heuristic. Although such abstracted problems can be solved efficiently, they yield inaccurate admissible heuristics precisely because those constraints that are central to solving the original problem are abstracted. This paper describes a method to reconstitute the abstracted constraints back into the solution to the abstracted problem while maintaining efficiency, thereby generating better admissible heuristics. Our results suggest that reconstitution can make good admissible heuristics even better.
Photovoltaic maximum power point search method using a light sensor
NASA Astrophysics Data System (ADS)
Ostrowski, Mariusz
2015-05-01
The main disadvantage of PV panels is their low efficiency and non-linear current-voltage characteristic. Both of the above depend on the insolation and the temperature. That is why, it is necessary to use the maximum power point search systems. Commonly used solutions vary not only in complexity and accuracy but also in the speed of searching the maximum power point. Usually, the measurement of current and voltage is used to determine the maximum power point. The most common in literature are the perturb and observe and incremental conductance methods. The disadvantage of these solutions is the need to search across the whole current-voltage curve, which results in a significant power loss. In order to prevent it, the techniques mentioned above are combined with other methods. This procedure determines the starting point of one of the above methods and results in shortening the search time. Modern solutions use the temperature measurement to determine the open circuit voltage. The simulations show that the voltage in the maximum power point depends mainly on the temperature of the photovoltaic panel, and the current depends mainly on the lighting conditions. The proposed method uses the measurement of illuminance and calculates the current at the maximum power point, which is used as a reference signal in power conversion system. Due to the non-linearity of the light sensor and of the photovoltaic panel, the relation between them cannot be determined directly. Therefore, the proposed method use the modified correlation function to calculate current corresponding to the light.
Regarding Chilcott's "Structural Functionalism as a Heuristic Device" Heuristically.
ERIC Educational Resources Information Center
Blot, Richard K.
1998-01-01
The heuristic value of Chilcott's essay lies less in its support for structural functionalism and more in its concern to reexamine theory in the work of earlier educational anthropologists for what earlier theories and practices can add to current research. (SLD)
An explicit-solvent conformation search method using open software
Gaalswyk, Kari
2016-01-01
Computer modeling is a popular tool to identify the most-probable conformers of a molecule. Although the solvent can have a large effect on the stability of a conformation, many popular conformational search methods are only capable of describing molecules in the gas phase or with an implicit solvent model. We have developed a work-flow for performing a conformation search on explicitly-solvated molecules using open source software. This method uses replica exchange molecular dynamics (REMD) to sample the conformational states of the molecule efficiently. Cluster analysis is used to identify the most probable conformations from the simulated trajectory. This work-flow was tested on drug molecules α-amanitin and cabergoline to illustrate its capabilities and effectiveness. The preferred conformations of these molecules in gas phase, implicit solvent, and explicit solvent are significantly different. PMID:27280078
An explicit-solvent conformation search method using open software.
Gaalswyk, Kari; Rowley, Christopher N
2016-01-01
Computer modeling is a popular tool to identify the most-probable conformers of a molecule. Although the solvent can have a large effect on the stability of a conformation, many popular conformational search methods are only capable of describing molecules in the gas phase or with an implicit solvent model. We have developed a work-flow for performing a conformation search on explicitly-solvated molecules using open source software. This method uses replica exchange molecular dynamics (REMD) to sample the conformational states of the molecule efficiently. Cluster analysis is used to identify the most probable conformations from the simulated trajectory. This work-flow was tested on drug molecules α-amanitin and cabergoline to illustrate its capabilities and effectiveness. The preferred conformations of these molecules in gas phase, implicit solvent, and explicit solvent are significantly different. PMID:27280078
A method of searching LDAP directories using XQuery
NASA Astrophysics Data System (ADS)
Hesselroth, Ted
2011-12-01
A method by which an LDAP directory can be searched using XQuery is described. The strategy behind the tool consists of four steps. First the XQuery script is examined and relevant XPath expressions are extracted, determined to be sufficient to define all information needed to perform the query. Then the XPath expressions are converted into their equivalent LDAP search filters by use of the published LDAP schema of the service, and search requests are made to the LDAP host. The search results are then merged and converted to an XML document that conforms to the hierarchy of the LDAP schema. Finally, the XQuery script is executed on the working XML document by conventional means. Examples are given of application of the tool in the Open Science Grid, which for discovery purposes operates an LDAP server that contains Glue schema-based information on site configuration and authorization policies. The XQuery scripts compactly replace hundreds of lines of custom python code that relied on the unix ldapsearch utility. Installation of the tool is available through the Virtual Data Toolkit.
Alpha-beta coordination method for collective search
Goldsmith, Steven Y.
2002-01-01
The present invention comprises a decentralized coordination strategy called alpha-beta coordination. The alpha-beta coordination strategy is a family of collective search methods that allow teams of communicating agents to implicitly coordinate their search activities through a division of labor based on self-selected roles and self-determined status. An agent can play one of two complementary roles. An agent in the alpha role is motivated to improve its status by exploring new regions of the search space. An agent in the beta role is also motivated to improve its status, but is conservative and tends to remain aggregated with other agents until alpha agents have clearly identified and communicated better regions of the search space. An agent can select its role dynamically based on its current status value relative to the status values of neighboring team members. Status can be determined by a function of the agent's sensor readings, and can generally be a measurement of source intensity at the agent's current location. An agent's decision cycle can comprise three sequential decision rules: (1) selection of a current role based on the evaluation of the current status data, (2) selection of a specific subset of the current data, and (3) determination of the next heading using the selected data. Variations of the decision rules produce different versions of alpha and beta behaviors that lead to different collective behavior properties.
Cumulative Query Method for Influenza Surveillance Using Search Engine Data
Seo, Dong-Woo; Sohn, Chang Hwan; Shin, Soo-Yong; Lee, JaeHo; Yu, Maengsoo; Kim, Won Young; Lim, Kyoung Soo; Lee, Sang-Il
2014-01-01
Background Internet search queries have become an important data source in syndromic surveillance system. However, there is currently no syndromic surveillance system using Internet search query data in South Korea. Objectives The objective of this study was to examine correlations between our cumulative query method and national influenza surveillance data. Methods Our study was based on the local search engine, Daum (approximately 25% market share), and influenza-like illness (ILI) data from the Korea Centers for Disease Control and Prevention. A quota sampling survey was conducted with 200 participants to obtain popular queries. We divided the study period into two sets: Set 1 (the 2009/10 epidemiological year for development set 1 and 2010/11 for validation set 1) and Set 2 (2010/11 for development Set 2 and 2011/12 for validation Set 2). Pearson’s correlation coefficients were calculated between the Daum data and the ILI data for the development set. We selected the combined queries for which the correlation coefficients were .7 or higher and listed them in descending order. Then, we created a cumulative query method n representing the number of cumulative combined queries in descending order of the correlation coefficient. Results In validation set 1, 13 cumulative query methods were applied, and 8 had higher correlation coefficients (min=.916, max=.943) than that of the highest single combined query. Further, 11 of 13 cumulative query methods had an r value of ≥.7, but 4 of 13 combined queries had an r value of ≥.7. In validation set 2, 8 of 15 cumulative query methods showed higher correlation coefficients (min=.975, max=.987) than that of the highest single combined query. All 15 cumulative query methods had an r value of ≥.7, but 6 of 15 combined queries had an r value of ≥.7. Conclusions Cumulative query method showed relatively higher correlation with national influenza surveillance data than combined queries in the development and validation
Doppler methods of search and monitoring of exoplanets
NASA Astrophysics Data System (ADS)
Panchuk, V. E.; Klochkova, V. G.; Sachkov, M. E.; Yushkin, M. V.
2015-12-01
The main stages of the development of Doppler methods of search and study of extrasolar planetary systems (exoplanets) are described. The main instrumental and methodological effects that influence the measurement accuracy of spectral line positions in the study of exoplanets are considered. The development of the domestic spectrograph for spectroscopic monitoring with high-precision determination of radial velocities is reported. Directions for further development of high-resolution spectroscopy are discussed.
SMMH - A Parallel Heuristic for Combinatorial Optimization Problems
Domingues, Guilherme; Morie, Yoshiyuki; Gu, Feng Long; Nanri, Takeshi; Murakami, Kazuaki
2007-12-26
The process of finding one or more optimal solutions for answering combinatorial optimization problems bases itself on the use of algorithms instances. Those instances usually have to explore a very large search spaces. Heuristics search focusing on the use of High-Order Hopfield neural networks is a largely deployed technique for very large search space. It can be established a very powerful analogy towards the dynamics evolution of a physics spin-glass system while minimizing its own energy and the energy function of the network. This paper presents a new approach for solving combinatorial optimization problems through parallel simulations, based on a High-Order Hopfield neural network using MPI specification.
SMMH--A Parallel Heuristic for Combinatorial Optimization Problems
Domingues, Guilherme; Morie, Yoshiyuki; Gu, Feng Long; Nanri, Takeshi; Murakami, Kazuaki
2007-12-26
The process of finding one or more optimal solutions for answering combinatorial optimization problems bases itself on the use of algorithms instances. Those instances usually have to explore a very large search spaces. Heuristics search focusing on the use of High-Order Hopfield neural networks is a largely deployed technique for very large search space. It can be established a very powerful analogy towards the dynamics evolution of a physics spin-glass system while minimizing its own energy and the energy function of the network. This paper presents a new approach for solving combinatorial optimization problems through parallel simulations, based on a High-Order Hopfield neural network using MPI specification.
The Gaussian CLs method for searches of new physics
NASA Astrophysics Data System (ADS)
Qian, X.; Tan, A.; Ling, J. J.; Nakajima, Y.; Zhang, C.
2016-08-01
We describe a method based on the CLs approach to present results in searches of new physics, under the condition that the relevant parameter space is continuous. Our method relies on a class of test statistics developed for non-nested hypotheses testing problems, denoted by ΔT, which has a Gaussian approximation to its parent distribution when the sample size is large. This leads to a simple procedure of forming exclusion sets for the parameters of interest, which we call the Gaussian CLs method. Our work provides a self-contained mathematical proof for the Gaussian CLs method that explicitly outlines the required conditions. These conditions are milder than that required by Wilks' theorem to set confidence intervals (CIs). We illustrate the Gaussian CLs method in an example of searching for a sterile neutrino, where the CLs approach was rarely used before. We also compare data analysis results produced by the Gaussian CLs method and various CI methods to showcase their differences.
An automated efficient conformation search of L-serine by the scaled hypersphere search method
NASA Astrophysics Data System (ADS)
Kishimoto, Naoki; Harayama, Manami; Ohno, Koichi
2016-05-01
Stable conformers of L-serine were automatically explored by applications of the scaled hypersphere search (SHS) method to equilibrium structures maintaining the chemical bond skeletons of serine. Energy barriers for conformational changes of L-serine were estimated from the heights of obtained transition structures. Zero-point-corrected electronic energies and Gibbs free energies of the 24 lowest energy conformers and 21 transition structures were calculated at 100, 298, and 400 K by a composite quantum chemistry method (Gaussian-4). Relative populations of 24 conformers including nine new conformers were calculated from the Gibbs energies assuming thermal equilibrium.
Comparison of double-ended transition state search methods
NASA Astrophysics Data System (ADS)
Koslover, Elena F.; Wales, David J.
2007-10-01
While a variety of double-ended transition state search methods have been developed, their relative performance in characterizing complex multistep pathways between structurally disparate molecular conformations remains unclear. Three such methods (doubly-nudged elastic band, a string method, and a growing string method) are compared for a series of benchmarks ranging from permutational isomerizations of the seven-atom Lennard-Jones cluster (LJ7) to highly cooperative LJ38 and LJ75 rearrangements, and the folding pathways of two peptides. A database of short paths between LJ13 local minima is used to explore the effects of parameters and suggest reasonable default values. Each double-ended method was employed within the framework of a missing connection network flow algorithm to construct more complicated multistep pathways. We find that in our implementation none of the three methods definitively outperforms the others, and that their relative effectiveness is strongly system and parameter dependent.
Comparison of double-ended transition state search methods.
Koslover, Elena F; Wales, David J
2007-10-01
While a variety of double-ended transition state search methods have been developed, their relative performance in characterizing complex multistep pathways between structurally disparate molecular conformations remains unclear. Three such methods (doubly-nudged elastic band, a string method, and a growing string method) are compared for a series of benchmarks ranging from permutational isomerizations of the seven-atom Lennard-Jones cluster (LJ(7)) to highly cooperative LJ(38) and LJ(75) rearrangements, and the folding pathways of two peptides. A database of short paths between LJ(13) local minima is used to explore the effects of parameters and suggest reasonable default values. Each double-ended method was employed within the framework of a missing connection network flow algorithm to construct more complicated multistep pathways. We find that in our implementation none of the three methods definitively outperforms the others, and that their relative effectiveness is strongly system and parameter dependent. PMID:17919006
A heuristic approach to incremental and reactive scheduling
NASA Technical Reports Server (NTRS)
Odubiyi, Jide B.; Zoch, David R.
1989-01-01
An heuristic approach to incremental and reactive scheduling is described. Incremental scheduling is the process of modifying an existing schedule if the initial schedule does not meet its stated initial goals. Reactive scheduling occurs in near real-time in response to changes in available resources or the occurrence of targets of opportunity. Only minor changes are made during both incremental and reactive scheduling because a goal of re-scheduling procedures is to minimally impact the schedule. The described heuristic search techniques, which are employed by the Request Oriented Scheduling Engine (ROSE), a prototype generic scheduler, efficiently approximate the cost of reaching a goal from a given state and effective mechanisms for controlling search.
NASA Astrophysics Data System (ADS)
Mazi, K.; Koussis, A. D.; Restrepo, P. J.; Koutsoyiannis, D.
2004-05-01
A hydrologic model calibration methodology that is based on groundwater data is developed and implemented using the US Geological Survey's precipitation-runoff modelling system (PRMS) and the modular modelling system (MMS), which performs automatic calibration of parameters. The developed methodology was tested in the Akrotiri basin, Cyprus. The necessity for the groundwater-based model calibration, rather than a typical runoff-based one, arose from the very intermittent character of the runoff in the Akrotiri basin, a case often met in semi-arid regions. Introducing a datum and converting groundwater storage to head made the observable groundwater level the calibration indicator. The modelling of the Akrotiri basin leads us to conclude that groundwater level is a useful indicator for hydrological model calibration that can be potentially used in other similar situations in the absence of river flow measurements. However, the option of an automatic calibration of the complex hydrologic model PRMS by MMS did not ensure a good outcome. On the other hand, automatic optimisation, combined with heuristic expert intervention, enabled achievement of good calibration and constitutes a valuable means for saving effort and improving modelling performance. To this end, results must be scrutinised, melding the viewpoint of physical sense with mathematical efficiency criteria. Thus optimised, PRMS achieved a low simulation error, good reproduction of the historic trend of the aquifer water level evolution and reasonable physical behaviour (good hydrologic balance, Reasonable match of aquifer level evolution, good estimation of mean natural recharge rate).
NASA Astrophysics Data System (ADS)
Bai, Danyu; Zhang, Zhihai
2014-08-01
This article investigates the open-shop scheduling problem with the optimal criterion of minimising the sum of quadratic completion times. For this NP-hard problem, the asymptotic optimality of the shortest processing time block (SPTB) heuristic is proven in the sense of limit. Moreover, three different improvements, namely, the job-insert scheme, tabu search and genetic algorithm, are introduced to enhance the quality of the original solution generated by the SPTB heuristic. At the end of the article, a series of numerical experiments demonstrate the convergence of the heuristic, the performance of the improvements and the effectiveness of the quadratic objective.
Hegemony, hermeneutics, and the heuristic of hope.
Dorcy, Kathleen Shannon
2010-01-01
Hope has become a commodity, one that society expects those who suffer to invest in and one that healthcare providers are expected to promote as an outcome. In nursing research, a single hegemonic epistemology/ontology has been implemented through an exclusive hermeneutic (interpretation of data) and has resulted in hope being designated as an external objective heuristic for those who suffer. Evidence is articulated in this article for adopting a broader method of analysis and interpretation (genealogy) that can facilitate fuller apprehension of hope in the human experience of suffering and despair. PMID:20154528
Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space.
Kalathil, Shaeen; Elias, Elizabeth
2015-11-01
This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB) using canonic signed digit (CSD) coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB. PMID:26644921
Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C
2015-01-01
Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175
Using Heuristic Evaluation to Foster Visualization Analysis and Design Skills.
Sousa Santos, Beatriz; Quintino Ferreira, Beatriz; Dias, Paulo
2016-01-01
In an effort to develop visualization analysis and design skills in master's level information visualization students, the authors use a well-known analytical usability evaluation method, heuristic evaluation, with different sets of heuristics to teach students to analyze visualization applications. The proposed approach, used for three consecutive years, has successfully stimulated critical analysis and discussion sessions as well as helped raise students' awareness concerning the benefit of using systematic analysis methods and the strategies and guidelines that should be used to design visualization applications. PMID:26780763
Drake, John H; Özcan, Ender; Burke, Edmund K
2016-01-01
Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on a single candidate solution, and two candidate solutions are required for crossover, a mechanism is required to control the choice of the other solution. The frameworks we propose maintain a list of potential solutions for use in crossover. We investigate the use of such lists at two conceptual levels. First, crossover is controlled at the hyper-heuristic level where no problem-specific information is required. Second, it is controlled at the problem domain level where problem-specific information is used to produce good-quality solutions to use in crossover. A number of selection hyper-heuristics are compared using these frameworks over three benchmark libraries with varying properties for an NP-hard optimisation problem: the multidimensional 0-1 knapsack problem. It is shown that allowing crossover to be managed at the domain level outperforms managing crossover at the hyper-heuristic level in this problem domain. PMID:25635698
NASA Astrophysics Data System (ADS)
Igeta, Hideki; Hasegawa, Mikio
Chaotic dynamics have been effectively applied to improve various heuristic algorithms for combinatorial optimization problems in many studies. Currently, the most used chaotic optimization scheme is to drive heuristic solution search algorithms applicable to large-scale problems by chaotic neurodynamics including the tabu effect of the tabu search. Alternatively, meta-heuristic algorithms are used for combinatorial optimization by combining a neighboring solution search algorithm, such as tabu, gradient, or other search method, with a global search algorithm, such as genetic algorithms (GA), ant colony optimization (ACO), or others. In these hybrid approaches, the ACO has effectively optimized the solution of many benchmark problems in the quadratic assignment problem library. In this paper, we propose a novel hybrid method that combines the effective chaotic search algorithm that has better performance than the tabu search and global search algorithms such as ACO and GA. Our results show that the proposed chaotic hybrid algorithm has better performance than the conventional chaotic search and conventional hybrid algorithms. In addition, we show that chaotic search algorithm combined with ACO has better performance than when combined with GA.
ERIC Educational Resources Information Center
Yeates, Keith Owen; Bigler, Erin D.; Dennis, Maureen; Gerhardt, Cynthia A.; Rubin, Kenneth H.; Stancin, Terry; Taylor, H. Gerry; Vannatta, Kathryn
2007-01-01
The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer…
Automated unit-level testing with heuristic rules
NASA Technical Reports Server (NTRS)
Carlisle, W. Homer; Chang, Kai-Hsiung; Cross, James H.; Keleher, William; Shackelford, Keith
1990-01-01
Software testing plays a significant role in the development of complex software systems. Current testing methods generally require significant effort to generate meaningful test cases. The QUEST/Ada system is a prototype system designed using CLIPS to experiment with expert system based test case generation. The prototype is designed to test for condition coverage, and attempts to generate test cases to cover all feasible branches contained in an Ada program. This paper reports on heuristics sued by the system. These heuristics vary according to the amount of knowledge obtained by preprocessing and execution of the boolean conditions in the program.
Social biases determine spatiotemporal sparseness of ciliate mating heuristics.
Clark, Kevin B
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present
Meta-Heuristic Combining Prior Online and Offline Information for the Quadratic Assignment Problem.
Sun, Jianyong; Zhang, Qingfu; Yao, Xin
2014-03-01
The construction of promising solutions for NP-hard combinatorial optimization problems (COPs) in meta-heuristics is usually based on three types of information, namely a priori information, a posteriori information learned from visited solutions during the search procedure, and online information collected in the solution construction process. Prior information reflects our domain knowledge about the COPs. Extensive domain knowledge can surely make the search effective, yet it is not always available. Posterior information could guide the meta-heuristics to globally explore promising search areas, but it lacks local guidance capability. On the contrary, online information can capture local structures, and its application can help exploit the search space. In this paper, we studied the effects of using this information on metaheuristic's algorithmic performances for the COPs. The study was illustrated by a set of heuristic algorithms developed for the quadratic assignment problem. We first proposed an improved scheme to extract online local information, then developed a unified framework under which all types of information can be combined readily. Finally, we studied the benefits of the three types of information to meta-heuristics. Conclusions were drawn from the comprehensive study, which can be used as principles to guide the design of effective meta-heuristic in the future. PMID:23757559
An iterative search method for strain measurement in EFPI sensors
NASA Astrophysics Data System (ADS)
Ebel, W. J.; Mitchell, K. K.
2012-04-01
In this paper, a new method is given for estimating strain in extrinsic, Fabry-Perot, interferometric (EFPI) fiber-optic sensors under sinusoidal excitation at the sensor. The algorithm has a low complexity and is appropriate for low-cost applications. It is an iterative search algorithm based upon a known, sinusoidal excitation and a mean-square-error objective function. The algorithm provides an estimate of the maximum time-varying strain due to the excitation. It is shown that, for a broad range of parameters, the algorithm converges to the global minima with a high degree of probability. Empirical test results for two fiber-optic sensors with different gauge lengths along with corresponding measurements from a resistive strain gauge are given and shown to compare very well.
New results in searching for axions by astronomical methods
NASA Astrophysics Data System (ADS)
Gnedin, Yu. N.; Piotrovich, M. Yu.
2016-01-01
We discuss the astronomical methods of searching for light Goldstone bosons (axions and arions). The basic idea is to use processes of coupling between axions and photons: a) the axion decay into two photons; b) the transformation process of photons into axions (arions) in the magnetic fields of stars and also of interstellar and intergalactic media; c) the inverse process of transformations of axions (arions) which are generated into cores of stars into X-ray photons. The decaying axions affect upon the diffuse extragalactic background radiation, the brightness of the night sky and especially on the intergalactic light of clusters of galaxies due to generation of the axion radiative decay emission line. The processes (b) and (c) are strongly dependent on polarization state of photon and may produce a noticeable amount of linear polarization.
Heuristical Strategies on the Study Theme "The Unsaturated Hydrocarbons -- Alkenes"
ERIC Educational Resources Information Center
Naumescu, Adrienne Kozan; Pasca, Roxana-Diana
2011-01-01
The influence of heuristical strategies upon the level of two experimental classes is studied in this paper. The didactic experiment took place at secondary school in Cluj-Napoca, in 2008-2009 school year. The study theme "The Unsaturated Hydrocarbons--Alkenes" has been efficiently learned by using the most active methods: laboratory…
A New Method to Web Knowledge Searching and Organizating
NASA Astrophysics Data System (ADS)
Li, Shengqi
One of the fundamental support of the web knowledge vision is a agent system that enables knowledge to be published to a searchable knowledge base and later retrieved by potential users. This is the basic motivation for the UDDI standard, one of the three standards fundation current web knowledge technology. However, this aspect of the technology has been the least successful, and the few web sites that today attempt to provide a web knowledge agent facility do so using a simple cataloguing method rather than UDDI. In this paper we analyze why the agent aspect of the web knowledge vision has proven so difficult to realize in practice and outline the technical difficulties involved in setting up and maintaining useful knowledge base of web knowledge. We then describe a practical method to web knowledge agent based on automated indexing and discuss the required technological foundations. We also suggest some ideas for improving the existing standards to better support this method and web knowledge searching in general.
Heuristics Applied in the Development of Advanced Space Mission Concepts
NASA Technical Reports Server (NTRS)
Nilsen, Erik N.
1998-01-01
Advanced mission studies are the first step in determining the feasibility of a given space exploration concept. A space scientist develops a science goal in the exploration of space. This may be a new observation method, a new instrument or a mission concept to explore a solar system body. In order to determine the feasibility of a deep space mission, a concept study is convened to determine the technology needs and estimated cost of performing that mission. Heuristics are one method of defining viable mission and systems architectures that can be assessed for technology readiness and cost. Developing a viable architecture depends to a large extent upon extending the existing body of knowledge, and applying it in new and novel ways. These heuristics have evolved over time to include methods for estimating technical complexity, technology development, cost modeling and mission risk in the unique context of deep space missions. This paper examines the processes involved in performing these advanced concepts studies, and analyzes the application of heuristics in the development of an advanced in-situ planetary mission. The Venus Surface Sample Return mission study provides a context for the examination of the heuristics applied in the development of the mission and systems architecture. This study is illustrative of the effort involved in the initial assessment of an advance mission concept, and the knowledge and tools that are applied.
NASA Astrophysics Data System (ADS)
Artem'eva, L. A.
2014-12-01
The parametric problem of equilibrium programming is examined. The mathematical programming problem, the search for a saddle-point, the multicriteria search for a Pareto point, etc. are particular cases of this parametric problem. The primal and dual variants of the extragradient method are proposed as a tool for searching for equilibrium points. The convergence of both variants is analyzed.
Heuristic segmentation of a nonstationary time series
NASA Astrophysics Data System (ADS)
Fukuda, Kensuke; Eugene Stanley, H.; Nunes Amaral, Luís A.
2004-02-01
Many phenomena, both natural and human influenced, give rise to signals whose statistical properties change under time translation, i.e., are nonstationary. For some practical purposes, a nonstationary time series can be seen as a concatenation of stationary segments. However, the exact segmentation of a nonstationary time series is a hard computational problem which cannot be solved exactly by existing methods. For this reason, heuristic methods have been proposed. Using one such method, it has been reported that for several cases of interest—e.g., heart beat data and Internet traffic fluctuations—the distribution of durations of these stationary segments decays with a power-law tail. A potential technical difficulty that has not been thoroughly investigated is that a nonstationary time series with a (scalefree) power-law distribution of stationary segments is harder to segment than other nonstationary time series because of the wider range of possible segment lengths. Here, we investigate the validity of a heuristic segmentation algorithm recently proposed by Bernaola-Galván et al. [Phys. Rev. Lett. 87, 168105 (2001)] by systematically analyzing surrogate time series with different statistical properties. We find that if a given nonstationary time series has stationary periods whose length is distributed as a power law, the algorithm can split the time series into a set of stationary segments with the correct statistical properties. We also find that the estimated power-law exponent of the distribution of stationary-segment lengths is affected by (i) the minimum segment length and (ii) the ratio R≡σɛ/σx¯, where σx¯ is the standard deviation of the mean values of the segments and σɛ is the standard deviation of the fluctuations within a segment. Furthermore, we determine that the performance of the algorithm is generally not affected by uncorrelated noise spikes or by weak long-range temporal correlations of the fluctuations within segments.
Coming Alive From Nine to Five: The Career Search Method.
ERIC Educational Resources Information Center
Michelozzi, Betty Neville; Michelozzi, Peter J.
The concept of career search is envisioned as a means to personal growth rather than merely a choice of occupations. A career search program is described which sets up a basic foundation of self-assessment, exploring personal values, interests, and skills. Four inventories are described which can help individuals develop self-descriptions in terms…
Efficient GRASP based heuristics for the capacitated continuous location-allocation problem
NASA Astrophysics Data System (ADS)
Luis, Martino; Ramli, Mohammad Fadzli; Saputra, Ruswiati Surya
2015-05-01
This paper explores the np-hard capacitated continuous location-allocation problem, where the number of facilities to be located is specified and each of which has a constant capacity. Efficient greedy randomised adaptive search procedure (GRASP) based heuristics are proposed to tackle the problem. A scheme that applies the furthest distance rule (FDR) and self-adjusted threshold parameters to generate initial facility locations that are situated sparsely within GRASP framework is also put forward. The construction of the restricted candidate list (RCL) within GRASP is also guided by applying a concept of restricted regions that prevents new facility locations to be sited too close to the previous selected facility locations. The performance of the proposed GRASP heuristics is evaluated by conducting experiments using data sets taken from the literature typically used for the uncapacitated continuous location-allocation problem. The preliminary computational experiments show that the proposed methods provide encouraging solutions when compared to recently published papers. Some future research avenues on the subject are also briefly highlighted.
A Heuristic Approach to Scheduling University Timetables.
ERIC Educational Resources Information Center
Loo, E. H.; And Others
1986-01-01
Categories of facilities utilization and scheduling requirements to be considered when using a heuristic approach to timetabling are described together with a nine-step algorithm and the computerized timetabling system, Timetable Schedules System (TTS); TTS utilizes heuristic approach. An example demonstrating use of TTS and a program flowchart…
Heuristics in an Educational System Design.
ERIC Educational Resources Information Center
Imbrogno, Salvatore
Using a heuristic system design is the most cost effective means for confronting unstructured policy problems that require action in cases in which there is a limited empirical data base or a diversity of opinion concerning preferred ends and feasible means. This paper discusses heuristic principles that can serve as guides to problem solving and…
"A Heuristic for Visual Thinking in History"
ERIC Educational Resources Information Center
Staley, David J.
2007-01-01
This article details a heuristic history teachers can use in assigning and evaluating multimedia projects in history. To use this heuristic successfully, requires more than simply following the steps in the list or stages in a recipe: in many ways, it requires a reorientation in what it means to think like an historian. This article, as much as…
A Multi-Start Evolutionary Local Search for the Two-Echelon Location Routing Problem
NASA Astrophysics Data System (ADS)
Nguyen, Viet-Phuong; Prins, Christian; Prodhon, Caroline
This paper presents a new hybrid metaheuristic between a greedy randomized adaptive search procedure (GRASP) and an evolutionary/iterated local search (ELS/ILS), using Tabu list to solve the two-echelon location routing problem (LRP-2E). The GRASP uses in turn three constructive heuristics followed by local search to generate the initial solutions. From a solution of GRASP, an intensification strategy is carried out by a dynamic alternation between ELS and ILS. In this phase, each child is obtained by mutation and evaluated through a splitting procedure of giant tour followed by a local search. The tabu list, defined by two characteristics of solution (total cost and number of trips), is used to avoid searching a space already explored. The results show that our metaheuristic clearly outperforms all previously published methods on LRP-2E benchmark instances. Furthermore, it is competitive with the best meta-heuristic published for the single-echelon LRP.
General heuristics algorithms for solving capacitated arc routing problem
NASA Astrophysics Data System (ADS)
Fadzli, Mohammad; Najwa, Nurul; Masran, Hafiz
2015-05-01
In this paper, we try to determine the near-optimum solution for the capacitated arc routing problem (CARP). In general, NP-hard CARP is a special graph theory specifically arises from street services such as residential waste collection and road maintenance. By purpose, the design of the CARP model and its solution techniques is to find optimum (or near-optimum) routing cost for a fleet of vehicles involved in operation. In other words, finding minimum-cost routing is compulsory in order to reduce overall operation cost that related with vehicles. In this article, we provide a combination of various heuristics algorithm to solve a real case of CARP in waste collection and benchmark instances. These heuristics work as a central engine in finding initial solutions or near-optimum in search space without violating the pre-setting constraints. The results clearly show that these heuristics algorithms could provide good initial solutions in both real-life and benchmark instances.
Heuristic Evaluation on Mobile Interfaces: A New Checklist
Yáñez Gómez, Rosa; Cascado Caballero, Daniel; Sevillano, José-Luis
2014-01-01
The rapid evolution and adoption of mobile devices raise new usability challenges, given their limitations (in screen size, battery life, etc.) as well as the specific requirements of this new interaction. Traditional evaluation techniques need to be adapted in order for these requirements to be met. Heuristic evaluation (HE), an Inspection Method based on evaluation conducted by experts over a real system or prototype, is based on checklists which are desktop-centred and do not adequately detect mobile-specific usability issues. In this paper, we propose a compilation of heuristic evaluation checklists taken from the existing bibliography but readapted to new mobile interfaces. Selecting and rearranging these heuristic guidelines offer a tool which works well not just for evaluation but also as a best-practices checklist. The result is a comprehensive checklist which is experimentally evaluated as a design tool. This experimental evaluation involved two software engineers without any specific knowledge about usability, a group of ten users who compared the usability of a first prototype designed without our heuristics, and a second one after applying the proposed checklist. The results of this experiment show the usefulness of the proposed checklist for avoiding usability gaps even with nontrained developers. PMID:25295300
Heuristic Techniques Application In A 3-D Space
NASA Astrophysics Data System (ADS)
Mazouz, A. Kader
1989-02-01
This paper discusses the application of a heuristic technique to stack regular and irregular shapes objects on the same container or on the same pallet. The computer representation of any object is based on the recursive octree method where each unit volume element is a voxel. Then, the choice of the space taken by any shape object within the volume is made through the heuristic approach. The heuristic technique developed is an evaluation function that compares all the available spaces based on weighing factors and threshold levels. The parameters used are shape, space available, contents of the object, and dimensions. The goal is to choose the most feasible available space every time an object is ready to be stacked. The heuristic algorithm is implemented within a knowledge based system to control a flexible material handling cell. Generally the cell comprises a material handling robot, a conveyance system that brings the objects to the cell where objects are distributed randomly to the cell, a vision system to identify the objects and verify the stacking procedure, and a computer to control and initiate the decision making process to stack all shape objects on the same volume.
Gillespie, James A; Quinn, Casey
2012-01-01
Background This is a methodological study investigating the online responses to a national debate over an important health and social problem in Russia. Russia is the largest Internet market in Europe, exceeding Germany in the absolute number of users. However, Russia is unusual in that the main search provider is not Google, but Yandex. Objective This study had two main objectives. First, to validate Yandex search patterns against those provided by Google, and second, to test this method's adequacy for investigating online interest in a 2010 national debate over Russian illicit drug policy. We hoped to learn what search patterns and specific search terms could reveal about the relative importance and geographic distribution of interest in this debate. Methods A national drug debate, centering on the anti-drug campaigner Egor Bychkov, was one of the main Russian domestic news events of 2010. Public interest in this episode was accompanied by increased Internet search. First, we measured the search patterns for 13 search terms related to the Bychkov episode and concurrent domestic events by extracting data from Google Insights for Search (GIFS) and Yandex WordStat (YaW). We conducted Spearman Rank Correlation of GIFS and YaW search data series. Second, we coded all 420 primary posts from Bychkov's personal blog between March 2010 and March 2012 to identify the main themes. Third, we compared GIFS and Yandex policies concerning the public release of search volume data. Finally, we established the relationship between salient drug issues and the Bychkov episode. Results We found a consistent pattern of strong to moderate positive correlations between Google and Yandex for the terms "Egor Bychkov" (r s = 0.88, P < .001), “Bychkov” (r s = .78, P < .001) and “Khimki”(r s = 0.92, P < .001). Peak search volumes for the Bychkov episode were comparable to other prominent domestic political events during 2010. Monthly search counts were 146,689 for “Bychkov” and
Differential Search Algorithm Based Edge Detection
NASA Astrophysics Data System (ADS)
Gunen, M. A.; Civicioglu, P.; Beşdok, E.
2016-06-01
In this paper, a new method has been presented for the extraction of edge information by using Differential Search Optimization Algorithm. The proposed method is based on using a new heuristic image thresholding method for edge detection. The success of the proposed method has been examined on fusion of two remote sensed images. The applicability of the proposed method on edge detection and image fusion problems have been analysed in detail and the empirical results exposed that the proposed method is useful for solving the mentioned problems.
Heuristic Approach to the Schwarzschild Geometry
NASA Astrophysics Data System (ADS)
Visser, Matt
In this article I present a simple Newtonian heuristic for motivating a weak-field approximation for the spacetime geometry of a point particle. The heuristic is based on Newtonian gravity, the notion of local inertial frames (the Einstein equivalence principle), plus the use of Galilean coordinate transformations to connect the freely falling local inertial frames back to the "fixed stars." Because of the heuristic and quasi-Newtonian manner in which the specific choice of spacetime geometry is motivated, we are at best justified in expecting it to be a weak-field approximation to the true spacetime geometry. However, in the case of a spherically symmetric point mass the result is coincidentally an exact solution of the full vacuum Einstein field equations — it is the Schwarzschild geometry in Painlevé-Gullstrand coordinates. This result is much stronger than the well-known result of Michell and Laplace whereby a Newtonian argument correctly estimates the value of the Schwarzschild radius — using the heuristic presented in this article one obtains the entire Schwarzschild geometry. The heuristic also gives sensible results — a Riemann flat geometry — when applied to a constant gravitational field. Furthermore, a subtle extension of the heuristic correctly reproduces the Reissner-Nordström geometry and even the de Sitter geometry. Unfortunately the heuristic construction is not truly generic. For instance, it is incapable of generating the Kerr geometry or anti-de Sitter space. Despite this limitation, the heuristic does have useful pedagogical value in that it provides a simple and direct plausibility argument (not a derivation) for the Schwarzschild geometry — suitable for classroom use in situations where the full power and technical machinery of general relativity might be inappropriate. The extended heuristic provides more challenging problems — suitable for use at the graduate level.
Deterministic algorithm with agglomerative heuristic for location problems
NASA Astrophysics Data System (ADS)
Kazakovtsev, L.; Stupina, A.
2015-10-01
Authors consider the clustering problem solved with the k-means method and p-median problem with various distance metrics. The p-median problem and the k-means problem as its special case are most popular models of the location theory. They are implemented for solving problems of clustering and many practically important logistic problems such as optimal factory or warehouse location, oil or gas wells, optimal drilling for oil offshore, steam generators in heavy oil fields. Authors propose new deterministic heuristic algorithm based on ideas of the Information Bottleneck Clustering and genetic algorithms with greedy heuristic. In this paper, results of running new algorithm on various data sets are given in comparison with known deterministic and stochastic methods. New algorithm is shown to be significantly faster than the Information Bottleneck Clustering method having analogous preciseness.
NASA Astrophysics Data System (ADS)
Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.
2015-08-01
The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.
Analysis Methods for the DRIFT Dark Matter Search
NASA Astrophysics Data System (ADS)
Ayad, R.; Hyatt, M.; Hanson-Hart, Z.; Katz-Hyman, M.; Maher, P.; Posner, A.; Martoff, C. J.; Kirkpatrick, J.; Snowden-Ifft, D. P.; Lawson, T. B.; Lightfoot, P. K.; Morgan, B.; Paling, S. M.; Roberts, J. W.; Robinson, M.; Spooner, N. J. C.
2003-04-01
The DRIFT Experiment [1] is an underground search for WIMP Dark Matter using a novel detector invented for this purpose: the Negative Ion TPC (NITPC). Data is collected in the form of digitized time-records of signals received on each active anode wire of the NITPC endcap. Analysis procedures developed to characterize this data and discriminate backgrounds (x-rays, gamma rays, alpha particles) from potential Dark Matter signals (simulated with neutron elastic scattering) will be discussed. [1] Low Pressure Negative Ion TPC for Dark Matter Search. D. P. Snowden-Ifft, C. J. Martoff, J. M. Burwell, Phys Rev. D. Rapid Comm. 61, 101301 (2000)
A set-covering based heuristic algorithm for the periodic vehicle routing problem.
Cacchiani, V; Hemmelmayr, V C; Tricoire, F
2014-01-30
We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems. PMID:24748696
Hybridization of decomposition and local search for multiobjective optimization.
Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto
2014-10-01
Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems. PMID:25222724
Heuristic Modeling for TRMM Lifetime Predictions
NASA Technical Reports Server (NTRS)
Jordan, P. S.; Sharer, P. J.; DeFazio, R. L.
1996-01-01
Analysis time for computing the expected mission lifetimes of proposed frequently maneuvering, tightly altitude constrained, Earth orbiting spacecraft have been significantly reduced by means of a heuristic modeling method implemented in a commercial-off-the-shelf spreadsheet product (QuattroPro) running on a personal computer (PC). The method uses a look-up table to estimate the maneuver frequency per month as a function of the spacecraft ballistic coefficient and the solar flux index, then computes the associated fuel use by a simple engine model. Maneuver frequency data points are produced by means of a single 1-month run of traditional mission analysis software for each of the 12 to 25 data points required for the table. As the data point computations are required only a mission design start-up and on the occasion of significant mission redesigns, the dependence on time consuming traditional modeling methods is dramatically reduced. Results to date have agreed with traditional methods to within 1 to 1.5 percent. The spreadsheet approach is applicable to a wide variety of Earth orbiting spacecraft with tight altitude constraints. It will be particularly useful to such missions as the Tropical Rainfall Measurement Mission scheduled for launch in 1997, whose mission lifetime calculations are heavily dependent on frequently revised solar flux predictions.
Mixed Integer Programming and Heuristic Scheduling for Space Communication
NASA Technical Reports Server (NTRS)
Lee, Charles H.; Cheung, Kar-Ming
2013-01-01
Optimal planning and scheduling for a communication network was created where the nodes within the network are communicating at the highest possible rates while meeting the mission requirements and operational constraints. The planning and scheduling problem was formulated in the framework of Mixed Integer Programming (MIP) to introduce a special penalty function to convert the MIP problem into a continuous optimization problem, and to solve the constrained optimization problem using heuristic optimization. The communication network consists of space and ground assets with the link dynamics between any two assets varying with respect to time, distance, and telecom configurations. One asset could be communicating with another at very high data rates at one time, and at other times, communication is impossible, as the asset could be inaccessible from the network due to planetary occultation. Based on the network's geometric dynamics and link capabilities, the start time, end time, and link configuration of each view period are selected to maximize the communication efficiency within the network. Mathematical formulations for the constrained mixed integer optimization problem were derived, and efficient analytical and numerical techniques were developed to find the optimal solution. By setting up the problem using MIP, the search space for the optimization problem is reduced significantly, thereby speeding up the solution process. The ratio of the dimension of the traditional method over the proposed formulation is approximately an order N (single) to 2*N (arraying), where N is the number of receiving antennas of a node. By introducing a special penalty function, the MIP problem with non-differentiable cost function and nonlinear constraints can be converted into a continuous variable problem, whose solution is possible.
A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.
Ali, Ahmed F; Tawhid, Mohamed A
2016-01-01
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time. PMID:27217988
Heuristic approach to deriving models for gene finding.
Besemer, J; Borodovsky, M
1999-10-01
Computer methods of accurate gene finding in DNA sequences require models of protein coding and non-coding regions derived either from experimentally validated training sets or from large amounts of anonymous DNA sequence. Here we propose a new, heuristic method producing fairly accurate inhomogeneous Markov models of protein coding regions. The new method needs such a small amount of DNA sequence data that the model can be built 'on the fly' by a web server for any DNA sequence >400 nt. Tests on 10 complete bacterial genomes performed with the GeneMark.hmm program demonstrated the ability of the new models to detect 93.1% of annotated genes on average, while models built by traditional training predict an average of 93.9% of genes. Models built by the heuristic approach could be used to find genes in small fragments of anonymous prokaryotic genomes and in genomes of organelles, viruses, phages and plasmids, as well as in highly inhomogeneous genomes where adjustment of models to local DNA composition is needed. The heuristic method also gives an insight into the mechanism of codon usage pattern evolution. PMID:10481031
Deciu, Cosmin; Sun, Jun; Wall, Mark A
2007-09-01
We discuss several aspects related to load balancing of database search jobs in a distributed computing environment, such as Linux cluster. Load balancing is a technique for making the most of multiple computational resources, which is particularly relevant in environments in which the usage of such resources is very high. The particular case of the Sequest program is considered here, but the general methodology should apply to any similar database search program. We show how the runtimes for Sequest searches of tandem mass spectral data can be predicted from profiles of previous representative searches, and how this information can be used for better load balancing of novel data. A well-known heuristic load balancing method is shown to be applicable to this problem, and its performance is analyzed for a variety of search parameters. PMID:17663575
Social welfare as small-scale help: evolutionary psychology and the deservingness heuristic.
Petersen, Michael Bang
2012-01-01
Public opinion concerning social welfare is largely driven by perceptions of recipient deservingness. Extant research has argued that this heuristic is learned from a variety of cultural, institutional, and ideological sources. The present article provides evidence supporting a different view: that the deservingness heuristic is rooted in psychological categories that evolved over the course of human evolution to regulate small-scale exchanges of help. To test predictions made on the basis of this view, a method designed to measure social categorization is embedded in nationally representative surveys conducted in different countries. Across the national- and individual-level differences that extant research has used to explain the heuristic, people categorize welfare recipients on the basis of whether they are lazy or unlucky. This mode of categorization furthermore induces people to think about large-scale welfare politics as its presumed ancestral equivalent: small-scale help giving. The general implications for research on heuristics are discussed. PMID:22375300
Optimization of pressurized water reactor shuffling by simulated annealing with heuristics
Stevens, J.G.; Smith, K.S.; Rempe, K.R.; Downar, T.J.
1995-09-01
Simulated-annealing optimization of reactor core loading patterns is implemented with support for design heuristics during candidate pattern generation. The SIMAN optimization module uses the advanced nodal method of SIMULATE-3 and the full cross-section detail of CASMO-3 to evaluate accurately the neutronic performance of each candidate, resulting in high-quality patterns. The use of heuristics within simulated annealing is explored. Heuristics improve the consistency of optimization results for both fast- and slow-annealing runs with no penalty from the exclusion of unusual candidates. Thus, the heuristic application of designer judgment during automated pattern generation is shown to be effective. The capability of the SIMAN module to find and evaluate families of loading patterns that satisfy design constraints and have good objective performance within practical run times is demonstrated. The use of automated evaluations of successive cycles to explore multicycle effects of design decisions is discussed.
A spectral KRMI conjugate gradient method under the strong-Wolfe line search
NASA Astrophysics Data System (ADS)
Khadijah, Wan; Rivaie, Mohd.; Mamat, Mustafa; Jusoh, Ibrahim
2016-06-01
In this paper, a modification of spectral conjugate gradient (CG) method is proposed which combines the advantages of the spectral CG method and the RMIL method namely as spectral Khadijah-Rivaie-Mustafa-Ibrahim (SKRMI) to solve unconstrained optimization problems. Based on inexact line searches, the objective function generates a sufficient descent direction and the global convergence property for the proposed method has been proved. Moreover, the method reduces to the standard RMIL method if exact line search is applied. Numerical results are also presented to examine the efficiency of the proposed method.
NASA Technical Reports Server (NTRS)
Mengshoel, Ole J.; Roth, Dan; Wilkins, David C.
2001-01-01
Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that
The Saccharomyces Genome Database: Advanced Searching Methods and Data Mining.
Cherry, J Michael
2015-12-01
At the core of the Saccharomyces Genome Database (SGD) are chromosomal features that encode a product. These include protein-coding genes and major noncoding RNA genes, such as tRNA and rRNA genes. The basic entry point into SGD is a gene or open-reading frame name that leads directly to the locus summary information page. A keyword describing function, phenotype, selective condition, or text from abstracts will also provide a door into the SGD. A DNA or protein sequence can be used to identify a gene or a chromosomal region using BLAST. Protein and DNA sequence identifiers, PubMed and NCBI IDs, author names, and function terms are also valid entry points. The information in SGD has been gathered and is maintained by a group of scientific biocurators and software developers who are devoted to providing researchers with up-to-date information from the published literature, connections to all the major research resources, and tools that allow the data to be explored. All the collected information cannot be represented or summarized for every possible question; therefore, it is necessary to be able to search the structured data in the database. This protocol describes the YeastMine tool, which provides an advanced search capability via an interactive tool. The SGD also archives results from microarray expression experiments, and a strategy designed to explore these data using the SPELL (Serial Pattern of Expression Levels Locator) tool is provided. PMID:26631124
Scheduling constrained tools using heuristic techniques
NASA Astrophysics Data System (ADS)
Maram, Venkataramana; Rahman, Syariza Abdul; Maram, Sandhya Rani
2015-12-01
One of the main challenge to the current manufacturing production planning is to provide schedules of operations to maximize resource utilization to yield highest overall productivity. This is achieved by scheduling available resources to activities. There can be many different real time scenarios with different combination of input resources to produce parts. In this paper, the problem is simplified to single machine with individual process times and due dates to represent the real world scheduling problem. The main objective function is to minimize the total tardiness or late jobs. Nearest greedy method of assignment problem algorithm is used to find the initial solution followed by Simulated Annealing (SA) algorithm for the improvement part. Simulated Annealing is one of the meta-heuristic techniques in solving combinatorial optimization problem. The general purpose Microsoft Visual C++ is used to developed algorithm for finding the best solution. The proposed hybrid approach able to generate best schedule in 7th and optimal in 170th iteration with tardiness 8 and 7 hours respectively.
Bflinks: Reliable Bugfix Links via Bidirectional References and Tuned Heuristics
2014-01-01
Background. Data from software version archives and defect databases can be used for defect insertion circumstance analysis and defect prediction. The first step in such analyses is identifying defect-correcting changes in the version archive (bugfix commits) and enriching them with additional metadata by establishing bugfix links to corresponding entries in the defect database. Candidate bugfix commits are typically identified via heuristic string matching on the commit message. Research Questions. Which filters could be used to obtain a set of bugfix links? How to tune their parameters? What accuracy is achieved? Method. We analyze a modular set of seven independent filters, including new ones that make use of reverse links, and evaluate visual heuristics for setting cutoff parameters. For a commercial repository, a product expert manually verifies over 2500 links to validate the results with unprecedented accuracy. Results. The heuristics pick a very good parameter value for five filters and a reasonably good one for the sixth. The combined filtering, called bflinks, provides 93% precision and only 7% results loss. Conclusion. Bflinks can provide high-quality results and adapts to repositories with different properties. PMID:27433506
Earthdata Search: Methods for Improving Data Discovery, Visualization, and Access
NASA Astrophysics Data System (ADS)
Quinn, P.; Pilone, D.; Crouch, M.; Siarto, J.; Sun, B.
2015-12-01
In a landscape of heterogeneous data from diverse sources and disciplines, producing useful tools poses a significant challenge. NASA's Earthdata Search application tackles this challenge, enabling discovery and inter-comparison of data across the wide array of scientific disciplines that use NASA Earth observation data. During this talk, we will give a brief overview of the application, and then share our approach for understanding and satisfying the needs of users from several disparate scientific communities. Our approach involves: - Gathering fine-grained metrics to understand user behavior - Using metrics to quantify user success - Combining metrics, feedback, and user research to understand user needs - Applying professional design toward addressing user needs - Using metrics and A/B testing to evaluate the viability of changes - Providing enhanced features for services to promote adoption - Encouraging good metadata quality and soliciting feedback for metadata issues - Open sourcing the application and its components to allow it to serve more users
NASA Technical Reports Server (NTRS)
Weaver, Johnathan M.
1993-01-01
A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.
A comparison of field-based similarity searching methods: CatShape, FBSS, and ROCS.
Moffat, Kirstin; Gillet, Valerie J; Whittle, Martin; Bravi, Gianpaolo; Leach, Andrew R
2008-04-01
Three field-based similarity methods are compared in retrospective virtual screening experiments. The methods are the CatShape module of CATALYST, ROCS, and an in-house program developed at the University of Sheffield called FBSS. The programs are used in both rigid and flexible searches carried out in the MDL Drug Data Report. UNITY 2D fingerprints are also used to provide a comparison with a more traditional approach to similarity searching, and similarity based on simple whole-molecule properties is used to provide a baseline for the more sophisticated searches. Overall, UNITY 2D fingerprints and ROCS with the chemical force field option gave comparable performance and were superior to the shape-only 3D methods. When the flexible methods were compared with the rigid methods, it was generally found that the flexible methods gave slightly better results than their respective rigid methods; however, the increased performance did not justify the additional computational cost required. PMID:18351728
A new method to improve network topological similarity search: applied to fold recognition
Lhota, John; Hauptman, Ruth; Hart, Thomas; Ng, Clara; Xie, Lei
2015-01-01
Motivation: Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework—Enrichment of Network Topological Similarity (ENTS)—to improve the performance of large scale similarity searches in bioinformatics. Results: We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network. Availability and implementation: Source code freely available upon request Contact: lxie@iscb.org PMID:25717198
NASA Astrophysics Data System (ADS)
Rocha, Humberto; Dias, Joana M.; Ferreira, Brígida C.; Lopes, Maria C.
2013-05-01
Generally, the inverse planning of radiation therapy consists mainly of the fluence optimization. The beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) consists of selecting appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance better organ sparing and to improve tumor coverage. However, in clinical practice, most of the time, beam directions continue to be manually selected by the treatment planner without objective and rigorous criteria. The goal of this paper is to introduce a novel approach that uses beam’s-eye-view dose ray tracing metrics within a pattern search method framework in the optimization of the highly non-convex BAO problem. Pattern search methods are derivative-free optimization methods that require a few function evaluations to progress and converge and have the ability to better avoid local entrapment. The pattern search method framework is composed of a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and ensures the convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Beam’s-eye-view dose metrics assign a score to each radiation beam direction and can be used within the pattern search framework furnishing a priori knowledge of the problem so that directions with larger dosimetric scores are tested first. A set of clinical cases of head-and-neck tumors treated at the Portuguese Institute of Oncology of Coimbra is used to discuss the potential of this approach in the optimization of the BAO problem.
The Stanford Cluster Search: Scope, Method, and Preliminary Results
NASA Astrophysics Data System (ADS)
Willick, Jeffrey A.; Thompson, Keith L.; Mathiesen, Benjamin F.; Perlmutter, Saul; Knop, Robert A.; Hill, Gary J.
2001-06-01
We describe the scientific motivation behind, and the methodology of, the Stanford Cluster Search (StaCS), a program to compile a catalog of optically selected galaxy clusters at intermediate and high (0.3<~z<~1) redshifts. The clusters are identified using a matched filter algorithm applied to deep CCD images covering ~60 deg2 of sky. These images are obtained from several data archives, principally that of the Berkeley Supernova Cosmology Project of Perlmutter et al. Potential clusters are confirmed with spectroscopic observations at the 9.2 m Hobby-Eberly Telescope. Follow-up observations at optical, submillimeter, and X-ray wavelengths are planned in order to estimate cluster masses. Our long-term scientific goal is to measure the cluster number density as a function of mass and redshift, n(M, z), which is sensitive to the cosmological density parameter Ωm and the amplitude of density fluctuations σ8. The combined data set will contain clusters ranging over an order of magnitude in mass and allow constraints on these parameters accurate to ~10%. We present our first spectroscopically confirmed cluster candidates and describe how to access them electronically. The Hobby-Eberly Telescope (HET) is a joint project of the University of Texas at Austin, the Pennsylvania State University, Stanford University, Ludwig-Maximillians-Universität München, and Georg-August-Universität Göttingen. The HET is named in honor of its principal benefactors, William P. Hobby and Robert E. Eberly.
Hybrid Evolutionary-Heuristic Algorithm for Capacitor Banks Allocation
NASA Astrophysics Data System (ADS)
Barukčić, Marinko; Nikolovski, Srete; Jović, Franjo
2010-11-01
The issue of optimal allocation of capacitor banks concerning power losses minimization in distribution networks are considered in this paper. This optimization problem has been recently tackled by application of contemporary soft computing methods such as: genetic algorithms, neural networks, fuzzy logic, simulated annealing, ant colony methods, and hybrid methods. An evolutionaryheuristic method has been proposed for optimal capacitor allocation in radial distribution networks. An evolutionary method based on genetic algorithm is developed. The proposed method has a reduced number of parameters compared to the usual genetic algorithm. A heuristic stage is used for improving the optimal solution given by the evolutionary stage. A new cost-voltage node index is used in the heuristic stage in order to improve the quality of solution. The efficiency of the proposed two-stage method has been tested on different test networks. The quality of solution has been verified by comparison tests with other methods on the same test networks. The proposed method has given significantly better solutions for time dependent load in the 69-bus network than found in references.
Nonlinear multi-agent path search method based on OFDM communication
NASA Astrophysics Data System (ADS)
Sato, Masatoshi; Igarashi, Yusuke; Tanaka, Mamoru
This paper presents novel shortest paths searching system based on analog circuit analysis which is called sequential local current comparison method on alternating-current (AC) circuit (AC-SLCC). Local current comparison (LCC) method is a path searching method where path is selected in the direction of the maximum current in a direct-current (DC) resistive circuit. Since a plurality of shortest paths searching by LCC method can be done by solving the current distribution on the resistive circuit analysis, the shortest path problem can be solved at supersonic speed. AC-SLCC method is a novel LCC method with orthogonal frequency division multiplexing (OFDM) communication on AC circuit. It is able to send data with the shortest path and without major data loss, and this suggest the possibility of application to various things (especially OFDM communication techniques).
A new type of descent conjugate gradient method with exact line search
NASA Astrophysics Data System (ADS)
Hajar, Nurul; Mamat, Mustafa; Rivaie, Mohd.; Jusoh, Ibrahim
2016-06-01
Nowadays, conjugate gradient (CG) methods are impressive for solving nonlinear unconstrained optimization problems. In this paper, a new CG method is proposed and analyzed. This new CG method satisfies descent condition and its global convergence is established using exact line search. Numerical results show that this new CG method substantially outperforms the previous CG methods. This new CG method is considered robust, efficient and provided faster and stable convergence.
NASA Astrophysics Data System (ADS)
Christober, C.; Rajan, Asir
2011-01-01
This paper presents a new approach to solve the short-term unit commitment problem using An Evolutionary Programming Based tabu search method with cooling and banking constraints. Numerical results are shown comparing the cost solutions and computation time obtained by using the evolutionary programming method and other conventional methods like dynamic programming, lagrangian relaxation.
Display format, highlight validity, and highlight method: Their effects on search performance
NASA Technical Reports Server (NTRS)
Donner, Kimberly A.; Mckay, Tim D.; Obrien, Kevin M.; Rudisill, Marianne
1991-01-01
Display format and highlight validity were shown to affect visual display search performance; however, these studies were conducted on small, artificial displays of alphanumeric stimuli. A study manipulating these variables was conducted using realistic, complex Space Shuttle information displays. A 2x2x3 within-subjects analysis of variance found that search times were faster for items in reformatted displays than for current displays. Responses to valid applications of highlight were significantly faster than responses to non or invalidly highlighted applications. The significant format by highlight validity interaction showed that there was little difference in response time to both current and reformatted displays when the highlight validity was applied; however, under the non or invalid highlight conditions, search times were faster with reformatted displays. A separate within-subject analysis of variance of display format, highlight validity, and several highlight methods did not reveal a main effect of highlight method. In addition, observed display search times were compared to search time predicted by Tullis' Display Analysis Program. Benefits of highlighting and reformatting displays to enhance search and the necessity to consider highlight validity and format characteristics in tandem for predicting search performance are discussed.
NASA Technical Reports Server (NTRS)
Wheeler, Ward C.
2003-01-01
The problem of determining the minimum cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete (Wang and Jiang, 1994). Traditionally, point estimations of hypothetical ancestral sequences have been used to gain heuristic, upper bounds on cladogram cost. These include procedures with such diverse approaches as non-additive optimization of multiple sequence alignment, direct optimization (Wheeler, 1996), and fixed-state character optimization (Wheeler, 1999). A method is proposed here which, by extending fixed-state character optimization, replaces the estimation process with a search. This form of optimization examines a diversity of potential state solutions for cost-efficient hypothetical ancestral sequences and can result in greatly more parsimonious cladograms. Additionally, such an approach can be applied to other NP-complete phylogenetic optimization problems such as genomic break-point analysis. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.
Wheeler, Ward C
2003-08-01
The problem of determining the minimum cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete (Wang and Jiang, 1994). Traditionally, point estimations of hypothetical ancestral sequences have been used to gain heuristic, upper bounds on cladogram cost. These include procedures with such diverse approaches as non-additive optimization of multiple sequence alignment, direct optimization (Wheeler, 1996), and fixed-state character optimization (Wheeler, 1999). A method is proposed here which, by extending fixed-state character optimization, replaces the estimation process with a search. This form of optimization examines a diversity of potential state solutions for cost-efficient hypothetical ancestral sequences and can result in greatly more parsimonious cladograms. Additionally, such an approach can be applied to other NP-complete phylogenetic optimization problems such as genomic break-point analysis. PMID:14531408
An efficient similarity search based on indexing in large DNA databases.
Jeong, In-Seon; Park, Kyoung-Wook; Kang, Seung-Ho; Lim, Hyeong-Seok
2010-04-01
Index-based search algorithms are an important part of a genomic search, and how to construct indices is the key to an index-based search algorithm to compute similarities between two DNA sequences. In this paper, we propose an efficient query processing method that uses special transformations to construct an index. It uses small storage and it rapidly finds the similarity between two sequences in a DNA sequence database. At first, a sequence is partitioned into equal length windows. We select the likely subsequences by computing Hamming distance to query sequence. The algorithm then transforms the subsequences in each window into a multidimensional vector space by indexing the frequencies of the characters, including the positional information of the characters in the subsequences. The result of our experiments shows that the algorithm has faster run time than other heuristic algorithms based on index structure. Also, the algorithm is as accurate as those heuristic algorithms. PMID:20418167
A modification of classical conjugate gradient method using strong Wolfe line search
NASA Astrophysics Data System (ADS)
Shoid, Syazni; Rivaie, Mohd.; Mamat, Mustafa
2016-06-01
Recently many researches try to develop and improve the Conjugate Gradient (CG) methods because of its convergence properties and low computation costing. In this paper, another CG coefficient (βk) will be proposed which is categorized as modification in such a way to improve the performance of the classical CG methods. This paper is focused on generating βk with several desirable properties: (1) generate descent search direction at each iterations; and (2) converge globally by using strong Wolfe line search. Numerical comparisons of three CG methods show the robustness and the efficiency of the new method in solving all given problems.
Program for searching for semiempirical parameters by the MNDO method
Bliznyuk, A.A.; Voityuk, A.A.
1987-09-01
The authors describe an program for optimizing atomic models constructed using the MNDO method which varies not only the parameters but also the scope for simple changes in the calculation scheme. The target function determines properties such as formation enthalpies, dipole moments, ionization potentials, and geometrical parameters. Software used to minimize the target function is based on the simplex method on the Nelder-Mead algorithm and on the Fletcher variable-metric method. The program is written in FORTRAN IV and implemented on the ES computer.
Heuristic optimization in penumbral image for high resolution reconstructed image
Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.
2010-10-15
Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
NASA Technical Reports Server (NTRS)
Lee, Charles H.; Cheung, Kar-Ming
2012-01-01
In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.
A review of the scientific rationale and methods used in the search for other planetary systems
NASA Technical Reports Server (NTRS)
Black, D. C.
1985-01-01
Planetary systems appear to be one of the crucial links in the chain leading from simple molecules to living systems, particularly complex (intelligent?) living systems. Although there is currently no observational proof of the existence of any planetary system other than our own, techniques are now being developed which will permit a comprehensive search for other planetary systems. The scientific rationale for and methods used in such a search effort are reviewed here.
Cooperative system and method using mobile robots for testing a cooperative search controller
Byrne, Raymond H.; Harrington, John J.; Eskridge, Steven E.; Hurtado, John E.
2002-01-01
A test system for testing a controller provides a way to use large numbers of miniature mobile robots to test a cooperative search controller in a test area, where each mobile robot has a sensor, a communication device, a processor, and a memory. A method of using a test system provides a way for testing a cooperative search controller using multiple robots sharing information and communicating over a communication network.
A speaker change detection method based on coarse searching
NASA Astrophysics Data System (ADS)
Zhang, Xue-yuan; He, Qian-hua; Li, Yan-xiong; He, Jun
2013-03-01
The conventional speaker change detection (SCD) method using Bayesian Information Criterion (BIC) has been widely used. However, its performance relies on the choice of penalty factor and suffers from mass calculation. The twostep SCD is less time consuming but generates more detection errors. The limitation of conventional method's performance originates from the two adjacent data windows. We propose a strategy that inserts an interval between the two adjacent fixed-size data windows in each analysis window. The dissimilarity value between the data windows is regarded as the probability of a speaker identity change within the interval area. Then this analysis window is slid along the audio by a large step to locate the areas where speaker change points may appear. Afterwards we only focus on these areas and locate precisely where the change points are. Other areas where a speaker change point unlikely appears are abandoned. The proposed method is computationally efficient and more robust to noise and penalty factor compared with conventional method. Evaluated on the corpus of China Central Television (CCTV) news, the proposed method obtains 74.18% reduction in calculation time and 22.24% improvement in F1-measure compared with the conventional approach.
Draw: A Heuristic for Expressive Writing.
ERIC Educational Resources Information Center
Taylor, Michael
1985-01-01
Proposes a heuristic to generate specific and vivid phrasing and to draw on the right hemisphere of the brain for the substance of the essay. Describes stages of process as DRAW (Delineate, Ruminate, Analogize, and Write). Emphasizes creative description and expressive language rather than generation of ideas. (JG)
Investigating Heuristic Evaluation: A Case Study.
ERIC Educational Resources Information Center
Goldman, Kate Haley; Bendoly, Laura
When museum professionals speak of evaluating a web site, they primarily mean formative evaluation, and by that they primarily mean testing the usability of the site. In the for-profit world, usability testing is a multi-million dollar industry, while non-profits often rely on far too few dollars to do too much. Hence, heuristic evaluation is one…
The Heuristic Interpretation of Box Plots
ERIC Educational Resources Information Center
Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim
2013-01-01
Box plots are frequently used, but are often misinterpreted by students. Especially the area of the box in box plots is often misinterpreted as representing number or proportion of observations, while it actually represents their density. In a first study, reaction time evidence was used to test whether heuristic reasoning underlies this…
Local search strategies for equational satisfiability.
Keefe, K.
2004-09-21
The search for models of an algebra is an important and demanding aspect of automated reasoning. Typically, a model is represented in the form of a matrix or a set of matrices. When a model is found that satisfies all the given theorems of an algebra, it is called a solution model. This paper considers algebras that can be represented by using a single operation, by way of the Sheffer stroke. The characteristic of needing only one operation to represent an algebra reduces the problem by requiring a search through all instances of a single matrix. This search is simple when the domain size is small, say 2, but for a larger domain size, say 10, the search space increases dramatically. Clearly, a method other than a brute-force, global search is desirable. Most modern model-finding programs use a global search; instead of checking every possible matrix, however a set of heuristics is used that allows the search space to be dramatically smaller and thus increases the likelihood of reaching a solution. An alternative approach is local search. This paper discusses several local search strategies that were applied to the problem of equational satisfiability.
(Re)searching Methods: Reading Fiction in Literary Response Groups
ERIC Educational Resources Information Center
Janzen, Melanie D.
2015-01-01
The trouble with education research is that the research is burdened with trouble before it begins. Working as a poststructural education researcher and engaged in a recent research project that sought to engage with questions of teacher identity, I employed an alternative data elicitation method of literary response groups--similar to that of…
Searching for triatomines. A new method for field search using UV light.
Catalá, Silvia
2010-10-01
Detection of triatomine bugs within a house is essential for the estimation of Chagas disease transmission risk and for evaluating the success of insecticidal control attempts. Small residual populations could represent an important risk but are difficult to detect by time manual sampling. Faecal marks from triatomines are clearly detectable with an ultraviolet (UV) light on most of the materials frequently used in rural buildings. A new method for finding triatomines is proposed here, based on the unexplored property of faeces to fluoresce when exposed to UV light. PMID:20457119
A Variable-Selection Heuristic for K-Means Clustering.
ERIC Educational Resources Information Center
Brusco, Michael J.; Cradit, J. Dennis
2001-01-01
Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)
Heuristics Made Easy: An Effort-Reduction Framework
ERIC Educational Resources Information Center
Shah, Anuj K.; Oppenheimer, Daniel M.
2008-01-01
In this article, the authors propose a new framework for understanding and studying heuristics. The authors posit that heuristics primarily serve the purpose of reducing the effort associated with a task. As such, the authors propose that heuristics can be classified according to a small set of effort-reduction principles. The authors use this…
Heuristic Diagrams as a Tool to Teach History of Science
ERIC Educational Resources Information Center
Chamizo, Jose A.
2012-01-01
The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The…
Methods and means used in programming intelligent searches of technical documents
NASA Technical Reports Server (NTRS)
Gross, David L.
1993-01-01
In order to meet the data research requirements of the Safety, Reliability & Quality Assurance activities at Kennedy Space Center (KSC), a new computer search method for technical data documents was developed. By their very nature, technical documents are partially encrypted because of the author's use of acronyms, abbreviations, and shortcut notations. This problem of computerized searching is compounded at KSC by the volume of documentation that is produced during normal Space Shuttle operations. The Centralized Document Database (CDD) is designed to solve this problem. It provides a common interface to an unlimited number of files of various sizes, with the capability to perform any diversified types and levels of data searches. The heart of the CDD is the nature and capability of its search algorithms. The most complex form of search that the program uses is with the use of a domain-specific database of acronyms, abbreviations, synonyms, and word frequency tables. This database, along with basic sentence parsing, is used to convert a request for information into a relational network. This network is used as a filter on the original document file to determine the most likely locations for the data requested. This type of search will locate information that traditional techniques, (i.e., Boolean structured key-word searching), would not find.
A Novel Searching Method for Distribution Network Topology to Maximize Outputs of PV Clusters
NASA Astrophysics Data System (ADS)
Sato, Tsunaki; Saitoh, Hiroumi
This paper proposes a novel searching method for radial distribution network to maximize outputs of PV generators. When a lot of PV generators are connected to distribution network, it is necessary to control PV outputs to keep the voltage within the regulated range of power quality. The aim of the paper is to find the optimal topology, that is the state of section switches so as to maximize the total PV outputs. This problem becomes a combinatorial optimization one and the exhaustive search results in enormous computation time. In this paper, a novel searching method is proposed which is based on the replacement of the complex combinatorial optimization problem with a minimization problem regarding with voltage profile of distribution network. The features of the proposed method are to utilize the relation between the total outputs of PV generators and the voltage profile, the superposition of radial electric circuit and a sequential algorithm for search in an optimal topology. In order to verify the proposed method, the comparison study has been done by using two distribution network models. As the result, there is possibility that the proposed method can find sub optimal topology in a short time compared with tabu search approach.
Applications of Principled Search Methods in Climate Influences and Mechanisms
NASA Technical Reports Server (NTRS)
Glymour, Clark
2005-01-01
Forest and grass fires cause economic losses in the billions of dollars in the U.S. alone. In addition, boreal forests constitute a large carbon store; it has been estimated that, were no burning to occur, an additional 7 gigatons of carbon would be sequestered in boreal soils each century. Effective wildfire suppression requires anticipation of locales and times for which wildfire is most probable, preferably with a two to four week forecast, so that limited resources can be efficiently deployed. The United States Forest Service (USFS), and other experts and agencies have developed several measures of fire risk combining physical principles and expert judgment, and have used them in automated procedures for forecasting fire risk. Forecasting accuracies for some fire risk indices in combination with climate and other variables have been estimated for specific locations, with the value of fire risk index variables assessed by their statistical significance in regressions. In other cases, the MAPSS forecasts [23, 241 for example, forecasting accuracy has been estimated only by simulated data. We describe alternative forecasting methods that predict fire probability by locale and time using statistical or machine learning procedures trained on historical data, and we give comparative assessments of their forecasting accuracy for one fire season year, April- October, 2003, for all U.S. Forest Service lands. Aside from providing an accuracy baseline for other forecasting methods, the results illustrate the interdependence between the statistical significance of prediction variables and the forecasting method used.
NASA Astrophysics Data System (ADS)
Yu, Fei; Hui, Mei; Han, Wei; Wang, Peng; Dong, Li-quan; Zhao, Yue-jin
2010-12-01
Image block matching is one of the motion estimation methods for video inter-frame coding and digital image stabilization. The methods used for matching and searching will greatly affect the accuracy and speed of block matching. The block matching method based on the oblique vectors is suggested in this paper where matching parameters contain both horizontal and vertical vectors in the image blocks at the same time. Improved matching information can be obtained after making correlative calculations in the oblique direction. A novel search method of matching block based on the idea of simulated annealing is presented in this paper to improve the searching speed, accuracy and robustness in the fast operation of the block-matching motion estimation. The simulated annealing algorithm can easily escape from the trap of local minima effectively. With the two methods the block matching can be used for motion estimation at the real-time image processing system and high estimation accuracy can be achieved. An image stabilization system based on DSP (Digital Signal Processing) system is developed to verify this algorithm. Results show that both the matching accuracy and the search speed are improved with the methods presented.
NASA Technical Reports Server (NTRS)
Jackson, G. A.
1972-01-01
A parameter identification method is presented which combines the best features of two well-established, existing methods: Continuous Parameter Tracking and Acceleration Search (Partan). In this paper the equations are developed for the general n-parameter identification problem, and results are given for a specific two parameter application.
Using Heuristic Algorithms to Optimize Observing Target Sequences
NASA Astrophysics Data System (ADS)
Sosnowska, D.; Ouadahi, A.; Buchschacher, N.; Weber, L.; Pepe, F.
2014-05-01
The preparation of observations is normally carried out at the telescope by the visiting observer. In order to help the observer, we propose several algorithms to automatically optimize the sequence of targets. The optimization consists of assuring that all the chosen targets are observable within the given time interval, and to find their best execution order in terms of the observation quality and the shortest telescope displacement time. Since an exhaustive search is too expensive in time, we researched heuristic algorithms, specifically: Min-Conflict, Non-Sorting Genetic Algorithms and Simulated Annealing. Multiple metaheuristics are used in parallel to swiftly give an approximation of the best solution, with all the constraints satisfied and the total execution time minimized. The optimization process has a duration on the order of tens of seconds, allowing for quick re-adaptation in case of changing atmospheric conditions. The graphical user interface allows the user to control the parameters of the optimization process. Therefore, the search can be adjusted in real time. The module was coded in a way to allow easily the addition of new constraints, and thus ensure its compatibility with different instruments. For now, the application runs as a plug-in to the observation preparation tool called New Short Term Scheduler, which is used on three spectrographs dedicated to the exoplanets search: HARPS at the La Silla observatory, HARPS North at the La Palma observatory and SOPHIE at the Observatoire de Haute-Provence.
Instruments and methods to search for extraterrestrial life
NASA Astrophysics Data System (ADS)
Hoover, Richard B.
2015-09-01
Is Life restricted to the Planet Earth? or Does life exist elsewhere in the Cosmos? The existence of extraterrestrial life is the fundamental question of Astrobiology. Detecting evidence for living organisms beyond our planet is even more difficult than finding fossilized remains of ancient organisms. Microbiological investigations during the past century have established the fundamental physical and chemical requirements and limits for life on Earth. It is now known that life requires only water, a source of energy, and a small suite of biogenic elements under a surprisingly wide range of environmental conditions. The discovery that microbial extremophiles live and grow over a very broad span of temperature, pH, salinity, pressure and radiation levels has greatly enhanced the possibility that life may be present on many bodies of our Solar System. Recent discoveries by Space Missions and Rovers have invalidated many long held paradigms regarding the distribution of water, organic chemicals and the possibility of life elsewhere in the Cosmos. This paper considers the discovery of water, ice and organics on distant planets, moons and comets and evidence for fossil organisms on Mars and in SNC and carbonaceous meteorites. Instruments and methods are considered for spectroscopy and fluorescence of biomolecules (e.g., photosynthetic pigments) for remote detection of conclusive evidence for extraterrestrial life. Optical Video Microscopy is discussed as a direct means for detecting extraterrestrial life using small visible light/UV video microscopes, with ample magnification to record motile bacteria and other living organisms in samples collected by Rovers or Landers. Locomotion of living cells of bacteria and other microbes requires great expenditure of energy and motile cells can be distinguished by video microscopy from the physico-chemical movements (by Brownian Motion, Diffusion or Current Drift) of dead cells, dust particles and abiotic mineral grains.
Free Energy-Based Conformational Search Algorithm Using the Movable Type Sampling Method.
Pan, Li-Li; Zheng, Zheng; Wang, Ting; Merz, Kenneth M
2015-12-01
In this article, we extend the movable type (MT) sampling method to molecular conformational searches (MT-CS) on the free energy surface of the molecule in question. Differing from traditional systematic and stochastic searching algorithms, this method uses Boltzmann energy information to facilitate the selection of the best conformations. The generated ensembles provided good coverage of the available conformational space including available crystal structures. Furthermore, our approach directly provides the solvation free energies and the relative gas and aqueous phase free energies for all generated conformers. The method is validated by a thorough analysis of thrombin ligands as well as against structures extracted from both the Protein Data Bank (PDB) and the Cambridge Structural Database (CSD). An in-depth comparison between OMEGA and MT-CS is presented to illustrate the differences between the two conformational searching strategies, i.e., energy-based versus free energy-based searching. These studies demonstrate that our MT-based ligand conformational search algorithm is a powerful approach to delineate the conformational ensembles of molecular species on free energy surfaces. PMID:26605406
A semantics-based method for clustering of Chinese web search results
NASA Astrophysics Data System (ADS)
Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong
2014-01-01
Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.
On the heuristic nature of medical decision-support systems.
Aliferis, C F; Miller, R A
1995-03-01
In the realm of medical decision-support systems, the term "heuristic systems" is often considered to be synonymous with "medical artificial intelligence systems" or with "systems employing informal model(s) of problem solving". Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation. PMID:9082138
Yeates, Keith Owen; Bigler, Erin D.; Dennis, Maureen; Gerhardt, Cynthia A.; Rubin, Kenneth H.; Stancin, Terry; Taylor, H. Gerry; Vannatta, Kathryn
2010-01-01
The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitive-affective substrates of children’s social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation. PMID:17469991
An Approach to Protein Name Extraction Using Heuristics and a Dictionary.
ERIC Educational Resources Information Center
Seki, Kazuhiro; Mostafa, Javed
2003-01-01
Proposes a method for protein name extraction from biological texts. The method exploits hand-crafted rules based on heuristics and a set of protein names (dictionary). The approach avoids use of natural language processing tools so as to improve processing speed. Evaluation experiments were conducted in terms of: accuracy, generalizability, and…
Heuristics, LPs, and treeds on trees
Mirchandani, P.; Magnanti, T.L.; Balakrishnan, A.
1994-12-31
We discuss the worst-case behavior of heuristics and linear programming relaxations for a class of overlay optimization problems that combine linked subproblems by {open_quotes}overlaying{close_quotes} higher level subproblems on top of the solution of the lower level subproblems. Even though the subproblems (for example, shortest path, minimum spanning tree, etc.) might independently be polynomially solvable, the simplest special cases of the overlay optimization problems are NP-hard. Using bounds on the heuristics of the underlying subproblems, our analysis develops worst-case bounds of {open_quotes}composite{close_quotes} heuristics for several classes of the overlay optimization problem; we also develop bounds on the degree of suboptimality of the linear programming relaxation of the overlay optimization model. As a part of this development, we introduce a new class of multi-tier multi-connected network design problems; these models generalize several telecommunication survivability models in the literature. We also discuss how our general analysis of the overly optimization extends to these survivable network design problems.
New conformational search method using genetic algorithm and knot theory for proteins.
Sakae, Y; Hiroyasu, T; Miki, M; Okamoto, Y
2011-01-01
We have proposed a parallel simulated annealing using genetic crossover as one of powerful conformational search methods, in order to find the global minimum energy structures for protein systems. The simulated annealing using genetic crossover method, which incorporates the attractive features of the simulated annealing and the genetic algorithm, is useful for finding a minimum potential energy conformation of protein systems. However, when we perform simulations by using this method, we often find obviously unnatural stable conformations, which have "knots" of a string of an amino-acid sequence. Therefore, we combined knot theory with our simulated annealing using genetic crossover method in order to avoid the knot conformations from the conformational search space. We applied this improved method to protein G, which has 56 amino acids. As the result, we could perform the simulations, which avoid knot conformations. PMID:21121049
ERIC Educational Resources Information Center
Chang, Ting-Wen; Kinshuk; Chen, Nian-Shing; Yu, Pao-Ta
2012-01-01
This study investigates the effects of successive and simultaneous information presentation methods on learner's visual search ability and working memory load for different information densities. Since the processing of information in the brain depends on the capacity of visual short-term memory (VSTM), the limited information processing capacity…
Shack-Hartmann wavefront sensor with large dynamic range by adaptive spot search method.
Shinto, Hironobu; Saita, Yusuke; Nomura, Takanori
2016-07-10
A Shack-Hartmann wavefront sensor (SHWFS) that consists of a microlens array and an image sensor has been used to measure the wavefront aberrations of human eyes. However, a conventional SHWFS has finite dynamic range depending on the diameter of the each microlens. The dynamic range cannot be easily expanded without a decrease of the spatial resolution. In this study, an adaptive spot search method to expand the dynamic range of an SHWFS is proposed. In the proposed method, spots are searched with the help of their approximate displacements measured with low spatial resolution and large dynamic range. By the proposed method, a wavefront can be correctly measured even if the spot is beyond the detection area. The adaptive spot search method is realized by using the special microlens array that generates both spots and discriminable patterns. The proposed method enables expanding the dynamic range of an SHWFS with a single shot and short processing time. The performance of the proposed method is compared with that of a conventional SHWFS by optical experiments. Furthermore, the dynamic range of the proposed method is quantitatively evaluated by numerical simulations. PMID:27409319
Searching for life in the Universe: unconventional methods for an unconventional problem.
Nealson, K H; Tsapin, A; Storrie-Lombardi, M
2002-12-01
The search for life, on and off our planet, can be done by conventional methods with which we are all familiar. These methods are sensitive and specific, and are often capable of detecting even single cells. However, if the search broadens to include life that may be different (even subtly different) in composition, the methods and even the approach must be altered. Here we discuss the development of what we call non-earthcentric life detection--detecting life with methods that could detect life no matter what its form or composition. To develop these methods, we simply ask, can we define life in terms of its general properties and particularly those that can be measured and quantified? Taking such an approach we can search for life using physics and chemistry to ask questions about structure, chemical composition, thermodynamics, and kinetics. Structural complexity can be searched for using computer algorithms that recognize complex structures. Once identified, these structures can be examined for a variety of chemical traits, including elemental composition, chirality, and complex chemistry. A second approach involves defining our environment in terms of energy sources (i.e., reductants), and oxidants (e.g. what is available to eat and breathe), and then looking for areas in which such phenomena are inexplicably out of chemical equilibrium. These disequilibria, when found, can then be examined in detail for the presence of the structural and chemical complexity that presumably characterizes any living systems. By this approach, we move the search for life to one that should facilitate the detection of any earthly life it encountered, as well as any non-conventional life forms that have structure, complex chemistry, and live via some form of redox chemistry. PMID:12497189
Gent, I.P.; MacIntyre, E.; Prosser, P.
1996-12-31
We introduce a parameter that measures the {open_quotes}constrainedness{close_quotes} of an ensemble of combinatorial problems. If problems are over-constrained, they are likely to be insoluble. If problems are under-constrained, they are likely to be soluble. This constrainedness parameter generalizes a number of parameters previously used in different NP-complete problem classes. Phase transitions in different NP classes can thus be directly compared. This parameter can also be used in a heuristic to guide search. The heuristic captures the intuition of making the most constrained choice first, since it is often useful to branch into the least constrained subproblem. Many widely disparate heuristics can be seen as minimizing constrainedness.
NASA Astrophysics Data System (ADS)
Ruan, Cong; Sun, Xiao-Min; Song, Yi-Xu
In this paper, we propose a method to optimize etching yield parameters. By means of defining a fitness function between the actual etching profile and the simulation profile, the etching yield parameters solving problem is transformed into an optimization problem. The problem is nonlinear and high dimensional, and each simulation is computationally expensive. To solve this problem, we need to search a better solution in a multidimensional space. Ordinal optimization and tabu search hybrid algorithm is introduced to solve this complex problem. This method ensures getting good enough solution in an acceptable time. The experimental results illustrate that simulation profile obtained by this method is very similar with the actual etching profile in surface topography. It also proves that our proposed method has feasibility and validity.
Removing External Degrees of Freedom from Transition-State Search Methods using Quaternions.
Melander, Marko; Laasonen, Kari; Jónsson, Hannes
2015-03-10
In finite systems, such as nanoparticles and gas-phase molecules, calculations of minimum energy paths (MEPs) connecting initial and final states of transitions as well as searches for saddle points are complicated by the presence of external degrees of freedom, such as overall translation and rotation. A method based on quaternion algebra for removing the external degrees of freedom is described here and applied in calculations using two commonly used methods: the nudged elastic band (NEB) method for MEPs and the DIMER method for finding the minimum mode in minimum mode following searches of first-order saddle points. With the quaternion approach, fewer images in the NEB are needed to represent MEPs accurately. In both NEB and DIMER calculations of finite systems, the number of iterations required to reach convergence is significantly reduced. The algorithms have been implemented in the Atomic Simulation Environment (ASE) open source software. PMID:26579757
NASA Astrophysics Data System (ADS)
Bakkiyaraj, Ashok; Kumarappan, N.
2015-09-01
This paper presents a new approach for evaluating the reliability indices of a composite power system that adopts binary differential evolution (BDE) algorithm in the search mechanism to select the system states. These states also called dominant states, have large state probability and higher loss of load curtailment necessary to maintain real power balance. A chromosome of a BDE algorithm represents the system state. BDE is not applied for its traditional application of optimizing a non-linear objective function, but used as tool for exploring more number of dominant states by producing new chromosomes, mutant vectors and trail vectors based on the fitness function. The searched system states are used to evaluate annualized system and load point reliability indices. The proposed search methodology is applied to RBTS and IEEE-RTS test systems and results are compared with other approaches. This approach evaluates the indices similar to existing methods while analyzing less number of system states.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
NASA Technical Reports Server (NTRS)
Cheung, Kar-Ming; Lee, Charles H.
2012-01-01
We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.
A heuristic approach using multiple criteria for environmentally benign 3PLs selection
NASA Astrophysics Data System (ADS)
Kongar, Elif
2005-11-01
Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.
Pandalai, Sudha P; Schulte, Paul A; Miller, Diane B
2015-01-01
Objective Research and interventions targeting the relationship between work, its attendant occupational hazards, and obesity are evolving but merit further consideration in the public health arena. In this discussion paper, conceptual heuristic models are described examining the role of obesity as both a risk factor and health outcome in the occupational setting. Methods PubMed was searched using specific criteria from 2000 and onwards for evidence to support conceptual models in which obesity serves as a risk factor for occupational disease or an outcome of occupational exposures. Nine models are presented: four where obesity is a risk factor and five where it is an adverse effect. Results A broad range of work-related health effects are associated with obesity including musculoskeletal disorders, asthma, liver disease, and cardiovascular disease, among others. Obesity can be associated with occupational hazards such as shift work, sedentary work, job stress, and exposure to some chemicals. Conclusion Identification of combinations of risk factors pertinent to obesity in the occupational environment will provide important guidance for research and prevention. PMID:23588858
Prediction of RNA Pseudoknots Using Heuristic Modeling with Mapping and Sequential Folding
Dawson, Wayne K.; Fujiwara, Kazuya; Kawai, Gota
2007-01-01
Predicting RNA secondary structure is often the first step to determining the structure of RNA. Prediction approaches have historically avoided searching for pseudoknots because of the extreme combinatorial and time complexity of the problem. Yet neglecting pseudoknots limits the utility of such approaches. Here, an algorithm utilizing structure mapping and thermodynamics is introduced for RNA pseudoknot prediction that finds the minimum free energy and identifies information about the flexibility of the RNA. The heuristic approach takes advantage of the 5′ to 3′ folding direction of many biological RNA molecules and is consistent with the hierarchical folding hypothesis and the contact order model. Mapping methods are used to build and analyze the folded structure for pseudoknots and to add important 3D structural considerations. The program can predict some well known pseudoknot structures correctly. The results of this study suggest that many functional RNA sequences are optimized for proper folding. They also suggest directions we can proceed in the future to achieve even better results. PMID:17878940
Goal representation heuristic dynamic programming on maze navigation.
Ni, Zhen; He, Haibo; Wen, Jinyu; Xu, Xin
2013-12-01
Goal representation heuristic dynamic programming (GrHDP) is proposed in this paper to demonstrate online learning in the Markov decision process. In addition to the (external) reinforcement signal in literature, we develop an adaptively internal goal/reward representation for the agent with the proposed goal network. Specifically, we keep the actor-critic design in heuristic dynamic programming (HDP) and include a goal network to represent the internal goal signal, to further help the value function approximation. We evaluate our proposed GrHDP algorithm on two 2-D maze navigation problems, and later on one 3-D maze navigation problem. Compared to the traditional HDP approach, the learning performance of the agent is improved with our proposed GrHDP approach. In addition, we also include the learning performance with two other reinforcement learning algorithms, namely Sarsa(λ) and Q-learning, on the same benchmarks for comparison. Furthermore, in order to demonstrate the theoretical guarantee of our proposed method, we provide the characteristics analysis toward the convergence of weights in neural networks in our GrHDP approach. PMID:24805221
Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems
NASA Astrophysics Data System (ADS)
Vasant, P.; Barsoum, N.
2010-06-01
In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.
A method of characterizing network topology based on the breadth-first search tree
NASA Astrophysics Data System (ADS)
Zhou, Bin; He, Zhe; Wang, Nianxin; Wang, Bing-Hong
2016-05-01
A method based on the breadth-first search tree is proposed in this paper to characterize the hierarchical structure of network. In this method, a similarity coefficient is defined to quantitatively distinguish networks, and quantitatively measure the topology stability of the network generated by a model. The applications of the method are discussed in ER random network, WS small-world network and BA scale-free network. The method will be helpful for deeply describing network topology and provide a starting point for researching the topology similarity and isomorphism of networks.
A fast tomographic method for searching the minimum free energy path
Chen, Changjun; Huang, Yanzhao; Xiao, Yi; Jiang, Xuewei
2014-10-21
Minimum Free Energy Path (MFEP) provides a lot of important information about the chemical reactions, like the free energy barrier, the location of the transition state, and the relative stability between reactant and product. With MFEP, one can study the mechanisms of the reaction in an efficient way. Due to a large number of degrees of freedom, searching the MFEP is a very time-consuming process. Here, we present a fast tomographic method to perform the search. Our approach first calculates the free energy surfaces in a sequence of hyperplanes perpendicular to a transition path. Based on an objective function and the free energy gradient, the transition path is optimized in the collective variable space iteratively. Applications of the present method to model systems show that our method is practical. It can be an alternative approach for finding the state-to-state MFEP.
Active Search on Carcasses versus Pitfall Traps: a Comparison of Sampling Methods.
Zanetti, N I; Camina, R; Visciarelli, E C; Centeno, N D
2016-04-01
The study of insect succession in cadavers and the classification of arthropods have mostly been done by placing a carcass in a cage, protected from vertebrate scavengers, which is then visited periodically. An alternative is to use specific traps. Few studies on carrion ecology and forensic entomology involving the carcasses of large vertebrates have employed pitfall traps. The aims of this study were to compare both sampling methods (active search on a carcass and pitfall trapping) for each coleopteran family, and to establish whether there is a discrepancy (underestimation and/or overestimation) in the presence of each family by either method. A great discrepancy was found for almost all families with some of them being more abundant in samples obtained through active search on carcasses and others in samples from traps, whereas two families did not show any bias towards a given sampling method. The fact that families may be underestimated or overestimated by the type of sampling technique highlights the importance of combining both methods, active search on carcasses and pitfall traps, in order to obtain more complete information on decomposition, carrion habitat and cadaveric families or species. Furthermore, a hypothesis advanced on the reasons for the underestimation by either sampling method showing biases towards certain families. Information about the sampling techniques indicating which would be more appropriate to detect or find a particular family is provided. PMID:26732526
An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics
NASA Technical Reports Server (NTRS)
Baluja, Shumeet
1995-01-01
This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.
ERIC Educational Resources Information Center
Ortiz, Lorelei A.
2013-01-01
To teach effective business communication, instructors must target students’ current weaknesses in writing. One method for doing so is by assigning writing exercises. When used heuristically, writing exercises encourage students to practice self-assessment, self-evaluation, active learning, and knowledge transfer, all while reinforcing the basics…
NASA Astrophysics Data System (ADS)
Pasam, Gopi Krishna; Manohar, T. Gowri
2015-07-01
Determination of available transfer capability (ATC) requires the use of experience, intuition and exact judgment in order to meet several significant aspects in the deregulated environment. Based on these points, this paper proposes two heuristic approaches to compute ATC. The first proposed heuristic algorithm integrates the five methods known as continuation repeated power flow, repeated optimal power flow, radial basis function neural network, back propagation neural network and adaptive neuro fuzzy inference system to obtain ATC. The second proposed heuristic model is used to obtain multiple ATC values. Out of these, a specific ATC value will be selected based on a number of social, economic, deregulated environmental constraints and related to specific applications like optimization, on-line monitoring, and ATC forecasting known as multi-objective decision based optimal ATC. The validity of results obtained through these proposed methods are scrupulously verified on various buses of the IEEE 24-bus reliable test system. The results presented and derived conclusions in this paper are very useful for planning, operation, maintaining of reliable power in any power system and its monitoring in an on-line environment of deregulated power system. In this way, the proposed heuristic methods would contribute the best possible approach to assess multiple objective ATC using integrated methods.
Getting Smart with Computers: Computer-Aided Heuristics for Student Writers.
ERIC Educational Resources Information Center
Kemp, Fred
1987-01-01
Evaluates several views of the relationship between computers and education, and criticizes the use of artificial intelligence and natural language processing software for evaluating student writing. Recommends utilizing programs that use heuristic methods to ask students a series of questions to help them organize and compose papers. (SKC)
ERIC Educational Resources Information Center
Batey, Mark
2012-01-01
The scientific study of creativity has proven a difficult undertaking. Researchers have employed a diversity of definitions and measurement methods. As a result, creativity research is underrepresented in the literature and the findings of different studies often prove difficult to draw into a coherent body of understanding. A heuristic framework…
Simple Heuristic Approach to Introduction of the Black-Scholes Model
ERIC Educational Resources Information Center
Yalamova, Rossitsa
2010-01-01
A heuristic approach to explaining of the Black-Scholes option pricing model in undergraduate classes is described. The approach draws upon the method of protocol analysis to encourage students to "think aloud" so that their mental models can be surfaced. It also relies upon extensive visualizations to communicate relationships that are…
A general heuristic for genome rearrangement problems.
Dias, Ulisses; Galvão, Gustavo Rodrigues; Lintzmayer, Carla Négri; Dias, Zanoni
2014-06-01
In this paper, we present a general heuristic for several problems in the genome rearrangement field. Our heuristic does not solve any problem directly, it is rather used to improve the solutions provided by any non-optimal algorithm that solve them. Therefore, we have implemented several algorithms described in the literature and several algorithms developed by ourselves. As a whole, we implemented 23 algorithms for 9 well known problems in the genome rearrangement field. A total of 13 algorithms were implemented for problems that use the notions of prefix and suffix operations. In addition, we worked on 5 algorithms for the classic problem of sorting by transposition and we conclude the experiments by presenting results for 3 approximation algorithms for the sorting by reversals and transpositions problem and 2 approximation algorithms for the sorting by reversals problem. Another algorithm with better approximation ratio can be found for the last genome rearrangement problem, but it is purely theoretical with no practical implementation. The algorithms we implemented in addition to our heuristic lead to the best practical results in each case. In particular, we were able to improve results on the sorting by transpositions problem, which is a very special case because many efforts have been made to generate algorithms with good results in practice and some of these algorithms provide results that equal the optimum solutions in many cases. Our source codes and benchmarks are freely available upon request from the authors so that it will be easier to compare new approaches against our results. PMID:24969750
Heuristic determination of quantitative data for knowledge acquisition in medicine.
Giuse, D A; Giuse, N B; Bankowitz, R A; Miller, R A
1991-06-01
Knowledge acquisition for medical knowledge bases can be aided by programs that suggest possible values for portions of the data. The paper presents an experiment which was used in designing a heuristic to help the process of knowledge acquisition. The heuristic helps to determine numerical data from stylized literature excerpts in the context of knowledge acquisition for the QMR medical knowledge base. Quantitative suggestions from the heuristics are shown to agree substantially with the data incorporated in the final version of the knowledge base. The experiment shows the potential of knowledge base specific heuristics in simplifying the task of knowledge base creation. PMID:1868695
Fast optimization of binary clusters using a novel dynamic lattice searching method
Wu, Xia Cheng, Wen
2014-09-28
Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd){sub 79} clusters with DFT-fit parameters of Gupta potential.
Heuristic theory of positron-helium scattering.
NASA Technical Reports Server (NTRS)
Drachman, R. J.
1971-01-01
An error in a previous modified adiabatic approximation (Drachman, 1966), due to a lack of generality in the form of the short-range correlation part of the wave function for L greater than zero, is corrected heuristically by allowing the monopole suppression parameter to depend on L. An L-dependent local potential is constructed to fit the well-known positron-hydrogen s, p, and d wave phase shifts below the rearrangement threshold. The same form of potential yields a positron-helium cross-section in agreement with a recent experimental measurement near threshold.
A new method to search for high-redshift clusters using photometric redshifts
Castignani, G.; Celotti, A.; Chiaberge, M.; Norman, C.
2014-09-10
We describe a new method (Poisson probability method, PPM) to search for high-redshift galaxy clusters and groups by using photometric redshift information and galaxy number counts. The method relies on Poisson statistics and is primarily introduced to search for megaparsec-scale environments around a specific beacon. The PPM is tailored to both the properties of the FR I radio galaxies in the Chiaberge et al. sample, which are selected within the COSMOS survey, and to the specific data set used. We test the efficiency of our method of searching for cluster candidates against simulations. Two different approaches are adopted. (1) We use two z ∼ 1 X-ray detected cluster candidates found in the COSMOS survey and we shift them to higher redshift up to z = 2. We find that the PPM detects the cluster candidates up to z = 1.5, and it correctly estimates both the redshift and size of the two clusters. (2) We simulate spherically symmetric clusters of different size and richness, and we locate them at different redshifts (i.e., z = 1.0, 1.5, and 2.0) in the COSMOS field. We find that the PPM detects the simulated clusters within the considered redshift range with a statistical 1σ redshift accuracy of ∼0.05. The PPM is an efficient alternative method for high-redshift cluster searches that may also be applied to both present and future wide field surveys such as SDSS Stripe 82, LSST, and Euclid. Accurate photometric redshifts and a survey depth similar or better than that of COSMOS (e.g., I < 25) are required.
GYutsis: heuristic based calculation of general recoupling coefficients
NASA Astrophysics Data System (ADS)
Van Dyck, D.; Fack, V.
2003-08-01
physical problem: A general recoupling coefficient for an arbitrary number of (integer or half-integer) angular momenta can be expressed as a formula consisting of products of 6- j coefficients summed over a certain number of variables. Such a formula can be generated using the program GYutsis (with a graphical user front end) or CycleCostAlgorithm (with a text-mode user front end). Method of solution: Using the graphical techniques of Yutsis, Levinson and Vanagas (1962) a summation formula for a general recoupling coefficient is obtained by representing the coefficient as a Yutsis graph and by performing a selection of reduction rules valid for such graphs. Each reduction rule contributes to the final summation formula by a numerical factor or by an additional summation variable. Whereas an optimal summation formula (i.e. with a minimum number of summation variables) is hard to obtain, we present here some new heuristic approaches for selecting an edge from a k-cycle in order to transform it into an ( k-1)-cycle ( k>3) in such a way that a 'good' summation formula is obtained. Typical running time: From instantaneously for the typical problems to 30 s for the heaviest problems on a Pentium II-350 Linux-system with 256 MB RAM.
RAId_DbS: Method for Peptide ID using Database Search with Accurate Statistics
NASA Astrophysics Data System (ADS)
Alves, Gelio; Ogurtsov, Aleksey; Yu, Yi-Kuo
2007-03-01
The key to proteomics studies, essential in systems biology, is peptide identification. Under tandem mass spectrometry, each spectrum generated consists of a list of mass/charge peaks along with their intensities. Software analysis is then required to identify from the spectrum peptide candidates that best interpret the spectrum. The library search, which compares the spectral peaks against theoretical peaks generated by each peptide in a library, is among the most popular methods. This method, although robust, lacks good quantitative statistical underpinning. As we show, many library search algorithms suffer from statistical instability. The need for a better statistical basis prompted us to develop RAId_DbS. Taking into account the skewness in the peak intensity distribution while scoring peptides, RAId_DbS provides an accurate statistical significance assignment to each peptide candidate. RAId_DbS will be a valuable tool especially when one intends to identify proteins through peptide identifications.
A structure-based flexible search method for motifs in RNA.
Veksler-Lublinsky, Isana; Ziv-Ukelson, Michal; Barash, Danny; Kedem, Klara
2007-09-01
The discovery of non-coding RNA (ncRNA) motifs and their role in regulating gene expression has recently attracted considerable attention. The goal is to discover these motifs in a sequence database. Current RNA motif search methods start from the primary sequence and only then take into account secondary structure considerations. One can think of developing a flexible structure-based motif search method that will filter datasets based on secondary structure first, while allowing extensive primary sequence factors and additional factors such as potential pseudoknots as constraints. Since different motifs vary in structure rigidity and in local sequence constraints, there is a need for algorithms and tools that can be fine-tuned according to the searched RNA motif, but differ in their approach from the RNAMotif descriptor language. We present an RNA motif search tool called STRMS (Structural RNA Motif Search), which takes as input the secondary structure of the query, including local sequence and structure constraints, and a target sequence database. It reports all occurrences of the query in the target, ranked by their similarity to the query, and produces an html file that displays graphical images of the predicted structures for both the query and the candidate hits. Our tool is flexible and takes into account a large number of sequence options and existence of potential pseudoknots as dictated by specific queries. Our approach combines pre-folding and an O(m n) RNA pattern matching algorithm based on subtree homeomorphism for ordered, rooted trees. An O(n(2) log n) extension is described that allows the search engine to take into account the pseudoknots typical to riboswitches. We employed STRMS in search for both new and known RNA motifs (riboswitches and tRNAs) in large target databases. Our results point to a number of additional purine bacterial riboswitch candidates in newly sequenced bacteria, and demonstrate high sensitivity on known riboswitches and t
Chen, Bor-Sen
2016-01-01
Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella’s rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the “brake component” in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each “brake component” were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the “brake component”. Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate “brake component” in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains. PMID:27096615
How do people judge risks: availability heuristic, affect heuristic, or both?
Pachur, Thorsten; Hertwig, Ralph; Steinmann, Florian
2012-09-01
How does the public reckon which risks to be concerned about? The availability heuristic and the affect heuristic are key accounts of how laypeople judge risks. Yet, these two accounts have never been systematically tested against each other, nor have their predictive powers been examined across different measures of the public's risk perception. In two studies, we gauged risk perception in student samples by employing three measures (frequency, value of a statistical life, and perceived risk) and by using a homogeneous (cancer) and a classic set of heterogeneous causes of death. Based on these judgments of risk, we tested precise models of the availability heuristic and the affect heuristic and different definitions of availability and affect. Overall, availability-by-recall, a heuristic that exploits people's direct experience of occurrences of risks in their social network, conformed to people's responses best. We also found direct experience to carry a high degree of ecological validity (and one that clearly surpasses that of affective information). However, the relative impact of affective information (as compared to availability) proved more pronounced in value-of-a-statistical-life and perceived-risk judgments than in risk-frequency judgments. Encounters with risks in the media, in contrast, played a negligible role in people's judgments. Going beyond the assumption of exclusive reliance on either availability or affect, we also found evidence for mechanisms that combine both, either sequentially or in a composite fashion. We conclude with a discussion of policy implications of our results, including how to foster people's risk calibration and the success of education campaigns. PMID:22564084
Memorability in Context: A Heuristic Story.
Geurten, Marie; Meulemans, Thierry; Willems, Sylvie
2015-01-01
We examined children's ability to employ a metacognitive heuristic based on memorability expectations to reduce false recognitions, and explored whether these expectations depend on the context in which the items are presented. Specifically, 4-, 6-, and 9-year-old children were presented with high-, medium-, and low-memorability words, either mixed together (Experiment 1) or separated into two different lists (Experiment 2). Results revealed that only children with a higher level of executive functioning (9-year-olds) used the memorability-based heuristic when all types of items were presented within the same list. However, all children, regardless of age or executive level, implemented the metacognitive rule when high- and low-memorability words were presented in two separate lists. Moreover, the results of Experiment 2 showed that participants processed medium-memorability words more conservatively when they were presented in a low- than in a high-memorability list, suggesting that children's memorability expectations are sensitive to list-context effects. PMID:26592531
Instructional Design for Heuristic-Based Problem Solving.
ERIC Educational Resources Information Center
Ingram, Albert L.
1988-01-01
Discussion of instructional design models focuses on a study concerned with developing effective instruction in heuristic-based problem solving for computer programing. Highlights include distinctions between algorithms and heuristics; pretests and posttests; revised instructional design procedures; student attitudes; task analysis; and…
On Dual Processing and Heuristic Approaches to Moral Cognition
ERIC Educational Resources Information Center
Lapsley, Daniel K.; Hill, Patrick L.
2008-01-01
We examine the implications of dual-processing theories of cognition for the moral domain, with particular emphasis upon "System 1" theories: the Social Intuitionist Model (Haidt), moral heuristics (Sunstein), fast-and-frugal moral heuristics (Gigerenzer), schema accessibility (Lapsley & Narvaez) and moral expertise (Narvaez). We argue that these…
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
Swift and Smart Decision Making: Heuristics that Work
ERIC Educational Resources Information Center
Hoy, Wayne K.; Tarter, C. J.
2010-01-01
Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…
Cultural Heuristics: Topics of Invention Based on Human Behavior.
ERIC Educational Resources Information Center
DeGeorge, James M.
Heuristic models help writers recall information, sometimes revealing unique combinations of information in ways not conceived previously. This makes heuristics a valuable technique for helping beginning writers generate writing ideas. Observing that all culture is communication, Edward Hall has organized Primary Message Systems (PMS), a framework…
A Heuristic Framework to Solve a General Delivery Problem
NASA Astrophysics Data System (ADS)
Lian, Lian; Castelain, Emmanuel
2010-06-01
This paper presents a new distribution and route planning problem, General Delivery Problem (GDP) which is more general than the well-known Vehicle Routing Problem. To solve a GDP, a three-phase framework heuristic approach based on decomposition techniques is introduced. The decomposition techniques are employed to divide an original problem into a set of sub-problems, which can reduce the problem size. A kind of decomposition technique, Capacity Clustering Algorithm (CCA), is embedded into the framework with Simulated Annealing (SA) to solve a special GDP. The proposed three-phase framework with the above two algorithms is compared with five other decomposition methods in a distribution instance of the Regional Fire and Emergency Center in the north of France.
Kurogi, Y; Miyata, K; Okamura, T; Hashimoto, K; Tsutsumi, K; Nasu, M; Moriyasu, M
2001-07-01
A three-dimensional pharmacophore model of mesangial cell (MC) proliferation inhibitors was generated from a training set of 4-(diethoxyphosphoryl)methyl-N-(3-phenyl-[1,2,4]thiadiazol-5-yl)benzamide, 2, and its derivatives using the Catalyst/HIPHOP software program. On the basis of the in vitro MC proliferation inhibitory activity, a pharmacophore model was generated as seven features consisting of two hydrophobic regions, two hydrophobic aromatic regions, and three hydrogen bond acceptors. Using this model as a three-dimensional query to search the Maybridge database, structurally novel 41 compounds were identified. The evaluation of MC proliferation inhibitory activity using available samples from the 41 identified compounds exhibited over 50% inhibitory activity at the 100 nM range. Interestingly, the newly identified compounds by the 3D database searching method exhibited the reduced inhibition of normal proximal tubular epithelial cell proliferation compared to a training set of compounds. PMID:11428924
Local search methods based on variable focusing for random K-satisfiability.
Lemoy, Rémi; Alava, Mikko; Aurell, Erik
2015-01-01
We introduce variable focused local search algorithms for satisfiabiliity problems. Usual approaches focus uniformly on unsatisfied clauses. The methods described here work by focusing on random variables in unsatisfied clauses. Variants are considered where variables are selected uniformly and randomly or by introducing a bias towards picking variables participating in several unsatistified clauses. These are studied in the case of the random 3-SAT problem, together with an alternative energy definition, the number of variables in unsatisfied constraints. The variable-based focused Metropolis search (V-FMS) is found to be quite close in performance to the standard clause-based FMS at optimal noise. At infinite noise, instead, the threshold for the linearity of solution times with instance size is improved by picking preferably variables in several UNSAT clauses. Consequences for algorithmic design are discussed. PMID:25679737
Local search methods based on variable focusing for random K -satisfiability
NASA Astrophysics Data System (ADS)
Lemoy, Rémi; Alava, Mikko; Aurell, Erik
2015-01-01
We introduce variable focused local search algorithms for satisfiabiliity problems. Usual approaches focus uniformly on unsatisfied clauses. The methods described here work by focusing on random variables in unsatisfied clauses. Variants are considered where variables are selected uniformly and randomly or by introducing a bias towards picking variables participating in several unsatistified clauses. These are studied in the case of the random 3-SAT problem, together with an alternative energy definition, the number of variables in unsatisfied constraints. The variable-based focused Metropolis search (V-FMS) is found to be quite close in performance to the standard clause-based FMS at optimal noise. At infinite noise, instead, the threshold for the linearity of solution times with instance size is improved by picking preferably variables in several UNSAT clauses. Consequences for algorithmic design are discussed.
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
A Versatile Method for Systematic Conformational Searches: Application to CheY
Petrella, Robert J.
2011-01-01
A novel molecular structure prediction method, the Z Method, is described. It provides a versatile platform for the development and use of systematic, grid-based conformational search protocols, in which statistical information (i.e., rotamers) can also be included. The Z Method generates trial structures by applying many changes of the same type to a single starting structure, thereby sampling the conformation space in an unbiased way. The method, implemented in the CHARMM program as the Z Module, is applied here to an illustrative model problem in which rigid, systematic searches are performed in a 36-dimensional conformational space that describes the relative positions of the ten secondary structural elements of the protein CheY. A polar hydrogen representation with an implicit solvation term (EEF1) is used to evaluate successively larger fragments of the protein generated in a hierarchical build-up procedure. After a final refinement stage, and a total computational time of about two-and-a-half days on AMD Opteron processors, the prediction is within 1.56 Å of the native structure. The errors in the predicted backbone dihedral angles are found to approximately cancel. Monte Carlo and simulated annealing trials on the same or smaller versions of the problem, using the same atomic model and energy terms, are shown to result in less accurate predictions. Although the problem solved here is a limited one, the findings illustrate the utility of systematic searches with atom-based models for macromolecular structure prediction and the importance of unbiased sampling in structure prediction methods. PMID:21557263
Cuevas, Erik; Díaz, Margarita
2015-01-01
In this paper, a new method for robustly estimating multiple view relations from point correspondences is presented. The approach combines the popular random sampling consensus (RANSAC) algorithm and the evolutionary method harmony search (HS). With this combination, the proposed method adopts a different sampling strategy than RANSAC to generate putative solutions. Under the new mechanism, at each iteration, new candidate solutions are built taking into account the quality of the models generated by previous candidate solutions, rather than purely random as it is the case of RANSAC. The rules for the generation of candidate solutions (samples) are motivated by the improvisation process that occurs when a musician searches for a better state of harmony. As a result, the proposed approach can substantially reduce the number of iterations still preserving the robust capabilities of RANSAC. The method is generic and its use is illustrated by the estimation of homographies, considering synthetic and real images. Additionally, in order to demonstrate the performance of the proposed approach within a real engineering application, it is employed to solve the problem of position estimation in a humanoid robot. Experimental results validate the efficiency of the proposed method in terms of accuracy, speed, and robustness. PMID:26339228
Cuevas, Erik; Díaz, Margarita
2015-01-01
In this paper, a new method for robustly estimating multiple view relations from point correspondences is presented. The approach combines the popular random sampling consensus (RANSAC) algorithm and the evolutionary method harmony search (HS). With this combination, the proposed method adopts a different sampling strategy than RANSAC to generate putative solutions. Under the new mechanism, at each iteration, new candidate solutions are built taking into account the quality of the models generated by previous candidate solutions, rather than purely random as it is the case of RANSAC. The rules for the generation of candidate solutions (samples) are motivated by the improvisation process that occurs when a musician searches for a better state of harmony. As a result, the proposed approach can substantially reduce the number of iterations still preserving the robust capabilities of RANSAC. The method is generic and its use is illustrated by the estimation of homographies, considering synthetic and real images. Additionally, in order to demonstrate the performance of the proposed approach within a real engineering application, it is employed to solve the problem of position estimation in a humanoid robot. Experimental results validate the efficiency of the proposed method in terms of accuracy, speed, and robustness. PMID:26339228
Heuristic Diagrams as a Tool to Teach History of Science
NASA Astrophysics Data System (ADS)
Chamizo, José A.
2012-05-01
The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The left side originally related in Gowin's Vee with philosophies, theories, models, laws or regularities now agrees with Toulmin's concepts (language, models as representation techniques and application procedures). Mexican science teachers without experience in science education research used the heuristic diagram to learn about the history of chemistry considering also in the left side two different historical times: past and present. Through a semantic differential scale teachers' attitude to the heuristic diagram was evaluated and its usefulness was demonstrated.
Approach to design neural cryptography: A generalized architecture and a heuristic rule
NASA Astrophysics Data System (ADS)
Mu, Nankun; Liao, Xiaofeng; Huang, Tingwen
2013-06-01
Neural cryptography, a type of public key exchange protocol, is widely considered as an effective method for sharing a common secret key between two neural networks on public channels. How to design neural cryptography remains a great challenge. In this paper, in order to provide an approach to solve this challenge, a generalized network architecture and a significant heuristic rule are designed. The proposed generic framework is named as tree state classification machine (TSCM), which extends and unifies the existing structures, i.e., tree parity machine (TPM) and tree committee machine (TCM). Furthermore, we carefully study and find that the heuristic rule can improve the security of TSCM-based neural cryptography. Therefore, TSCM and the heuristic rule can guide us to designing a great deal of effective neural cryptography candidates, in which it is possible to achieve the more secure instances. Significantly, in the light of TSCM and the heuristic rule, we further expound that our designed neural cryptography outperforms TPM (the most secure model at present) on security. Finally, a series of numerical simulation experiments are provided to verify validity and applicability of our results.
Model-Free Dual Heuristic Dynamic Programming.
Ni, Zhen; He, Haibo; Zhong, Xiangnan; Prokhorov, Danil V
2015-08-01
Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires offline training for the model network, and thus resulting in extra computational cost. In this brief, we propose a model-free DHP (MF-DHP) design based on finite-difference technique. In particular, we adopt multilayer perceptron with one hidden layer for both the action and the critic networks design, and use delayed objective functions to train both the action and the critic networks online over time. We test both the MF-DHP and MB-DHP approaches with a discrete time example and a continuous time example under the same parameter settings. Our simulation results demonstrate that the MF-DHP approach can obtain a control performance competitive with that of the traditional MB-DHP approach while requiring less computational resources. PMID:25955997
A Synthesized Heuristic Task Scheduling Algorithm
Dai, Yanyan; Zhang, Xiangli
2014-01-01
Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance. PMID:25254244
ERIC Educational Resources Information Center
Mau, Wei-Cheng; Kopischke, Amie
2001-01-01
Surveys college graduates regarding their job-seeking behaviors and outcomes. Examined race and sex differences among the job search strategies used; number of job interviews; number of job offers; annual salary; and job satisfaction. Results indicated significant differences in underemployment and job satisfaction as a function of race, and in…
A method for comparing non-nested models with application to astrophysical searches for new physics
NASA Astrophysics Data System (ADS)
Algeri, Sara; Conrad, Jan; van Dyk, David A.
2016-05-01
Searches for unknown physics and decisions between competing astrophysical models to explain data both rely on statistical hypothesis testing. The usual approach in searches for new physical phenomena is based on the statistical likelihood ratio test and its asymptotic properties. In the common situation, when neither of the two models under comparison is a special case of the other i.e. when the hypotheses are non-nested, this test is not applicable. In astrophysics, this problem occurs when two models that reside in different parameter spaces are to be compared. An important example is the recently reported excess emission in astrophysical γ-rays and the question whether its origin is known astrophysics or dark matter. We develop and study a new, simple, generally applicable, frequentist method and validate its statistical properties using a suite of simulations studies. We exemplify it on realistic simulated data of the Fermi-Large Area Telescope γ-ray satellite, where non-nested hypotheses testing appears in the search for particle dark matter.
Parallel Harmony Search Based Distributed Energy Resource Optimization
Ceylan, Oguzhan; Liu, Guodong; Tomsovic, Kevin
2015-01-01
This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.
Tabu search techniques for large high-school timetabling problems
Schaerf, A.
1996-12-31
The high-school timetabling problem consists in assigning all the lectures of a high school to the time periods in such a way that no teacher (or class) is involved in more than one lecture at a time and other side constraints are satisfied. The problem is NP-complete and is usually tackled using heuristic methods. This paper describes a solution algorithm (and its implementation) based on Tabu Search. The algorithm interleaves different types of moves and makes use of an adaptive relaxation of the hard constraints. The implementation of the algorithm has been successfully experimented in some large high schools with various kinds of side constraints.
NASA Technical Reports Server (NTRS)
Shull, Forrest; Seaman, Carolyn; Feldman, Raimund; Haingaertner, Ralf; Regardie, Myrna
2008-01-01
In 2008, we have continued analyzing the inspection data in an effort to better understand the applicability and effect of the inspection heuristics on inspection outcomes. Our research goals during this period are: 1. Investigate the effect of anomalies in the dataset (e.g. the very large meeting length values for some inspections) on our results 2. Investigate the effect of the heuristics on other inspection outcome variables (e.g. effort) 3. Investigate whether the recommended ranges can be modified to give inspection planners more flexibility without sacrificing effectiveness 4. Investigate possible refinements or modifications to the heuristics for specific subdomains (partitioned, e.g., by size, domain, or Center) This memo reports our results to date towards addressing these goals. In the next section, the first goal is addressed by describing the types of anomalies we have found in our dataset, how we have addressed them, and the effect of these changes on our previously reported results. In the following section, on "methodology", we describe the analyses we have conducted to address the other three goals and the results of these analyses are described in the "results" section. Finally, we conclude with future plans for continuing our investigation.
Heuristic modeling of macromolecule release from PLGA microspheres.
Szlęk, Jakub; Pacławski, Adam; Lau, Raymond; Jachowicz, Renata; Mendyk, Aleksander
2013-01-01
Dissolution of protein macromolecules from poly(lactic-co-glycolic acid) (PLGA) particles is a complex process and still not fully understood. As such, there are difficulties in obtaining a predictive model that could be of fundamental significance in design, development, and optimization for medical applications and toxicity evaluation of PLGA-based multiparticulate dosage form. In the present study, two models with comparable goodness of fit were proposed for the prediction of the macromolecule dissolution profile from PLGA micro- and nanoparticles. In both cases, heuristic techniques, such as artificial neural networks (ANNs), feature selection, and genetic programming were employed. Feature selection provided by fscaret package and sensitivity analysis performed by ANNs reduced the original input vector from a total of 300 input variables to 21, 17, 16, and eleven; to achieve a better insight into generalization error, two cut-off points for every method was proposed. The best ANNs model results were obtained by monotone multi-layer perceptron neural network (MON-MLP) networks with a root-mean-square error (RMSE) of 15.4, and the input vector consisted of eleven inputs. The complicated classical equation derived from a database consisting of 17 inputs was able to yield a better generalization error (RMSE) of 14.3. The equation was characterized by four parameters, thus feasible (applicable) to standard nonlinear regression techniques. Heuristic modeling led to the ANN model describing macromolecules release profiles from PLGA microspheres with good predictive efficiency. Moreover genetic programming technique resulted in classical equation with comparable predictability to the ANN model. PMID:24348037
Heuristic modeling of macromolecule release from PLGA microspheres
Szlęk, Jakub; Pacławski, Adam; Lau, Raymond; Jachowicz, Renata; Mendyk, Aleksander
2013-01-01
Dissolution of protein macromolecules from poly(lactic-co-glycolic acid) (PLGA) particles is a complex process and still not fully understood. As such, there are difficulties in obtaining a predictive model that could be of fundamental significance in design, development, and optimization for medical applications and toxicity evaluation of PLGA-based multiparticulate dosage form. In the present study, two models with comparable goodness of fit were proposed for the prediction of the macromolecule dissolution profile from PLGA micro- and nanoparticles. In both cases, heuristic techniques, such as artificial neural networks (ANNs), feature selection, and genetic programming were employed. Feature selection provided by fscaret package and sensitivity analysis performed by ANNs reduced the original input vector from a total of 300 input variables to 21, 17, 16, and eleven; to achieve a better insight into generalization error, two cut-off points for every method was proposed. The best ANNs model results were obtained by monotone multi-layer perceptron neural network (MON-MLP) networks with a root-mean-square error (RMSE) of 15.4, and the input vector consisted of eleven inputs. The complicated classical equation derived from a database consisting of 17 inputs was able to yield a better generalization error (RMSE) of 14.3. The equation was characterized by four parameters, thus feasible (applicable) to standard nonlinear regression techniques. Heuristic modeling led to the ANN model describing macromolecules release profiles from PLGA microspheres with good predictive efficiency. Moreover genetic programming technique resulted in classical equation with comparable predictability to the ANN model. PMID:24348037
NASA Astrophysics Data System (ADS)
Wallace, Ryan J.
The purpose of this study was to determine the impact of advanced search and rescue devices and techniques on search duration for general aviation aircraft crashes. The study assessed three categories of emergency locator transmitters, including 121.5 MHz, 406 MHz, and GPS-Assisted 406 MHz devices. The impact of the COSPAS-SARSAT organization ceasing satellite monitoring for 121.5 MHz ELTs in 2009 was factored into the study. Additionally, the effect of using radar forensic analysis and cellular phone forensic search methods were also assessed. The study's data was derived from an Air Force Rescue Coordination Center database and included 365 historical general aviation search and rescue missions conducted between 2006 and 2011. Highly skewed data was transformed to meet normality requirements for parametric testing. The significance of each ELT model was assessed using a combination of Brown-Forsythe Means Testing or Orthogonal Contrast Testing. ANOVA and Brown-Forsythe Means testing was used to evaluate cellular phone and radar forensic search methods. A Spearman's Rho test was used to determine if the use of multiple search methods produced an additive effect in search efficiency. Aircraft which utilized an Emergency Locator Transmitter resulted in a shorter search duration than those which did not use such devices. Aircraft utilizing GPS-Aided 406 MHz ELTs appeared to require less time to locate than if equipped with other ELT models, however, this assessment requires further study due to limited data. Aircraft equipped with 406 MHz ELTs required slightly less time to locate than aircraft equipped with older 121.5 MHz ELTs. The study found no substantial difference in the search durations for 121.5 MHz ELTs monitored by COSPAS-SARSAT verses those which were not. Significance testing revealed that the use of cellular phone forensic data and radar forensic data both resulted in substantially higher mission search durations. Some possible explanations for this
Hybrid Genetic Algorithm - Local Search Method for Ground-Water Management
NASA Astrophysics Data System (ADS)
Chiu, Y.; Nishikawa, T.; Martin, P.
2008-12-01
Ground-water management problems commonly are formulated as a mixed-integer, non-linear programming problem (MINLP). Relying only on conventional gradient-search methods to solve the management problem is computationally fast; however, the methods may become trapped in a local optimum. Global-optimization schemes can identify the global optimum, but the convergence is very slow when the optimal solution approaches the global optimum. In this study, we developed a hybrid optimization scheme, which includes a genetic algorithm and a gradient-search method, to solve the MINLP. The genetic algorithm identifies a near- optimal solution, and the gradient search uses the near optimum to identify the global optimum. Our methodology is applied to a conjunctive-use project in the Warren ground-water basin, California. Hi- Desert Water District (HDWD), the primary water-manager in the basin, plans to construct a wastewater treatment plant to reduce future septic-tank effluent from reaching the ground-water system. The treated wastewater instead will recharge the ground-water basin via percolation ponds as part of a larger conjunctive-use strategy, subject to State regulations (e.g. minimum distances and travel times). HDWD wishes to identify the least-cost conjunctive-use strategies that control ground-water levels, meet regulations, and identify new production-well locations. As formulated, the MINLP objective is to minimize water-delivery costs subject to constraints including pump capacities, available recharge water, water-supply demand, water-level constraints, and potential new-well locations. The methodology was demonstrated by an enumerative search of the entire feasible solution and comparing the optimum solution with results from the branch-and-bound algorithm. The results also indicate that the hybrid method identifies the global optimum within an affordable computation time. Sensitivity analyses, which include testing different recharge-rate scenarios, pond
Hydro-thermal Commitment Scheduling by Tabu Search Method with Cooling-Banking Constraints
NASA Astrophysics Data System (ADS)
Nayak, Nimain Charan; Rajan, C. Christober Asir
This paper presents a new approach for developing an algorithm for solving the Unit Commitment Problem (UCP) in a Hydro-thermal power system. Unit Commitment is a nonlinear optimization problem to determine the minimum cost turn on/off schedule of the generating units in a power system by satisfying both the forecasted load demand and various operating constraints of the generating units. The effectiveness of the proposed hybrid algorithm is proved by the numerical results shown comparing the generation cost solutions and computation time obtained by using Tabu Search Algorithm with other methods like Evolutionary Programming and Dynamic Programming in reaching proper unit commitment.
Common-sense chemistry: The use of assumptions and heuristics in problem solving
NASA Astrophysics Data System (ADS)
Maeyer, Jenine Rachel
Students experience difficulty learning and understanding chemistry at higher levels, often because of cognitive biases stemming from common sense reasoning constraints. These constraints can be divided into two categories: assumptions (beliefs held about the world around us) and heuristics (the reasoning strategies or rules used to build predictions and make decisions). A better understanding and characterization of these constraints are of central importance in the development of curriculum and teaching strategies that better support student learning in science. It was the overall goal of this thesis to investigate student reasoning in chemistry, specifically to better understand and characterize the assumptions and heuristics used by undergraduate chemistry students. To achieve this, two mixed-methods studies were conducted, each with quantitative data collected using a questionnaire and qualitative data gathered through semi-structured interviews. The first project investigated the reasoning heuristics used when ranking chemical substances based on the relative value of a physical or chemical property, while the second study characterized the assumptions and heuristics used when making predictions about the relative likelihood of different types of chemical processes. Our results revealed that heuristics for cue selection and decision-making played a significant role in the construction of answers during the interviews. Many study participants relied frequently on one or more of the following heuristics to make their decisions: recognition, representativeness, one-reason decision-making, and arbitrary trend. These heuristics allowed students to generate answers in the absence of requisite knowledge, but often led students astray. When characterizing assumptions, our results indicate that students relied on intuitive, spurious, and valid assumptions about the nature of chemical substances and processes in building their responses. In particular, many
The recognition heuristic: a review of theory and tests.
Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G
2011-01-01
The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266
The Recognition Heuristic: A Review of Theory and Tests
Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.
2011-01-01
The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266
An R-peak detection method that uses an SVD filter and a search back system.
Jung, Woo-Hyuk; Lee, Sang-Goog
2012-12-01
In this paper, we present a method for detecting the R-peak of an ECG signal by using an singular value decomposition (SVD) filter and a search back system. The ECG signal was detected in two phases: the pre-processing phase and the decision phase. The pre-processing phase consisted of the stages for the SVD filter, Butterworth High Pass Filter (HPF), moving average (MA), and squaring, whereas the decision phase consisted of a single stage that detected the R-peak. In the pre-processing phase, the SVD filter removed noise while the Butterworth HPF eliminated baseline wander. The MA removed the remaining noise of the signal that had gone through the SVD filter to make the signal smooth, and squaring played a role in strengthening the signal. In the decision phase, the threshold was used to set the interval before detecting the R-peak. When the latest R-R interval (RRI), suggested by Hamilton et al., was greater than 150% of the previous RRI, the method of detecting the R-peak in such an interval was modified to be 150% or greater than the smallest interval of the two most latest RRIs. When the modified search back system was used, the error rate of the peak detection decreased to 0.29%, compared to 1.34% when the modified search back system was not used. Consequently, the sensitivity was 99.47%, the positive predictivity was 99.47%, and the detection error was 1.05%. Furthermore, the quality of the signal in data with a substantial amount of noise was improved, and thus, the R-peak was detected effectively. PMID:22922087
[Searching for WDMS Candidates In SDSS-DR10 With Automatic Method].
Jiang, Bin; Wang, Cheng-you; Wang, Wen-yu; Wang, Wei
2015-05-01
The Sloan Digital Sky Survey (SDSS) has released the latest data (DR10) which covers the first APOGEE spectra. The massive spectra can be used for large sample research inscluding the structure and evolution of the Galaxy and multi-wave-band identi cation. In addition, the spectra are also ideal for searching for rare and special objects like white dwarf main-sequence star (WDMS). WDMS consist of a white dwarf primary and a low-mass main-sequence (MS) companion which has positive significance to the study of evolution and parameter of close binaries. WDMS is generally discovered by repeated imaging of the same area of sky, measuring light curves for objects or through photometric selection with follow-up observations. These methods require significant manual processing time with low accuracy and the real-time processing requirements can not be satisfied. In this paper, an automatic and efficient method for searching for WDMS candidates is presented. The method Genetic Algorithm (GA) is applied in the newly released SDSS-DR10 spectra. A total number of 4 140 WDMS candidates are selected by the method and 24 of them are new discoveries which prove that our approach of finding special celestial bodies in massive spectra data is feasible. In addition, this method is also applicable to mining other special celestial objects in sky survey telescope data. We report the identfication of 24 new WDMS with spectra. A compendium of positions, mjd, plate and fiberid of these new discoveries is presented which enrich the spectral library and will be useful to the research of binary evolution models. PMID:26415473
LITERATURE SEARCH FOR METHODS FOR HAZARD ANALYSES OF AIR CARRIER OPERATIONS.
MARTINEZ - GURIDI,G.; SAMANTA,P.
2002-07-01
Representatives of the Federal Aviation Administration (FAA) and several air carriers under Title 14 of the Code of Federal Regulations (CFR) Part 121 developed a system-engineering model of the functions of air-carrier operations. Their analyses form the foundation or basic architecture upon which other task areas are based: hazard analyses, performance measures, and risk indicator design. To carry out these other tasks, models may need to be developed using the basic architecture of the Air Carrier Operations System Model (ACOSM). Since ACOSM encompasses various areas of air-carrier operations and can be used to address different task areas with differing but interrelated objectives, the modeling needs are broad. A literature search was conducted to identify and analyze the existing models that may be applicable for pursuing the task areas in ACOSM. The intent of the literature search was not necessarily to identify a specific model that can be directly used, but rather to identify relevant ones that have similarities with the processes and activities defined within ACOSM. Such models may provide useful inputs and insights in structuring ACOSM models. ACOSM simulates processes and activities in air-carrier operation, but, in a general framework, it has similarities with other industries where attention also has been paid to hazard analyses, emphasizing risk management, and in designing risk indicators. To assure that efforts in other industries are adequately considered, the literature search includes publications from other industries, e.g., chemical, nuclear, and process industries. This report discusses the literature search, the relevant methods identified and provides a preliminary assessment of their use in developing the models needed for the ACOSM task areas. A detailed assessment of the models has not been made. Defining those applicable for ACOSM will need further analyses of both the models and tools identified. The report is organized in four chapters
Economic tour package model using heuristic
NASA Astrophysics Data System (ADS)
Rahman, Syariza Abdul; Benjamin, Aida Mauziah; Bakar, Engku Muhammad Nazri Engku Abu
2014-07-01
A tour-package is a prearranged tour that includes products and services such as food, activities, accommodation, and transportation, which are sold at a single price. Since the competitiveness within tourism industry is very high, many of the tour agents try to provide attractive tour-packages in order to meet tourist satisfaction as much as possible. Some of the criteria that are considered by the tourist are the number of places to be visited and the cost of the tour-packages. Previous studies indicate that tourists tend to choose economical tour-packages and aiming to visit as many places as they can cover. Thus, this study proposed tour-package model using heuristic approach. The aim is to find economical tour-packages and at the same time to propose as many places as possible to be visited by tourist in a given geographical area particularly in Langkawi Island. The proposed model considers only one starting point where the tour starts and ends at an identified hotel. This study covers 31 most attractive places in Langkawi Island from various categories of tourist attractions. Besides, the allocation of period for lunch and dinner are included in the proposed itineraries where it covers 11 popular restaurants around Langkawi Island. In developing the itinerary, the proposed heuristic approach considers time window for each site (hotel/restaurant/place) so that it represents real world implementation. We present three itineraries with different time constraints (1-day, 2-day and 3-day tour-package). The aim of economic model is to minimize the tour-package cost as much as possible by considering entrance fee of each visited place. We compare the proposed model with our uneconomic model from our previous study. The uneconomic model has no limitation to the cost with the aim to maximize the number of places to be visited. Comparison between the uneconomic and economic itinerary has shown that the proposed model have successfully achieved the objective that
Midtrimester termination of pregnancy--search for a better method continues.
Chhabra, S; Menon, G
1991-11-01
Every day a new method of termination of second trimester pregnancy clearly indicates that we have still not found a simple, safe, effective and economic method of termination of pregnancy in second trimester. Present study of 855 cases aims at searching out something better from available modalities. Age old hypertonic saline and ethacridine lactate were used with adjuvants like hyaluronidase and a preparation containing isapgol husk to reduce injection abortion interval and failures. Life threatening dangers of hypertonic saline are known. Ethacridine lactate seems to be safe. By giving it intra-amniotically with these adjuvants its major disadvantages could be minimised. There was no mortality. However, there was morbidity in the series. PMID:1787317
Hariri, Nadjla; Ravandi, Somayyeh Nadi
2014-01-01
Background: Medline is one of the most important databases in the biomedical field. One of the most important hosts for Medline is Elton B. Stephens CO. (EBSCO), which has presented different search methods that can be used based on the needs of the users. Visual search and MeSH-controlled search methods are among the most common methods. The goal of this research was to compare the precision of the retrieved sources in the EBSCO Medline base using MeSH-controlled and visual search methods. Methods: This research was a semi-empirical study. By holding training workshops, 70 students of higher education in different educational departments of Kashan University of Medical Sciences were taught MeSH-Controlled and visual search methods in 2012. Then, the precision of 300 searches made by these students was calculated based on Best Precision, Useful Precision, and Objective Precision formulas and analyzed in SPSS software using the independent sample T Test, and three precisions obtained with the three precision formulas were studied for the two search methods. Results: The mean precision of the visual method was greater than that of the MeSH-Controlled search for all three types of precision, i.e. Best Precision, Useful Precision, and Objective Precision, and their mean precisions were significantly different (P <0.001). Sixty-five percent of the researchers indicated that, although the visual method was better than the controlled method, the control of keywords in the controlled method resulted in finding more proper keywords for the searches. Fifty-three percent of the participants in the research also mentioned that the use of the combination of the two methods produced better results. Conclusion: For users, it is more appropriate to use a natural, language-based method, such as the visual method, in the EBSCO Medline host than to use the controlled method, which requires users to use special keywords. The potential reason for their preference was that the visual
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
The Priority Heuristic: Making Choices Without Trade-Offs
Brandstätter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph
2010-01-01
Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, we generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (i) Allais' paradox, (ii) risk aversion for gains if probabilities are high, (iii) risk seeking for gains if probabilities are low (lottery tickets), (iv) risk aversion for losses if probabilities are low (buying insurance), (v) risk seeking for losses if probabilities are high, (vi) certainty effect, (vii) possibility effect, and (viii) intransitivities. We test how accurately the heuristic predicts people's choices, compared to previously proposed heuristics and three modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory. PMID:16637767
Plying Your Craft: Instructional Development and the Use of Heuristics.
ERIC Educational Resources Information Center
Noel, Kent L.; Hewlett, Brent
1981-01-01
Examines an instructional systems design (ISD) model used by Bell Laboratories as an illustration of how heuristics can be brought to bear upon the design and development of instructional materials. Ten references are listed. (Author/MER)
ERIC Educational Resources Information Center
de Leeuw, L.
Sixty-four fifth and sixth-grade pupils were taught number series extrapolation by either an algorithm, fully prescribed problem-solving method or a heuristic, less prescribed method. The trained problems were within categories of two degrees of complexity. There were 16 subjects in each cell of the 2 by 2 design used. Aptitude Treatment…
The Ecosystem Approach: Perspectives, Heuristics and Interpretations
NASA Astrophysics Data System (ADS)
Kim, J.; Kang, M.; Malla Thakuri, B.; Yun, J.
2012-12-01
Based on the perspective of self-organization and complexity, we employed the ecosystem approach to translate the observed forest water and carbon dynamics into narratives. Multi-years' time series of the eddy covariance flux measurements from 2007 to 2010 are used to examine the ecohydrology in two adjacent deciduous and coniferous forest ecosystems in central Korea. Traditional descriptive analysis revealed contrasting interannual variability in net carbon uptake and evapotranspiration between the two forests, consistent with the interpretation on the basis of resilience framework. In a thermodynamic sense, net entropy production of the two forests was different in magnitude but their seasonal and interannual variability was consistent. The analysis of information entropy using the same data enabled to delineate the systems' state in terms of process network with an indication of self-organization through hierarchical aggregations of the subsystems. Finally, the ecosystem approach not only provided us with new perspectives, heuristics and interpretation, but also shed a light to prediction through parsimonious parameterization based on the maximum entropy production principle, for instance. (This study was supported by the Korea Meteorological Administration Research and Development Program under Grant CATER2012-3030. The flux data were provided by KoFlux and CarboEastAsia - A3 Foresight Program.)
Critics and advisors: Heuristic knowledge and manufacturability
Rivera, J.J.; Stubblefield, W.A.; Ames, A.L.
1996-06-01
In recent years, much of the progress in Computer-Aided Manufacturing has emphasized the use of simulation, finite-element analysis, and other science-based techniques to plan and evaluate manufacturing processes. These approaches are all based on the idea that we can build sufficiently faithful models of complex manufacturing processes such as machining, welding, and casting. Although there has been considerable progress in this area, it continues to suffer from difficulties: the first of these is that the kind of highly accurate models that this approach requires may take many person months to construct, and the second is the large amount of computing resources needed to run these simulations. Two design advisors, Near Net-Shape Advisor and Design for Machinability Advisor, are being developed to explore the role of heuristic, knowledge-based systems for manufacturing processes, both as an alternative to more analytical techniques, and also in support of these techniques. Currently the advisors are both in the prototype stage. All indications lead to the conclusion that the advisors will be successful and lay the groundwork for additional systems such as these in the future.
Heuristic Medicine: The Methodists and Metalepsis.
Webster, Colin
2015-09-01
In the first century B.C.E., a group of Greek physicians called the Methodists denied that medicine could be based on such "hidden causes" as humors, atoms, or elements. They argued that the inner workings of the body were ultimately unknowable, existing beyond the limits of human knowledge and inference. Yet they insisted that medical certainty was still possible, claiming that every disease shared one of three directly apprehensible "manifest commonalities"--stricture, laxity, or some mixture of the two. Medicine could therefore be a science; it was simply noncausal in structure. This essay examines these medical theories in light of Herbert Simon's concept of "bounded rationality," suggesting that the Methodists were proposing a type of medical "heuristic" in response to the limitations of human knowledge and processing power. At the same time, the essay suggests that such an epistemology had its consequences, setting up an ontological crunch whereby the demands formerly placed on diseases and their causes transferred to "affections" and the commonalities, with successive generations of Methodists disagreeing about the status of symptoms, signs, and diseased states. Borrowing vocabulary from the Methodists themselves, the essay calls the consequent ontological slippage between causes and effects "metalepsis". PMID:26685524
Neural Basis of Scientific Innovation Induced by Heuristic Prototype
Qiu, Jiang; Wei, Dongtao; Liu, Yijun; Zhang, Qinlin
2013-01-01
A number of major inventions in history have been based on bionic imitation. Heuristics, by applying biological systems to the creation of artificial devices and machines, might be one of the most critical processes in scientific innovation. In particular, prototype heuristics propositions that innovation may engage automatic activation of a prototype such as a biological system to form novel associations between a prototype's function and problem-solving. We speculated that the cortical dissociation between the automatic activation and forming novel associations in innovation is critical point to heuristic creativity. In the present study, novel and old scientific innovations (NSI and OSI) were selected as experimental materials in using learning-testing paradigm to explore the neural basis of scientific innovation induced by heuristic prototype. College students were required to resolve NSI problems (to which they did not know the answers) and OSI problems (to which they knew the answers). From two fMRI experiments, our results showed that the subjects could resolve NSI when provided with heuristic prototypes. In Experiment 1, it was found that the lingual gyrus (LG; BA18) might be related to prototype heuristics in college students resolving NSI after learning a relative prototype. In Experiment 2, the LG (BA18) and precuneus (BA31) were significantly activated for NSI compared to OSI when college students learned all prototypes one day before the test. In addition, the mean beta-values of these brain regions of NSI were all correlated with the behavior accuracy of NSI. As our hypothesis indicated, the findings suggested that the LG might be involved in forming novel associations using heuristic information, while the precuneus might be involved in the automatic activation of heuristic prototype during scientific innovation. PMID:23372641
A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map
NASA Astrophysics Data System (ADS)
Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad
2016-06-01
In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.
Case-parental control method in the search for disease-susceptibility genes
Khoury, M.J. )
1994-08-01
Historically, the search for disease-susceptibility genes has taken on two approaches, the linkage approach, traditionally the domain of the geneticist, and the association approach, traditionally the domain of the epidemiologist. The problem with association studies has been the choice of an appropriate control group with which cases can be compared with respect to the allelic distribution. The choice of appropriate controls has been extensively discussed in the epidemiology literature. To deal with confounding due to population stratification, sibling controls have been used as one group to adjust for genetic background. In the approach discussed by Knapp et al and Schaid and Sommer, the control group is a fictitious group formed by the parental alleles (at the locus of interest) that have not been transmitted to the proband. Cases and controls can then be compared with respect to the distribution of marker alleles at this locus, and measures of relative risk (haplotype or genotype relative risks) can be derived. The use of parental controls can provide a valuable method to search for disease-susceptibility genes for common diseases and to look for evidence of genotype-environment interaction. It is hoped that this methodology will be increasingly used in genetic-epidemiologic studies of disease.
ERIC Educational Resources Information Center
Conrad, Jack G.; Claussen, Joanne Smestad; Yang, Changwen
2002-01-01
Compares standard global information retrieval searching with more localized techniques to address the database selection problem that users often have when searching for the most relevant database, based on experiences with the Westlaw Directory. Findings indicate that a browse plus search approach in a hierarchical environment produces the most…
A search for streams and associations in meteor databases. Method of Indices
NASA Astrophysics Data System (ADS)
Svoreň, J.; Neslušan, L.; Porubčan, V.
2000-08-01
A new method of searching for minor meteor streams and associations is presented and discussed. The procedure, based only on mathematical statistics, enables a parallel separation of major and minor streams or associations. The approach utilizes a division of the ranges of examined parameters into equidistant intervals. The method is tested on the IAU Meteor Data Center Lund catalogue of precise photographic orbits representing the most extensive set of photographic meteor orbits. Besides the five orbital elements incorporated in the Southworth-Hawkins D-criterion, we have also included in the procedure the coordinates of the radiant which belong to the most accurately known parameters and the geocentric velocity as a significant parameter characteristic for physically related orbits. The basic idea of the procedure is a division of the observed ranges of parameters into a number of equidistant intervals and assignment of indices to a meteor according to the intervals pertinent to its parameters. The meteors with equal indices are regarded as mutually related. Since various parameters listed in the catalogue contain various relative errors, it is necessary to use several intervals in the division of each parameter to obtain a good fit with the real orbital distribution. The relative ratios, approximated by small integers, corresponding to the reciprocal values of the relative errors, were applied as the basic numbers for the division of the parameters. To test the quality of this method, the first step presented in this paper is aimed at wider intervals providing a less detailed classification (a smaller branching). In this step all the major streams (except of the northern branch of δ-Aquarids) were identified, confirming the efficiency of the procedure. After combining the related groups, 16 streams were identified. The search program also identifies widely spread Taurids. There are separated orbits pertinent to some minor streams such as the o-Draconids, κ
Probabilistic dual heuristic programming-based adaptive critic
NASA Astrophysics Data System (ADS)
Herzallah, Randa
2010-02-01
Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.
New insights into diversification of hyper-heuristics.
Ren, Zhilei; Jiang, He; Xuan, Jifeng; Hu, Yan; Luo, Zhongxuan
2014-10-01
There has been a growing research trend of applying hyper-heuristics for problem solving, due to their ability of balancing the intensification and the diversification with low level heuristics. Traditionally, the diversification mechanism is mostly realized by perturbing the incumbent solutions to escape from local optima. In this paper, we report our attempt toward providing a new diversification mechanism, which is based on the concept of instance perturbation. In contrast to existing approaches, the proposed mechanism achieves the diversification by perturbing the instance under solving, rather than the solutions. To tackle the challenge of incorporating instance perturbation into hyper-heuristics, we also design a new hyper-heuristic framework HIP-HOP (recursive acronym of HIP-HOP is an instance perturbation-based hyper-heuristic optimization procedure), which employs a grammar guided high level strategy to manipulate the low level heuristics. With the expressive power of the grammar, the constraints, such as the feasibility of the output solution could be easily satisfied. Numerical results and statistical tests over both the Ising spin glass problem and the p -median problem instances show that HIP-HOP is able to achieve promising performances. Furthermore, runtime distribution analysis reveals that, although being relatively slow at the beginning, HIP-HOP is able to achieve competitive solutions once given sufficient time. PMID:25222719
Heuristic Reasoning in Chemistry: Making decisions about acid strength
NASA Astrophysics Data System (ADS)
McClary, LaKeisha; Talanquer, Vicente
2011-07-01
The characterization of students' reasoning strategies is of central importance in the development of instructional strategies that foster meaningful learning. In particular, the identification of shortcut reasoning procedures (heuristics) used by students to reduce cognitive load can help us devise strategies to facilitate the development of more analytical ways of thinking. The central goal of this qualitative study was thus to investigate heuristic reasoning as used by organic chemistry college students, focusing our attention on their ability to predict the relative acid strength of chemical compounds represented using explicit composition and structural features (i.e., structural formulas). Our results indicated that many study participants relied heavily on one or more of the following heuristics to make most of their decisions: reduction, representativeness, and lexicographic. Despite having visual access to reach structural information about the substances included in each ranking task, many students relied on isolated composition features to make their decisions. However, the specific characteristics of the tasks seemed to trigger heuristic reasoning in different ways. Although the use of heuristics allowed students to simplify some components of the ranking tasks and generate correct responses, it often led them astray. Very few study participants predicted the correct trends based on scientifically acceptable arguments. Our results suggest the need for instructional interventions that explicitly develop college chemistry students' abilities to monitor their thinking and evaluate the effectiveness of analytical versus heuristic reasoning strategies in different contexts.
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.
NASA Astrophysics Data System (ADS)
Shakir, Ali; AL-Khateeb, Belal; Shaker, Khalid; Jalab, Hamid A.
2014-12-01
The design of course timetables for academic institutions is a very difficult job due to the huge number of possible feasible timetables with respect to the problem size. This process contains lots of constraints that must be taken into account and a large search space to be explored, even if the size of the problem input is not significantly large. Different heuristic approaches have been proposed in the literature in order to solve this kind of problem. One of the efficient solution methods for this problem is tabu search. Different neighborhood structures based on different types of move have been defined in studies using tabu search. In this paper, different neighborhood structures on the operation of tabu search are examined. The performance of different neighborhood structures is tested over eleven benchmark datasets. The obtained results of every neighborhood structures are compared with each other. Results obtained showed the disparity between each neighborhood structures and another in terms of penalty cost.
Analysis of Methods for Growth Detection in the Search for Extraterrestrial Life
Merek, Edward L.; Oyama, Vance I.
1968-01-01
In the search for life on other planets, experiments designed to detect the growth of microorganisms may prove to be definitive when coupled with chemical characterization and metabolic experiments. If organisms are not abundant, growth provides the only means for obtaining a large mass of biological material suitable for chemical compositional analyses and metabolic assays. Several methods of monitoring growth are described. Of these, optical monitoring in a unique system free of soil particles is advanced as the most appropriate. Theoretical problems related to the formulation of culture media are discussed, and several possible solutions are proposed. The sampling system, the type of monitoring, the size and placement of inoculum, and the medium volume and composition are contingent upon one another and must be integrated without sacrifice to the biological demands. Images Fig. 4 PMID:5659365
NASA Technical Reports Server (NTRS)
Fymat, A. L.
1976-01-01
The paper studies the inversion of the radiative transfer equation describing the interaction of electromagnetic radiation with atmospheric aerosols. The interaction can be considered as the propagation in the aerosol medium of two light beams: the direct beam in the line-of-sight attenuated by absorption and scattering, and the diffuse beam arising from scattering into the viewing direction, which propagates more or less in random fashion. The latter beam has single scattering and multiple scattering contributions. In the former case and for single scattering, the problem is reducible to first-kind Fredholm equations, while for multiple scattering it is necessary to invert partial integrodifferential equations. A nonlinear minimization search method, applicable to the solution of both types of problems has been developed, and is applied here to the problem of monitoring aerosol pollution, namely the complex refractive index and size distribution of aerosol particles.
Tau reconstruction methods at an electron-positron collider in the search for new physics
NASA Astrophysics Data System (ADS)
Li, Jinmian; Williams, Anthony G.
2016-04-01
By exploiting the relatively long lifetime of the tau lepton, we propose several novel methods for searching for new physics at an electron-positron collider. We consider processes that involve final states consisting of a tau lepton pair plus two missing particles. The mass and spin of the new physics particles can be measured in 3-prong tau decays. The tau polarization, which reflects the coupling to new physics, can be measured from the τ →π ν decay channel using the impact parameter distribution of the charged pion. We also discuss the corresponding backgrounds for these measurements, the next-to-leading order (NLO) effects, and the implications of finite detector resolution.
Grid-Search Location Methods for Ground-Truth Collection from Local and Regional Seismic Networks
Schultz, C A; Rodi, W; Myers, S C
2003-07-24
The objective of this project is to develop improved seismic event location techniques that can be used to generate more and better quality reference events using data from local and regional seismic networks. Their approach is to extend existing methods of multiple-event location with more general models of the errors affecting seismic arrival time data, including picking errors and errors in model-based travel-times (path corrections). Toward this end, they are integrating a grid-search based algorithm for multiple-event location (GMEL) with a new parameterization of travel-time corrections and new kriging method for estimating the correction parameters from observed travel-time residuals. Like several other multiple-event location algorithms, GMEL currently assumes event-independent path corrections and is thus restricted to small event clusters. The new parameterization assumes that travel-time corrections are a function of both the event and station location, and builds in source-receiver reciprocity and correlation between the corrections from proximate paths as constraints. The new kriging method simultaneously interpolates travel-time residuals from multiple stations and events to estimate the correction parameters as functions of position. They are currently developing the algorithmic extensions to GMEL needed to combine the new parameterization and kriging method with the simultaneous location of events. The result will be a multiple-event location method which is applicable to non-clustered, spatially well-distributed events. They are applying the existing components of the new multiple-event location method to a data set of regional and local arrival times from Nevada Test Site (NTS) explosions with known origin parameters. Preliminary results show the feasibility and potential benefits of combining the location and kriging techniques. They also show some preliminary work on generalizing of the error model used in GMEL with the use of mixture
Grid-Search Location Methods for Ground-Truth Collection From Local and Regional Seismic Networks
William Rodi; Craig A. Schultz; Gardar Johannesson; Stephen C. Myers
2005-05-13
This project investigated new techniques for improving seismic event locations derived from regional and local networks. The technqiues include a new approach to empirical travel-time calibration that simultaneously fits data from multiple stations and events, using a generalization of the kriging method, and predicts travel-time corrections for arbitrary event-station paths. We combined this calibration approach with grid-search event location to produce a prototype new multiple-event location method that allows the use of spatially well-distributed events and takes into account correlations between the travel-time corrections from proximate event-station paths. Preliminary tests with a high quality data set from Nevada Test Site explosions indicated that our new calibration/location method offers improvement over the conventional multiple-event location methods now in common use, and is applicable to more general event-station geometries than the conventional methods. The tests were limited, however, and further research is needed to fully evaluate, and improve, the approach. Our project also demonstrated the importance of using a realistic model for observational errors in an event location procedure. We took the initial steps in developing a new error model based on mixture-of-Gaussians probability distributions, which possess the properties necessary to characterize the complex arrival time error processes that can occur when picking low signal-to-noise arrivals. We investigated various inference methods for fitting these distributions to observed travel-time residuals, including a Markov Chain Monte Carlo technique for computing Bayesian estimates of the distribution parameters.
Bennett, Joseph W.; Rabe, Karin M.
2012-11-15
In this concept paper, the development of strategies for the integration of first-principles methods with crystallographic database mining for the discovery and design of novel ferroelectric materials is discussed, drawing on the results and experience derived from exploratory investigations on three different systems: (1) the double perovskite Sr(Sb{sub 1/2}Mn{sub 1/2})O{sub 3} as a candidate semiconducting ferroelectric; (2) polar derivatives of schafarzikite MSb{sub 2}O{sub 4}; and (3) ferroelectric semiconductors with formula M{sub 2}P{sub 2}(S,Se){sub 6}. A variety of avenues for further research and investigation are suggested, including automated structure type classification, low-symmetry improper ferroelectrics, and high-throughput first-principles searches for additional representatives of structural families with desirable functional properties. - Graphical abstract: Integration of first-principles methods with crystallographic database mining, for the discovery and design of novel ferroelectric materials, could potentially lead to new classes of multifunctional materials. Highlights: Black-Right-Pointing-Pointer Integration of first-principles methods and database mining. Black-Right-Pointing-Pointer Minor structural families with desirable functional properties. Black-Right-Pointing-Pointer Survey of polar entries in the Inorganic Crystal Structural Database.
Local search for the generalized tree alignment problem
2013-01-01
Background A phylogeny postulates shared ancestry relationships among organisms in the form of a binary tree. Phylogenies attempt to answer an important question posed in biology: what are the ancestor-descendent relationships between organisms? At the core of every biological problem lies a phylogenetic component. The patterns that can be observed in nature are the product of complex interactions, constrained by the template that our ancestors provide. The problem of simultaneous tree and alignment estimation under Maximum Parsimony is known in combinatorial optimization as the Generalized Tree Alignment Problem (GTAP). The GTAP is the Steiner Tree Problem for the sequence edit distance. Like many biologically interesting problems, the GTAP is NP-Hard. Typically the Steiner Tree is presented under the Manhattan or the Hamming distances. Results Experimentally, the accuracy of the GTAP has been subjected to evaluation. Results show that phylogenies selected using the GTAP from unaligned sequences are competitive with the best methods and algorithms available. Here, we implement and explore experimentally existing and new local search heuristics for the GTAP using simulated and real data. Conclusions The methods presented here improve by more than three orders of magnitude in execution time the best local search heuristics existing to date when applied to real data. PMID:23441880
NASA Astrophysics Data System (ADS)
Konak, Abdullah
2014-01-01
This article presents a network design problem with relays considering the two-edge network connectivity. The problem arises in telecommunications and logistic networks where a constraint is imposed on the distance that a commodity can travel on a route without being processed by a relay, and the survivability of the network is critical in case of a component failure. The network design problem involves selecting two-edge disjoint paths between source and destination node pairs and determining the location of relays to minimize the network design cost. The formulated problem is solved by a hybrid approach of a genetic algorithm (GA) and a Lagrangian heuristic such that the GA searches for two-edge disjoint paths for each commodity, and the Lagrangian heuristic is used to determine relays on these paths. The performance of the proposed hybrid approach is compared to the previous approaches from the literature, with promising results.
Elliptical tiling method to generate a 2-dimensional set of templates for gravitational wave search
NASA Astrophysics Data System (ADS)
Arnaud, Nicolas; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Kreckelbergh, Stephane; Porter, Edward K.
2003-05-01
Searching for a signal depending on unknown parameters in a noisy background with matched filtering techniques always requires an analysis of the data with several templates in parallel in order to ensure a proper match between the filter and the real waveform. The key feature of such an implementation is the design of the filter bank which must be small to limit the computational cost while keeping the detection efficiency as high as possible. This paper presents a geometrical method that allows one to cover the corresponding physical parameter space by a set of ellipses, each of them being associated with a given template. After the description of the main characteristics of the algorithm, the method is applied in the field of gravitational wave (GW) data analysis, for the search of damped sine signals. Such waveforms are expected to be produced during the deexcitation phase of black holes—the so-called “ringdown” signals—and are also encountered in some numerically computed supernova signals. First, the number of templates
Formal versus heuristic modeling for multitarget Bayes filtering
NASA Astrophysics Data System (ADS)
Mahler, Ronald P. S.
2004-08-01
The multisensor-multitarget Bayes filter is the foundation for multi-sensor-multitarget detection, tracking, and identification. This paper addresses the question of principled implementation of this filter. Algorithms can always be cobbled together using catch-as-catch-can heuristic techniques. In formal Bayes modeling one instead derives statistically precise, implementation-independent equations from which principle approximations can then be derived. Indeed, this has become the accepted methodology for single-sensor, single-target tracking R&D. In the case of the multitarget filter, however, partisans of a so-called "plain-vanilla Bayesian approach" have disparaged formal Bayes modelling, and have protrayed specific, ad hoc implementations as completely general, "powerful and robust computational methods." In this and a companion paper I expose the speciousness of such claims. This paper reviews the elements of formal Bayes modeling and approximation, describes what they must look like in the multitarget case, and contrasts them with the "plain-vanilla Bayesian approach."
Searching chromosomal landmarks in Indian lentils through EMA-based Giemsa staining method.
Jha, Timir Baran; Halder, Mihir
2016-09-01
Lentil is one of the oldest protein-rich food crop with only one cultivated and six wild species. India is one important cultivator, producer and consumer of lentils and possesses a large number of germplasms. All species of lentil show 2n = 14 chromosomes. The primary objective of the present paper is to search chromosomal landmarks through enzymatic maceration and air drying (EMA)-based Giemsa staining method in five Indian lentil species not reported elsewhere at a time. Additionally, gametic chromosome analysis, tendril formation and seed morphology have been studied to ascertain interspecific relationships in lentils. Chromosome analysis in Lens culinaris, Lens orientalis and Lens odemensis revealed that they contain intercalary sat chromosome and similar karyotypic formula, while Lens nigricans and Lens lamottei showed presence of terminal sat chromosomes not reported earlier. This distinct morphological feature in L. nigricans and L. lamottei may be considered as chromosomal landmark. Meiotic analysis showed n = 7 bivalents in L. culinaris, L. nigricans and L. lamottei. No tendril formation was observed in L. culinaris, L. orientalis and L. odemensis while L. nigricans and L. lamottei developed very prominent tendrils. Based on chromosomal analysis, tendril formation and seed morphology, the five lentil species can be separated into two distinct groups. The outcome of this research may enrich conventional and biotechnological breeding programmes in lentil and may facilitate an easy and alternative method for identification of interspecific hybrids. PMID:26342302
Tyteca, Eva; Vanderlinden, Kim; Favier, Maxime; Clicq, David; Cabooter, Deirdre; Desmet, Gert
2014-09-01
Linear gradient programs are very frequently used in reversed phase liquid chromatography to enhance the selectivity compared to isocratic separations. Multi-linear gradient programs on the other hand are only scarcely used, despite their intrinsically larger separation power. Because the gradient-conformity of the latest generation of instruments has greatly improved, a renewed interest in more complex multi-segment gradient liquid chromatography can be expected in the future, raising the need for better performing gradient design algorithms. We explored the possibilities of a new type of multi-segment gradient optimization algorithm, the so-called "one-segment-per-group-of-components" optimization strategy. In this gradient design strategy, the slope is adjusted after the elution of each individual component of the sample, letting the retention properties of the different analytes auto-guide the course of the gradient profile. Applying this method experimentally to four randomly selected test samples, the separation time could on average be reduced with about 40% compared to the best single linear gradient. Moreover, the newly proposed approach performed equally well or better than the multi-segment optimization mode of a commercial software package. Carrying out an extensive in silico study, the experimentally observed advantage could also be generalized over a statistically significant amount of different 10 and 20 component samples. In addition, the newly proposed gradient optimization approach enables much faster searches than the traditional multi-step gradient design methods. PMID:25039066
Incorrect Likelihood Methods Were Used to Infer Scaling Laws of Marine Predator Search Behaviour
Edwards, Andrew M.; Freeman, Mervyn P.; Breed, Greg A.; Jonsen, Ian D.
2012-01-01
Background Ecologists are collecting extensive data concerning movements of animals in marine ecosystems. Such data need to be analysed with valid statistical methods to yield meaningful conclusions. Principal Findings We demonstrate methodological issues in two recent studies that reached similar conclusions concerning movements of marine animals (Nature 451∶1098; Science 332∶1551). The first study analysed vertical movement data to conclude that diverse marine predators (Atlantic cod, basking sharks, bigeye tuna, leatherback turtles and Magellanic penguins) exhibited “Lévy-walk-like behaviour”, close to a hypothesised optimal foraging strategy. By reproducing the original results for the bigeye tuna data, we show that the likelihood of tested models was calculated from residuals of regression fits (an incorrect method), rather than from the likelihood equations of the actual probability distributions being tested. This resulted in erroneous Akaike Information Criteria, and the testing of models that do not correspond to valid probability distributions. We demonstrate how this led to overwhelming support for a model that has no biological justification and that is statistically spurious because its probability density function goes negative. Re-analysis of the bigeye tuna data, using standard likelihood methods, overturns the original result and conclusion for that data set. The second study observed Lévy walk movement patterns by mussels. We demonstrate several issues concerning the likelihood calculations (including the aforementioned residuals issue). Re-analysis of the data rejects the original Lévy walk conclusion. Conclusions We consequently question the claimed existence of scaling laws of the search behaviour of marine predators and mussels, since such conclusions were reached using incorrect methods. We discourage the suggested potential use of “Lévy-like walks” when modelling consequences of fishing and climate change, and caution that
Graph coloring heuristics for solving examination timetabling problem at Universiti Utara Malaysia
NASA Astrophysics Data System (ADS)
Abdul-Rahman, Syariza; Sobri, Nur Suriani; Omar, Mohd Faizal; Benjamin, Aida Mauziah; Ramli, Razamin
2014-12-01
Examination timetabling is a well-studied combinatorial optimization problem involving scheduling a set of examinations into a restricted number of time-slots while satisfying a defined set of constraints. This paper presents a real-world, capacitated examination timetabling problem from Universiti Utara Malaysia (UUM), Malaysia. This dataset differs from the others reported in the literature with respect to its size, complexity and constraints. Until recently, examination timetabling in UUM is done manually with a little guidance from spreadsheet computer software for checking clashes. The propriety system is unable to do the examination timetabling automatically. Besides, the introduced datasets also consider a new constraint that has never been modeled before in timetabling literature, which is lecturer's preference. Moreover, splitting examination across several rooms and a number of hard constraints such as no mixed duration of examination within individual periods, clashes free schedule and room capacity requirement are also need to be adhered. These constraints provide an additional challenge in solving the examination timetabling problem, mainly at UUM. In this paper, graph coloring heuristics are employed to schedule examinations at each step during timetable construction. We used the concept of bin packing heuristics to assign examination to room with respect to the capacity. Since this is a new dataset and no solutions have been published in the literature yet, we only compare the results with an existing manual solution. It is found that the proposed constructive heuristic able to produce good quality solution for the tested problem. The proposed graph coloring heuristics are proved to be superior to the current method employed by the University and found to perform well in comparison.
Applied tagmemics: A heuristic approach to the use of graphic aids in technical writing
NASA Technical Reports Server (NTRS)
Brownlee, P. P.; Kirtz, M. K.
1981-01-01
In technical report writing, two needs which must be met if reports are to be useable by an audience are the language needs and the technical needs of that particular audience. A heuristic analysis helps to decide the most suitable format for information; that is, whether the information should be presented verbally or visually. The report writing process should be seen as an organic whole which can be divided and subdivided according to the writer's purpose, but which always functions as a totality. The tagmemic heuristic, because it itself follows a process of deconstructing and reconstructing information, lends itself to being a useful approach to the teaching of technical writing. By applying the abstract questions this heuristic asks to specific parts of the report. The language and technical needs of the audience are analyzed by examining the viability of the solution within the givens of the corporate structure, and by deciding which graphic or verbal format will best suit the writer's purpose. By following such a method, answers which are both specific and thorough in their range of application are found.
Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis
Huang, Yan Xin; Bao, Yong Li; Guo, Shu Yan; Wang, Yan; Zhou, Chun Guang; Li, Yu Xin
2008-01-01
Background The prediction of conformational B-cell epitopes is one of the most important goals in immunoinformatics. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues of interaction between an antigen and an antibody. Consequently, this area of research has received considerable attention from immunologists, structural biologists and computational biologists. Phage-displayed random peptide libraries are powerful tools used to obtain mimotopes that are selected by binding to a given monoclonal antibody (mAb) in a similar way to the native epitope. These mimotopes can be considered as functional epitope mimics. Mimotope analysis based methods can predict not only linear but also conformational epitopes and this has been the focus of much research in recent years. Though some algorithms based on mimotope analysis have been proposed, the precise localization of the interaction site mimicked by the mimotopes is still a challenging task. Results In this study, we propose a method for B-cell epitope prediction based on mimotope analysis called Pep-3D-Search. Given the 3D structure of an antigen and a set of mimotopes (or a motif sequence derived from the set of mimotopes), Pep-3D-Search can be used in two modes: mimotope or motif. To evaluate the performance of Pep-3D-Search to predict epitopes from a set of mimotopes, 10 epitopes defined by crystallography were compared with the predicted results from a Pep-3D-Search: the average Matthews correlation oefficient (MCC), sensitivity and precision were 0.1758, 0.3642 and 0.6948. Compared with other available prediction algorithms, Pep-3D-Search showed comparable MCC, specificity and precision, and could provide novel, rational results. To verify the capability of Pep-3D-Search to align a motif sequence to a 3D structure for predicting epitopes, 6 test cases were used. The predictive performance of Pep-3D-Search was demonstrated to be superior to that of other
Discovery and problem solving: Triangulation as a weak heuristic
NASA Technical Reports Server (NTRS)
Rochowiak, Daniel
1987-01-01
Recently the artificial intelligence community has turned its attention to the process of discovery and found that the history of science is a fertile source for what Darden has called compiled hindsight. Such hindsight generates weak heuristics for discovery that do not guarantee that discoveries will be made but do have proven worth in leading to discoveries. Triangulation is one such heuristic that is grounded in historical hindsight. This heuristic is explored within the general framework of the BACON, GLAUBER, STAHL, DALTON, and SUTTON programs. In triangulation different bases of information are compared in an effort to identify gaps between the bases. Thus, assuming that the bases of information are relevantly related, the gaps that are identified should be good locations for discovery and robust analysis.
Plan-graph Based Heuristics for Conformant Probabilistic Planning
NASA Technical Reports Server (NTRS)
Ramakrishnan, Salesh; Pollack, Martha E.; Smith, David E.
2004-01-01
In this paper, we introduce plan-graph based heuristics to solve a variation of the conformant probabilistic planning (CPP) problem. In many real-world problems, it is the case that the sensors are unreliable or take too many resources to provide knowledge about the environment. These domains are better modeled as conformant planning problems. POMDP based techniques are currently the most successful approach for solving CPP but have the limitation of state- space explosion. Recent advances in deterministic and conformant planning have shown that plan-graphs can be used to enhance the performance significantly. We show that this enhancement can also be translated to CPP. We describe our process for developing the plan-graph heuristics and estimating the probability of a partial plan. We compare the performance of our planner PVHPOP when used with different heuristics. We also perform a comparison with a POMDP solver to show over a order of magnitude improvement in performance.
A Comparison of Genetic Programming Variants for Hyper-Heuristics
Harris, Sean
2015-03-01
Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.
The inherence heuristic as a source of essentialist thought.
Salomon, Erika; Cimpian, Andrei
2014-10-01
Humans are essentialists: They believe hidden "essences" underlie membership in natural and social kinds. Although essentialism has well-established implications for important societal issues (e.g., discrimination), little is known about its origins. According to a recent proposal, essentialism emerges from a broader inherence heuristic-an intuitive tendency to explain patterns in terms of the inherent properties of their constituents (e.g., we have orange juice for breakfast [pattern] because citrus aromas [inherent feature] wake us up). We tested two predictions of this proposal-that reliance on the inherence heuristic predicts endorsement of essentialist beliefs, even when adjusting for potentially confounding variables (Studies 1 and 2), and that reducing reliance on the inherence heuristic produces a downstream reduction in essentialist thought (Studies 3 and 4). The results were consistent with these predictions and thus provided evidence for a new theoretical perspective on the cognitive underpinnings of psychological essentialism. PMID:25037751
The seismic method in the search for oil and gas: Current techniques and future developments
Berkhout, A.J.
1986-08-01
In applying seismic echo techniques to oil and gas exploration, the underground is ''illuminated'' from the surface by acoustic waves. The incident wavefield is reflected at the geologic layer boundaries and is registered at the surface, yielding detailed information on earth's upper structure. An important aspect of the seismic method is that an unprocessed seismic image does not represent the actual picture. Each reflection has been distorted during its propagation through earth. These distortions have to be corrected before an accurate picture can be developed. This is in most cases accomplished by ''seismic inversion.'' In this paper, current seismic techniques for oil and gas search, and their further development, are reviewed, with emphasis on seismic inversion. It is shown that important new developments in theory, software, and hardware have yielded significant improvements in wave theory solutions. Most research results presented are general and apply equally well to other echo technique applications, such as ultrasonic medical imaging, nondestructive testing, acoustic microscopy, sonar, and ground radar.
Thermodynamic ground state of MgB{sub 6} predicted from first principles structure search methods
Wang, Hui; Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5E2 ; LeBlanc, K. A.; Gao, Bo; Yao, Yansun; Canadian Light Source, Saskatoon, Saskatchewan S7N 0X4
2014-01-28
Crystalline structures of magnesium hexaboride, MgB{sub 6}, were investigated using unbiased structure searching methods combined with first principles density functional calculations. An orthorhombic Cmcm structure was predicted as the thermodynamic ground state of MgB{sub 6}. The energy of the Cmcm structure is significantly lower than the theoretical MgB{sub 6} models previously considered based on a primitive cubic arrangement of boron octahedra. The Cmcm structure is stable against the decomposition to elemental magnesium and boron solids at atmospheric pressure and high pressures up to 18.3 GPa. A unique feature of the predicted Cmcm structure is that the boron atoms are clustered into two forms: localized B{sub 6} octahedra and extended B{sub ∞} ribbons. Within the boron ribbons, the electrons are delocalized and this leads to a metallic ground state with vanished electric dipoles. The present prediction is in contrast to the previous proposal that the crystalline MgB{sub 6} maintains a semiconducting state with permanent dipole moments. MgB{sub 6} is estimated to have much weaker electron-phonon coupling compared with that of MgB{sub 2}, and therefore it is not expected to be able to sustain superconductivity at high temperatures.
Zhang, H H; Gao, S; Chen, W; Shi, L; D’Souza, W D; Meyer, R R
2013-01-01
An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the Nested Partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are superior quality. PMID:23459411
Noncoplanar beam angle optimization in IMRT treatment planning using pattern search methods
NASA Astrophysics Data System (ADS)
Rocha, Humberto; Dias, Joana M.; Ferreira, Brígida C.; Lopes, Maria C.
2015-05-01
Radiation therapy is used to treat localized cancers, aiming to deliver a dose of radiation to the tumor volume to sterilize all cancer cells while minimizing the collateral effects on the surrounding healthy organs and tissues. The planning of radiation therapy treatments requires decisions regarding the angles used for radiation incidence, the fluence intensities and, if multileaf collimators are used, the definition of the leaf sequencing. The beam angle optimization problem consists in finding the optimal number and incidence directions of the irradiation beams. The selection of appropriate radiation incidence directions is important for the quality of the treatment. However, the possibility of improving the quality of treatment plans by an optimized selection of the beam incidences is seldom done in the clinical practice. Adding the possibility for noncoplanar incidences is even more rarely used. Nevertheless, the advantage of noncoplanar beams is well known. The optimization of noncoplanar beam incidences may further allow the reduction of the number of beams needed to reach a clinically acceptable plan. In this paper we present the benefits of using pattern search methods for the optimization of the highly non-convex noncoplanar beam angle optimization problem.
NASA Astrophysics Data System (ADS)
Zhang, H. H.; Gao, S.; Chen, W.; Shi, L.; D'Souza, W. D.; Meyer, R. R.
2013-03-01
An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality.
Drory Retwitzer, Matan; Kifer, Ilona; Sengupta, Supratim; Yakhini, Zohar; Barash, Danny
2015-01-01
Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is to find additional eukaryotic riboswitches since more than 20 riboswitch classes have been found in prokaryotes but only one class has been found in eukaryotes. Moreover, this single known class of eukaryotic riboswitch, namely the TPP riboswitch class, has been found in bacteria, archaea, fungi and plants but not in animals. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods such as a combination of BLAST and pattern matching techniques that incorporate base-pairing considerations. None of these approaches perform energy minimization structure predictions. There is a clear motivation to develop new bioinformatics methods, aside of the ongoing advances in covariance models, that will sample the sequence search space more flexibly using structural guidance while retaining the computational efficiency of sequence-based methods. We present a new energy minimization approach that transforms structure-based search into a sequence-based search, thereby enabling the utilization of well established sequence-based search utilities such as BLAST and FASTA. The transformation to sequence space is obtained by using an extended inverse RNA folding problem solver with sequence and structure constraints, available within RNAfbinv. Examples in applying the new method are presented for the purine and preQ1 riboswitches. The method is described in detail along with its findings in prokaryotes. Potential uses in finding novel eukaryotic riboswitches and optimizing pre-designed synthetic riboswitches based on ligand simulations are discussed. The method components are freely available for use. PMID
SNPs Selection using Gravitational Search Algorithm and Exhaustive Search for Association Mapping
NASA Astrophysics Data System (ADS)
Kusuma, W. A.; Hasibuan, L. S.; Istiadi, M. A.
2016-01-01
Single Nucleotide Polymorphisms (SNPs) are known having association to phenotipic variations. The study of linking SNPs to interest phenotype is refer to Association Mapping (AM), which is classified as a combinatorial problem. Exhaustive Search (ES) approach is able to be implemented to select targeted SNPs exactly since it evaluate all possible combinations of SNPs, but it is not efficient in terms of computer resources and computation time. Heuristic Search (HS) approach is an alternative to improve the performance of ES in those terms, but it still suffers high false positive SNPs in each combinations. Gravitational Search Algorithm (GSA) is a new HS algorithm that yields better performance than other nature inspired HS. This paper proposed a new method which combined GSA and ES to identify the most appropriate combination of SNPs linked to interest phenotype. Testing was conducted using dataset without epistasis and dataset with epistasis. Using dataset without epistasis with 7 targeted SNPs, the proposed method identified 7 SNPs - 6 True Positive (TP) SNPs and 1 False Positive (FP) SNP- with association value of 0.83. In addition, the proposed method could identified 3 SNPs- 2 TP SNP and 1 FP SNP with association value of 0.87 by using dataset with epistases and 5 targeted SNPs. The results showed that the method is robust in reducing redundant SNPs and identifying main markers.
NASA Astrophysics Data System (ADS)
Lazorenko, P. F.; Sahlmann, J.; Ségransan, D.; Martín, E. L.; Mayor, M.; Queloz, D.; Udry, S.
2014-05-01
Aims: We describe the astrometric reduction of images obtained with the FORS2/VLT camera in the framework of an astrometric planet search around 20 M/L-transition dwarfs. We present the correction of systematic errors, the achieved astrometric performance, and a new astrometric catalogue containing the faint reference stars in 20 fields located close to the Galactic plane. Methods: Remote reference stars were used both to determine the astrometric trajectories of the nearby planet search targets and to identify and correct systematic errors. Results: We detected three types of systematic errors in the FORS2 astrometry: the relative motion of the camera's two CCD chips, errors that are correlated in space, and an error contribution of as yet unexplained origin. The relative CCD motion probably has a thermal origin and typically is 0.001-0.010 px (~0.1-1 mas), but sometimes amounts to 0.02-0.05 px (3-6 mas). This instability and space-correlated errors are detected and mitigated using reference stars. The third component of unknown origin has an amplitude of 0.03-0.14 mas and is independent of the observing conditions. We find that a consecutive sequence of 32 images of a well-exposed star over 40 min at 0.6'' seeing results in a median rms of the epoch residuals of 0.126 mas. Overall, the epoch residuals are distributed according to a normal law with a χ2 value near unity. We compiled a catalogue of 12 000 stars with I-band magnitudes of 16-22 located in 20 fields, each covering ~ 2' × 2'. It contains I-band magnitudes, ICRF positions with 40-70 mas precision, and relative proper motions and absolute trigonometric parallaxes with a precision of 0.1 mas/yr and 0.1 mas at the bright end, respectively. Conclusions: This work shows that an astrometric accuracy of ~100 micro-arcseconds over two years can be achieved with a large optical telescope in a survey covering several targets and varying observing conditions. Based on observations made with ESO telescopes at the
Reasoning by analogy as an aid to heuristic theorem proving.
NASA Technical Reports Server (NTRS)
Kling, R. E.
1972-01-01
When heuristic problem-solving programs are faced with large data bases that contain numbers of facts far in excess of those needed to solve any particular problem, their performance rapidly deteriorates. In this paper, the correspondence between a new unsolved problem and a previously solved analogous problem is computed and invoked to tailor large data bases to manageable sizes. This paper outlines the design of an algorithm for generating and exploiting analogies between theorems posed to a resolution-logic system. These algorithms are believed to be the first computationally feasible development of reasoning by analogy to be applied to heuristic theorem proving.
Heuristic judgment of mass ratio in two-body collisions.
Gilden, D L; Proffitt, D R
1994-12-01
The logic of judging relative mass from a two-body collision is developed from data presented by Runeson and Vedeler (1993). Data from two experiments are analyzed on a point-by-point basis, and strong support for the theory that mass-ratio judgments are mediated by separate speed and angle heuristics is shown. This analysis is accomplished by reducing the collision event to two elementary features: the presence of ricochet and the ratio of exit speeds. The heuristics that both ricochet and greater exit speed specify relative lightness are shown to explain the basic patterns of data presented by Runeson and Vedeler. PMID:7816541
The continuous period search method and its application to the young solar analogue HD 116956
NASA Astrophysics Data System (ADS)
Lehtinen, J.; Jetsu, L.; Hackman, T.; Kajatkari, P.; Henry, G. W.
2011-03-01
Aims: We formulate an improved time series analysis method for the analysis of photometry of active stars. This new continuous period search (CPS) method is applied to 12 years of V band photometry of the young solar analogue HD 116956 (NQ UMa). Methods: The new method is developed from the previous three stage period analysis (TSPA) method. Our improvements are the use of a sliding window in choosing the modelled datasets, a criterion applied to select the best model for each dataset and the computation of the time scale of change of the light curve. We test the performance of CPS with simulated and real data. Results: The CPS has a much improved time resolution which allows us to better investigate fast evolution of stellar light curves. We can also separate between the cases when the data is best described by periodic (i.e. rotational modulation of brightness) and aperiodic (e.g. constant brightness) models. We find, however, that the performance of the CPS has certain limitations. It does not determine the correct model complexity in all cases, especially when the underlying light curve is constant and the number of observations too small. Also the sensitivity in detecting two close light curve minima is limited and it has a certain amount of intrinsic instability in its period estimation. Using the CPS, we find persistent active longitudes in the star HD 116956 and a "flip-flop" event that occurred during the year 1999. Assuming that the surface differential rotation of the star causes observable period variations in the stellar light curve, we determine the differential rotation coefficient to be |k| > 0.11. The mean timescale of change of the light curve during the whole 12 year observing period was overline{TC=44.1} d, which is of the same order as the predicted convective turnover time of the star. We also investigate the presence of activity cycles on the star, but do not find any conclusive evidence supporting them. The analysed photometry and numerical
New Tabu Search based global optimization methods outline of algorithms and study of efficiency.
Stepanenko, Svetlana; Engels, Bernd
2008-04-15
The study presents two new nonlinear global optimization routines; the Gradient Only Tabu Search (GOTS) and the Tabu Search with Powell's Algorithm (TSPA). They are based on the Tabu-Search strategy, which tries to determine the global minimum of a function by the steepest descent-mildest ascent strategy. The new algorithms are explained and their efficiency is compared with other approaches by determining the global minima of various well-known test functions with varying dimensionality. These tests show that for most tests the GOTS possesses a much faster convergence than global optimizer taken from the literature. The efficiency of the TSPA compares to the efficiency of genetic algorithms. PMID:17910004
A Spatial Overlay Ranking Method for a Geospatial Search of Text Objects
Lanfear, Kenneth J.
2006-01-01
Earth-science researchers need the capability to find relevant information by location and topic. Conventional geographic techniques that simply check whether polygons intersect can efficiently achieve a high recall on location, but can not achieve precision for ranking results in likely order of importance to the reader. A spatial overlay ranking based upon how well an object's footprint matches the search area provides a more effective way to spatially search a collection of reports, and avoids many of the problems associated with an 'in/out' (True/False) boolean search. Moreover, spatial overlay ranking appears to work well even when spatial extent is defined only by a simple bounding box.
Model Specification Searches Using Ant Colony Optimization Algorithms
ERIC Educational Resources Information Center
Marcoulides, George A.; Drezner, Zvi
2003-01-01
Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.
TRStalker: an efficient heuristic for finding fuzzy tandem repeats
Pellegrini, Marco; Renda, M. Elena; Vecchio, Alessio
2010-01-01
Motivation: Genomes in higher eukaryotic organisms contain a substantial amount of repeated sequences. Tandem Repeats (TRs) constitute a large class of repetitive sequences that are originated via phenomena such as replication slippage and are characterized by close spatial contiguity. They play an important role in several molecular regulatory mechanisms, and also in several diseases (e.g. in the group of trinucleotide repeat disorders). While for TRs with a low or medium level of divergence the current methods are rather effective, the problem of detecting TRs with higher divergence (fuzzy TRs) is still open. The detection of fuzzy TRs is propaedeutic to enriching our view of their role in regulatory mechanisms and diseases. Fuzzy TRs are also important as tools to shed light on the evolutionary history of the genome, where higher divergence correlates with more remote duplication events. Results: We have developed an algorithm (christened TRStalker) with the aim of detecting efficiently TRs that are hard to detect because of their inherent fuzziness, due to high levels of base substitutions, insertions and deletions. To attain this goal, we developed heuristics to solve a Steiner version of the problem for which the fuzziness is measured with respect to a motif string not necessarily present in the input string. This problem is akin to the ‘generalized median string’ that is known to be an NP-hard problem. Experiments with both synthetic and biological sequences demonstrate that our method performs better than current state of the art for fuzzy TRs and that the fuzzy TRs of the type we detect are indeed present in important biological sequences. Availability: TRStalker will be integrated in the web-based TRs Discovery Service (TReaDS) at bioalgo.iit.cnr.it. Contact: marco.pellegrini@iit.cnr.it Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20529928
Davies, N; Manthorpe, J; Sampson, E L; Iliffe, S
2015-01-01
Introduction End of life care guidance for people with dementia is lacking and this has been made more problematic in England with the removal of one of the main end of life care guidelines which offered some structure, the Liverpool Care Pathway. This guidance gap may be eased with the development of heuristics (rules of thumb) which offer a fast and frugal form of decision-making. Objective To develop a toolkit of heuristics (rules of thumb) for practitioners to use when caring for people with dementia at the end of life. Method and analysis A mixed-method study using a co-design approach to develop heuristics in three phases. In phase 1, we will conduct at least six focus groups with family carers, health and social care practitioners from both hospital and community care services, using the ‘think-aloud’ method to understand decision-making processes and to develop a set of heuristics. The focus group topic guide will be developed from the findings of a previous study of 46 interviews of family carers about quality end-of-life care for people with dementia and a review of the literature. A multidisciplinary development team of health and social care practitioners will synthesise the findings from the focus groups to devise and refine a toolkit of heuristics. Phase 2 will test the use of heuristics in practice in five sites: one general practice, one community nursing team, one hospital ward and two palliative care teams working in the community. Phase 3 will evaluate and further refine the toolkit of heuristics through group interviews, online questionnaires and semistructured interviews. Ethics and dissemination This study has received ethical approval from a local NHS research ethics committee (Rec ref: 15/LO/0156). The findings of this study will be presented in peer-reviewed publications and national and international conferences. PMID:26338688
NASA Astrophysics Data System (ADS)
Ding, Zhe; Xu, Zhanqi; Zeng, Xiaodong; Ma, Tao; Yang, Fan
2014-04-01
By adopting the orthogonal frequency division multiplexing technology, spectrum-sliced elastic optical path networks can offer flexible bandwidth to each connection request and utilize the spectrum resources efficiently. The routing and spectrum assignment (RSA) problems in SLICE networks are solved by using heuristic algorithms in most prior studies and addressed by intelligent algorithms in few investigations. The performance of RSA algorithms can be further improved if we could combine such two types of algorithms. Therefore, we propose three hybrid RSA algorithms: DACE-GMSF, DACE-GLPF, and DACE-GEMkPSF, which are the combination of the heuristic algorithm and coevolution based on distance-adaptive policy. In the proposed algorithms, we first groom the connection requests, then sort the connection requests by using the heuristic algorithm (most subcarriers first, longest path first, and extended most k paths' slots first), and finally search the approximately optimal solution with the coevolutionary policy. We present a model of the RSA problem by using integral linear programming, and key elements in the proposed algorithms are addressed in detail. Simulations under three topologies show that the proposed hybrid RSA algorithms can save spectrum resources efficiently.
Computational Protein Design Using AND/OR Branch-and-Bound Search.
Zhou, Yichao; Wu, Yuexin; Zeng, Jianyang
2016-06-01
The computation of the global minimum energy conformation (GMEC) is an important and challenging topic in structure-based computational protein design. In this article, we propose a new protein design algorithm based on the AND/OR branch-and-bound (AOBB) search, a variant of the traditional branch-and-bound search algorithm, to solve this combinatorial optimization problem. By integrating with a powerful heuristic function, AOBB is able to fully exploit the graph structure of the underlying residue interaction network of a backbone template to significantly accelerate the design process. Tests on real protein data show that our new protein design algorithm is able to solve many problems that were previously unsolvable by the traditional exact search algorithms, and for the problems that can be solved with traditional provable algorithms, our new method can provide a large speedup by several orders of magnitude while still guaranteeing to find the global minimum energy conformation (GMEC) solution. PMID:27167301
PISA: Federated Search in P2P Networks with Uncooperative Peers
NASA Astrophysics Data System (ADS)
Ren, Zujie; Shou, Lidan; Chen, Gang; Chen, Chun; Bei, Yijun
Recently, federated search in P2P networks has received much attention. Most of the previous work assumed a cooperative environment where each peer can actively participate in information publishing and distributed document indexing. However, little work has addressed the problem of incorporating uncooperative peers, which do not publish their own corpus statistics, into a network. This paper presents a P2P-based federated search framework called PISA which incorporates uncooperative peers as well as the normal ones. In order to address the indexing needs for uncooperative peers, we propose a novel heuristic query-based sampling approach which can obtain high-quality resource descriptions from uncooperative peers at relatively low communication cost. We also propose an effective method called RISE to merge the results returned by uncooperative peers. Our experimental results indicate that PISA can provide quality search results, while utilizing the uncooperative peers at a low cost.
NASA Astrophysics Data System (ADS)
Tiwari, Rajiv; Waghole, Vikas
2015-07-01
Bearing standards impose restrictions on the internal geometry of spherical roller bearings. Geometrical and strength constraints conditions have been formulated for the optimization of bearing design. The long fatigue life is one of the most important criteria in the optimum design of bearing. The life is directly proportional to the dynamic capacity; hence, the objective function has been chosen as the maximization of dynamic capacity. The effect of speed and static loads acting on the bearing are also taken into account. Design variables for the bearing include five geometrical parameters: the roller diameter, the roller length, the bearing pitch diameter, the number of rollers, and the contact angle. There are a few design constraint parameters which are also included in the optimization, the bounds of which are obtained by initial runs of the optimization. The optimization program is made to run for different values of these design constraint parameters and a range of the parameters is obtained for which the objective function has a higher value. The artificial bee colony algorithm (ABCA) has been used to solve the constrained optimized problem and the optimum design is compared with the one obtained from the grid search method (GSM), both operating independently. Both the ABCA and the GSM have been finally combined together to reach the global optimum point. A constraint violation study has also been carried out to give priority to the constraint having greater possibility of violations. Optimized bearing designs show a better performance parameter with those specified in bearing catalogs. The sensitivity analysis of bearing parameters has also been carried out to see the effect of manufacturing tolerance on the objective function.
Chain Gang: A Framegame for Teaching Algorithms and Heuristics.
ERIC Educational Resources Information Center
Thiagarajan, Sivasailam; Pasigna, Aida L.
1985-01-01
Describes basic structure of a framegame, Chain Gang, in which self-instructional modules teach a cognitive skill. Procedures are presented for loading new content into the game's basic framework to teach algorithms or heuristics and for game modification to suit different situations. Handouts used in the basic game are appended. (MBR)
Computer-Assisted Test Assembly Using Optimization Heuristics.
ERIC Educational Resources Information Center
Leucht, Richard M.
1998-01-01
Presents a variation of a "greedy" algorithm that can be used in test-assembly problems. The algorithm, the normalized weighted absolute-deviation heuristic, selects items to have a locally optimal fit to a moving set of average criterion values. Demonstrates application of the model. (SLD)
A Heuristic Parsing Procedure for a Language Learning Program.
ERIC Educational Resources Information Center
Lindsay, Robert K.
This paper reports a portion of a research effort to develop a program which will simulate the language learning behavior of humans. Here presented is a heuristic parsing procedure which accepts natural language sentences and produces for each a form of analysis called a "labeled dependency tree." The formal grammar on which the procedure is based…
The Electrophysiological Correlates of Scientific Innovation Induced by Heuristic Information
ERIC Educational Resources Information Center
Luo, Junlong; Du, Xiumin; Tang, Xiaochen; Zhang, Entao; Li, Haijiang; Zhang, Qinglin
2013-01-01
In this study, novel and old scientific innovations (NSI and OSI) were selected as materials to explore the electrophysiological correlates of scientific innovation induced by heuristic information. Using event-related brain potentials (ERPs) to do so, college students solved NSI problems (for which they did not know the answers) and OSI problems…
Compensatory Reading among ESL Learners: A Reading Strategy Heuristic
ERIC Educational Resources Information Center
Ismail, Shaik Abdul Malik Mohamed; Petras, Yusof Ede; Mohamed, Abdul Rashid; Eng, Lin Siew
2015-01-01
This paper aims to gain an insight to the relationship of two different concepts about reading comprehension, namely, the linear model of comprehension and the interactive compensatory theory. Drawing on both the above concepts, a heuristic was constructed about three different reading strategies determined by the specific ways the literal,…
Resolution of seven-axis manipulator redundancy: A heuristic issue
NASA Technical Reports Server (NTRS)
Chen, I.
1990-01-01
An approach is presented for the resolution of the redundancy of a seven-axis manipulator arm from the AI and expert systems point of view. This approach is heuristic, analytical, and globally resolves the redundancy at the position level. When compared with other approaches, this approach has several improved performance capabilities, including singularity avoidance, repeatability, stability, and simplicity.
Implementing the Science Writing Heuristic in the Chemistry Laboratory
ERIC Educational Resources Information Center
Burke, K. A.; Greenbowe, Thomas J.; Hand, Brian M.
2006-01-01
The Science Writing Heuristic (SWH) is an instructional technique that combines inquiry, collaborative learning, and writing to change the nature of the chemistry laboratory for students and instructors. The SWH provides a format for students to guide their discussions, their thinking, and writing about how science activities relate to their own…
How cognitive heuristics can explain social interactions in spatial movement.
Seitz, Michael J; Bode, Nikolai W F; Köster, Gerta
2016-08-01
The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. PMID:27581483
Development of Heuristic Bias Detection in Elementary School
ERIC Educational Resources Information Center
De Neys, Wim; Feremans, Vicky
2013-01-01
Although human reasoning is often biased by intuitive heuristics, recent studies have shown that adults and adolescents detect the biased nature of their judgments. The present study focused on the development of this critical bias sensitivity by examining the detection skills of young children in elementary school. Third and 6th graders were…
Ethical Reasoning: A Heuristic Approach for Business Educators.
ERIC Educational Resources Information Center
Molberg, Diane R.
For the teaching of business report writing, ethical reasoning can be used as a heuristic for thinking that will encourage a more effective communication pattern for business students. Writing processes can be applied to thinking processes to help students approach theoretical concepts, make decisions, and write more effective business reports. A…
A Heuristic for Disassembly Planning in Remanufacturing System
2014-01-01
This study aims to improve the efficiency of disassembly planning in remanufacturing environment. Even though disassembly processes are considered as the reverse of the corresponding assembly processes, under some technological and management constraints the feasible and efficient disassembly planning can be achieved by only well-designed algorithms. In this paper, we propose a heuristic for disassembly planning with the existence of disassembled part/subassembly demands. A mathematical model is formulated for solving this problem to determine the sequence and quantity of disassembly operations to minimize the disassembly costs under sequence-dependent setup and capacity constraints. The disassembly costs consist of the setup cost, part inventory holding cost, disassembly processing cost, and purchasing cost that resulted from unsatisfied demand. A simple but efficient heuristic algorithm is proposed to improve the quality of solution and computational efficiency. The main idea of heuristic is to divide the planning horizon into the smaller planning windows and improve the computational efficiency without much loss of solution quality. Performances of the heuristic are investigated through the computational experiments. PMID:24895679
A heuristic for disassembly planning in remanufacturing system.
Sung, Jinmo; Jeong, Bongju
2014-01-01
This study aims to improve the efficiency of disassembly planning in remanufacturing environment. Even though disassembly processes are considered as the reverse of the corresponding assembly processes, under some technological and management constraints the feasible and efficient disassembly planning can be achieved by only well-designed algorithms. In this paper, we propose a heuristic for disassembly planning with the existence of disassembled part/subassembly demands. A mathematical model is formulated for solving this problem to determine the sequence and quantity of disassembly operations to minimize the disassembly costs under sequence-dependent setup and capacity constraints. The disassembly costs consist of the setup cost, part inventory holding cost, disassembly processing cost, and purchasing cost that resulted from unsatisfied demand. A simple but efficient heuristic algorithm is proposed to improve the quality of solution and computational efficiency. The main idea of heuristic is to divide the planning horizon into the smaller planning windows and improve the computational efficiency without much loss of solution quality. Performances of the heuristic are investigated through the computational experiments. PMID:24895679
Making Predictions about Chemical Reactivity: Assumptions and Heuristics
ERIC Educational Resources Information Center
Maeyer, Jenine; Talanquer, Vicente
2013-01-01
Diverse implicit cognitive elements seem to support but also constrain reasoning in different domains. Many of these cognitive constraints can be thought of as either implicit assumptions about the nature of things or reasoning heuristics for decision-making. In this study we applied this framework to investigate college students'…
The Priority Heuristic: Making Choices without Trade-Offs
ERIC Educational Resources Information Center
Brandstatter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph
2006-01-01
Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic…
Heuristics guide cooperative behaviors in public goods game
NASA Astrophysics Data System (ADS)
Wang, Yongjie; Chen, Tong
2015-12-01
In public goods game (PGG), player's cooperative behavior is not pure economical rationality, but social preference and prosocial intuition play extremely important roles as well. Social preference and prosocial intuition can be guided by heuristics from one's neighbors in daily life. To better investigate the impacts of heuristics on the evolution of cooperation, four types of agents are introduced into our spatial PGG. Through numerical simulations, results show that the larger percentages of cooperators with independent thought, the easier emergence and maintenance of collective cooperative behaviors. Additionally, we find that differentia heuristic capability has great effect on the equilibrium of PGG. Cooperation can be obviously promoted, when heuristic capability of cooperators with independent thought is stronger than that of defectors with independent thought. Finally, we observe that cooperators with independent thought and defectors with independent thought are favorable for the formation of some high quality clusters, which can resist the invasion between each other. Our work may help us understand more clearly the mechanism of cooperation in real world.
Heuristic Reasoning in Chemistry: Making Decisions about Acid Strength
ERIC Educational Resources Information Center
McClary, Lakeisha; Talanquer, Vicente
2011-01-01
The characterization of students' reasoning strategies is of central importance in the development of instructional strategies that foster meaningful learning. In particular, the identification of shortcut reasoning procedures (heuristics) used by students to reduce cognitive load can help us devise strategies to facilitate the development of more…
Prototypes Are Key Heuristic Information in Insight Problem Solving
ERIC Educational Resources Information Center
Yang, Wenjing; Dietrich, Arne; Liu, Peiduo; Ming, Dan; Jin, Yule; Nusbaum, Howard C.; Qiu, Jiang; Zhang, Qinglin
2016-01-01
Evidence from a range of fields indicates that inventions are often inspired by drawing a parallel to solutions found in nature. However, the cognitive mechanism of this process is not well understood. The cognitive mechanism of heuristic prototype in scientific innovation was tested with 3 experiments. First, 84 historical accounts of important…
Enhancements of branch and bound methods for the maximal constraint satisfaction problem
Wallace, R.J.
1996-12-31
Two methods are described for enhancing performance of branch and bound methods for overconstrained CSPs. These methods improve either the upper or lower bound, respectively, during search, so the two can be combined. Upper bounds are improved by using heuristic repair methods before search to find a good solution quickly, whose cost is used as the initial upper bound. The method for improving lower bounds is an extension of directed arc consistency preprocessing, used in conjunction with forward checking. After computing directed arc consistency counts, inferred counts are computed for all values based on minimum counts for values of adjacent variables that are later in the search order. This inference process can be iterated, so that counts are cascaded from the end to the beginning of the search order, to augment the initial counts. Improvements in time and effort are demonstrated for both techniques using random problems.
Walking tree heuristics for biological string alignment, gene location, and phylogenies
NASA Astrophysics Data System (ADS)
Cull, P.; Holloway, J. L.; Cavener, J. D.
1999-03-01
Basic biological information is stored in strings of nucleic acids (DNA, RNA) or amino acids (proteins). Teasing out the meaning of these strings is a central problem of modern biology. Matching and aligning strings brings out their shared characteristics. Although string matching is well-understood in the edit-distance model, biological strings with transpositions and inversions violate this model's assumptions. We propose a family of heuristics called walking trees to align biologically reasonable strings. Both edit-distance and walking tree methods can locate specific genes within a large string when the genes' sequences are given. When we attempt to match whole strings, the walking tree matches most genes, while the edit-distance method fails. We also give examples in which the walking tree matches substrings even if they have been moved or inverted. The edit-distance method was not designed to handle these problems. We include an example in which the walking tree "discovered" a gene. Calculating scores for whole genome matches gives a method for approximating evolutionary distance. We show two evolutionary trees for the picornaviruses which were computed by the walking tree heuristic. Both of these trees show great similarity to previously constructed trees. The point of this demonstration is that WHOLE genomes can be matched and distances calculated. The first tree was created on a Sequent parallel computer and demonstrates that the walking tree heuristic can be efficiently parallelized. The second tree was created using a network of work stations and demonstrates that there is suffient parallelism in the phylogenetic tree calculation that the sequential walking tree can be used effectively on a network.
Heuristic optimization of the scanning path of particle therapy beams
Pardo, J.; Donetti, M.; Bourhaleb, F.; Ansarinejad, A.; Attili, A.; Cirio, R.; Garella, M. A.; Giordanengo, S.; Givehchi, N.; La Rosa, A.; Marchetto, F.; Monaco, V.; Pecka, A.; Peroni, C.; Russo, G.; Sacchi, R.
2009-06-15
Quasidiscrete scanning is a delivery strategy for proton and ion beam therapy in which the beam is turned off when a slice is finished and a new energy must be set but not during the scanning between consecutive spots. Different scanning paths lead to different dose distributions due to the contribution of the unintended transit dose between spots. In this work an algorithm to optimize the scanning path for quasidiscrete scanned beams is presented. The classical simulated annealing algorithm is used. It is a heuristic algorithm frequently used in combinatorial optimization problems, which allows us to obtain nearly optimal solutions in acceptable running times. A study focused on the best choice of operational parameters on which the algorithm performance depends is presented. The convergence properties of the algorithm have been further improved by using the next-neighbor algorithm to generate the starting paths. Scanning paths for two clinical treatments have been optimized. The optimized paths are found to be shorter than the back-and-forth, top-to-bottom (zigzag) paths generally provided by the treatment planning systems. The gamma method has been applied to quantify the improvement achieved on the dose distribution. Results show a reduction of the transit dose when the optimized paths are used. The benefit is clear especially when the fluence per spot is low, as in the case of repainting. The minimization of the transit dose can potentially allow the use of higher beam intensities, thus decreasing the treatment time. The algorithm implemented for this work can optimize efficiently the scanning path of quasidiscrete scanned particle beams. Optimized scanning paths decrease the transit dose and lead to better dose distributions.
Algo-Heuristic Theory of Performance, Learning, and Instruction: Subject, Problems, Principles.
ERIC Educational Resources Information Center
Landa, Lev N.
1984-01-01
The algo-heuristic theory is concerned with identifying unobservable cognitive processes and their unconscious component cognitive operations, including learning how to describe them algorithmically and heuristically, and how to devise specific instructional tools (algorithmic and heuristic) to develop cognitive processes much faster. (BW)
ERIC Educational Resources Information Center
Koichu, Boris; Berman, Abraham; Moore, Michael
2007-01-01
The relationships between heuristic literacy development and mathematical achievements of middle school students were explored during a 5-month classroom experiment in two 8th grade classes (N = 37). By heuristic literacy we refer to an individual's capacity to use heuristic vocabulary in problem-solving discourse and to approach scholastic…
Investigating the Impacts of Design Heuristics on Idea Initiation and Development
ERIC Educational Resources Information Center
Kramer, Julia; Daly, Shanna R.; Yilmaz, Seda; Seifert, Colleen M.; Gonzalez, Richard
2015-01-01
This paper presents an analysis of engineering students' use of Design Heuristics as part of a team project in an undergraduate engineering design course. Design Heuristics are an empirically derived set of cognitive "rules of thumb" for use in concept generation. We investigated heuristic use in the initial concept generation phase,…
Kinjo, Akira R.; Nakamura, Haruki
2012-01-01
Comparison and classification of protein structures are fundamental means to understand protein functions. Due to the computational difficulty and the ever-increasing amount of structural data, however, it is in general not feasible to perform exhaustive all-against-all structure comparisons necessary for comprehensive classifications. To efficiently handle such situations, we have previously proposed a method, now called GIRAF. We herein describe further improvements in the GIRAF protein structure search and alignment method. The GIRAF method achieves extremely efficient search of similar structures of ligand binding sites of proteins by exploiting database indexing of structural features of local coordinate frames. In addition, it produces refined atom-wise alignments by iterative applications of the Hungarian method to the bipartite graph defined for a pair of superimposed structures. By combining the refined alignments based on different local coordinate frames, it is made possible to align structures involving domain movements. We provide detailed accounts for the database design, the search and alignment algorithms as well as some benchmark results.
Brown, Elliot G
2003-01-01
The Medical Dictionary for Regulatory Activities (MedDRA) is a unified standard terminology for recording and reporting adverse drug event data. Its introduction is widely seen as a significant improvement on the previous situation, where a multitude of terminologies of widely varying scope and quality were in use. However, there are some complexities that may cause difficulties, and these will form the focus for this paper. Two methods of searching MedDRA-coded databases are described: searching based on term selection from all of MedDRA and searching based on terms in the safety database. There are several potential traps for the unwary in safety searches. There may be multiple locations of relevant terms within a system organ class (SOC) and lack of recognition of appropriate group terms; the user may think that group terms are more inclusive than is the case. MedDRA may distribute terms relevant to one medical condition across several primary SOCs. If the database supports the MedDRA model, it is possible to perform multiaxial searching: while this may help find terms that might have been missed, it is still necessary to consider the entire contents of the SOCs to find all relevant terms and there are many instances of incomplete secondary linkages. It is important to adjust for multiaxiality if data are presented using primary and secondary locations. Other sources for errors in searching are non-intuitive placement and the selection of terms as preferred terms (PTs) that may not be widely recognised. Some MedDRA rules could also result in errors in data retrieval if the individual is unaware of these: in particular, the lack of multiaxial linkages for the Investigations SOC, Social circumstances SOC and Surgical and medical procedures SOC and the requirement that a PT may only be present under one High Level Term (HLT) and one High Level Group Term (HLGT) within any single SOC. Special Search Categories (collections of PTs assembled from various SOCs by
Darzi, Soodabeh; Tiong, Sieh Kiong; Tariqul Islam, Mohammad; Rezai Soleymanpour, Hassan; Kibria, Salehin
2016-01-01
An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents’ positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness. PMID:27399904
Darzi, Soodabeh; Tiong, Sieh Kiong; Tariqul Islam, Mohammad; Rezai Soleymanpour, Hassan; Kibria, Salehin
2016-01-01
An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents' positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness. PMID:27399904
Developing and Validating Personas in e-Commerce: A Heuristic Approach
NASA Astrophysics Data System (ADS)
Thoma, Volker; Williams, Bryn
A multi-method persona development process in a large e-commerce business is described. Personas are fictional representations of customers that describe typical user attributes to facilitate a user-centered approach in interaction design. In the current project persona attributes were derived from various data sources, such as stakeholder interviews, user tests and interviews, data mining, customer surveys, and ethnographic (direct observation, diary studies) research. The heuristic approach of using these data sources conjointly allowed for an early validation of relevant persona dimensions.
Heuristic reduction of gyro drift in IMU-based personnel tracking systems
NASA Astrophysics Data System (ADS)
Borenstein, Johann; Ojeda, Lauro; Kwanmuang, Surat
2009-05-01
The paper pertains to the reduction of measurement errors in gyroscopes used for tracking the position of walking persons. Some of these tracking systems commonly use inertial or other means to measure distance traveled, and one or more gyros to measure changes in heading. MEMS-type gyros or IMUs are best suited for this task because of their small size and low weight. However, these gyros have large drift rates and can be sensitive to accelerations. The Heuristic Drift Reduction (HDR) method presented in this paper estimates the drift component and eliminates it, reducing heading errors by almost one order of magnitude.
Smart internet search engine through 6W
NASA Astrophysics Data System (ADS)
Goehler, Stephen; Cader, Masud; Szu, Harold
2006-04-01
Current Internet search engine technology is limited in its ability to display necessary relevant information to the user. Yahoo, Google and Microsoft use lookup tables or indexes which limits the ability of users to find their desired information. While these companies have improved their results over the years by enhancing their existing technology and algorithms with specialized heuristics such as PageRank, there is a need for a next generation smart search engine that can effectively interpret the relevance of user searches and provide the actual information requested. This paper explores whether a smarter Internet search engine can effectively fulfill a user's needs through the use of 6W representations.
Heuristic approach to capillary pressures averaging
Coca, B.P.
1980-10-01
Several methods are available to average capillary pressure curves. Among these are the J-curve and regression equations of the wetting-fluid saturation in porosity and permeability (capillary pressure held constant). While the regression equation seem completely empiric, the J-curve method seems to be theoretically sound due to its expression based on a relation between the average capillary radius and the permeability-porosity ratio. An analysis is given of each of these methods.
Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD)
Khowaja, Kamran; Salim, Siti Salwah
2015-01-01
In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen’s set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen’s heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system. PMID:26196385
NASA Astrophysics Data System (ADS)
Ji, Hong-Fei; Jiao, Yi; Wang, Sheng; Ji, Da-Heng; Yu, Cheng-Hui; Zhang, Yuan; Huang, Xiao-Biao
2015-12-01
The robust conjugate direction search (RCDS) method has high tolerance to noise in beam experiments. It has been demonstrated that this method can be used to optimize the machine performance of a light source online. In our study, taking BEPCII as an example, the feasibility of online tuning of the luminosity in a circular collider is explored, through numerical simulation and preliminary online experiments. It is shown that the luminosity that is artificially decreased by a deviation of beam orbital offset from optimal trajectory can be recovered with this method. Supported by National Natural Science Foundation of China (11475202, 11405187) and Youth Innovation Promotion Association of Chinese Academy of Sciences (2015009)
ERIC Educational Resources Information Center
Hildreth, Charles R.
This study was designed to be a state-of-the-art survey and investigation of intelligent "front end" design approaches and software for improving subject access and subject searching in today's large online bibliographic retrieval systems and online public access catalogs (OPACS). The report begins with an illustrated overview of retrieval…
Methods of searching and analyzing the data of the gear tooth profile in gear cutter CAD
NASA Astrophysics Data System (ADS)
Pang, Xing-hua; Wang, Er-hua
2011-05-01
In gear-cutter CAD(Computer Aided Design), certain points belonging to series cutter loci which were generated by the simulation of the cutting process may form a gear-tooth profile. Finding out such points and analyzing them to predict the properties of a new gear is also a very important step which determines the succedent analyzing steps. However, the problem of abstracting these data from the loci rapidly and accurately remains to be solved. The two algorithms presented in this paper, concentric-arcs searching and revolving-scan searching, would provide theoretic basis for the on-line gear-tooth analysis. The former focuses on drawing concentric-arcs between the dedendum and addendum of the gear, the latter concentrates on drawing radial lines between two angles.Such arcs and lines will intersect one or more lines of the cutter profile.Correspongding screening criterions will greatly contribute to juge and identify useful intersections which may form the gear profile, and the gear-tooth shape analysis will be carried out as a result. Keyword: gear cutter; CAD; concentric-arcs searching; revolving-scan searching.
Methods of searching and analyzing the data of the gear tooth profile in gear cutter CAD
NASA Astrophysics Data System (ADS)
Pang, Xing-Hua; Wang, Er-Hua
2010-12-01
In gear-cutter CAD(Computer Aided Design), certain points belonging to series cutter loci which were generated by the simulation of the cutting process may form a gear-tooth profile. Finding out such points and analyzing them to predict the properties of a new gear is also a very important step which determines the succedent analyzing steps. However, the problem of abstracting these data from the loci rapidly and accurately remains to be solved. The two algorithms presented in this paper, concentric-arcs searching and revolving-scan searching, would provide theoretic basis for the on-line gear-tooth analysis. The former focuses on drawing concentric-arcs between the dedendum and addendum of the gear, the latter concentrates on drawing radial lines between two angles.Such arcs and lines will intersect one or more lines of the cutter profile.Correspongding screening criterions will greatly contribute to juge and identify useful intersections which may form the gear profile, and the gear-tooth shape analysis will be carried out as a result. Keyword: gear cutter; CAD; concentric-arcs searching; revolving-scan searching.
Recruitment, Job Search, and the United States Employment Service. Volume II: Tables and Methods.
ERIC Educational Resources Information Center
Camil Associates, Inc., Philadelphia, PA.
This volume contains the appendixes to Volume I of the report on recruitment, job search, and the United States Employment Service in 20 middle-sized American cities. Appendix A contains 165 pages of tables. Appendix B (63 pages) contains details of sample design, data analysis, and estimate precision under the categories of: Overview of the study…
Fast method of homology and purine-pyrimidine mutual relations between DNA sequences search.
Korotkov, E V
1994-01-01
A new algorithm for scanning sequences is described. This algorithm uses the boolean operators AND and OR. The mutual information between the sequences is used as a measure of sequence interrelation. It allows evaluation of the probability of accidental sequence interrelation in a quantitative manner. The proposed algorithm was used for searching for MB1 repeats in human and other mammalian sequences. PMID:7841466
An Interactive Iterative Method for Electronic Searching of Large Literature Databases
ERIC Educational Resources Information Center
Hernandez, Marco A.
2013-01-01
PubMed® is an on-line literature database hosted by the U.S. National Library of Medicine. Containing over 21 million citations for biomedical literature--both abstracts and full text--in the areas of the life sciences, behavioral studies, chemistry, and bioengineering, PubMed® represents an important tool for researchers. PubMed® searches return…
Heuristic decomposition for non-hierarchic systems
NASA Technical Reports Server (NTRS)
Bloebaum, Christina L.; Hajela, P.
1991-01-01
Design and optimization is substantially more complex in multidisciplinary and large-scale engineering applications due to the existing inherently coupled interactions. The paper introduces a quasi-procedural methodology for multidisciplinary optimization that is applicable for nonhierarchic systems. The necessary decision-making support for the design process is provided by means of an embedded expert systems capability. The method employs a decomposition approach whose modularity allows for implementation of specialized methods for analysis and optimization within disciplines.
A heuristic two-dimensional presentation of microsatellite-based data applied to dogs and wolves
Veit-Kensch, Claudia E; Medugorac, Ivica; Jedrzejewski, Włodzimierz; Bunevich, Aleksei N; Foerster, Martin
2007-01-01
Methods based on genetic distance matrices usually lose information during the process of tree-building by converting a multi-dimensional matrix into a phylogenetic tree. We applied a heuristic method of two-dimensional presentation to achieve a better resolution of the relationship between breeds and individuals investigated. Four hundred and nine individuals from nine German dog breed populations and one free-living wolf population were analysed with a marker set of 23 microsatellites. The result of the two-dimensional presentation was partly comparable with and complemented a model-based analysis that uses genotype patterns. The assignment test and the neighbour-joining tree based on allele sharing estimate allocated 99% and 97% of the individuals according to their breed, respectively. The application of the two-dimensional presentation to distances on the basis of the proportion of shared alleles resulted in comparable and further complementary insight into inferred population structure by multilocus genotype data. We expect that the inference of population structure in domesticated species with complex breeding histories can be strongly supported by the two-dimensional presentation based on the described heuristic method. PMID:17612483
Parallel iterative solution of sparse linear systems using orderings from graph coloring heuristics
Jones, M.T.; Plassmann, P.E.
1990-12-01
The efficiency of a parallel implementation of the conjugate gradient method preconditioned by an incomplete Cholesky factorization can vary dramatically depending on the column ordering chosen. One method to minimize the number of major parallel steps is to choose an ordering based on a coloring of the symmetric graph representing the nonzero adjacency structure of the matrix. In this paper, we compare the performance of the preconditioned conjugate gradient method using these coloring orderings with a number of standard orderings on matrices arising from applications in structural engineering. Because optimal colorings for these systems may not be a priori known: we employ several graph coloring heuristics to obtain consistent colorings. Based on lower bounds obtained from the local structure of these systems, we find that the colorings determined by these heuristics are nearly optimal. For these problems, we find that the increase in parallelism afforded by the coloring-based orderings more than offsets any increase in the number of iterations required for the convergence of the conjugate gradient algorithm.
NASA Astrophysics Data System (ADS)
Li, Xiang-Tao; Yin, Ming-Hao
2012-05-01
We study the parameter estimation of a nonlinear chaotic system, which can be essentially formulated as a multidimensional optimization problem. In this paper, an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy. Experiments are conducted on the Lorenz system and the Chen system. The proposed algorithm is used to estimate the parameters for these two systems. Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.
Tabu Search enhances network robustness under targeted attacks
NASA Astrophysics Data System (ADS)
Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi
2016-03-01
We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.
An ant colony algorithm on continuous searching space
NASA Astrophysics Data System (ADS)
Xie, Jing; Cai, Chao
2015-12-01
Ant colony algorithm is heuristic, bionic and parallel. Because of it is property of positive feedback, parallelism and simplicity to cooperate with other method, it is widely adopted in planning on discrete space. But it is still not good at planning on continuous space. After a basic introduction to the basic ant colony algorithm, we will propose an ant colony algorithm on continuous space. Our method makes use of the following three tricks. We search for the next nodes of the route according to fixed-step to guarantee the continuity of solution. When storing pheromone, it discretizes field of pheromone, clusters states and sums up the values of pheromone of these states. When updating pheromone, it makes good resolutions measured in relative score functions leave more pheromone, so that ant colony algorithm can find a sub-optimal solution in shorter time. The simulated experiment shows that our ant colony algorithm can find sub-optimal solution in relatively shorter time.
Task Assignment Heuristics for Parallel and Distributed CFD Applications
NASA Technical Reports Server (NTRS)
Lopez-Benitez, Noe; Djomehri, M. Jahed; Biswas, Rupak
2003-01-01
This paper proposes a task graph (TG) model to represent a single discrete step of multi-block overset grid computational fluid dynamics (CFD) applications. The TG model is then used to not only balance the computational workload across the overset grids but also to reduce inter-grid communication costs. We have developed a set of task assignment heuristics based on the constraints inherent in this class of CFD problems. Two basic assignments, the smallest task first (STF) and the largest task first (LTF), are first presented. They are then systematically costs. To predict the performance of the proposed task assignment heuristics, extensive performance evaluations are conducted on a synthetic TG with tasks defined in terms of the number of grid points in predetermined overlapping grids. A TG derived from a realistic problem with eight million grid points is also used as a test case.
Unsafe sex: decision-making biases and heuristics.
Kaplan, B J; Shayne, V T
1993-01-01
This paper suggests that continued high-risk behavior is the result of the heuristics used to make judgments under uncertainty, and that the same heuristics may be mobilized to increase the use of safer-sex practices. In order to explain why it is that individuals fail to make effective use of the information they may have concerning rates of infection, consequences of infection and their own at-risk status, theory and research in several areas will be considered. Developments in the breadth of areas to which basic research on decision-making has been applied continue to provide new approaches toward understanding and overcoming the processes by which we reason (Kahnemann, 1991). It is worth reminding ourselves that public health campaigns in other areas have led to changes in behavior. Reasoning, even with its biases, is still the route by which we make decisions, most of them effective and self-protective. PMID:8297709
The source of the truth bias: Heuristic processing?
Street, Chris N H; Masip, Jaume
2015-06-01
People believe others are telling the truth more often than they actually are; this is called the truth bias. Surprisingly, when a speaker is judged at multiple points across their statement the truth bias declines. Previous claims argue this is evidence of a shift from (biased) heuristic processing to (reasoned) analytical processing. In four experiments we contrast the heuristic-analytic model (HAM) with alternative accounts. In Experiment 1, the decrease in truth responding was not the result of speakers appearing more deceptive, but was instead attributable to the rater's processing style. Yet contrary to HAMs, across three experiments we found the decline in bias was not related to the amount of processing time available (Experiments 1-3) or the communication channel (Experiment 2). In Experiment 4 we found support for a new account: that the bias reflects whether raters perceive the statement to be internally consistent. PMID:25707774
NASA Astrophysics Data System (ADS)
Wang, Li; Sun, Xiaogang; Xing, Jian
2012-12-01
An inversion technique which combines the pattern search algorithm with the Tikhonov smoothing functional for retrieval of particle size distribution (PSD) by light extinction method is proposed. In the unparameterized shape-independent model, we first transform the PSD inversion problem into an optimization problem, with the Tikhonov smoothing functional employed to model the objective function. The optimization problem is then solved by the pattern search algorithm. To ensure good convergence rate and accuracy of the whole retrieval, a competitive strategy for determining the initial point of the pattern search algorithm is also designed. The accuracy and limitations of the proposed technique are tested by the inversion results of synthetic and real standard polystyrene particles immersed in water. In addition, the issues about the objective function and computation time are further discussed. Both simulation and experimental results show that the technique can be successfully applied to retrieve the PSD with high reliability and stability in the presence of random noise. Compared with the Phillips-Twomey method and genetic algorithm, the proposed technique has certain advantages in terms of reaching a more accurate and steady optimal solution with less computational effort, thus making this technique more suitable for quick and accurate measurement of PSD.
Mathew, R; Davies, N; Manthorpe, J; Iliffe, S
2016-01-01
Objective Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. Design A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. Data sources A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. Results The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. Conclusions The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. PMID:27436665
Wang, Lin; Zheng, Jinjian; Gong, Xiaoyi; Hartman, Robert; Antonucci, Vincent
2015-02-01
Development of a robust HPLC method for pharmaceutical analysis can be very challenging and time-consuming. In our laboratory, we have developed a new workflow leveraging ACD/Labs software tools to improve the performance of HPLC method development. First, we established ACD-based analytical method databases that can be searched by chemical structure similarity. By taking advantage of the existing knowledge of HPLC methods archived in the databases, one can find a good starting point for HPLC method development, or even reuse an existing method as is for a new project. Second, we used the software to predict compound physicochemical properties before running actual experiments to help select appropriate method conditions for targeted screening experiments. Finally, after selecting stationary and mobile phases, we used modeling software to simulate chromatographic separations for optimized temperature and gradient program. The optimized new method was then uploaded to internal databases as knowledge available to assist future method development efforts. Routine implementation of such standardized workflows has the potential to reduce the number of experiments required for method development and facilitate systematic and efficient development of faster, greener and more robust methods leading to greater productivity. In this article, we used Loratadine method development as an example to demonstrate efficient method development using this new workflow. PMID:25481084
NASA Astrophysics Data System (ADS)
Noor-E-Alam, Md.; Doucette, John
2015-08-01
Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.
Miloua, R; Kebbab, Z; Chiker, F; Sahraoui, K; Khadraoui, M; Benramdane, N
2012-02-15
We propose the use of a pattern search optimization technique in combination with a seed preprocessing procedure to determine the optical constants and thickness of thin films using only the transmittance spectra. The approach is quite flexible, straightforward to implement, and efficient in reaching the best fitting. We demonstrate the effectiveness of the method in extracting optical constants, even when the films are not displaying interference fringes. Comparison to a real-coded genetic algorithm shows that the modified pattern search is fast, almost accurate, and does not need any parameter adjustments. The approach is successfully applied to extract the thickness and optical constants of spray pyrolyzed nanocrystalline CdO thin films. PMID:22344069
NASA Technical Reports Server (NTRS)
Van Dongen, H. P.; Olofsen, E.; VanHartevelt, J. H.; Kruyt, E. W.; Dinges, D. F. (Principal Investigator)
1999-01-01
Periodogram analysis of unequally spaced time-series, as part of many biological rhythm investigations, is complicated. The mathematical framework is scattered over the literature, and the interpretation of results is often debatable. In this paper, we show that the Lomb-Scargle method is the appropriate tool for periodogram analysis of unequally spaced data. A unique procedure of multiple period searching is derived, facilitating the assessment of the various rhythms that may be present in a time-series. All relevant mathematical and statistical aspects are considered in detail, and much attention is given to the correct interpretation of results. The use of the procedure is illustrated by examples, and problems that may be encountered are discussed. It is argued that, when following the procedure of multiple period searching, we can even benefit from the unequal spacing of a time-series in biological rhythm research.
VHP - An environment for the remote visualization of heuristic processes
NASA Technical Reports Server (NTRS)
Crawford, Stuart L.; Leiner, Barry M.
1991-01-01
A software system called VHP is introduced which permits the visualization of heuristic algorithms on both resident and remote hardware platforms. The VHP is based on the DCF tool for interprocess communication and is applicable to remote algorithms which can be on different types of hardware and in languages other than VHP. The VHP system is of particular interest to systems in which the visualization of remote processes is required such as robotics for telescience applications.
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.
A Multi-Inner-World Genetic Algorithm Using Multiple Heuristics to Optimize Delivery Schedule
NASA Astrophysics Data System (ADS)
Sakurai, Yoshitaka; Onoyama, Takashi; Tsukamoto, Natsuki; Takada, Kouhei; Tsuruta, Setsuo
A delivery route optimization that improves the efficiency of real time delivery or a distribution network requires to solve several tens to hundreds cities Traveling Salesman Problems (TSP) (1)(2) within interactive response time, with expert-level accuracy (less than about 3% of error rate). To meet these requirements, a multi-inner-world Genetic Algorithm (Miw-GA) method is developed. This method combines several types of GA's inner worlds. Each world of this method uses a different type of heuristics such as a 2-opt type mutation world and a block (Nearest Insertion) type mutation world. Comparison based on the results of experiments proved the method is superior to others and our previously proposed method.
Discovery of Nine Gamma-Ray Pulsars in Fermi-Lat Data Using a New Blind Search Method
NASA Technical Reports Server (NTRS)
Celik-Tinmaz, Ozlem; Ferrara, E. C.; Pletsch, H. J.; Allen, B.; Aulbert, C.; Fehrmann, H.; Kramer, M.; Barr, E. D.; Champion, D. J.; Eatough, R. P.; Freire, P. C. C.; Reich, W.; Lyne, A. G.; Ray, P. S.
2011-01-01
We report the discovery of nine previously unknown gamma-ray pulsars in a blind search of data from the Fermi Large Area Telescope (LAT). The pulsars were found with a novel hierarchical search method originally developed for detecting continuous gravitational waves from rapidly rotating neutron stars. Designed to find isolated pulsars spinning at up to kHz frequencies, the new method is computationally efficient, and incorporates several advances, including a metric-based gridding of the search parameter space (frequency, frequency derivative and sky location) and the use of photon probability weights. The nine pulsars have spin frequencies between 3 and 12 Hz, and characteristic ages ranging from 17 kyr to 3 Myr. Two of them, PSRs Jl803-2149 and J2111+4606, are young and energetic Galactic-plane pulsars (spin-down power above 6 x 10(exp 35) ergs per second and ages below 100 kyr). The seven remaining pulsars, PSRs J0106+4855, J010622+3749, Jl620-4927, Jl746-3239, J2028+3332,J2030+4415, J2139+4716, are older and less energetic; two of them are located at higher Galactic latitudes (|b| greater than 10 degrees). PSR J0106+4855 has the largest characteristic age (3 Myr) and the smallest surface magnetic field (2x 10(exp 11)G) of all LAT blind-search pulsars. PSR J2139+4716 has the lowest spin-down power (3 x l0(exp 33) erg per second) among all non-recycled gamma-ray pulsars ever found. Despite extensive multi-frequency observations, only PSR J0106+4855 has detectable pulsations in the radio band. The other eight pulsars belong to the increasing population of radio-quiet gamma-ray pulsars.
Pletsch, H. J.; Allen, B.; Aulbert, C.; Fehrmann, H.; Guillemot, L.; Kramer, M.; Barr, E. D.; Champion, D. J.; Eatough, R. P.; Freire, P. C. C.; Ray, P. S.; Belfiore, A.; Dormody, M.; Camilo, F.; Caraveo, P. A.; Celik, Oe.; Ferrara, E. C.; Hessels, J. W. T.; Keith, M.; Kerr, M. E-mail: guillemo@mpifr-bonn.mpg.de; and others
2012-01-10
We report the discovery of nine previously unknown gamma-ray pulsars in a blind search of data from the Fermi Large Area Telescope (LAT). The pulsars were found with a novel hierarchical search method originally developed for detecting continuous gravitational waves from rapidly rotating neutron stars. Designed to find isolated pulsars spinning at up to kHz frequencies, the new method is computationally efficient and incorporates several advances, including a metric-based gridding of the search parameter space (frequency, frequency derivative, and sky location) and the use of photon probability weights. The nine pulsars have spin frequencies between 3 and 12 Hz, and characteristic ages ranging from 17 kyr to 3 Myr. Two of them, PSRs J1803-2149 and J2111+ 4606, are young and energetic Galactic-plane pulsars (spin-down power above 6 Multiplication-Sign 10{sup 35} erg s{sup -1} and ages below 100 kyr). The seven remaining pulsars, PSRs J0106+4855, J0622+3749, J1620-4927, J1746-3239, J2028+3332, J2030+4415, and J2139+4716, are older and less energetic; two of them are located at higher Galactic latitudes (|b| > 10 Degree-Sign ). PSR J0106+4855 has the largest characteristic age (3 Myr) and the smallest surface magnetic field (2 Multiplication-Sign 10{sup 11} G) of all LAT blind-search pulsars. PSR J2139+4716 has the lowest spin-down power (3 Multiplication-Sign 10{sup 33} erg s{sup -1}) among all non-recycled gamma-ray pulsars ever found. Despite extensive multi-frequency observations, only PSR J0106+4855 has detectable pulsations in the radio band. The other eight pulsars belong to the increasing population of radio-quiet gamma-ray pulsars.
Recipient design in human communication: simple heuristics or perspective taking?
Blokpoel, Mark; van Kesteren, Marlieke; Stolk, Arjen; Haselager, Pim; Toni, Ivan; van Rooij, Iris
2012-01-01
Humans have a remarkable capacity for tuning their communicative behaviors to different addressees, a phenomenon also known as recipient design. It remains unclear how this tuning of communicative behavior is implemented during live human interactions. Classical theories of communication postulate that recipient design involves perspective taking, i.e., the communicator selects her behavior based on her hypotheses about beliefs and knowledge of the recipient. More recently, researchers have argued that perspective taking is computationally too costly to be a plausible mechanism in everyday human communication. These researchers propose that computationally simple mechanisms, or heuristics, are exploited to perform recipient design. Such heuristics may be able to adapt communicative behavior to an addressee with no consideration for the addressee's beliefs and knowledge. To test whether the simpler of the two mechanisms is sufficient for explaining the “how” of recipient design we studied communicators' behaviors in the context of a non-verbal communicative task (the Tacit Communication Game, TCG). We found that the specificity of the observed trial-by-trial adjustments made by communicators is parsimoniously explained by perspective taking, but not by simple heuristics. This finding is important as it suggests that humans do have a computationally efficient way of taking beliefs and knowledge of a recipient into account. PMID:23055960
Heuristic and analytic processing in online sports betting.
d'Astous, Alain; Di Gaspero, Marc
2015-06-01
This article presents the results of two studies that examine the occurrence of heuristic (i.e., intuitive and fast) and analytic (i.e., deliberate and slow) processes among people who engage in online sports betting on a regular basis. The first study was qualitative and was conducted with a convenience sample of 12 regular online sports gamblers who described the processes by which they arrive at a sports betting decision. The results of this study showed that betting online on sports events involves a mix of heuristic and analytic processes. The second study consisted in a survey of 161 online sports gamblers where performance in terms of monetary gains, experience in online sports betting, propensity to collect and analyze relevant information prior to betting, and use of bookmaker odds were measured. This study showed that heuristic and analytic processes act as mediators of the relationship between experience and performance. The findings stemming of these two studies give some insights into gamblers' modes of thinking and behaviors in an online sports betting context and show the value of the dual mediation process model for research that looks at gambling activities from a judgment and decision making perspective. PMID:24390714
Bidding Heuristics for Simultaneous Auctions: Lessons from TAC Travel
NASA Astrophysics Data System (ADS)
Greenwald, Amy; Naroditskiy, Victor; Lee, Seong Jae
We undertake an experimental study of heuristics designed for the Travel division of the Trading Agent Competition. Our primary goal is to analyze the performance of the sample average approximation (SAA) heuristic, which is approximately optimal in the decision-theoretic (DT) setting, in this game-theoretic (GT) setting. To this end, we conduct experiments in four settings, three DT and one GT. The relevant distinction between the DT and the GT settings is: in the DT settings, agents' strategies do not affect the distribution of prices. Because of this distinction, the DT experiments are easier to analyze than the GT experiments. Moreover, settings with normally distributed prices, and controlled noise, are easier to analyze than those with competitive equilibrium prices. In the studied domain, analysis of the DT settings with possibly noisy normally distributed prices informs our analysis of the richer DT and GT settings with competitive equilibrium prices. In future work, we plan to investigate whether this experimental methodology - namely, transferring knowledge gained in a DT setting with noisy signals to a GT setting - can be applied to analyze heuristics for playing other complex games.
Visualization for Hyper-Heuristics: Back-End Processing
Simon, Luke
2015-03-01
Modern society is faced with increasingly complex problems, many of which can be formulated as generate-and-test optimization problems. Yet, general-purpose optimization algorithms may sometimes require too much computational time. In these instances, hyperheuristics may be used. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario, finding the solution significantly faster than its predecessor. However, it may be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics and an easy-to-understand scientific visualization for the produced solutions. To support the development of this GUI, my portion of the research involved developing algorithms that would allow for parsing of the data produced by the hyper-heuristics. This data would then be sent to the front-end, where it would be displayed to the end user.
NASA Astrophysics Data System (ADS)
Cabrol, N. A.; Wettergreen, D. S.; Whittaker, R.; Grin, E. A.; Moersch, J. E.; Chong-Diaz, G.; Cockell, C. S.; Coppin, P.; Dohm, J. M.; Fisher, G.; Hock, A. N.; Marinangeli, L.; Minkley, N.; Ori, G. G.; Piatek, J. L.; Waggoner, A.; Warren-Rhodes, K.; Weinstein, S.; Wyatt, M.; Apostolopoulos, D.; Smith, T.; Wagner, M.; Stubbs, K.; Thomas, G.; Glasgow, J.
2005-03-01
LITA develops and field tests a long-range automated rover and a science payload to search for microbial life in the Atacama. The Atacama's evolution provides a unique training ground for designing and testing exploration strategies and life detection methods for the search for life on Mars.
Combining Global Tabu Search with Local Search for Solving Systems of Equalities and Inequalities
NASA Astrophysics Data System (ADS)
Ramadas, Gisela C. V.; Fernandes, Edite M. G. P.
2011-09-01
This papers aims at providing a combined strategy for solving systems of equalities and inequalities. The combined strategy uses two types of steps: a global search step and a local search step. The global step relies on a tabu search heuristic and the local step uses a deterministic search known as Hooke and Jeeves. The choice of step, at each iteration, is based on the level of reduction of the l2-norm of the error function observed in the equivalent system of equations, compared with the previous iteration.
Armstrong, Jerawan C.; Favorite, Jeffrey A.
2012-06-20
The Levenberg-Marquardt (or simply Marquardt) and differential evolution (DE) optimization methods were recently applied to solve inverse transport problems. The Marquardt method is fast but convergence of the method is dependent on the initial guess. While it has been shown to work extremely well at finding an optimum independent of the initial guess, the DE method does not provide a global optimal solution in some problems. In this paper, we apply the Mesh Adaptive Direct Search (MADS) algorithm to solve the inverse problem of material interface location identification in one-dimensional spherical radiation source/shield systems, and we compare the results obtained by MADS to those obtained by Levenberg-Marquardt and DE.
NASA Astrophysics Data System (ADS)
Ahlers, Dirk; Boll, Susanne
In recent years, the relation of Web information to a physical location has gained much attention. However, Web content today often carries only an implicit relation to a location. In this chapter, we present a novel location-based search engine that automatically derives spatial context from unstructured Web resources and allows for location-based search: our focused crawler applies heuristics to crawl and analyze Web pages that have a high probability of carrying a spatial relation to a certain region or place; the location extractor identifies the actual location information from the pages; our indexer assigns a geo-context to the pages and makes them available for a later spatial Web search. We illustrate the usage of our spatial Web search for location-based applications that provide information not only right-in-time but also right-on-the-spot.
Fink, Arlene; Beck, John C
2015-08-01
This mixed-methods study developed and evaluated an online program to improve older adults' skills in identifying high-quality web-based health information. We conducted focus groups and individual interviews to collect data on older adults' preferences for online instruction and information. We used the findings to develop, pilot test, and evaluate an interactive website which was grounded in health behavior change models, adult education, and website construction. Sixty four participants were randomly assigned to Your Health Online: Guiding eSearches or to an analogous slide-based-tutorial and compared in their knowledge, self-efficacy, and program assessment. Experimental participants assigned significantly higher ratings of usability and learning to the new site than controls did to their tutorial although no differences were found in self-efficacy or knowledge. Experimental participants reported that participation was likely to improve future searches. Information is now needed to examine if such programs actually improve health searches, ehealth literacy, and health outcomes. PMID:24652883
Peterson, Sean M.; Streby, Henry M.; Lehman, Justin A.; Kramer, Gunnar R.; Fish, Alexander C.; Andersen, David E.
2015-01-01
We compared the efficacy of standard nest-searching methods with finding nests via radio-tagged birds to assess how search technique influenced our determination of nest-site characteristics and nest success for Golden-winged Warblers (Vermivora chrysoptera). We also evaluated the cost-effectiveness of using radio-tagged birds to find nests. Using standard nest-searching techniques for 3 populations, we found 111 nests in locations with habitat characteristics similar to those described in previous studies: edges between forest and relatively open areas of early successional vegetation or shrubby wetlands, with 43% within 5 m of forest edge. The 83 nests found using telemetry were about half as likely (23%) to be within 5 m of forest edge. We spent little time searching >25 m into forest because published reports state that Golden-winged Warblers do not nest there. However, 14 nests found using telemetry (18%) were >25 m into forest. We modeled nest success using nest-searching method, nest age, and distance to forest edge as explanatory variables. Nest-searching method explained nest success better than nest age alone; we estimated that nests found using telemetry were 10% more likely to fledge young than nests found using standard nest-searching methods. Although radio-telemetry was more expensive than standard nest searching, the cost-effectiveness of both methods differed depending on searcher experience, amount of equipment owned, and bird population density. Our results demonstrate that telemetry can be an effective method for reducing bias in Golden-winged Warbler nest samples, can be cost competitive with standard nest-searching methods in some situations, and is likely to be a useful approach for finding nests of other forest-nesting songbirds.
Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations.
Branke, Jürgen; Hildebrandt, Torsten; Scholz-Reiter, Bernd
2015-01-01
Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by experts in a time consuming trial-and-error process. Recently, evolutionary algorithms have been proposed to automate the design process. There are several possibilities to represent rules for this hyper-heuristic search. Because the representation determines the search neighborhood and the complexity of the rules that can be evolved, a suitable choice of representation is key for a successful evolutionary algorithm. In this paper we empirically compare three different representations, both numeric and symbolic, for automated rule design: A linear combination of attributes, a representation based on artificial neural networks, and a tree representation. Using appropriate evolutionary algorithms (CMA-ES for the neural network and linear representations, genetic programming for the tree representation), we empirically investigate the suitability of each representation in a dynamic stochastic job shop scenario. We also examine the robustness of the evolved dispatching rules against variations in the underlying job shop scenario, and visualize what the rules do, in order to get an intuitive understanding of their inner workings. Results indicate that the tree representation using an improved version of genetic programming gives the best results if many candidate rules can be evaluated, closely followed by the neural network representation that already leads to good results for small to moderate computational budgets. The linear representation is found to be competitive only for extremely small computational budgets. PMID:24885679
A simple heuristic for blindfolded record linkage
Lowe, Henry; Das, Amar; Ferris, Todd
2012-01-01
Objectives To address the challenge of balancing privacy with the need to create cross-site research registry records on individual patients, while matching the data for a given patient as he or she moves between participating sites. To evaluate the strategy of generating anonymous identifiers based on real identifiers in such a way that the chances of a shared patient being accurately identified were maximized, and the chances of incorrectly joining two records belonging to different people were minimized. Methods Our hypothesis was that most variation in names occurs after the first two letters, and that date of birth is highly reliable, so a single match variable consisting of a hashed string built from the first two letters of the patient's first and last names plus their date of birth would have the desired characteristics. We compared and contrasted the match algorithm characteristics (rate of false positive v. rate of false negative) for our chosen variable against both Social Security Numbers and full names. Results In a data set of 19 000 records, a derived match variable consisting of a 2-character prefix from both first and last names combined with date of birth has a 97% sensitivity; by contrast, an anonymized identifier based on the patient's full names and date of birth has a sensitivity of only 87% and SSN has sensitivity 86%. Conclusion The approach we describe is most useful in situations where privacy policies preclude the full exchange of the identifiers required by more sophisticated and sensitive linkage algorithms. For data sets of sufficiently high quality this effective approach, while producing a lower rate of matching than more complex algorithms, has the merit of being easy to explain to institutional review boards, adheres to the minimum necessary rule of the HIPAA privacy rule, and is faster and less cumbersome to implement than a full probabilistic linkage. PMID:22298567
Parsimony score of phylogenetic networks: hardness results and a linear-time heuristic.
Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir
2009-01-01
Phylogenies-the evolutionary histories of groups of organisms-play a major role in representing the interrelationships among biological entities. Many methods for reconstructing and studying such phylogenies have been proposed, almost all of which assume that the underlying history of a given set of species can be represented by a binary tree. Although many biological processes can be effectively modeled and summarized in this fashion, others cannot: recombination, hybrid speciation, and horizontal gene transfer result in networks of relationships rather than trees of relationships. In previous works, we formulated a maximum parsimony (MP) criterion for reconstructing and evaluating phylogenetic networks, and demonstrated its quality on biological as well as synthetic data sets. In this paper, we provide further theoretical results as well as a very fast heuristic algorithm for the MP criterion of phylogenetic networks. In particular, we provide a novel combinatorial definition of phylogenetic networks in terms of "forbidden cycles," and provide detailed hardness and hardness of approximation proofs for the "small" MP problem. We demonstrate the performance of our heuristic in terms of time and accuracy on both biological and synthetic data sets. Finally, we explain the difference between our model and a similar one formulated by Nguyen et al., and describe the implications of this difference on the hardness and approximation results. PMID:19644176
NASA Technical Reports Server (NTRS)
Haftka, R. T.; Adelman, H. M.
1984-01-01
Orbiting spacecraft such as large space antennas have to maintain a highly accurate space to operate satisfactorily. Such structures require active and passive controls to mantain an accurate shape under a variety of disturbances. Methods for the optimum placement of control actuators for correcting static deformations are described. In particular, attention is focused on the case were control locations have to be selected from a large set of available sites, so that integer programing methods are called for. The effectiveness of three heuristic techniques for obtaining a near-optimal site selection is compared. In addition, efficient reanalysis techniques for the rapid assessment of control effectiveness are presented. Two examples are used to demonstrate the methods: a simple beam structure and a 55m space-truss-parabolic antenna.
NASA Technical Reports Server (NTRS)
Haftka, R. T.; Adelman, H. M.
1985-01-01
Orbiting spacecraft such as large space antennas have to maintain a highly accurate shape to operate satisfactorily. Such structures require active and passive controls to maintain an accurate shape under a variety of disturbances. Methods for the optimum placement of control actuators for correcting static deformations are described. In particular, attention is focused on the case were control locations have to be selected from a large set of available sites, so that integer programing methods are called for. The effectiveness of three heuristic techniques for obtaining a near-optimal site selection is compared. In addition, efficient reanalysis techniques for the rapid assessment of control effectiveness are presented. Two examples are used to demonstrate the methods: a simple beam structure and a 55m space-truss-parabolic antenna.
ERIC Educational Resources Information Center
Homan, Michael; Worley, Penny
This course syllabus describes methods for optimizing online searching, using as an example searching on the National Library of Medicine (NLM) online system. Four major activities considered are the online interview, query analysis and search planning, online interaction, and post-search analysis. Within the context of these activities, concepts…
Agüero-Chapin, Guillermin; Molina-Ruiz, Reinaldo; Maldonado, Emanuel; de la Riva, Gustavo; Sánchez-Rodríguez, Aminael; Vasconcelos, Vitor; Antunes, Agostinho
2013-01-01
The introduction of two-dimension (2D) graphs and their numerical characterization for comparative analyses of DNA/RNA and protein sequences without the need of sequence alignments is an active yet recent research topic in bioinformatics. Here, we used a 2D artificial representation (four-color maps) with a simple numerical characterization through topological indices (TIs) to aid the discovering of remote homologous of Adenylation domains (A-domains) from the Nonribosomal Peptide Synthetases (NRPS) class in the proteome of the cyanobacteria Microcystis aeruginosa. Cyanobacteria are a rich source of structurally diverse oligopeptides that are predominantly synthesized by NPRS. Several A-domains share amino acid identities lower than 20 % being a possible source of remote homologous. Therefore, A-domains cannot be easily retrieved by BLASTp searches using a single template. To cope with the sequence diversity of the A-domains we have combined homology-search methods with an alignment-free tool that uses protein four-color-maps. TI2BioP (Topological Indices to BioPolymers) version 2.0, available at http://ti2biop.sourceforge.net/ allowed the calculation of simple TIs from the protein sequences (four-color maps). Such TIs were used as input predictors for the statistical estimations required to build the alignment-free models. We concluded that the use of graphical/numerical approaches in cooperation with other sequence search methods, like multi-templates BLASTp and profile HMM, can give the most complete exploration of the repertoire of highly diverse protein families. PMID:23874386
van Luijk, Judith; Cuijpers, Yvonne; van der Vaart, Lilian; Leenaars, Marlies; Ritskes-Hoitinga, Merel
2011-10-01
A local survey conducted among scientists into the current practice of searching for information on Three Rs (i.e. Replacement, Reduction and Refinement) methods has highlighted the gap between the statutory requirement to apply Three Rs methods and the lack of criteria to search for them. To verify these findings on a national level, we conducted a survey among scientists throughout The Netherlands. Due to the low response rate, the results give an impression of opinions, rather than being representative of The Netherlands as a whole. The findings of both surveys complement each other, and indicate that there is room for improvement. Scientists perceive searching the literature for information on Three Rs methods to be a difficult task, and specific Three Rs search skills and knowledge of Three Rs databases are limited. Rather than using a literature search, many researchers obtain information on these methods through personal communication, which means that published information on possible Three Rs methods often remains unfound and unused. A solution might be to move beyond the direct search for information on Three Rs methods and choose another approach. One approach that seems rather appropriate is that of systematic review. This provides insight into the necessity for any new animal studies, as well as optimal implementation of available data and the prevention of unnecessary animal use in the future. PMID:22103937
Ramos-Fernández, Antonio; Paradela, Alberto; Navajas, Rosana; Albar, Juan Pablo
2008-09-01
Tandem mass spectrometry-based proteomics is currently in great demand of computational methods that facilitate the elimination of likely false positives in peptide and protein identification. In the last few years, a number of new peptide identification programs have been described, but scores or other significance measures reported by these programs cannot always be directly translated into an easy to interpret error rate measurement such as the false discovery rate. In this work we used generalized lambda distributions to model frequency distributions of database search scores computed by MASCOT, X!TANDEM with k-score plug-in, OMSSA, and InsPecT. From these distributions, we could successfully estimate p values and false discovery rates with high accuracy. From the set of peptide assignments reported by any of these engines, we also defined a generic protein scoring scheme that enabled accurate estimation of protein-level p values by simulation of random score distributions that was also found to yield good estimates of protein-level false discovery rate. The performance of these methods was evaluated by searching four freely available data sets ranging from 40,000 to 285,000 MS/MS spectra. PMID:18515861
Shaffer, Franklin D.
2013-03-12
The application relates to particle trajectory recognition from a Centroid Population comprised of Centroids having an (x, y, t) or (x, y, f) coordinate. The method is applicable to visualization and measurement of particle flow fields of high particle. In one embodiment, the centroids are generated from particle images recorded on camera frames. The application encompasses digital computer systems and distribution mediums implementing the method disclosed and is particularly applicable to recognizing trajectories of particles in particle flows of high particle concentration. The method accomplishes trajectory recognition by forming Candidate Trajectory Trees and repeated searches at varying Search Velocities, such that initial search areas are set to a minimum size in order to recognize only the slowest, least accelerating particles which produce higher local concentrations. When a trajectory is recognized, the centroids in that trajectory are removed from consideration in future searches.
Naghibi, Tofigh; Hoffmann, Sarah; Pfister, Beat
2015-08-01
Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mining applications. In the feature subset selection problem there are two main issues that need to be addressed: (i) Finding an appropriate measure function than can be fairly fast and robustly computed for high-dimensional data. (ii) A search strategy to optimize the measure over the subset space in a reasonable amount of time. In this article mutual information between features and class labels is considered to be the measure function. Two series expansions for mutual information are proposed, and it is shown that most heuristic criteria suggested in the literature are truncated approximations of these expansions. It is well-known that searching the whole subset space is an NP-hard problem. Here, instead of the conventional sequential search algorithms, we suggest a parallel search strategy based on semidefinite programming (SDP) that can search through the subset space in polynomial time. By exploiting the similarities between the proposed algorithm and an instance of the maximum-cut problem in graph theory, the approximation ratio of this algorithm is derived and is compared with the approximation ratio of the backward elimination method. The experiments show that it can be misleading to judge the quality of a measure solely based on the classification accuracy, without taking the effect of the non-optimum search strategy into account. PMID:26352993
Marzilli Ericson, Keith M.; White, John Myles; Laibson, David; Cohen, Jonathan D.
2015-01-01
Heuristic models have been proposed for many domains of choice. We compare heuristic models of intertemporal choice, which can account for many of the known intertemporal choice anomalies, to discounting models. We conduct an out-of-sample, cross-validated comparison of intertemporal choice models. Heuristic models outperform traditional utility discounting models, including models of exponential and hyperbolic discounting. The best performing models predict choices by using a weighted average of absolute differences and relative (percentage) differences of the attributes of the goods in a choice set. We conclude that heuristic models explain time-money tradeoff choices in experiments better than utility discounting models. PMID:25911124
Heuristic-based scheduling algorithm for high level synthesis
NASA Technical Reports Server (NTRS)
Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye
1992-01-01
A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.
An architecture for heuristic control of real-time processes
NASA Technical Reports Server (NTRS)
Raulefs, P.; Thorndyke, P. W.
1987-01-01
Abstract Process management combines complementary approaches of heuristic reasoning and analytical process control. Management of a continuous process requires monitoring the environment and the controlled system, assessing the ongoing situation, developing and revising planned actions, and controlling the execution of the actions. For knowledge-intensive domains, process management entails the potentially time-stressed cooperation among a variety of expert systems. By redesigning a blackboard control architecture in an object-oriented framework, researchers obtain an approach to process management that considerably extends blackboard control mechanisms and overcomes limitations of blackboard systems.
Some heuristic procedures for analyzing random vibration of nonlinear oscillators.
NASA Technical Reports Server (NTRS)
Crandall, S. H.
1971-01-01
The stationary response of a lightly damped nonlinear oscillator subjected to wideband random excitation can be examined as an example of thermal equilibrium. It may be assumed that the response consists of a series of free-vibration cycles with small random fluctuations in phase and amplitude. Certain statistical properties of the response can be estimated by averaging corresponding properties of the free vibration with respect to cycle amplitude distributions. Such heuristic procedures for determining the expected frequency and the autocorrelation function of the stationary response are outlined. Some additional results concerning first-passage problems for nonlinear oscillators are included.
TORC3: Token-ring clearing heuristic for currency circulation
NASA Astrophysics Data System (ADS)
Humes, Carlos, Jr.; Lauretto, Marcelo S.; Nakano, Fábio; Pereira, Carlos A. B.; Rafare, Guilherme F. G.; Stern, Julio Michael
2012-10-01
Clearing algorithms are at the core of modern payment systems, facilitating the settling of multilateral credit messages with (near) minimum transfers of currency. Traditional clearing procedures use batch processing based on MILP - mixed-integer linear programming algorithms. The MILP approach demands intensive computational resources; moreover, it is also vulnerable to operational risks generated by possible defaults during the inter-batch period. This paper presents TORC3 - the Token-Ring Clearing Algorithm for Currency Circulation. In contrast to the MILP approach, TORC3 is a real time heuristic procedure, demanding modest computational resources, and able to completely shield the clearing operation against the participating agents' risk of default.
A method to search for solar flares jointly observed by multiple instruments.
NASA Astrophysics Data System (ADS)
Milligan, Ryan
2016-07-01
Our current fleet of space-based solar observatories offer us a wealth of opportunities to study solar flares over a range of wavelengths, and the greatest advances in our understanding of flare physics often come from coordinated observations between different instruments. However, despite considerable effort to try and coordinate this armada of instruments over the years (e.g. through the Max Millennium Program of Solar Flare Research), there are frustratingly few solar flares that have been well and truly observed by most or all instruments simultaneously. This is due to a range of factors such as instruments having a limited field of view, satellites in low-Earth orbit going into eclipse, and observing schedules being uploaded days in advance. I shall describe a new technique to retrospectively search archival databases for flares jointly observed by RHESSI, SDO/EVE, Hinode/EIS+SOT, and IRIS. I shall also present a summary of how many flares have been observed by different configurations of these instruments since the launch of SDO.
`Reverse Chemical Evolution': A New Method to Search for Thermally Stable Biopolymers
NASA Astrophysics Data System (ADS)
Mitsuzawa, Shigenobu; Yukawa, Tetsuyuki
2003-04-01
The primitive sea on Earth may have had high-temperature and high-pressure conditions similar to those in present-day hydrothermal environments. If life originated in the hot sea, thermal stability of the constituent molecules would have been necessary. Thus far, however, it has been reported that biopolymers hydrolyze too rapidly to support life at temperatures of more than 200 °C. We herein propose a novel approach, called reverse chemical evolution, to search for biopolymers notably more stable against thermal decomposition than previously reported. The essence of the approach is that hydrolysis of a protein or functional RNA (m-, t-, r-RNA) at high temperature and high pressure simulating the ancient sea environment may yield thermally stable peptides or RNAs at higher concentrations than other peptides or RNAs. An experimental test hydrolyzing bovine ribonuclease A in aqueous solution at 205 °C and 25 MPa yielded three prominently stable molecules weighing 859, 1030 and 695 Da. They are thermally some tens or hundreds times more stable than a polyglycine of comparable mass. Sequence analyses of the 859- and 1030-Da molecules revealed that they are a heptapeptide and its homologue, respectively, elongated by two amino acids at the N-terminal region, originally embedded as residues 112-120 in the protein. They consist mainly of hydrophobic amino acids.
In Search of Easy-to-Use Methods for Calibrating ADCP's for Velocity and Discharge Measurements
Oberg, K.
2002-01-01
A cost-effective procedure for calibrating acoustic Doppler current profilers (ADCP) in the field was presented. The advantages and disadvantages of various methods which are used for calibrating ADCP were discussed. The proposed method requires the use of differential global positioning system (DGPS) with sub-meter accuracy and standard software for collecting ADCP data. The method involves traversing a long (400-800 meter) course at a constant compass heading and speed, while collecting simultaneous DGPS and ADCP data.
The Dynamical Recollection of Interconnected Neural Networks Using Meta-heuristics
NASA Astrophysics Data System (ADS)
Kuremoto, Takashi; Watanabe, Shun; Kobayashi, Kunikazu; Feng, Laing-Bing; Obayashi, Masanao
The interconnected recurrent neural networks are well-known with their abilities of associative memory of characteristic patterns. For example, the traditional Hopfield network (HN) can recall stored pattern stably, meanwhile, Aihara's chaotic neural network (CNN) is able to realize dynamical recollection of a sequence of patterns. In this paper, we propose to use meta-heuristic (MH) methods such as the particle swarm optimization (PSO) and the genetic algorithm (GA) to improve traditional associative memory systems. Using PSO or GA, for CNN, optimal parameters are found to accelerate the recollection process and raise the rate of successful recollection, and for HN, optimized bias current is calculated to improve the network with dynamical association of a series of patterns. Simulation results of binary pattern association showed effectiveness of the proposed methods.