Theoretical Analysis of Heuristic Search Methods for Online POMDPs.
Ross, Stéphane; Pineau, Joelle; Chaib-Draa, Brahim
2008-01-01
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have also been proposed recently, and proven to be remarkably scalable, but without the theoretical guarantees of their offline counterparts. Thus it seems natural to try to unify offline and online techniques, preserving the theoretical properties of the former, and exploiting the scalability of the latter. In this paper, we provide theoretical guarantees on an anytime algorithm for POMDPs which aims to reduce the error made by approximate offline value iteration algorithms through the use of an efficient online searching procedure. The algorithm uses search heuristics based on an error analysis of lookahead search, to guide the online search towards reachable beliefs with the most potential to reduce error. We provide a general theorem showing that these search heuristics are admissible, and lead to complete and ε-optimal algorithms. This is, to the best of our knowledge, the strongest theoretical result available for online POMDP solution methods. We also provide empirical evidence showing that our approach is also practical, and can find (provably) near-optimal solutions in reasonable time.
Learning to Search: From Weak Methods to Domain-Specific Heuristics.
ERIC Educational Resources Information Center
Langley, Pat
1985-01-01
Examines processes by which general but weak search methods are transformed into powerful, domain-specific search strategies by classifying types of heuristics learning that can occur and components that contribute to such learning. A learning system--SAGE.2--and its structure, behavior in different domains, and future directions are explored. (36…
Zhao, Wanqing; Meng, Qinggang; Chung, Paul W H
2016-04-01
Using distributed task allocation methods for cooperating multivehicle systems is becoming increasingly attractive. However, most effort is placed on various specific experimental work and little has been done to systematically analyze the problem of interest and the existing methods. In this paper, a general scenario description and a system configuration are first presented according to search and rescue scenario. The objective of the problem is then analyzed together with its mathematical formulation extracted from the scenario. Considering the requirement of distributed computing, this paper then proposes a novel heuristic distributed task allocation method for multivehicle multitask assignment problems. The proposed method is simple and effective. It directly aims at optimizing the mathematical objective defined for the problem. A new concept of significance is defined for every task and is measured by the contribution to the local cost generated by a vehicle, which underlies the key idea of the algorithm. The whole algorithm iterates between a task inclusion phase, and a consensus and task removal phase, running concurrently on all the vehicles where local communication exists between them. The former phase is used to include tasks into a vehicle's task list for optimizing the overall objective, while the latter is to reach consensus on the significance value of tasks for each vehicle and to remove the tasks that have been assigned to other vehicles. Numerical simulations demonstrate that the proposed method is able to provide a conflict-free solution and can achieve outstanding performance in comparison with the consensus-based bundle algorithm.
BCI Control of Heuristic Search Algorithms
Cavazza, Marc; Aranyi, Gabor; Charles, Fred
2017-01-01
The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users’ mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A* algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA*. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid
BCI Control of Heuristic Search Algorithms.
Cavazza, Marc; Aranyi, Gabor; Charles, Fred
2017-01-01
The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users' mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A* algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA*. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid
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.
Remotely sensed image processing service composition based on heuristic search
NASA Astrophysics Data System (ADS)
Yang, Xiaoxia; Zhu, Qing; Li, Hai-feng; Zhao, Wen-hao
2008-12-01
As remote sensing technology become ever more powerful with multi-platform and multi-sensor, it has been widely recognized for contributing to geospatial information efforts. Because the remotely sensed image processing demands large-scale, collaborative processing and massive storage capabilities to satisfy the increasing demands of various applications, the effect and efficiency of the remotely sensed image processing is far from the user's expectation. The emergence of Service Oriented Architecture (SOA) may make this challenge manageable. It encapsulate all processing function into services and recombine them with service chain. The service composition on demand has become a hot topic. Aiming at the success rate, quality and efficiency of processing service composition for remote sensing application, a remote sensed image processing service composition method is proposed in this paper. It composes services for a user requirement through two steps: 1) dynamically constructs a complete service dependency graph for user requirement on-line; 2) AO* based heuristic searches for optimal valid path in service dependency graph. These services within the service dependency graph are considered relevant to the specific request, instead of overall registered services. The second step, heuristic search is a promising approach for automated planning. Starting with the initial state, AO* uses a heuristic function to select states until the user requirement is reached. Experimental results show that this method has a good performance even the repository has a large number of processing services.
Heuristics for Relevancy Ranking of Earth Dataset Search Results
NASA Technical Reports Server (NTRS)
Lynnes, Christopher; Quinn, Patrick; Norton, James
2016-01-01
As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.
Best-First Heuristic Search for Multicore Machines
2010-01-01
w factor of the optimal solution cost) (Davis, Bramanti -Gregor, & Wang, 1988). It is possible to modify AHDA*, BFPSDD, and PBNF to use weights to... Bramanti -Gregor, A., & Wang, J. (1988). The advantages of using depth and breadth components in heuristic search. In Methodologies for Intelligent Systems 3
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.
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.
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.
A method for extracting drainage networks with heuristic information from digital elevation models.
Hou, Kun; Yang, Wei; Sun, Jigui; Sun, Tieli
2011-01-01
Depression filling and direction assignment over flat areas are critical issues in hydrologic analysis. This paper proposes a method to handle depressions and flat areas in one procedure. Being different from the traditional raster neighbourhoods processing with little heuristic information, the method is designed to compensate for the inadequate searching information of other methods. The proposed method routes flow through depressions and flat areas by searching for the outlet using the heuristic information. Heuristic information can reveal the general trend slope of the DEM (digital elevation models) and help the proposed method find the outlet accurately. The method is implemented in Pascal and experiments are carried out on actual DEM data. It can be seen from the comparison with the four existing methods that the proposed method can get a closer match result with the ground truth network. Moreover, the proposed method can avoid the generation of the unrealistic parallel drainage lines, unreal drainage lines and spurious terrain features.
Local search heuristic for the discrete leader-follower problem with multiple follower objectives
NASA Astrophysics Data System (ADS)
Kochetov, Yury; Alekseeva, Ekaterina; Mezmaz, Mohand
2016-10-01
We study a discrete bilevel problem, called as well as leader-follower problem, with multiple objectives at the lower level. It is assumed that constraints at the upper level can include variables of both levels. For such ill-posed problem we define feasible and optimal solutions for pessimistic case. A central point of this work is a two stage method to get a feasible solution under the pessimistic case, given a leader decision. The target of the first stage is a follower solution that violates the leader constraints. The target of the second stage is a pessimistic feasible solution. Each stage calls a heuristic and a solver for a series of particular mixed integer programs. The method is integrated inside a local search based heuristic that is designed to find near-optimal leader solutions.
NASA Astrophysics Data System (ADS)
Phillips, Carolyn L.
2014-09-01
In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.
Comparative study of heuristic evaluation and usability testing methods.
Thyvalikakath, Thankam Paul; Monaco, Valerie; Thambuganipalle, Himabindu; Schleyer, Titus
2009-01-01
Usability methods, such as heuristic evaluation, cognitive walk-throughs and user testing, are increasingly used to evaluate and improve the design of clinical software applications. There is still some uncertainty, however, as to how those methods can be used to support the development process and evaluation in the most meaningful manner. In this study, we compared the results of a heuristic evaluation with those of formal user tests in order to determine which usability problems were detected by both methods. We conducted heuristic evaluation and usability testing on four major commercial dental computer-based patient records (CPRs), which together cover 80% of the market for chairside computer systems among general dentists. Both methods yielded strong evidence that the dental CPRs have significant usability problems. An average of 50% of empirically-determined usability problems were identified by the preceding heuristic evaluation. Some statements of heuristic violations were specific enough to precisely identify the actual usability problem that study participants encountered. Other violations were less specific, but still manifested themselves in usability problems and poor task outcomes. In this study, heuristic evaluation identified a significant portion of problems found during usability testing. While we make no assumptions about the generalizability of the results to other domains and software systems, heuristic evaluation may, under certain circumstances, be a useful tool to determine design problems early in the development cycle.
Protein sequence-similarity search acceleration using a heuristic algorithm with a sensitive matrix.
Lim, Kyungtaek; Yamada, Kazunori D; Frith, Martin C; Tomii, Kentaro
2016-12-01
Protein database search for public databases is a fundamental step in the target selection of proteins in structural and functional genomics and also for inferring protein structure, function, and evolution. Most database search methods employ amino acid substitution matrices to score amino acid pairs. The choice of substitution matrix strongly affects homology detection performance. We earlier proposed a substitution matrix named MIQS that was optimized for distant protein homology search. Herein we further evaluate MIQS in combination with LAST, a heuristic and fast database search tool with a tunable sensitivity parameter m, where larger m denotes higher sensitivity. Results show that MIQS substantially improves the homology detection and alignment quality performance of LAST across diverse m parameters. Against a protein database consisting of approximately 15 million sequences, LAST with m = 10(5) achieves better homology detection performance than BLASTP, and completes the search 20 times faster. Compared to the most sensitive existing methods being used today, CS-BLAST and SSEARCH, LAST with MIQS and m = 10(6) shows comparable homology detection performance at 2.0 and 3.9 times greater speed, respectively. Results demonstrate that MIQS-powered LAST is a time-efficient method for sensitive and accurate homology search.
An interdisciplinary heuristic evaluation method for universal building design.
Afacan, Yasemin; Erbug, Cigdem
2009-07-01
This study highlights how heuristic evaluation as a usability evaluation method can feed into current building design practice to conform to universal design principles. It provides a definition of universal usability that is applicable to an architectural design context. It takes the seven universal design principles as a set of heuristics and applies an iterative sequence of heuristic evaluation in a shopping mall, aiming to achieve a cost-effective evaluation process. The evaluation was composed of three consecutive sessions. First, five evaluators from different professions were interviewed regarding the construction drawings in terms of universal design principles. Then, each evaluator was asked to perform the predefined task scenarios. In subsequent interviews, the evaluators were asked to re-analyze the construction drawings. The results showed that heuristic evaluation could successfully integrate universal usability into current building design practice in two ways: (i) it promoted an iterative evaluation process combined with multi-sessions rather than relying on one evaluator and on one evaluation session to find the maximum number of usability problems, and (ii) it highlighted the necessity of an interdisciplinary ad hoc committee regarding the heuristic abilities of each profession. A multi-session and interdisciplinary heuristic evaluation method can save both the project budget and the required time, while ensuring a reduced error rate for the universal usage of the built environments.
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.
Hitch-hiking: a parallel heuristic search strategy, applied to the phylogeny problem.
Charleston, M A
2001-01-01
The article introduces a parallel heuristic search strategy ("Hitch-hiking") which can be used in conjunction with other random-walk heuristic search strategies. It is applied to an artificial phylogeny problem, in which character sequences are evolved using pseudo-random numbers from a hypothetical ancestral sequence. The objective function to be minimized is the minimum number of character-state changes required on a binary tree that could account for the sequences observed at the tips (leaves) of the tree -- the Maximum Parsimony criterion. The Hitch-hiking strategy is shown to be useful in that it is robust and that on average the solutions found using the strategy are better than those found without. Also the strategy can dynamically provide information on the characteristics of the landscape of the problem. I argue that Hitch-hiking as a scheme for parallelization of existing heuristic search strategies is of potentially very general use, in many areas of combinatorial optimization.
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
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…
Heuristics in Problem Solving: The Role of Direction in Controlling Search Space
ERIC Educational Resources Information Center
Chu, Yun; Li, Zheng; Su, Yong; Pizlo, Zygmunt
2010-01-01
Isomorphs of a puzzle called m+m resulted in faster solution times and an easily reproduced solution path in a labeled version of the problem compared to a more difficult binary version. We conjecture that performance is related to a type of heuristic called direction that not only constrains search space in the labeled version, but also…
A lifelong learning hyper-heuristic method for bin packing.
Sim, Kevin; Hart, Emma; Paechter, Ben
2015-01-01
We describe a novel hyper-heuristic system that continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; and representative problems and heuristics are incorporated into a self-sustaining network of interacting entities inspired by methods in artificial immune systems. The network is plastic in both its structure and content, leading to the following properties: it exploits existing knowledge captured in the network to rapidly produce solutions; it can adapt to new problems with widely differing characteristics; and it is capable of generalising over the problem space. The system is tested on a large corpus of 3,968 new instances of 1D bin-packing problems as well as on 1,370 existing problems from the literature; it shows excellent performance in terms of the quality of solutions obtained across the datasets and in adapting to dynamically changing sets of problem instances compared to previous approaches. As the network self-adapts to sustain a minimal repertoire of both problems and heuristics that form a representative map of the problem space, the system is further shown to be computationally efficient and therefore scalable.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths
NASA Astrophysics Data System (ADS)
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [http://www.cs.ubc.ca/~hoos/5/benchm.html]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
A New Improved Hybrid Meta-Heuristics Method for Unit Commitment with Nonlinear Fuel Cost Function
NASA Astrophysics Data System (ADS)
Okawa, Kenta; Mori, Hiroyuki
In this paper, a new improved hybrid meta-heuristic method is proposed to solve the unit commitment problem effectively. The objective is to minimize operation cost while satisfying the power balance constraints and so on. It may be formulated as a nonlinear mixed-integer problem. In other words, the unit commitment problem is hard to solve. Therefore, this paper makes use of a hybrid meta-heuristic method with two layers. Layer 1 determines the on/off conditions of generators with tabu search (TS) while Layer 2 evaluates output of generators with evolutionary particle swarm optimization (EPSO). The construction phase of Greedy Randomized Adaptive Search Procedure (GRASP) is used to create initial feasible solutions efficiently. Three kinds of meta-heuristic methods such as TS, EPSO and GRASP are combined to solve the problem. In addition, a parallel scheme of EPSO is developed to improve the computational efficient as well as the accuracy. The effectiveness of the proposed method is tested in sample systems.
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.
Index Fund Optimization Using a Genetic Algorithm and a Heuristic Local Search
NASA Astrophysics Data System (ADS)
Orito, Yukiko; Inoguchi, Manabu; Yamamoto, Hisashi
It is well known that index funds are popular passively managed portfolios and have been used very extensively for the hedge trading. Index funds consist of a certain number of stocks of listed companies on a stock market such that the fund's return rates follow a similar path to the changing rates of the market indices. However it is hard to make a perfect index fund consisting of all companies included in the given market index. Thus, the index fund optimization can be viewed as a combinatorial optimization for portfolio managements. In this paper, we propose an optimization method that consists of a genetic algorithm and a heuristic local search algorithm to make strong linear association between the fund's return rates and the changing rates of market index. We apply the method to the Tokyo Stock Exchange and make index funds whose return rates follow a similar path to the changing rates of Tokyo Stock Price Index (TOPIX). The results show that our proposal method makes the index funds with strong linear association to the market index by small computing time.
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.
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
2012-01-01
Background Previous studies on tumor classification based on gene expression profiles suggest that gene selection plays a key role in improving the classification performance. Moreover, finding important tumor-related genes with the highest accuracy is a very important task because these genes might serve as tumor biomarkers, which is of great benefit to not only tumor molecular diagnosis but also drug development. Results This paper proposes a novel gene selection method with rich biomedical meaning based on Heuristic Breadth-first Search Algorithm (HBSA) to find as many optimal gene subsets as possible. Due to the curse of dimensionality, this type of method could suffer from over-fitting and selection bias problems. To address these potential problems, a HBSA-based ensemble classifier is constructed using majority voting strategy from individual classifiers constructed by the selected gene subsets, and a novel HBSA-based gene ranking method is designed to find important tumor-related genes by measuring the significance of genes using their occurrence frequencies in the selected gene subsets. The experimental results on nine tumor datasets including three pairs of cross-platform datasets indicate that the proposed method can not only obtain better generalization performance but also find many important tumor-related genes. Conclusions It is found that the frequencies of the selected genes follow a power-law distribution, indicating that only a few top-ranked genes can be used as potential diagnosis biomarkers. Moreover, the top-ranked genes leading to very high prediction accuracy are closely related to specific tumor subtype and even hub genes. Compared with other related methods, the proposed method can achieve higher prediction accuracy with fewer genes. Moreover, they are further justified by analyzing the top-ranked genes in the context of individual gene function, biological pathway, and protein-protein interaction network. PMID:22830977
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.
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
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.
Animal, Vegetable, Mineral: A Method for Introducing Heuristics.
ERIC Educational Resources Information Center
Rivers, Thomas M.
Students beginning a freshman composition class tend to regard writing as an editing process rather than as a process which encompasses intelligence, character, and humanity. Helping students understand and master heuristic procedures on the way to developing composition skills can be facilitated by the use of the game Twenty Questions to learn…
A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.
Hart, Emma; Sim, Kevin
2016-01-01
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.
Hemmelmayr, Vera C; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-12-01
In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP.
Hemmelmayr, Vera C.; Cordeau, Jean-François; Crainic, Teodor Gabriel
2012-01-01
In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. PMID:23483764
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
Complexity, Heuristic, and Search Analysis for the Games of Crossings and Epaminondas
2014-03-27
second. 40 Next, leveraging heuristics from Lines of Action and the ancient Egyptian game Seega, the evaluation function was modified to take into account...Institute of Technology Air University Air Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Master of...17 2.7.3 History Heuristic . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.7.4 Transposition Tables
NASA Astrophysics Data System (ADS)
Zhu, Meng-Hua; Liu, Liang-Gang; You, Zhong; Xu, Ao-Ao
2009-03-01
In this paper, a heuristic approach based on Slavic's peak searching method has been employed to estimate the width of peak regions for background removing. Synthetic and experimental data are used to test this method. With the estimated peak regions using the proposed method in the whole spectrum, we find it is simple and effective enough to be used together with the Statistics-sensitive Nonlinear Iterative Peak-Clipping method.
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.
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.
AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search
1976-07-01
conclusions contained in this document are those of the author (s) and should not be interpreted as necessarily representing the official policies...faculties, skills . The more familiar the parts, the more striking the new whole. -- Koestler Suppose a large collection of these heuristic strategies...hitherto unknown to the author . A couple bits of new mathematics have been inipired by AM.2 A synergetic AM-human combination can sometimes produce
Formal and heuristic system decomposition methods in multidisciplinary synthesis
NASA Astrophysics Data System (ADS)
Bloebaum, Christina Lynne
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 is to develop an efficient holistic design synthesis methodology that takes advantage of the synergistic nature of integrated design. Although the design process encompasses several stages in which optimization methods could be applied, the present study addresses the applications of optimization in the preliminary design stage, in which the most capability for positive change exists. A primary concern in this stage involves implementation of an accurate and efficient mathematical representation of large engineering systems. Without such a representation, meaningful design synthesis is impossible. Multilevel decomposition methods provide a systematic approach for decoupling the large complex systems found in multidisciplinary design problems into smaller, more manageable subsystems. These methods account for the couplings between the intrinsically linked disciplinary analysis modules on the basis of a linear sensitivity analysis. In a majority of such efforts, the decomposition is governed either by an obvious hierarchy in the system or on the basis of discipline.
Kushniruk, Andre W; Monkman, Helen; Tuden, Danica; Bellwood, Paule; Borycki, Elizabeth M
2015-01-01
Developing more usable healthcare information systems has become an important goal in health informatics. Although methods from usability engineering have appeared and been effectively applied in the design and evaluation of healthcare systems, there continues to be reports of deployment of unusable systems and issues with adoption of healthcare IT worldwide. In this paper we propose a new cost-effective usability engineering approach for healthcare IT that integrates two of the major usability inspection approaches (heuristic evaluation and cognitive walkthrough) into one combined approach that leverages the advantages of both heuristic evaluation and cognitive walkthrough. The approach will be described as will a pilot application of the method in evaluating the usability of a well-known electronic health record system. Implications and future work will also be described.
Albrecht, Andreas A; Day, Luke; Abdelhadi Ep Souki, Ouala; Steinhöfel, Kathleen
2016-02-01
The analysis of energy landscapes plays an important role in mathematical modelling, simulation and optimisation. Among the main features of interest are the number and distribution of local minima within the energy landscape. Granier and Kallel proposed in 2002 a new sampling procedure for estimating the number of local minima. In the present paper, we focus on improved heuristic implementations of the general framework devised by Granier and Kallel with regard to run-time behaviour and accuracy of predictions. The new heuristic method is demonstrated for the case of partial energy landscapes induced by RNA secondary structures. While the computation of minimum free energy RNA secondary structures has been studied for a long time, the analysis of folding landscapes has gained momentum over the past years in the context of co-transcriptional folding and deeper insights into cell processes. The new approach has been applied to ten RNA instances of length between 99 nt and 504 nt and their respective partial energy landscapes defined by secondary structures within an energy offset ΔE above the minimum free energy conformation. The number of local minima within the partial energy landscapes ranges from 1440 to 3441. Our heuristic method produces for the best approximations on average a deviation below 3.0% from the true number of local minima.
Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.
Siswantoro, Joko; Prabuwono, Anton Satria; Abdullah, Azizi; 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.
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.
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.
NASA Astrophysics Data System (ADS)
Mugunthan, Pradeep; Shoemaker, Christine A.; Regis, Rommel G.
2005-11-01
The performance of function approximation (FA) methods is compared to heuristic and derivative-based nonlinear optimization methods for automatic calibration of biokinetic parameters of a groundwater bioremediation model of chlorinated ethenes on a hypothetical and a real field case. For the hypothetical case, on the basis of 10 trials on two different objective functions, the FA methods had the lowest mean and smaller deviation of the objective function among all algorithms for a combined Nash-Sutcliffe objective and among all but the derivative-based algorithm for a total squared error objective. The best algorithms in the hypothetical case were applied to calibrate eight parameters to data obtained from a site in California. In three trials the FA methods outperformed heuristic and derivative-based methods for both objective functions. This study indicates that function approximation methods could be a more efficient alternative to heuristic and derivative-based methods for automatic calibration of computationally expensive bioremediation models.
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.
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)
Liu, Z. Y. C.; Shirzaei, M.
2015-12-01
Impact craters on the terrestrial planets are typically surrounded by a continuous ejecta blanket that the initial emplacement is via ballistic sedimentation. Following an impact event, a significant volume of material is ejected and falling debris surrounds the crater. Aerodynamics rule governs the flight path and determines the spatial distribution of these ejecta. Thus, for the planets with atmosphere, the preserved ejecta deposit directly recorded the interaction of ejecta and atmosphere at the time of impact. In this study, we develop a new framework to establish links between distribution of the ejecta, age of the impact and the properties of local atmosphere. Given the radial distance of the continuous ejecta extent from crater, an inverse aerodynamic modeling approach is employed to estimate the local atmospheric drags and density as well as the lift forces at the time of impact. Based on earlier studies, we incorporate reasonable value ranges for ejection angle, initial velocity, aerodynamic drag, and lift in the model. In order to solve the trajectory differential equations, obtain the best estimate of atmospheric density, and the associated uncertainties, genetic algorithm is applied. The method is validated using synthetic data sets as well as detailed maps of impact ejecta associated with five fresh martian and two lunar impact craters, with diameter of 20-50 m, 10-20 m, respectively. The estimated air density for martian carters range 0.014-0.028 kg/m3, consistent with the recent surface atmospheric density measurement of 0.015-0.020 kg/m3. This constancy indicates the robustness of the presented methodology. In the following, the inversion results for the lunar craters yield air density of 0.003-0.008 kg/m3, which suggest the inversion results are accurate to the second decimal place. This framework will be applied to older martian craters with preserved ejecta blankets, which expect to constrain the long-term evolution of martian atmosphere.
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.
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)
Zittersteijn, M.; Vananti, A.; Schildknecht, T.; Dolado Perez, J. C.; Martinot, V.
2016-11-01
Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). The MTT problem quickly becomes an NP-hard combinatorial optimization problem. This means that the effort required to solve the MTT problem increases exponentially with the number of tracked objects. In an attempt to find an approximate solution of sufficient quality, several Population-Based Meta-Heuristic (PBMH) algorithms are implemented and tested on simulated optical measurements. These first results show that one of the tested algorithms, namely the Elitist Genetic Algorithm (EGA), consistently displays the desired behavior of finding good approximate solutions before reaching the optimum. The results further suggest that the algorithm possesses a polynomial time complexity, as the computation times are consistent with a polynomial model. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the association and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.
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.
Decentralized Bayesian search using approximate dynamic programming methods.
Zhao, Yijia; Patek, Stephen D; Beling, Peter A
2008-08-01
We consider decentralized Bayesian search problems that involve a team of multiple autonomous agents searching for targets on a network of search points operating under the following constraints: 1) interagent communication is limited; 2) the agents do not have the opportunity to agree in advance on how to resolve equivalent but incompatible strategies; and 3) each agent lacks the ability to control or predict with certainty the actions of the other agents. We formulate the multiagent search-path-planning problem as a decentralized optimal control problem and introduce approximate dynamic heuristics that can be implemented in a decentralized fashion. After establishing some analytical properties of the heuristics, we present computational results for a search problem involving two agents on a 5 x 5 grid.
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.
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.
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…
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.
A heuristic nonlinear constructive method for electric power distribution system reconfiguration
NASA Astrophysics Data System (ADS)
McDermott, Thomas E.
1998-12-01
The electric power distribution system usually operates in a radial configuration, with tie switches between circuits to provide alternate feeds. The losses would be minimized if all switches were closed, but this is not done because it complicates the system's protection against overcurrents. Whenever a component fails, some of the switches must be operated to restore power to as many customers as possible. As loads vary with time, switch operations may reduce losses in the system. Both of these are applications for reconfiguration. The problem is combinatorial, which precludes algorithms that guarantee a global optimum. Most existing reconfiguration algorithms fall into two categories. In the first, branch exchange, the system operates in a feasible radial configuration and the algorithm opens and closes candidate switches in pairs. In the second, loop cutting, the system is completely meshed and the algorithm opens candidate switches to reach a feasible radial configuration. Reconfiguration algorithms based on linearized transshipment, neural networks, heuristics, genetic algorithms, and simulated annealing have also been reported, but not widely used. These existing reconfiguration algorithms work with a simplified model of the power system, and they handle voltage and current constraints approximately, if at all. The algorithm described here is a constructive method, using a full nonlinear power system model that accurately handles constraints. The system starts with all switches open and all failed components isolated. An optional network power flow provides a lower bound on the losses. Then the algorithm closes one switch at a time to minimize the increase in a merit figure, which is the real loss divided by the apparent load served. The merit figure increases with each switch closing. This principle, called discrete ascent optimal programming (DAOP), has been applied to other power system problems, including economic dispatch and phase balancing. For
Search systems and computer-implemented search methods
Payne, Deborah A.; Burtner, Edwin R.; Hampton, Shawn D.; Gillen, David S.; Henry, Michael J.
2017-03-07
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.
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.
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
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.
Analytical Methods in Search Theory
1979-11-01
DETERMINISTIC ANb CONDITIONALLY DETERMTNISTIC S, ART -1 EQUATrONS References: 14,15. The deterministic search equation is: 3 • ’ ( f) - pf (3-1) at (IX...34le arts "." 2 pp., Mae 13M. Aanmtch CohtfractO~4*VI Partial Umnsitvatantൖ" 36 00 Alto 1174, IPtla, AD � fita IN t110 JOR" Of .1 M 04PIn Angeeeo...e" ISMO f Pdu ttarrtioegt, A. LeVas, "Market Anetytis with Th aleaiapsicMP"Ag11 isella Petdr Pattmcs Affecting Reseatch & RNational B 1peiarttso
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.
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.
The TSTS Method in Cultural Heritage Search
NASA Astrophysics Data System (ADS)
Stawniak, Mirosław; Cellary, Wojciech
In cultural heritage content management systems in which cultural objects are described with the use of their semantic, temporal and spatial properties, the search capabilities taking all those properties into consideration are very limited. The difficulty comes from the fact that concepts evolve over time and depend on location. In this paper the TSTS search method is presented based on the TST similarity measure that allows assessing the similarity factor between different resources in a knowledgebase. A ranked search result is generated basing on the semantic distance between the fuzzy set created for the user query and fuzzy sets describing potential results in the time-space continuum.
Automated detection of heuristics and biases among pathologists in a computer-based system.
Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia
2013-08-01
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 diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.
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.
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.
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.
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
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.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Genetic algorithms as global random search methods
NASA Technical Reports Server (NTRS)
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
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…
Ichikawa, Kazuki; Morishita, Shinichi
2014-01-01
K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.
Heuristically Driven Search Methods for Topology Control in Directional Wireless Hybrid Networks
2007-03-01
sovereign options for the defense of the United States of America and its global interests- -to fly and fight in Air, Space, and Cyberspace.” One of...model has been formulated, it can be integrated into a linear solver. Erwin used Xpress -Optimizer, a component of the Xpress -MP suite and a well-known...no global information is used to make decisions. On the other hand, greedy techniques are often acceptable substitutes for approximation algorithms
A Heuristic Automatic and Robust ROI Detection Method for Medical Image Warermarking.
Mousavi, Seyed Mojtaba; Naghsh, Alireza; Abu-Bakar, S A R
2015-08-01
This paper presents an automatic region of interest (ROI) segmentation method for application of watermarking in medical images. The advantage of using this scheme is that the proposed method is robust against different attacks such as median, Wiener, Gaussian, and sharpening filters. In other words, this technique can produce the same result for the ROI before and after these attacks. The proposed algorithm consists of three main parts; suggesting an automatic ROI detection system, evaluating the robustness of the proposed system against numerous attacks, and finally recommending an enhancement part to increase the strength of the composed system against different attacks. Results obtained from the proposed method demonstrated the promising performance of the method.
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.
A novel heuristic algorithm for capacitated vehicle routing problem
NASA Astrophysics Data System (ADS)
Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre
2017-02-01
The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.
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.
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.
Heuristic Traversal Of A Free Space Graph
NASA Astrophysics Data System (ADS)
Holmes, Peter D.; Jungert, Erland
1989-01-01
In order to plan paths within a physical working space, effective data structures must be used for spatial representation. A free space graph is a data structure derived from a systematic decomposition of the unobstructed portions of the working space. For the two-dimensional case, this work describes an heuristic method for traversal and search of one particular type of free space graph. The focus herein regards the "dialogue" between an A* search process and an inference engine whose rules employ spatial operators for classification of local topologies within the free space graph. This knowledge-based technique is used to generate plans which describe admissible sequences of movement between selected start and goal configurations.
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.
NASA Astrophysics Data System (ADS)
Wang, Lunche; Kisi, Ozgur; Zounemat-Kermani, Mohammad; Li, Hui
2017-01-01
Pan evaporation (Ep) plays important roles in agricultural water resources management. One of the basic challenges is modeling Ep using limited climatic parameters because there are a number of factors affecting the evaporation rate. This study investigated the abilities of six different soft computing methods, multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at various sites crossing a wide range of climates during 1961-2000 are used for model development and validation. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations using local input combinations (for example, the MAE (mean absolute errors), RMSE (root mean square errors), and determination coefficient (R2) are 0.314 mm/day, 0.405 mm/day and 0.988, respectively for HEB station), while GRNN model performed better in Tibetan Plateau (MAE, RMSE and R2 are 0.459 mm/day, 0.592 mm/day and 0.932, respectively). The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ (Beijing), CQ (Chongqing) and HK (Haikou) stations. Therefore, it can be concluded that Ep could be successfully predicted using above models in hydrological modeling studies.
A Heuristic Method of Optimal Generalized Hypercube Encoding for Pictorial Databases.
1980-01-15
the GHm codes are: (X1 ,.. *, • ..- 1 ; am., an; bm ... , bn), where (x-,. x1 , ,z ,.. ., z ) is in S for some coordinates, z, z ; and a =mm {y,: for...PROBLEM 1 Given m, the method of choosing m-1 handles which will generate optimal GHm codes for a point set S is based on the following ideas: * For each...generate GHm encoded tuples, and their number was counted for a different number of point set and dimensions of space. To find the optimal GHm encoding
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.
NASA Astrophysics Data System (ADS)
Blais-Stevens, A.; Behnia, P.
2015-05-01
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 (derived from a 5 m × 5 m DEM), surficial geology, permafrost distribution, 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.
NASA Astrophysics Data System (ADS)
Edalati, Sh; Houshangi far, A.; Torabi, N.; Baneshi, Z.; Behjat, A.
2017-02-01
Poly(3,4-ethylendioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) was deposited on a fluoride-doped tin oxide glass substrate using a heuristic method to fabricate platinum-free counter electrodes for dye-sensitized solar cells (DSSCs). In this heuristic method a thin layer of PEDOT:PPS is obtained by spin coating the PEDOT:PSS on a Cu substrate and then removing the substrate with FeCl3. The characteristics of the deposited PEDOT:PSS were studied by energy dispersive x-ray analysis and scanning electron microscopy, which revealed the micro-electronic specifications of the cathode. The aforementioned DSSCs exhibited a solar conversion efficiency of 3.90%, which is far higher than that of DSSCs with pure PEDOT:PSS (1.89%). This enhancement is attributed not only to the micro-electronic specifications but also to the HNO3 treatment through our heuristic method. The results of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and Tafel polarization plots show the modified cathode has a dual function, including excellent conductivity and electrocatalytic activity for iodine reduction.
NASA Astrophysics Data System (ADS)
Salcedo-Sanz, S.
2016-10-01
Meta-heuristic algorithms are problem-solving methods which try to find good-enough solutions to very hard optimization problems, at a reasonable computation time, where classical approaches fail, or cannot even been applied. Many existing meta-heuristics approaches are nature-inspired techniques, which work by simulating or modeling different natural processes in a computer. Historically, many of the most successful meta-heuristic approaches have had a biological inspiration, such as evolutionary computation or swarm intelligence paradigms, but in the last few years new approaches based on nonlinear physics processes modeling have been proposed and applied with success. Non-linear physics processes, modeled as optimization algorithms, are able to produce completely new search procedures, with extremely effective exploration capabilities in many cases, which are able to outperform existing optimization approaches. In this paper we review the most important optimization algorithms based on nonlinear physics, how they have been constructed from specific modeling of a real phenomena, and also their novelty in terms of comparison with alternative existing algorithms for optimization. We first review important concepts on optimization problems, search spaces and problems' difficulty. Then, the usefulness of heuristics and meta-heuristics approaches to face hard optimization problems is introduced, and some of the main existing classical versions of these algorithms are reviewed. The mathematical framework of different nonlinear physics processes is then introduced as a preparatory step to review in detail the most important meta-heuristics based on them. A discussion on the novelty of these approaches, their main computational implementation and design issues, and the evaluation of a novel meta-heuristic based on Strange Attractors mutation will be carried out to complete the review of these techniques. We also describe some of the most important application areas, in
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.
Heuristics of Twelfth Graders Building Isomorphisms
ERIC Educational Resources Information Center
Powell, Arthur B.; Maher, Carolyn A.
2003-01-01
This report analyzes the discursive interactions of four students to understand what heuristic methods they develop as well as how and why they build isomorphisms to resolve a combinatorial problem set in a non-Euclidian context. The findings suggest that results of their heuristic actions lead them to build isomorphisms that in turn allow them to…
Yen, Po-Yin; Bakken, Suzanne
2009-01-01
We evaluated a web-based communication tool for nurse scheduling using two common usability evaluation methods, heuristic evaluation and end-user think aloud protocol. We found that heuristic evaluation performed by human-computer interaction (HCI) experts revealed more general interface design problems, while end-users’ think-aloud protocols identified more obstacles to task performance. To provide the most effective and thorough evaluation results, a combination of heuristic evaluation and end-user think-aloud protocol is recommended. PMID:20351946
Comparison tomography relocation hypocenter grid search and guided grid search method in Java island
NASA Astrophysics Data System (ADS)
Nurdian, S. W.; Adu, N.; Palupi, I. R.; Raharjo, W.
2016-11-01
The main data in this research is earthquake data recorded from 1952 to 2012 with 9162 P wave and 2426 events are recorded by 30 stations located around Java island. Relocation hypocenter processed using grid search and guidded grid search method. Then the result of relocation hypocenter become input for tomography pseudo bending inversion process. It can be used to identification the velocity distribution in subsurface. The result of relocation hypocenter by grid search and guided grid search method after tomography process shown in locally and globally. In locally area grid search method result is better than guided grid search according to geological reseach area. But in globally area the result of guided grid search method is better for a broad area because the velocity variation is more diverse than the other one and in accordance with local geological research conditions.
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.
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.
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.
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.
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…
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 &…
Heuristics for Online Information Retrieval: A Typology and Preliminary Listing.
ERIC Educational Resources Information Center
Harter, Stephen P.; Peters, Anne Rogers
1985-01-01
Presents typology of online search heuristics consisting of six main classes: philosophical attitudes and overall approach; language of problem description; record and file structure; concept formulation and reformulation; recall and precision; and cost efficiency. Heuristics in each of the six classes are listed and selected examples are briefly…
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.
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.
Efficient protein structure search using indexing methods.
Kim, Sungchul; Sael, Lee; Yu, Hwanjo
2013-01-01
Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.
NASA Astrophysics Data System (ADS)
Yoshizawa, Akira; Nisizima, Shoiti; Shimomura, Yutaka; Kobayashi, Hiromichi; Matsuo, Yuichi; Abe, Hiroyuki; Fujiwara, Hitoshi
2006-03-01
A new methodology for the Reynolds-averaged Navier-Stokes modeling is presented on the basis of the amalgamation of heuristic-modeling and turbulence-theory methods. A characteristic turbulence time scale is synthesized in a heuristic manner through the combination of several characteristic time scales. An algebraic model of turbulent-viscosity type for the Reynolds stress is derived from the Reynolds-stress transport equation with the time scale embedded. It is applied to the state of weak spatial and temporal nonequilibrium, and is compared with its theoretical counterpart derived by the two-scale direct-interaction approximation. The synthesized time scale is justified through the agreement of the two expressions derived by these entirely different methods. The derived model is tested in rotating isotropic, channel, and homogeneous-shear flows. It is extended to a nonlinear algebraic model and a supersonic model. The latter is shown to succeed in reproducing the reduction in the growth rate of a free-shear layer flow, without causing wrong effects on wall-bounded flows such as channel and boundary-layer flows.
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…
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.
2006-08-01
theater distribution problem and find excellent solutions. This research utilizes advanced tabu search techniques, including reactive tabu search and...5.4.2 Within Cycle Swap (WCS) Move Neighborhood.............................. 102 5.4.3 Complete Route Insert ( CRI ) Move Neighborhood...Fractional Factorial Design........................................... 128 6.3 An Excel – VBA based LPDPTW Problem Generator
Job Search Methods: Consequences for Gender-based Earnings Inequality.
ERIC Educational Resources Information Center
Huffman, Matt L.; Torres, Lisa
2001-01-01
Data from adults in Atlanta, Boston, and Los Angeles (n=1,942) who searched for work using formal (ads, agencies) or informal (networks) methods indicated that type of method used did not contribute to the gender gap in earnings. Results do not support formal job search as a way to reduce gender inequality. (Contains 55 references.) (SK)
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…
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.
Real-time earthquake monitoring using a search engine method.
Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong
2014-12-04
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
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
Hyper-heuristics with low level parameter adaptation.
Ren, Zhilei; Jiang, He; Xuan, Jifeng; Luo, Zhongxuan
2012-01-01
Recent years have witnessed the great success of hyper-heuristics applying to numerous real-world applications. Hyper-heuristics raise the generality of search methodologies by manipulating a set of low level heuristics (LLHs) to solve problems, and aim to automate the algorithm design process. However, those LLHs are usually parameterized, which may contradict the domain independent motivation of hyper-heuristics. In this paper, we show how to automatically maintain low level parameters (LLPs) using a hyper-heuristic with LLP adaptation (AD-HH), and exemplify the feasibility of AD-HH by adaptively maintaining the LLPs for two hyper-heuristic models. Furthermore, aiming at tackling the search space expansion due to the LLP adaptation, we apply a heuristic space reduction (SAR) mechanism to improve the AD-HH framework. The integration of the LLP adaptation and the SAR mechanism is able to explore the heuristic space more effectively and efficiently. To evaluate the performance of the proposed algorithms, we choose the p-median problem as a case study. The empirical results show that with the adaptation of the LLPs and the SAR mechanism, the proposed algorithms are able to achieve competitive results over the three heterogeneous classes of benchmark instances.
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…
NASA Astrophysics Data System (ADS)
Nishi, Tatsushi; Yamamoto, Shinichiro; Konishi, Masami
The storage allocation planning problem in warehouse management is to determine the allocation of products to the storage space and intermediate operations for retrieving products so as to minimize the number of operations, and maximize the collected number of products for each customer when the sequence of requests for inlet and retrieval operations are given. In this paper, we propose an efficient beam search method for generating a near optimal solution with a reasonable computation time. A heuristic procedure is also proposed in order to reduce a search space in the beam search method by using the information of subsequent inlet and retrieving requests. The validity of the proposed method is confirmed by comparing the results with the optimal solution derived by solving an MILP problem. The effectiveness of the proposed method is demonstrated by solving an actual large-sized problem consisting of more than 3000 operations.
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.
Training and search methods for speech recognition.
Jelinek, F
1995-01-01
Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance. PMID:7479810
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.
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.
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.
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.
Accelerated Profile HMM Searches.
Eddy, Sean R
2011-10-01
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.
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.
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.
Behavior of heuristics on large and hard satisfiability problems
NASA Astrophysics Data System (ADS)
Ardelius, John; Aurell, Erik
2006-09-01
We study the behavior of a heuristic for solving random satisfiability problems by stochastic local search near the satisfiability threshold. The heuristic for average satisfiability (ASAT), is similar to the Focused Metropolis Search heuristic, and shares the property of being focused, i.e., only variables in unsatisfied clauses are updated in each step. It is significantly simpler than the benchmark WALKSAT heuristic. We show that ASAT solves instances as large as N=106 in linear time, on average, up to a ratio of 4.21 clauses per variable in random three-satisfiability. For K higher than 3, ASAT appears to solve instances of K -satisfiability up to the Montanari-Ricci-Tersenghi-Parisi full replica symmetry breaking (FSRB) threshold denoted αs(K) in linear time.
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.
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.
Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice
Riva, Silvia; Monti, Marco; Antonietti, Alessandro
2011-01-01
Introduction Over-the-counter (OTC) drugs are widely available and often purchased by consumers without advice from a health care provider. Many people rely on self-management of medications to treat common medical conditions. Although OTC medications are regulated by the National and the International Health and Drug Administration, many people are unaware of proper dosing, side effects, adverse drug reactions, and possible medication interactions. Purpose This study examined how subjects make their decisions to select an OTC drug, evaluating the role of cognitive heuristics which are simple and adaptive rules that help the decision-making process of people in everyday contexts. Subjects and methods By analyzing 70 subjects’ information-search and decision-making behavior when selecting OTC drugs, we examined the heuristics they applied in order to assess whether simple decision-making processes were also accurate and relevant. Subjects were tested with a sequence of two experimental tests based on a computerized Java system devised to analyze participants’ choices in a virtual environment. Results We found that subjects’ information-search behavior reflected the use of fast and frugal heuristics. In addition, although the heuristics which correctly predicted subjects’ decisions implied significantly fewer cues on average than the subjects did in the information-search task, they were accurate in describing order of information search. A simple combination of a fast and frugal tree and a tallying rule predicted more than 78% of subjects’ decisions. Conclusion The current emphasis in health care is to shift some responsibility onto the consumer through expansion of self medication. To know which cognitive mechanisms are behind the choice of OTC drugs is becoming a relevant purpose of current medical education. These findings have implications both for the validity of simple heuristics describing information searches in the field of OTC drug choices and
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.
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.
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.
Search area Expanding Strategy and Dynamic Priority Setting Method in the Improved 2-opt Method
NASA Astrophysics Data System (ADS)
Matayoshi, Mitsukuni; Nakamura, Morikazu; Miyagi, Hayao
We propose a new 2-opt base method in a Memetic algorithm, that is, Genetic Algorithms(GAs) with a local search. The basic idea is from the fast 2-opt(1) method and the improved 2-opt method(20). Our new search method uses the “Priority" employed in the improved 2-opt method. The “Priority" represents the contribution level in exchange of genes. Matayoshi's method exchanges genes based on previous contribution to the fitness value improvement. We propose a new search method by using the concept of the Priority. We call our method the search area expanding strategy method in the improved 2-opt method. Our method escalates the search area by using “Priority". In computer experiment, it is shown that the computation time to find exact solution depends on the value of the Priority. If our method does not set an appropriate priority beforehand, then we propose the method to adapt to suitable value. If improvement does not achieved for certain generations, our dynamic priority method tries to modify the priority by the mutation operation. Experimental results show that the search area expanding strategy method embedded with the dynamic priority setting method can find the exact solution at earlier generation than other methods for comparison.
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.
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.
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.
Reliable Transition State Searches Integrated with the Growing String Method.
Zimmerman, Paul
2013-07-09
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.
Using Pattern Search Methods for Surface Structure Determinationof Nanomaterials
Zhao, Zhengji; Meza, Juan; Van Hove, Michel
2006-06-09
Atomic scale surface structure plays an important roleindescribing many properties of materials, especially in the case ofnanomaterials. One of the most effective techniques for surface structuredetermination is low-energy electron diffraction (LEED), which can beused in conjunction with optimization to fit simulated LEED intensitiesto experimental data. This optimization problem has a number ofcharacteristics that make it challenging: it has many local minima, theoptimization variables can be either continuous or categorical, theobjective function can be discontinuous, there are no exact analyticderivatives (and no derivatives at all for categorical variables), andfunction evaluations are expensive. In this study, we show how to apply aparticular class of optimization methods known as pattern search methodsto address these challenges. These methods donot explicitly usederivatives, and are particularly appropriate when categorical variablesare present, an important feature that has not been addressed in previousLEED studies. We have found that pattern search methods can produceexcellent results, compared to previously used methods, both in terms ofperformance and locating optimal results.
A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems
NASA Astrophysics Data System (ADS)
Abtahi, Amir-Reza; Bijari, Afsane
2017-09-01
In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems.
A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems
NASA Astrophysics Data System (ADS)
Abtahi, Amir-Reza; Bijari, Afsane
2016-09-01
In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems.
Reexamining our bias against heuristics.
McLaughlin, Kevin; Eva, Kevin W; Norman, Geoff R
2014-08-01
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 of bias in the literature implicating the use of heuristics in diagnostic error and highlight the fact that there are also data suggesting that under certain circumstances using heuristics may lead to better decisions that formal analysis. They suggest that diagnostic error is frequently misattributed to the use of heuristics and propose an alternative view whereby content knowledge is the root cause of diagnostic performance and heuristics lie on the causal pathway between knowledge and diagnostic error or success.
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.
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 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…
Exploration of Stellarator Configuration Space with Global Search Methods
H.E. Mynick; N. Pomphrey; S. Ethier
2001-09-10
An exploration of stellarator configuration space z for quasi-axisymmetric stellarator (QAS) designs is discussed, using methods which provide a more global view of that space. To this end, we have implemented a ''differential evolution'' (DE) search algorithm in an existing stellarator optimizer, which is much less prone to become trapped in local, suboptimal minima of the cost function chi than the local search methods used previously. This search algorithm is complemented by mapping studies of chi over z aimed at gaining insight into the results of the automated searches. We find that a wide range of the attractive QAS configurations previously found fall into a small number of classes, with each class corresponding to a basin of chi(z). We develop maps on which these earlier stellarators can be placed, the relations among them seen, and understanding gained into the physics differences between them. It is also found that, while still large, the region of z space containing practically realizable QAS configurations is much smaller than earlier supposed.
Kheiri, Ahmed; Keedwell, Ed
2016-06-03
Operations research is a well established field that uses computational systems to support decisions in business and public life. Good solutions to operations research problems can make a large difference to the efficient running of businesses and organisations and so the field often searches for new methods to improve these solutions. The high school timetabling problem is an example of an operations research problem and is a challenging task which requires assigning events and resources to time slots subject to a set of constraints. In this paper a new sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling problems. In this study, we present an easy-to-implement, easy-to-maintain and effective sequence-based selection hyper-heuristic to solve high school timetabling problems using a benchmark of unified real-world instances collected from different countries. We show that with sequence-based methods, it is possible to discover new best known solutions for a number of the problems in the timetabling domain. Through this investigation, the usefulness of sequence-based selection hyper-heuristics has been demonstrated and the capability of these methods has been shown to exceed the state-of-the-art.
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.
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.
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…
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.
Conformational analysis of macrocycles: finding what common search methods miss.
Bonnet, Pascal; Agrafiotis, Dimitris K; Zhu, Fangqiang; Martin, Eric
2009-10-01
As computational drug design becomes increasingly reliant on virtual screening and on high-throughput 3D modeling, the need for fast, robust, and reliable methods for sampling molecular conformations has become greater than ever. Furthermore, chemical novelty is at a premium, forcing medicinal chemists to explore more complex structural motifs and unusual topologies. This necessitates the use of conformational sampling techniques that work well in all cases. Here, we compare the performance of several popular conformational search algorithms on three broad classes of macrocyclic molecules. These methods include Catalyst, CAESAR, MacroModel, MOE, Omega, Rubicon and two newer self-organizing algorithms known as stochastic proximity embedding (SPE) and self-organizing superimposition (SOS) that have been developed at Johnson & Johnson. Our results show a compelling advantage for the three distance geometry methods (SOS, SPE, and Rubicon) followed to a lesser extent by MacroModel. The remaining techniques, particularly those based on systematic search, often failed to identify any of the lowest energy conformations and are unsuitable for this class of structures. Taken together with our previous study on drug-like molecules (Agrafiotis, D. K.; Gibbs, A.; Zhu, F.; Izrailev, S.; Martin, E. Conformational Sampling of Bioactive Molecules: A Comparative Study. J. Chem. Inf. Model., 2007, 47, 1067-1086), these results suggest that SPE and SOS are two of the most robust and universally applicable conformational search methods, with the latter being preferred because of its superior speed.
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
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.
System and Method for Tracking Vehicles Using Random Search Algorithms.
1997-01-31
patent application is available for licensing. Requests for information should be addressed to: OFFICE OF NAVAL RESEARCH DEPARTMENT OF THE NAVY...relates to a system and a method for 22 tracking vehicles using random search algorithm methodolgies . 23 (2) Description of the Prior Art 24 Contact...algorithm methodologies for finding peaks in non-linear 14 functions. U.S. Patent No. 5,148,513 to Koza et al., for 15 example, relates to a non-linear
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…
The Gaussian CLs method for searches of new physics
Qian, X.; Tan, A.; Ling, J. J.; ...
2016-04-23
Here 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 requiredmore » conditions. These conditions are milder than that required by the 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.« less
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…
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.
A Geographical Heuristic Routing Protocol for VANETs
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-01-01
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254
A Geographical Heuristic Routing Protocol for VANETs.
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-09-23
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation).
Heuristics in Composition and Literary Criticism.
ERIC Educational Resources Information Center
McCarthy, B. Eugene
1978-01-01
Describes the "particle, wave, field" heuristic for gathering information, and shows how students can apply that heuristic in analyzing literature and in using procedures of historical criticism. (RL)
How the twain can meet: Prospect theory and models of heuristics in risky choice.
Pachur, Thorsten; Suter, Renata S; Hertwig, Ralph
2017-03-01
Two influential approaches to modeling choice between risky options are algebraic models (which focus on predicting the overt decisions) and models of heuristics (which are also concerned with capturing the underlying cognitive process). Because they rest on fundamentally different assumptions and algorithms, the two approaches are usually treated as antithetical, or even incommensurable. Drawing on cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as the currently most influential instance of a descriptive algebraic model, we demonstrate how the two modeling traditions can be linked. CPT's algebraic functions characterize choices in terms of psychophysical (diminishing sensitivity to probabilities and outcomes) as well as psychological (risk aversion and loss aversion) constructs. Models of heuristics characterize choices as rooted in simple information-processing principles such as lexicographic and limited search. In computer simulations, we estimated CPT's parameters for choices produced by various heuristics. The resulting CPT parameter profiles portray each of the choice-generating heuristics in psychologically meaningful ways-capturing, for instance, differences in how the heuristics process probability information. Furthermore, CPT parameters can reflect a key property of many heuristics, lexicographic search, and track the environment-dependent behavior of heuristics. Finally, we show, both in an empirical and a model recovery study, how CPT parameter profiles can be used to detect the operation of heuristics. We also address the limits of CPT's ability to capture choices produced by heuristics. Our results highlight an untapped potential of CPT as a measurement tool to characterize the information processing underlying risky choice.
A systematic method for search term selection in systematic reviews.
Thompson, Jenna; Davis, Jacqueline; Mazerolle, Lorraine
2014-06-01
The wide variety of readily available electronic media grants anyone the freedom to retrieve published references from almost any area of research around the world. Despite this privilege, keeping up with primary research evidence is almost impossible because of the increase in professional publishing across disciplines. Systematic reviews are a solution to this problem as they aim to synthesize all current information on a particular topic and present a balanced and unbiased summary of the findings. They are fast becoming an important method of research across a number of fields, yet only a small number of guidelines exist on how to define and select terms for a systematic search. This article presents a replicable method for selecting terms in a systematic search using the semantic concept recognition software called leximancer (Leximancer, University of Queensland, Brisbane, Australia). We use this software to construct a set of terms from a corpus of literature pertaining to transborder interventions for drug control and discuss the applicability of this method to systematic reviews in general. This method aims to contribute a more 'systematic' approach for selecting terms in a manner that is entirely replicable for any user.
Search a methane hydrate in the Arctic with photonics methods
NASA Astrophysics Data System (ADS)
Grishkanich, Alexsandr S.; Polyakov, Vadim; Sidorov, Igor; Kascheev, Sergey; Elizarov, Valentin; Zhevlakov, Aleksandr; Mak, Andrey
2016-04-01
Identifying methane anomalies responsible for the temperature increase, by hiking trails in the Arctic requires great human labor. It is necessary to use lidar methods for search and identification of methane from permafrost. Necessary to create a Raman lidar for monitoring of emissions of methane hydrate from the permafrost. Hyperspectral resolution would resolve the isotope shifts in the Stokes spectra, thereby to determine the isotopic composition of methane ratio C14/C12 CH4 carbon emissions and identify the source for study (permafrost or oil deposits)
Improving Nearest Neighbour Search in 3d Spatial Access Method
NASA Astrophysics Data System (ADS)
Suhaibaha, A.; Rahman, A. A.; Uznir, U.; Anton, F.; Mioc, D.
2016-10-01
Nearest Neighbour (NN) is one of the important queries and analyses for spatial application. In normal practice, spatial access method structure is used during the Nearest Neighbour query execution to retrieve information from the database. However, most of the spatial access method structures are still facing with unresolved issues such as overlapping among nodes and repetitive data entry. This situation will perform an excessive Input/Output (IO) operation which is inefficient for data retrieval. The situation will become more crucial while dealing with 3D data. The size of 3D data is usually large due to its detail geometry and other attached information. In this research, a clustered 3D hierarchical structure is introduced as a 3D spatial access method structure. The structure is expected to improve the retrieval of Nearest Neighbour information for 3D objects. Several tests are performed in answering Single Nearest Neighbour search and k Nearest Neighbour (kNN) search. The tests indicate that clustered hierarchical structure is efficient in handling Nearest Neighbour query compared to its competitor. From the results, clustered hierarchical structure reduced the repetitive data entry and the accessed page. The proposed structure also produced minimal Input/Output operation. The query response time is also outperformed compared to the other competitor. For future outlook of this research several possible applications are discussed and summarized.
NASA Astrophysics Data System (ADS)
Gutenko, Ievgeniia; Peng, Hao; Gu, Xianfeng; Barish, Mathew; Kaufman, Arie
2016-03-01
Accurate estimation of splenic volume is crucial for the determination of disease progression and response to treatment for diseases that result in enlargement of the spleen. However, there is no consensus with respect to the use of single or multiple one-dimensional, or volumetric measurement. Existing methods for human reviewers focus on measurement of cross diameters on a representative axial slice and craniocaudal length of the organ. We propose two heuristics for the selection of the optimal axial plane for splenic volume estimation: the maximal area axial measurement heuristic and the novel conformal welding shape-based heuristic. We evaluate these heuristics on time-variant data derived from both healthy and sick subjects and contrast them to established heuristics. Under certain conditions our heuristics are superior to standard practice volumetric estimation methods. We conclude by providing guidance on selecting the optimal heuristic for splenic volume estimation.
Heuristic scenario builder for power system operator training
Irisarri, G.; Rafian, M. ); Miller, B.N. ); Dobrowolski, E.J. )
1992-05-01
The Heuristic Scenario Builder (HSB), a knowledge-based training scenario builder for the EPRI Operator Training Simulator (OTS), is described in this paper. Expert systems and heuristic searches are used in the HSB to find training scenarios that closely fit trainee profiles and that address particular training requirements. Expert knowledge obtained from instructors and other operations personnel is used throughout the HSB to determine the scenarios. The HSB is an integral part of the OTS and is currently in operation at Philadelphia Electric's OTS installation.
Burke, Meghan Catherine; Mirokhin, Yuri A; Tchekhovskoi, Dmitrii V; Markey, Sanford P; Heidbrink Thompson, Jenny L; Larkin, Christopher; Stein, Stephen E
2017-04-03
We present a mass spectral library based method to identify tandem mass spectra of peptides that contain unanticipated modifications and amino acid variants. We describe this as a 'hybrid' method because it combines matching both ion m/z and mass losses. The losses are differences in mass between an ion peak and its precursor mass. This difference, termed DeltaMass, is used to shift the product ions in the library spectrum that contain the modification, thereby allowing library product ions that contain the unexpected modification to match the query spectrum. Clustered unidentified spectra from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Chinese hamster ovary cells were used to evaluate this method. Results demonstrate the ability of the hybrid method to identify unanticipated modifications, insertions and deletions, which may include those due to an incomplete protein sequence database or to search settings that exclude the correct identification, in high resolution tandem mass spectra without regard of their precursor mass. This has been made possible by indexing of m/z values of each fragment ion and their difference in mass from their precursor ion.
The use of JOIS through the CAPTAIN : Provision of simple searching methods
NASA Astrophysics Data System (ADS)
Takano, Katsuhiro
JICST has started the services of two systems which enable to use JOIS through CAPTAIN in cooperation with A.M.S. Co. Ltd. and Kokusai Sogo Database K.K. They provide three types of searching methods which incorporate features of CAPTAIN. The first one is theme searching. You are allowed to search theme only by selecting subject area number of science and technology or theme numbers that have been registered on the CAPTAIN screen. The second one is instructed searching. You are allowed to search only by particular numbers or search terms according to the searching instructions appeared on the screen. The last one in direct searching. You are allowed to search by directly entering commands which correspond to JOIS commands. This paper outlines the systems which connect JOIS to CAPTAIN centering on these searching methods.
Heuristics for Job-Shop Scheduling
1988-01-01
None 11. KEY WORDS (Continue on fewer&* Slde II neceseome aid idontify by Wock numberh) scheduling job-shop heuristic geometric 20. ABSTRACT (C nRtnue...partial fulfillment of the requirements for the degree of Doctor of Science in Mechanical Engineering. Abstract Two methods of obtaining approximate... Representation 27 2.1 Cartesian Completion Space. .. .. .. .. .I.. ... ... ... ... 27 2.2 Capabilities and Limitations of the Representation
Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.
Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán
2014-03-11
While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.
Lin, Chia-Ching; Tsai, Chin-Chung
2007-10-01
To acquire a better understanding of the online search strategies that students employ to use the Internet, this study investigated six university students' approaches to Web-based information searches. A new method, called navigation flow map (NFM), is presented that graphically displays the fluid and multilayered relationships between Web navigation and information retrieval that students use while navigating the Web. To document the application of NFM, the Web search strategies of six university students were analyzed as they used the Internet to perform two different tasks: scientific-based and social studies-based information searches. Through protocol analyses using the NFM method, the students' searching strategies were categorized into two types: Match or Exploration. The findings revealed that participants with an Exploration approach had more complicated and richer task-specific ways of searching information than those with a Match approach; and further, through between-task comparisons, we found that participants appeared to use different searching strategies to process natural science information compared to social studies information. Finally, the participants in the Exploration group also exhibited better task performance on the criterion measures than those in the Match group.
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.
When decision heuristics and science collide.
Yu, Erica C; Sprenger, Amber M; Thomas, Rick P; Dougherty, Michael R
2014-04-01
The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.
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.
Fluency heuristic: a model of how the mind exploits a by-product of information retrieval.
Hertwig, Ralph; Herzog, Stefan M; Schooler, Lael J; Reimer, Torsten
2008-09-01
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 most of an automatic by-product of retrieval from memory, namely, retrieval fluency. In 4 experiments, the authors show that retrieval fluency can be a proxy for real-world quantities, that people can discriminate between two objects' retrieval fluencies, and that people's inferences are in line with the fluency heuristic (in particular fast inferences) and with experimentally manipulated fluency. The authors conclude that the fluency heuristic may be one tool in the mind's repertoire of strategies that artfully probes memory for encapsulated frequency information that can veridically reflect statistical regularities in the world.
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)
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
Variable neighborhood search for reverse engineering of gene regulatory networks.
Nicholson, Charles; Goodwin, Leslie; Clark, Corey
2017-01-01
A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time.
Phylogenomic Methods to Guide Paleontological Searches for the Early Cyanobacteria
NASA Astrophysics Data System (ADS)
Blank, C. E.
2004-12-01
Phylogenomic methods can help paleontologists target their searches for early microbial microfossils and potentially help them better interpret the early fossil record. In this study, the deep-branching relationships in the cyanobacteria were resolved using whole genome sequences, multiple genes for taxa lacking genomes, and intein presence/absence in the DnaE protein. Once a framework tree was produced, characters were mapped onto the tree. Characters included morphology (unicellular vs. filamentous), habitat (marine vs. freshwater), metabolism (use of sulfide as electron donor, nitrogen fixation), presence/absence of complex morphological traits (akinetes, heterocysts, hormogonia), salt tolerance, and thermal tolerance. It was found that the earliest cyanobacteria were unicellular coccoids, with cell diameters < 2 microns, that lived in freshwater environments. This suggests that paleontologists should focus their searches for the earliest cyanobacteria to freshwater deposits (lakes, streams) and to small diameter coccoids (not mats, not filaments). The earliest "cyanobacterial" microfossils (Eosynechococcus and Eoentophysalis) are large-diameter coccoids found in shallow marine platform carbonates. Because these cells have large diameters, if they were cyanobacteria one would also expect to see their sister taxa in the fossil record (i.e., large-diameter filamentous forms with sheaths, also akinetes). Because these are not found until 2.0 Ga (and akinetes until 1.5 Ga), this suggests that these earliest microfossils are not cyanobacteria. There are several instances in the cyanobacterial tree where ancestors with low salt tolerance gave rise to lineages that grow in brackish, marine, and/or hypersaline environments. This suggests that either the cyanobacteria first originated on continents and later colonized more saline environments, or that the cyanobacteria first originated in shallow "seas" that were not very saline but gradually became more saline by about
Heuristic reconstructions of neutron penumbral images
Nozaki, Shinya; Chen Yenwei
2004-10-01
Penumbral imaging is a technique of coded aperture imaging proposed for imaging of highly penetrating radiations. To date, the penumbral imaging technique has been successfully applied to neutron imaging in laser fusion experiments. Since the reconstruction of penumbral images is based on linear deconvolution methods, such as inverse filter and Wiener filer, the point spread function of apertures should be space invariant; it is also sensitive to the noise contained in penumbral images. In this article, we propose a new heuristic reconstruction method for neutron penumbral imaging, which can be used for a space-variant imaging system and is also very tolerant to the noise.
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.
How Forgetting Aids Heuristic Inference
ERIC Educational Resources Information Center
Schooler, Lael J.; Hertwig, Ralph
2005-01-01
Some theorists, ranging from W. James (1890) to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2…
Conflict and Bias in Heuristic Judgment
ERIC Educational Resources Information Center
Bhatia, Sudeep
2017-01-01
Conflict has been hypothesized to play a key role in recruiting deliberative processing in reasoning and judgment tasks. This claim suggests that changing the task so as to add incorrect heuristic responses that conflict with existing heuristic responses can make individuals less likely to respond heuristically and can increase response accuracy.…
Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space
Kalathil, Shaeen; Elias, Elizabeth
2014-01-01
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
A new conjugate gradient method and its global convergence under the exact line search
NASA Astrophysics Data System (ADS)
Omer, Osman; Rivaie, Mohd; Mamat, Mustafa; Abdalla, Awad
2014-12-01
The conjugate gradient methods are numerously used for solving nonlinear unconstrained optimization problems, especially of large scale. Their wide applications are due to their simplicity and low memory requirement. To analyze conjugate gradient methods, two types of line searches are used; exact and inexact. In this paper, we present a new method of nonlinear conjugate gradient methods under the exact line search. The theoretical analysis shows that the new method generates a descent direction in each iteration and globally convergent under the exact line search. Moreover, numerical experiments based on comparing the new method with other well known conjugate gradient methods show that the new is efficient for some unconstrained optimization problems.
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.
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.
Familiarity and Recollection in Heuristic Decision Making
Schwikert, Shane R.; Curran, Tim
2014-01-01
Heuristics involve the ability to utilize memory to make quick judgments by exploiting fundamental cognitive abilities. In the current study we investigated the memory processes that contribute to the recognition heuristic and the fluency heuristic, which are both presumed to capitalize on the by-products of memory to make quick decisions. In Experiment 1, we used a city-size comparison task while recording event-related potentials (ERPs) to investigate the potential contributions of familiarity and recollection to the two heuristics. ERPs were markedly different for recognition heuristic-based decisions and fluency heuristic-based decisions, suggesting a role for familiarity in the recognition heuristic and recollection in the fluency heuristic. In Experiment 2, we coupled the same city-size comparison task with measures of subjective pre-experimental memory for each stimulus in the task. Although previous literature suggests the fluency heuristic relies on recognition speed alone, our results suggest differential contributions of recognition speed and recollected knowledge to these decisions, whereas the recognition heuristic relies on familiarity. Based on these results, we created a new theoretical frame work that explains decisions attributed to both heuristics based on the underlying memory associated with the choice options. PMID:25347534
Familiarity and recollection in heuristic decision making.
Schwikert, Shane R; Curran, Tim
2014-12-01
Heuristics involve the ability to utilize memory to make quick judgments by exploiting fundamental cognitive abilities. In the current study we investigated the memory processes that contribute to the recognition heuristic and the fluency heuristic, which are both presumed to capitalize on the byproducts of memory to make quick decisions. In Experiment 1, we used a city-size comparison task while recording event-related potentials (ERPs) to investigate the potential contributions of familiarity and recollection to the 2 heuristics. ERPs were markedly different for recognition heuristic-based decisions and fluency heuristic-based decisions, suggesting a role for familiarity in the recognition heuristic and recollection in the fluency heuristic. In Experiment 2, we coupled the same city-size comparison task with measures of subjective preexperimental memory for each stimulus in the task. Although previous literature suggests the fluency heuristic relies on recognition speed alone, our results suggest differential contributions of recognition speed and recollected knowledge to these decisions, whereas the recognition heuristic relies on familiarity. Based on these results, we created a new theoretical framework that explains decisions attributed to both heuristics based on the underlying memory associated with the choice options.
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.
Web of science: a unique method of cited reference searching.
Sevinc, Alper
2004-07-01
The number of times an article is acknowledged as a reference in another article reflects its scientific impact. Citation analysis is one of the parameters for assessing the quality of research published in scientific, technology and social science journals. Web of Science enables users to search current and retrospective multidisciplinary information. Parameters and practical applications evaluating journal and article citation characteristics available through the Science Citation Index are summarized.
Web of science: a unique method of cited reference searching.
Sevinc, Alper
2004-01-01
The number of times an article is acknowledged as a reference in another article reflects its scientific impact. Citation analysis is one of the parameters for assessing the quality of research published in scientific, technology and social science journals. Web of Science enables users to search current and retrospective multidisciplinary information. Parameters and practical applications evaluating journal and article citation characteristics available through the Science Citation Index are summarized. Images Figure 1 Figure 2 PMID:15253331
A Pattern Search Filter Method for Nonlinear Programming Without Derivatives
2003-06-12
this context. Optimality conditions for a differentiable function can be stated in terms of the cone generated by the convex hull of a set S, i.e...Corollary 5.10. It gives conditions for the limit point of a refining sequence to satisfy optimality conditions on problem (1.1). It is that the convex ...useful division into global SEARCH and local POLL steps. It is shown here that the algorithm identifies limit points at which optimality conditions
A Relatively Painless Method of Introduction to the Psychological Literature Search
ERIC Educational Resources Information Center
Gardner, Louis E.
1977-01-01
Described is an innovative teaching method for developing student psychological literature search skills. The method involves empirical analysis of cliches and writing abstracts of psychological studies used in support or rejection of cliche hypotheses. (Author/DB)
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…
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.
Social biases determine spatiotemporal sparseness of ciliate mating heuristics
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
A bicriteria heuristic for an elective surgery scheduling problem.
Marques, Inês; Captivo, M Eugénia; Vaz Pato, Margarida
2015-09-01
Resource rationalization and reduction of waiting lists for surgery are two main guidelines for hospital units outlined in the Portuguese National Health Plan. This work is dedicated to an elective surgery scheduling problem arising in a Lisbon public hospital. In order to increase the surgical suite's efficiency and to reduce the waiting lists for surgery, two objectives are considered: maximize surgical suite occupation and maximize the number of surgeries scheduled. This elective surgery scheduling problem consists of assigning an intervention date, an operating room and a starting time for elective surgeries selected from the hospital waiting list. Accordingly, a bicriteria surgery scheduling problem arising in the hospital under study is presented. To search for efficient solutions of the bicriteria optimization problem, the minimization of a weighted Chebyshev distance to a reference point is used. A constructive and improvement heuristic procedure specially designed to address the objectives of the problem is developed and results of computational experiments obtained with empirical data from the hospital are presented. This study shows that by using the bicriteria approach presented here it is possible to build surgical plans with very good performance levels. This method can be used within an interactive approach with the decision maker. It can also be easily adapted to other hospitals with similar scheduling conditions.
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.
The Saccharomyces Genome Database: Advanced Searching Methods and Data Mining.
Cherry, J Michael
2015-12-02
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.
New hybrid conjugate gradient methods with the generalized Wolfe line search.
Xu, Xiao; Kong, Fan-Yu
2016-01-01
The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.
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…
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
A single cognitive heuristic process meets the complexity of domain-specific moral heuristics.
Dubljević, Veljko; Racine, Eric
2014-10-01
The inherence heuristic (a) offers modest insights into the complex nature of both the is-ought tension in moral reasoning and moral reasoning per se, and (b) does not reflect the complexity of domain-specific moral heuristics. Formal and general in nature, we contextualize the process described as "inherence heuristic" in a web of domain-specific heuristics (e.g., agent specific; action specific; consequences specific).
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 Astrophysics Data System (ADS)
Lambert, A. J. D.; Gupta, Surendra M.
2005-11-01
This paper deals with disassembly sequencing problems subjected to sequence dependent disassembly costs. We present a heuristic and an iterative method based on partial branch and bound concept to solve such problems. Since heuristic methods intrinsically generate suboptimum solutions, we compared the heuristically obtained solutions with the exact solutions to see if they are reasonably good or not. This process, however, is limited to small or perhaps medium sized problems only as the required CPU time for exact methods tends to increase exponentially with the problem size. For the problems tested, we observed that the methods described in this paper generate surprisingly good results using almost negligible amount of CPU time.
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.
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.
Goloboff, Pablo A
2014-10-01
Three different types of data sets, for which the uniquely most parsimonious tree can be known exactly but is hard to find with heuristic tree search methods, are studied. Tree searches are complicated more by the shape of the tree landscape (i.e. the distribution of homoplasy on different trees) than by the sheer abundance of homoplasy or character conflict. Data sets of Type 1 are those constructed by Radel et al. (2013). Data sets of Type 2 present a very rugged landscape, with narrow peaks and valleys, but relatively low amounts of homoplasy. For such a tree landscape, subjecting the trees to TBR and saving suboptimal trees produces much better results when the sequence of clipping for the tree branches is randomized instead of fixed. An unexpected finding for data sets of Types 1 and 2 is that starting a search from a random tree instead of a random addition sequence Wagner tree may increase the probability that the search finds the most parsimonious tree; a small artificial example where these probabilities can be calculated exactly is presented. Data sets of Type 3, the most difficult data sets studied here, comprise only congruent characters, and a single island with only one most parsimonious tree. Even if there is a single island, missing entries create a very flat landscape which is difficult to traverse with tree search algorithms because the number of equally parsimonious trees that need to be saved and swapped to effectively move around the plateaus is too large. Minor modifications of the parameters of tree drifting, ratchet, and sectorial searches allow travelling around these plateaus much more efficiently than saving and swapping large numbers of equally parsimonious trees with TBR. For these data sets, two new related criteria for selecting taxon addition sequences in Wagner trees (the "selected" and "informative" addition sequences) produce much better results than the standard random or closest addition sequences. These new methods for Wagner
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
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.
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.
"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…
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.
Global Search Capabilities of Indirect Methods for Impulsive Transfers
NASA Astrophysics Data System (ADS)
Shen, Hong-Xin; Casalino, Lorenzo; Luo, Ya-Zhong
2015-09-01
An optimization method which combines an indirect method with homotopic approach is proposed and applied to impulsive trajectories. Minimum-fuel, multiple-impulse solutions, with either fixed or open time are obtained. The homotopic approach at hand is relatively straightforward to implement and does not require an initial guess of adjoints, unlike previous adjoints estimation methods. A multiple-revolution Lambert solver is used to find multiple starting solutions for the homotopic procedure; this approach can guarantee to obtain multiple local solutions without relying on the user's intuition, thus efficiently exploring the solution space to find the global optimum. The indirect/homotopic approach proves to be quite effective and efficient in finding optimal solutions, and outperforms the joint use of evolutionary algorithms and deterministic methods in the test cases.
An Empirical Study in the Simulation of Heuristic Error Behavior.
1986-01-01
generation (global] procedure initialize.graph.descriptor (var g graph -descriptor); varIi : integer; 0. begin g.depth := 0; g.gsnerated := 0; g expanded...state puzzle-state; var search-tree, graph : node.ptr; var g : graph -descriptor); e%:. " var start, current, c, p node-ptr; open. successor-list node...node.ptr; .e inv- g graph -descriptor; profile-input, profil*-output : text; frequency : array (1..max-heuristics, 0 .max-n. 0.max-k] of integer; profile
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.
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 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.
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 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
SEARCH FOR MITOGENETIC RADIATION BY MEANS OF THE PHOTOELECTRIC METHOD
Lorenz, Egon
1934-01-01
The intensity of mitogenetic radiation was estimated from data given by Gurwitsch. The sensitivity of the biological method and of the physical methods were compared. With onion-base pulp and onion roots as mitogenetic inductors, the photographic method gave no perceptible blackening for exposures up to 184 hours. A photoelectric counter tube was described with cadmium as photoelectric metal. Its sensitivity was such that a radiation intensity of 10 to 15 quanta per cm.2 per second of the Hg line 2536 A was detectable. Spurious effects produced by the counter tube were described and means for their avoidance given. A number of different biological materials, all supposed to be excellent mitogenetic radiators, were investigated by means of the counter tube. No mitogenetic radiation could be detected. PMID:19872817
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.
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.
NASA Astrophysics Data System (ADS)
Zhang, Chen; Ni, Zhiwei; Ni, Liping; Tang, Na
2016-10-01
Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.
(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…
The method of common search direction of joint inversion
NASA Astrophysics Data System (ADS)
Zhao, C.; Tang, R.
2013-12-01
In geophysical inversion, the first step is to construct an objective function. The second step is using the optimization algorithm to minimize the objective function, such as the gradient method and the conjugate gradient method. Compared with the former, the conjugate gradient method can find a better direction to make the error decreasing faster and has been widely used for a long time. At present, the joint inversion is generally using the conjugate gradient method. The most important thing of joint inversion is to construct the partial derivative matrix with respect to different physical properties. Then we should add the constraints among different physical properties into the integrated matrix and also use the cross gradient as constrained of joint inversion. There are two ways to apply the cross gradient into inverse process that can be added to the data function or the model function. One way is adding the cross gradient into data function. The partial derivative matrix will grow two times, meanwhile it's also requested to calculate the cross gradient of each grid and bring great computation cost.
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 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.
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.
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.
Search for Hepatitis A Viruses by New Methods
1981-09-01
marmoset liver tissue and from chimpanzee fecal p * material. Four weeks after In~culation of PLC/PRF/I, Niahlavu and MC-3 cells a significant increase... Marmoset -adapted HAV was prepared from about 5 grams of marmoset liver by 6 either of two methods. * -". (I) Procedure I (Figure A): Initial studies have...the results obtained using this procedure. .6 S 6) l •••• , ~. (2) Procedure It (Figure 7): Marmoset liver tissue was homogenized with PBS, pH 7.4
Kamachi, Takashi; Yoshizawa, Kazunari
2016-02-22
A conformational search program for finding low-energy conformations of large noncovalent complexes has been developed. A quantitatively reliable semiempirical quantum mechanical PM6-DH+ method, which is able to accurately describe noncovalent interactions at a low computational cost, was employed in contrast to conventional conformational search programs in which molecular mechanical methods are usually adopted. Our approach is based on the low-mode method whereby an initial structure is perturbed along one of its low-mode eigenvectors to generate new conformations. This method was applied to determine the most stable conformation of transition state for enantioselective alkylation by the Maruoka and cinchona alkaloid catalysts and Hantzsch ester hydrogenation of imines by chiral phosphoric acid. Besides successfully reproducing the previously reported most stable DFT conformations, the conformational search with the semiempirical quantum mechanical calculations newly discovered a more stable conformation at a low computational cost.
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.
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.
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.
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.
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.
Dual-mode nested search method for categorical uncertain multi-objective optimization
NASA Astrophysics Data System (ADS)
Tang, Long; Wang, Hu
2016-10-01
Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.
BetaSearch: a new method for querying β-residue motifs
2012-01-01
Background Searching for structural motifs across known protein structures can be useful for identifying unrelated proteins with similar function and characterising secondary structures such as β-sheets. This is infeasible using conventional sequence alignment because linear protein sequences do not contain spatial information. β-residue motifs are β-sheet substructures that can be represented as graphs and queried using existing graph indexing methods, however, these approaches are designed for general graphs that do not incorporate the inherent structural constraints of β-sheets and require computationally-expensive filtering and verification procedures. 3D substructure search methods, on the other hand, allow β-residue motifs to be queried in a three-dimensional context but at significant computational costs. Findings We developed a new method for querying β-residue motifs, called BetaSearch, which leverages the natural planar constraints of β-sheets by indexing them as 2D matrices, thus avoiding much of the computational complexities involved with structural and graph querying. BetaSearch exhibits faster filtering, verification, and overall query time than existing graph indexing approaches whilst producing comparable index sizes. Compared to 3D substructure search methods, BetaSearch achieves 33 and 240 times speedups over index-based and pairwise alignment-based approaches, respectively. Furthermore, we have presented case-studies to demonstrate its capability of motif matching in sequentially dissimilar proteins and described a method for using BetaSearch to predict β-strand pairing. Conclusions We have demonstrated that BetaSearch is a fast method for querying substructure motifs. The improvements in speed over existing approaches make it useful for efficiently performing high-volume exploratory querying of possible protein substructural motifs or conformations. BetaSearch was used to identify a nearly identical β-residue motif between an entirely
Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.
Carrascal, A; Manrique, D; Ríos, J; Rossi, C
2003-01-01
This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.
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.
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.
Free Energy-Based Conformational Search Algorithm Using the Movable Type Sampling Method.
Pan, Li-Li; Zheng, Zheng; Wang, Ting; Merz, Kenneth M
2015-12-08
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.
Social heuristics shape intuitive cooperation.
Rand, David G; Peysakhovich, Alexander; Kraft-Todd, Gordon T; Newman, George E; Wurzbacher, Owen; Nowak, Martin A; Greene, Joshua D
2014-04-22
Cooperation is central to human societies. Yet relatively little is known about the cognitive underpinnings of cooperative decision making. Does cooperation require deliberate self-restraint? Or is spontaneous prosociality reined in by calculating self-interest? Here we present a theory of why (and for whom) intuition favors cooperation: cooperation is typically advantageous in everyday life, leading to the formation of generalized cooperative intuitions. Deliberation, by contrast, adjusts behaviour towards the optimum for a given situation. Thus, in one-shot anonymous interactions where selfishness is optimal, intuitive responses tend to be more cooperative than deliberative responses. We test this 'social heuristics hypothesis' by aggregating across every cooperation experiment using time pressure that we conducted over a 2-year period (15 studies and 6,910 decisions), as well as performing a novel time pressure experiment. Doing so demonstrates a positive average effect of time pressure on cooperation. We also find substantial variation in this effect, and show that this variation is partly explained by previous experience with one-shot lab experiments.
The Search Conference as a Method in Planning Community Health Promotion Actions.
Magnus, Eva; Knudtsen, Margunn Skjei; Wist, Guri; Weiss, Daniel; Lillefjell, Monica
2016-08-19
Aims: The aim of this article is to describe and discuss how the search conference can be used as a method for planning health promotion actions in local communities. Design and methods: The article draws on experiences with using the method for an innovative project in health promotion in three Norwegian municipalities. The method is described both in general and how it was specifically adopted for the project. Results and conclusions: The search conference as a method was used to develop evidence-based health promotion action plans. With its use of both bottom-up and top-down approaches, this method is a relevant strategy for involving a community in the planning stages of health promotion actions in line with political expectations of participation, ownership, and evidence-based initiatives.
Heuristic thinking makes a chemist smart.
Graulich, Nicole; Hopf, Henning; Schreiner, Peter R
2010-05-01
We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.
Search strategies in a human water maze analogue analyzed with automatic classification methods.
Schoenfeld, Robby; Moenich, Nadine; Mueller, Franz-Josef; Lehmann, Wolfgang; Leplow, Bernd
2010-03-17
Although human spatial cognition is at the focus of intense research efforts, experimental evidence on how search strategies differ among age and gender groups remains elusive. To address this problem, we investigated the interaction between age, sex, and strategy usage within a novel virtual water maze-like procedure (VWM). We studied 28 young adults 20-29 years (14 males) and 30 middle-aged adults 50-59 years (15 males). Younger age groups outperformed older groups with respect to place learning. We also observed a moderate sex effect, with males outperforming females. Unbiased classification of human search behavior within this paradigm was done by means of an exploratory method using sparse non-negative matrix factorization (SNMF) and a parameter-based algorithm as an a priori classifier. Analyses of search behavior with the SNMF and the parameter-based method showed that the older group relied on less efficient search strategies, but females did not drop so dramatically. Place learning was related to the adaptation of elaborated search strategies. Participants using place-directed strategies obtained the highest score on place learning, and deterioration of place learning in the elderly was due to the use of less efficient non-specific strategies. A high convergence of the SNMF and the parameter-based classifications could be shown. Furthermore, the SNMF classification was cross validated with the traditional eyeballing method. As a result of this analysis, we conclude that SNMF is a robust exploratory method for the classification of search behavior in water maze procedures.
A new convergent conjugate gradient method under the exact line search
NASA Astrophysics Data System (ADS)
Omer, Osman; Mamat, Mustafa; Rivaie, Mohd
2015-05-01
Conjugate gradient methods are widely used for unconstrained optimization problems, especially large scale problems. That is, for its simplicity, low memory requirement, and global convergence properties. In this paper, we study the global convergence properties of a new conjugate gradient method under the exact line search. Under some assumptions, the proofs of the sufficient descent property and the global convergence are given. The numerical results show that our new method is efficient for some unconstrained optimization problems.
Automatic Reaction Pathway Search via Combined Molecular Dynamics and Coordinate Driving Method.
Yang, Manyi; Zou, Jingxiang; Wang, Guoqiang; Li, Shuhua
2017-02-16
We proposed and implemented a combined molecular dynamics and coordinate driving (MD/CD) method for automatically searching multistep reaction pathways of chemical reactions. In this approach, the molecular dynamic (MD) method at the molecular mechanics (MM) or semiempirical quantum mechanical (QM) level is employed to explore the conformational space of the minimum structures, and the modified coordinate driving (CD) method is used to build reaction pathways for representative conformers. The MD/CD method is first applied to two model reactions (the Claisen rearrangement and the intermolecular aldol reaction). By comparing the obtained results with those of the existing methods, we found that the MD/CD method has a comparable performance in searching low-energy reaction pathways. Then, the MD/CD method is further applied to investigate two reactions: the electrocyclic reaction of benzocyclobutene-7-carboxaldehyde and the intramolecular Diels-Alder reaction of ketothioester with 11 effectively rotatable single bonds. For the first reaction, our results can correctly account for its torquoselectivity. For the second one, our method predicts eight reaction channels, leading to eight different stereo- and regioselective products. The MD/CD method is expected to become an efficient and cost-effective theoretical tool for automatically searching low-energy reaction pathways for relatively complex chemical reactions.
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…
An adaptive random search for short term generation scheduling with network constraints
Velasco, Jonás; Selley, Héctor J.
2017-01-01
This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach. PMID:28234954
An adaptive random search for short term generation scheduling with network constraints.
Marmolejo, J A; Velasco, Jonás; Selley, Héctor J
2017-01-01
This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.
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.
A health literacy and usability heuristic evaluation of a mobile consumer health application.
Monkman, Helen; Kushniruk, Andre
2013-01-01
Usability and health literacy are two critical factors in the design and evaluation of consumer health information systems. However, methods for evaluating these two factors in conjunction remain limited. This study adapted a set of existing guidelines for the design of consumer health Web sites into evidence-based evaluation heuristics tailored specifically for mobile consumer health applications. In order to test the approach, a mobile consumer health application (app) was then evaluated using these heuristics. In addition to revealing ways to improve the usability of the system, this analysis identified opportunities to augment the content to make it more understandable by users with limited health literacy. This study successfully demonstrated the utility of converting existing design guidelines into heuristics for the evaluation of usability and health literacy. The heuristics generated could be applied for assessing and revising other existing consumer health information systems.
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.
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.
ERIC Educational Resources Information Center
Hubbard, Joan C.; North, Alexa B.; Arjomand, H. Lari
1997-01-01
Examines methods used to search for entry-level managerial positions and assesses how human resource and personnel directors in Georgia perceive these methods. Findings indicate that few of the directors use electronic technology to fill such positions, but they view positively those applicants who use electronic job searching methods. (RJM)
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 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.
Frequency-based heuristics for material perception
Giesel, Martin; Zaidi, Qasim
2013-01-01
People often make rapid visual judgments of the properties of surfaces they are going to walk on or touch. How do they do this when the interactions of illumination geometry with 3-D material structure and object shape result in images that inverse optics algorithms cannot resolve without externally imposed constraints? A possibly effective strategy would be to use heuristics based on information that can be gleaned rapidly from retinal images. By using perceptual scaling of a large sample of images, combined with correspondence and canonical correlation analyses, we discovered that material properties, such as roughness, thickness, and undulations, are characterized by specific scales of luminance variations. Using movies, we demonstrate that observers' percepts of these 3-D qualities vary continuously as a function of the relative energy in corresponding 2-D frequency bands. In addition, we show that judgments of roughness, thickness, and undulations are predictably altered by adaptation to dynamic noise at the corresponding scales. These results establish that the scale of local 3-D structure is critical in perceiving material properties, and that relative contrast at particular spatial frequencies is important for perceiving the critical 3-D structure from shading cues, so that cortical mechanisms for estimating material properties could be constructed by combining the parallel outputs of sets of frequency-selective neurons. These results also provide methods for remote sensing of material properties in machine vision, and rapid synthesis, editing and transfer of material properties for computer graphics and animation. PMID:24317425
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.
Pillai, R.S.; Rathi, A.K.
1995-02-01
The main objective of synchronized signal timing is to keep traffic moving along arterials in platoons throughout the signal system by proper setting of left turn phase sequence at signals along the arterials/networks. The synchronization of traffic signals located along the urban/suburban arterials in metropolitan areas is perhaps one of the most cost-effective methods for improving traffic flow along these streets. MAXBAND Version 2.1 (formerly known as MAXBAND-86), a progression-based optimization model, is used for generating signal timing plan for urban networks. This model formulates the problem as a mixed integer linear program and uses Land and Powell branch and bound search to arrive at the optimal solution. The computation time of MAXBAND Version 2.1 tends to be excessive for realistic multiarterial network problems due to the exhaustive nature of the branch and bound search technique. Furthermore, the Land and Powell branch and bound code is known to be numerically unstable, which results in suboptimal solutions for network problems with a range on the cycle time variable. This report presents the development of a new version of MAXBAND called MAXBAND Version 3.1. This new version has a fast heuristic algorithm and a fast optimal algorithm for generating signal timing plan for arterials and networks. MAXBAND 3.1 can generate optimal/near-optimal solutions in fraction of the time needed to compute the optimal solution by Version 2.1. The heuristic algorithm in the new model is based on restricted search using branch and bound technique. The algorithm for generating the optimal solution is faster and more efficient than version 2.1 algorithm. Furthermore, the new version is numerically stable. The efficiency of the new model is demonstrated by numerical results for a set of test problems.
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
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.
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.
Study of Fuze Structure and Reliability Design Based on the Direct Search Method
NASA Astrophysics Data System (ADS)
Lin, Zhang; Ning, Wang
2017-03-01
Redundant design is one of the important methods to improve the reliability of the system, but mutual coupling of multiple factors is often involved in the design. In my study, Direct Search Method is introduced into the optimum redundancy configuration for design optimization, in which, the reliability, cost, structural weight and other factors can be taken into account simultaneously, and the redundant allocation and reliability design of aircraft critical system are computed. The results show that this method is convenient and workable, and applicable to the redundancy configurations and optimization of various designs upon appropriate modifications. And this method has a good practical value.
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.
Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques
1990-01-01
Engineering Laboratory (HEL) (301) 278-5867, DSN 298-5867 Rajay Goyal, Neena Sathi, Bill Elm, Ivan Johnson* Carnegie Group Inc. (412) 642-6900 Dr. Mark ... Fox The Robotics Institute, Carnegie Mellon University BACKGROUND The dynamics and complexity of logistics planning require decision suppon tools
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.
Fast optimization of binary clusters using a novel dynamic lattice searching method
NASA Astrophysics Data System (ADS)
Wu, Xia; Cheng, Wen
2014-09-01
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)79 clusters with DFT-fit parameters of Gupta potential.
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)79 clusters with DFT-fit parameters of Gupta potential.
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.
Combining heuristic and statistical techniques in landslide hazard assessments
NASA Astrophysics Data System (ADS)
Cepeda, Jose; Schwendtner, Barbara; Quan, Byron; Nadim, Farrokh; Diaz, Manuel; Molina, Giovanni
2014-05-01
As a contribution to the Global Assessment Report 2013 - GAR2013, coordinated by the United Nations International Strategy for Disaster Reduction - UNISDR, a drill-down exercise for landslide hazard assessment was carried out by entering the results of both heuristic and statistical techniques into a new but simple combination rule. The data available for this evaluation included landslide inventories, both historical and event-based. In addition to the application of a heuristic method used in the previous editions of GAR, the availability of inventories motivated the use of statistical methods. The heuristic technique is largely based on the Mora & Vahrson method, which estimates hazard as the product of susceptibility and triggering factors, where classes are weighted based on expert judgment and experience. Two statistical methods were also applied: the landslide index method, which estimates weights of the classes for the susceptibility and triggering factors based on the evidence provided by the density of landslides in each class of the factors; and the weights of evidence method, which extends the previous technique to include both positive and negative evidence of landslide occurrence in the estimation of weights for the classes. One key aspect during the hazard evaluation was the decision on the methodology to be chosen for the final assessment. Instead of opting for a single methodology, it was decided to combine the results of the three implemented techniques using a combination rule based on a normalization of the results of each method. The hazard evaluation was performed for both earthquake- and rainfall-induced landslides. The country chosen for the drill-down exercise was El Salvador. The results indicate that highest hazard levels are concentrated along the central volcanic chain and at the centre of the northern mountains.
NASA Astrophysics Data System (ADS)
Korotkov, E. V.; Korotkova, M. A.
2017-01-01
The purpose of this study was to detect latent periodicity in the presence of deletions or insertions in the analyzed data, when the points of deletions or insertions are unknown. A mathematical method was developed to search for periodicity in the numerical series, using dynamic programming and random matrices. The developed method was applied to search for periodicity in the Euro/Dollar (Eu/) exchange rate, since 2001. The presence of periodicity within the period length equal to 24 h in the analyzed financial series was shown. Periodicity can be detected only with insertions and deletions. The results of this study show that periodicity phase shifts, depend on the observation time. The reasons for the existence of the periodicity in the financial ranks are discussed.
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
Brown, D.L.; Gorin, M.B.; Weeks, D.E. )
1994-03-01
The affected-pedigree-member (APM) method of linkage analysis is a nonparametric statistic that tests for nonrandom cosegregation of a disease and marker loci. The APM statistic is based on the observation that if a marker locus is near a disease-susceptibility locus, then affected individuals within a family should be more similar at the marker locus than is expected by chance. The APM statistic measures marker similarity in terms of identity by state (IBS) of marker alleles; that is, two alleles are IBS if they are the same, regardless of their ancestral origin. Since the APM statistic measures increased marker similarity, it makes no assumptions concerning how the disease is inherited; this can be an advantage when dealing with complex diseases for which the mode of inheritance is difficult to determine. The authors investigate here the power of the APM statistic to detect linkage in the context of a genomewide search. In such a search, the APM statistic is evaluated at a grid of markers. Then regions with high APM statistics are investigated more thoroughly by typing more markers in the region. Using simulated data, they investigate various search strategies and recommended an optimal search strategy that maximizes the power to detect linkage while minimizing the false-positive rate and number of markers. They determine an optimal series of three increasing cut-points and an independent criterion for significance. 14 refs., 7 figs., 4 tabs.
The Search Conference as a Method in Planning Community Health Promotion Actions
Magnus, Eva; Knudtsen, Margunn Skjei; Wist, Guri; Weiss, Daniel; Lillefjell, Monica
2016-01-01
Aims: The aim of this article is to describe and discuss how the search conference can be used as a method for planning health promotion actions in local communities. Design and methods: The article draws on experiences with using the method for an innovative project in health promotion in three Norwegian municipalities. The method is described both in general and how it was specifically adopted for the project. Results and conclusions: The search conference as a method was used to develop evidence-based health promotion action plans. With its use of both bottom-up and top-down approaches, this method is a relevant strategy for involving a community in the planning stages of health promotion actions in line with political expectations of participation, ownership, and evidence-based initiatives. Significance for public health This article describe and discuss how the Search conference can be used as a method when working with knowledge based health promotion actions in local communities. The article describe the sequences of the conference and shows how this have been adapted when planning and prioritizing health promotion actions in three Norwegian municipalities. The significance of the article is that it shows how central elements in the planning of health promotion actions, as participation and involvements as well as evidence was a fundamental thinking in how the conference were accomplished. The article continue discussing how the method function as both a top-down and a bottom-up strategy, and in what way working evidence based can be in conflict with a bottom-up strategy. The experiences described can be used as guidance planning knowledge based health promotion actions in communities. PMID:27747199
NASA Astrophysics Data System (ADS)
Omer, Osman; Rivaie, Mohd; Mamat, Mustafa; Amani, Zahrahtul
2015-02-01
Conjugate gradient methods are one of the most used methods for solving nonlinear unconstrained optimization problems, especially of large scale. Their wide applications are due to their simplicity and low memory requirement. The sufficient descent property is an important issue in the analyses and implementations of conjugate gradient methods. In this paper, a new conjugate gradient method is proposed for unconstrained optimization problems. The theoretical analysis shows that the directions generated by the new method are always satisfy the sufficient descent property, and this property is independent of the line search used. Furthermore, a numerical experiment based on comparing the new method with other known conjugate gradient methods shows that the new is efficient for some unconstrained optimization problems.
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.
The Gaussian CL_{s} method for searches of new physics
Qian, X.; Tan, A.; Ling, J. J.; Nakajima, Y.; Zhang, C.
2016-04-23
Here we describe a method based on the CL_{s} 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 CL_{s} method. Our work provides a self-contained mathematical proof for the Gaussian CL_{s} method, that explicitly outlines the required conditions. These conditions are milder than that required by the Wilks' theorem to set confidence intervals (CIs). We illustrate the Gaussian CL_{s} method in an example of searching for a sterile neutrino, where the CL_{s} approach was rarely used before. We also compare data analysis results produced by the Gaussian CL_{s} method and various CI methods to showcase their differences.
Efficient Globally Optimal Consensus Maximisation with Tree Search.
Chin, Tat-Jun; Purkait, Pulak; Eriksson, Anders; Suter, David
2017-04-01
Maximum consensus is one of the most popular criteria for robust estimation in computer vision. Despite its widespread use, optimising the criterion is still customarily done by randomised sample-and-test techniques, which do not guarantee optimality of the result. Several globally optimal algorithms exist, but they are too slow to challenge the dominance of randomised methods. Our work aims to change this state of affairs by proposing an efficient algorithm for global maximisation of consensus. Under the framework of LP-type methods, we show how consensus maximisation for a wide variety of vision tasks can be posed as a tree search problem. This insight leads to a novel algorithm based on A* search. We propose efficient heuristic and support set updating routines that enable A* search to efficiently find globally optimal results. On common estimation problems, our algorithm is much faster than previous exact methods. Our work identifies a promising direction for globally optimal consensus maximisation.
Neighbourhood search feature selection method for content-based mammogram retrieval.
Chandy, D Abraham; Christinal, A Hepzibah; Theodore, Alwyn John; Selvan, S Easter
2017-03-01
Content-based image retrieval plays an increasing role in the clinical process for supporting diagnosis. This paper proposes a neighbourhood search method to select the near-optimal feature subsets for the retrieval of mammograms from the Mammographic Image Analysis Society (MIAS) database. The features based on grey level cooccurrence matrix, Daubechies-4 wavelet, Gabor, Cohen-Daubechies-Feauveau 9/7 wavelet and Zernike moments are extracted from mammograms available in the MIAS database to form the combined or fused feature set for testing various feature selection methods. The performance of feature selection methods is evaluated using precision, storage requirement and retrieval time measures. Using the proposed method, a significant improvement is achieved in mean precision rate and feature dimension. The results show that the proposed method outperforms the state-of-the-art feature selection methods.
On methods for correcting for the look-elsewhere effect in searches for new physics
NASA Astrophysics Data System (ADS)
Algeri, S.; van Dyk, D. A.; Conrad, J.; Anderson, B.
2016-12-01
The search for new significant peaks over a energy spectrum often involves a statistical multiple hypothesis testing problem. Separate tests of hypothesis are conducted at different locations over a fine grid producing an ensemble of local p-values, the smallest of which is reported as evidence for the new resonance. Unfortunately, controlling the false detection rate (type I error rate) of such procedures may lead to excessively stringent acceptance criteria. In the recent physics literature, two promising statistical tools have been proposed to overcome these limitations. In 2005, a method to ``find needles in haystacks'' was introduced by Pilla et al. [1], and a second method was later proposed by Gross and Vitells [2] in the context of the ``look-elsewhere effect'' and trial factors. We show that, although the two methods exhibit similar performance for large sample sizes, for relatively small sample sizes, the method of Pilla et al. leads to an artificial inflation of statistical power that stems from an increase in the false detection rate. This method, on the other hand, becomes particularly useful in multidimensional searches, where the Monte Carlo simulations required by Gross and Vitells are often unfeasible. We apply the methods to realistic simulations of the Fermi Large Area Telescope data, in particular the search for dark matter annihilation lines. Further, we discuss the counter-intuitive scenario where the look-elsewhere corrections are more conservative than much more computationally efficient corrections for multiple hypothesis testing. Finally, we provide general guidelines for navigating the tradeoffs between statistical and computational efficiency when selecting a statistical procedure for signal detection.
Hybridization of evolutionary algorithms and local search by means of a clustering method.
Martínez-Estudillo, Alfonso C; Hervás-Martínez, César; Martínez-Estudillo, Francisco J; García-Pedrajas, Nicolás
2006-06-01
This paper presents a hybrid evolutionary algorithm (EA) to solve nonlinear-regression problems. Although EAs have proven their ability to explore large search spaces, they are comparatively inefficient in fine tuning the solution. This drawback is usually avoided by means of local optimization algorithms that are applied to the individuals of the population. The algorithms that use local optimization procedures are usually called hybrid algorithms. On the other hand, it is well known that the clustering process enables the creation of groups (clusters) with mutually close points that hopefully correspond to relevant regions of attraction. Local-search procedures can then be started once in every such region. This paper proposes the combination of an EA, a clustering process, and a local-search procedure to the evolutionary design of product-units neural networks. In the methodology presented, only a few individuals are subject to local optimization. Moreover, the local optimization algorithm is only applied at specific stages of the evolutionary process. Our results show a favorable performance when the regression method proposed is compared to other standard methods.
Cooperative unmanned aerial vehicle (UAV) search in dynamic environments using stochastic methods
NASA Astrophysics Data System (ADS)
Flint, Matthew D.
Within this dissertation, the problem of the control of the decentralized path planning decision processes of multiple cooperating autonomous aerial vehicles engaged in search of an uncertain environment is considered. The environment is modeled in a probabilistic fashion, such that both a priori and dynamic information about it can be incorporated. The components of the environment include both target information and threat information. Using the information about the environment, a computationally feasible decision process is formulated that can decide; in a near optimal fashion, which path a searching vehicle should take, using a dynamic programming algorithm with a limited look ahead horizon, with the possibility to extend the horizon using Approximate Dynamic Programming. A planning vehicle trust take into account the effects of its (local) actions on meeting global goals. This is accomplished using a passive and predictive cooperation scheme among the vehicles. Lastly, a flexible simulator has been developed, using sound simulation analysis methods, to simulate a UAV search team, which can be used to create statistically valid results demonstrating the effectiveness of the model and solution methods.
Amador Carrascal, Carolina; Chen, Shigao; Manduca, Armando; Greenleaf, James F; Urban, Matthew W
2017-04-01
Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocity values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index, ultrasound scanners, scanning protocols, and ultrasound image quality. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this paper, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time [spatiotemporal peak (STP)]; the second method applies an amplitude filter [spatiotemporal thresholding (STTH)] to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared with TTP in phantom. Moreover, in a cohort of 14 healthy subjects, STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared with conventional TTP.
Teaching a Heuristic Approach to Information Retrieval.
ERIC Educational Resources Information Center
Ury, Connie Jo; And Others
1997-01-01
Discusses lifelong learning and the need for information retrieval skills, and describes how Northwest Missouri State University incorporates a heuristic model of library instruction in which students continually evaluate and refine information-seeking practices while progressing through all levels of courses in diverse disciplines. (Author/LRW)
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…
Improving Multi-Component Maintenance Acquisition with a Greedy Heuristic Local Algorithm
2013-04-01
need to improve the decision making process for system sustainment including maintenance, repair, and overhaul ( MRO ) operations and the acquisition of... MRO parts. To help address the link between sustainment policies and acquisition, this work develops a greedy heuristic?based local search algorithm to...concerns, there is a need to improve the decision making process for system sustainment, including maintenance, repair, and overhaul ( MRO
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.
Kurogi, Y; Miyata, K; Okamura, T; Hashimoto, K; Tsutsumi, K; Nasu, M; Moriyasu, M
2001-07-05
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.
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…
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…
NASA Astrophysics Data System (ADS)
Tanizawa, Ken; Hirose, Akira
Adaptive polarization mode dispersion (PMD) compensation is required for the speed-up and advancement of the present optical communications. The combination of a tunable PMD compensator and its adaptive control method achieves adaptive PMD compensation. In this paper, we report an effective search control algorithm for the feedback control of the PMD compensator. The algorithm is based on the hill-climbing method. However, the step size changes randomly to prevent the convergence from being trapped at a local maximum or a flat, unlike the conventional hill-climbing method. The randomness depends on the Gaussian probability density functions. We conducted transmission simulations at 160Gb/s and the results show that the proposed method provides more optimal compensator control than the conventional hill-climbing method.
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.
Cheng, Chia-Ying; Tsai, Chia-Feng; Chen, Yu-Ju; Sung, Ting-Yi; Hsu, Wen-Lian
2013-05-03
As spectral library searching has received increasing attention for peptide identification, constructing good decoy spectra from the target spectra is the key to correctly estimating the false discovery rate in searching against the concatenated target-decoy spectral library. Several methods have been proposed to construct decoy spectral libraries. Most of them construct decoy peptide sequences and then generate theoretical spectra accordingly. In this paper, we propose a method, called precursor-swap, which directly constructs decoy spectral libraries directly at the "spectrum level" without generating decoy peptide sequences by swapping the precursors of two spectra selected according to a very simple rule. Our spectrum-based method does not require additional efforts to deal with ion types (e.g., a, b or c ions), fragment mechanism (e.g., CID, or ETD), or unannotated peaks, but preserves many spectral properties. The precursor-swap method is evaluated on different spectral libraries and the results of obtained decoy ratios show that it is comparable to other methods. Notably, it is efficient in time and memory usage for constructing decoy libraries. A software tool called Precursor-Swap-Decoy-Generation (PSDG) is publicly available for download at http://ms.iis.sinica.edu.tw/PSDG/.
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
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
Proportional reasoning as a heuristic-based process: time constraint and dual task considerations.
Gillard, Ellen; Van Dooren, Wim; Schaeken, Walter; Verschaffel, Lieven
2009-01-01
The present study interprets the overuse of proportional solution methods from a dual process framework. Dual process theories claim that analytic operations involve time-consuming executive processing, whereas heuristic operations are fast and automatic. In two experiments to test whether proportional reasoning is heuristic-based, the participants solved "proportional" problems, for which proportional solution methods provide correct answers, and "nonproportional" problems known to elicit incorrect answers based on the assumption of proportionality. In Experiment 1, the available solution time was restricted. In Experiment 2, the executive resources were burdened with a secondary task. Both manipulations induced an increase in proportional answers and a decrease in correct answers to nonproportional problems. These results support the hypothesis that the choice for proportional methods is heuristic-based.
Usability of a Patient Education and Motivation Tool Using Heuristic Evaluation
Arora, Mohit; Dai, Liwei; Price, Kathleen; Vizer, Lisa; Sears, Andrew
2009-01-01
Background Computer-mediated educational applications can provide a self-paced, interactive environment to deliver educational content to individuals about their health condition. These programs have been used to deliver health-related information about a variety of topics, including breast cancer screening, asthma management, and injury prevention. We have designed the Patient Education and Motivation Tool (PEMT), an interactive computer-based educational program based on behavioral, cognitive, and humanistic learning theories. The tool is designed to educate users and has three key components: screening, learning, and evaluation. Objective The objective of this tutorial is to illustrate a heuristic evaluation using a computer-based patient education program (PEMT) as a case study. The aims were to improve the usability of PEMT through heuristic evaluation of the interface; to report the results of these usability evaluations; to make changes based on the findings of the usability experts; and to describe the benefits and limitations of applying usability evaluations to PEMT. Methods PEMT was evaluated by three usability experts using Nielsen’s usability heuristics while reviewing the interface to produce a list of heuristic violations with severity ratings. The violations were sorted by heuristic and ordered from most to least severe within each heuristic. Results A total of 127 violations were identified with a median severity of 3 (range 0 to 4 with 0 = no problem to 4 = catastrophic problem). Results showed 13 violations for visibility (median severity = 2), 38 violations for match between system and real world (median severity = 2), 6 violations for user control and freedom (median severity = 3), 34 violations for consistency and standards (median severity = 2), 11 violations for error severity (median severity = 3), 1 violation for recognition and control (median severity = 3), 7 violations for flexibility and efficiency (median severity = 2), 9 violations
Heuristical Feature Extraction from LIDAR Data and Their Visualization
NASA Astrophysics Data System (ADS)
Ghosh, S.; Lohani, B.
2011-09-01
Extraction of landscape features from LiDAR data has been studied widely in the past few years. These feature extraction methodologies have been focussed on certain types of features only, namely the bare earth model, buildings principally containing planar roofs, trees and roads. In this paper, we present a methodology to process LiDAR data through DBSCAN, a density based clustering method, which extracts natural and man-made clusters. We then develop heuristics to process these clusters and simplify them to be sent to a visualization engine.
Heuristic algorithm for off-lattice protein folding problem*
Chen, Mao; Huang, Wen-qi
2006-01-01
Enlightened by the law of interactions among objects in the physical world, we propose a heuristic algorithm for solving the three-dimensional (3D) off-lattice protein folding problem. Based on a physical model, the problem is converted from a nonlinear constraint-satisfied problem to an unconstrained optimization problem which can be solved by the well-known gradient method. To improve the efficiency of our algorithm, a strategy was introduced to generate initial configuration. Computational results showed that this algorithm could find states with lower energy than previously proposed ground states obtained by nPERM algorithm for all chains with length ranging from 13 to 55. PMID:16365919
[Searching for dwarf nova candidates with automatic methods in massive spectra].
Wang, Wen-Yu; Wang, Xin-Jun; Pan, Jing-Chang
2013-12-01
In the present paper, an automatic and efficient method for searching for dwarf nova candidates is presented. The methods PCA (principal component analysis) and SVM (support vector machine) are applied in the newly released SDSS-DR9 spectra. The final dimensions of the feature space are determined by the identification accuracy of training samples with different dimensions constrained by SVM. The massive spectra are dimension reduced by PCA at first and classified by the best SVM clas sifier. The final less number of candidates can be identified manually. A total number of 276 dwarf nova candidates are selected by the method and 6 of them are new discoveries which prove that our approach to finding special celestial bodies in massive spectra data is feasible. The new discoveries of this paper are added in the current dwarf nova template library which can contribute to constructing a more accurate feature space. The method proposed in this paper can also be used for special objects searching in other sky survey telescopes like Guoshoujing (Large Sky Area Multi-Object Fiber Spectroscopic Telescope -LAMOST) telescope.
Search Complexities for HTN Planning
2013-01-01
perfect strategy for n× n chess requires time exponential in n. Journal of Combinatorial Theory, Series A, 31(2):199–214, 1981. Thomas Geier and Pascal...Intelligence Research, 20:291–341, 2003. J. Hoffmann and Bernhard Nebel. The FF planning system: Fast plan generation through heuristic search. Journal
Brown, K M; Elliott, S J; Leatherdale, S T; Robertson-Wilson, J
2015-12-01
The environments in which population health interventions occur shape both their implementation and outcomes. Hence, when evaluating these interventions, we must explore both intervention content and context. Mixed methods (integrating quantitative and qualitative methods) provide this opportunity. However, although criteria exist for establishing rigour in quantitative and qualitative research, there is poor consensus regarding rigour in mixed methods. Using the empirical example of school-based obesity interventions, this methodological review examined how mixed methods have been used and reported, and how rigour has been addressed. Twenty-three peer-reviewed mixed methods studies were identified through a systematic search of five databases and appraised using the guidelines for Good Reporting of a Mixed Methods Study. In general, more detailed description of data collection and analysis, integration, inferences and justifying the use of mixed methods is needed. Additionally, improved reporting of methodological rigour is required. This review calls for increased discussion of practical techniques for establishing rigour in mixed methods research, beyond those for quantitative and qualitative criteria individually. A guide for reporting mixed methods research in population health should be developed to improve the reporting quality of mixed methods studies. Through improved reporting, mixed methods can provide strong evidence to inform policy and practice.
An Update on Teaching the Employment Search.
ERIC Educational Resources Information Center
Andrews, Deborah, Ed.; Dyrud, Marilyn A., Ed.
1997-01-01
Presents five articles dealing with teaching job search strategies: (1) "Preparing a Scannable Resume" (Carol Roever); (2) "Preparing an Online Resume" (Tim Krause); (3) "Using the World Wide Web to Teach Employment Communication" (K. Virginia Hemby); (4) "A Visual Heuristic for Promoting a Rhetorically Based Job Search" (Helen Foster); and (5)…
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
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.
Structuralism and Its Heuristic Implications.
ERIC Educational Resources Information Center
Greene, Ruth M.
1984-01-01
The author defines structuralism (a method for modeling and analyzing event systems in a space-time framework), traces its origins to the work of J. Piaget and M. Fourcault, and discusses its implications for learning. (CL)
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 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.
Freyhult, Eva K.; Bollback, Jonathan P.; Gardner, Paul P.
2007-01-01
Homology search is one of the most ubiquitous bioinformatic tasks, yet it is unknown how effective the currently available tools are for identifying noncoding RNAs (ncRNAs). In this work, we use reliable ncRNA data sets to assess the effectiveness of methods such as BLAST, FASTA, HMMer, and Infernal. Surprisingly, the most popular homology search methods are often the least accurate. As a result, many studies have used inappropriate tools for their analyses. On the basis of our results, we suggest homology search strategies using the currently available tools and some directions for future development. PMID:17151342
Mullins, Mary M; DeLuca, Julia B; Crepaz, Nicole; Lyles, Cynthia M
2014-06-01
Systematic reviews are an essential tool for researchers, prevention providers and policy makers who want to remain current with the evidence in the field. Systematic review must adhere to strict standards, as the results can provide a more objective appraisal of evidence for making scientific decisions than traditional narrative reviews. An integral component of a systematic review is the development and execution of a comprehensive systematic search to collect available and relevant information. A number of reporting guidelines have been developed to ensure quality publications of systematic reviews. These guidelines provide the essential elements to include in the review process and report in the final publication for complete transparency. We identified the common elements of reporting guidelines and examined the reporting quality of search methods in HIV behavioral intervention literature. Consistent with the findings from previous evaluations of reporting search methods of systematic reviews in other fields, our review shows a lack of full and transparent reporting within systematic reviews even though a plethora of guidelines exist. This review underscores the need for promoting the completeness of and adherence to transparent systematic search reporting within systematic reviews.
Fairness heuristic theory: valid but not empirical.
Arnadóttir, Steinvör Pöll
2002-09-01
Fairness heuristic theory is concerned with how people react to outcomes of their dealings with authorities, and makes some predictions concerning the relationship between perceived fairness of procedures, perceived fairness of outcomes and acceptance of outcomes. Although considerable effort has been put into establishing empirical evidence for the theory, it is argued that such efforts have no bearing upon the truth of the theory. Central propositions of fairness heuristic theory that have recently been tested empirically are examined and found to be nonempirical and noncontingent. The propositions, it is argued, are necessary truths of commonsense psychology that are not falsifiable by empirical outcomes. Hence, empirical research designed to test them, it is argued, is fruitless and misguided.
ERIC Educational Resources Information Center
Vaucher, Marius
1980-01-01
This study defines the notion of communication methodology, situates the context in which it operates, and concentrates on the problem of the acquisition of knowledge in general, and of language acquisition, in particular. From the notion of methodology, the study moves to the method of global communication, that is, a method comprising four…
Heuristics and Biases in Military Decision Making
2010-10-01
to embrace improvisation and reflection.3 The theory of reflection-in-action requires practitioners to question the structure of assumptions within...how we make decisions shape these heuristics and their accompanying biases. The theory of reflection-in-action and its implications for decision... theory ) which sought to describe human behavior as a rational maximization of cost-benefit decisions, Kahne- man and Tversky provided a simple
Structuring Decisions. The Role of Structuring Heuristics
1981-08-01
tasks to be carried out: 1. Develop interactive Multiattribute Utility Theory ( MAUT ) aid with dynamic capability, 2. Collect and investigate heuristics... Multiattribute Utility Theory When the value of a consequence can be completely described in terms of money (e.g., worth $1,000), utility assessment may be...C. Application of multiattribute utility theory . In H. Junger- mann & G. de Zeeuw (Eds.), Decision making and change in human affairs. Amsterdam
Heuristic Automation for Decluttering Tactical Displays
2007-01-01
2001b). Heuristic Automation for Decluttering Tactical Displays Mark St. John, Harvey S. Smallman, and Daniel I. Manes , Pacific Science...an ill-defined and com- plex function of many aircraft attributes and requires years of experience to train (Kaempf, Wolf , & Miller,1993; Liebhaber...best judgment. According to this design strategy (e.g., Parasuraman & Riley, 1997, pp. 244, 249; St. John & Manes , 2002; St. John, Oonk, & Osga, 2000
Research on Topology Optimization of Truss Structures Based on the Improved Group Search Optimizer
NASA Astrophysics Data System (ADS)
Haobin, Xie; Feng, Liu; Lijuan, Li; Chun, Wang
2010-05-01
In this paper, a novel optimization algorithm, named group search optimizer (GSO), is used to truss structure topology optimization. The group search optimizer is improved in two aspects which including using harmony memory and adhering to the boundary. Two topology methods, such as heuristic topology and discretization of topology variables, are incorporated with GSO to make sure that the topology optimization works well. In the end of the paper, two numerical examples were used to test the improved GSO. Calculation results show that the improved GSO is feasible and robust for truss topology optimization.
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…
Nakagawa, Toshiaki; Hara, Takeshi; Fujita, Hiroshi; Horita, Katsuhei; Iwase, Takuji; Endo, Tokiko
2008-07-01
In this study, we developed an automatic extraction scheme for the precise recognition of the contours of masses on digital mammograms in order to improve a computer-aided diagnosis (CAD) system. We propose a radial-searching contour extraction method based on a modified active contour model (ACM). In this technique, after determining the central point of a mass by searching for the direction of the density gradient, we arranged an initial contour at the central point, and the movement of a control point was limited to directions radiating from the central point. Moreover, it became possible to increase the extraction accuracy by sorting out the pixel used for processing and using two images-an edge-intensity image and a degree-of-separation image defined based on the pixel-value histogram-for calculation of the image forces used for constraints on deformation of the ACM. We investigated the accuracy of the automated extraction method by using 53 masses with several "difficult contours" on 53 digitized mammograms. The extraction results were compared quantitatively with the "correct segmentation" represented by an experienced physician's sketches. The numbers of cases in which the extracted region corresponded to the correct region with overlap ratios of more than 81 and 61% were 30 and 45, respectively. The initial results obtained with this technique show that it will be useful for the segmentation of masses in CAD schemes.
A hybrid solar panel maximum power point search method that uses light and temperature sensors
NASA Astrophysics Data System (ADS)
Ostrowski, Mariusz
2016-04-01
Solar cells have low efficiency and non-linear characteristics. To increase the output power solar cells are connected in more complex structures. Solar panels consist of series of connected solar cells with a few bypass diodes, to avoid negative effects of partial shading conditions. Solar panels are connected to special device named the maximum power point tracker. This device adapt output power from solar panels to load requirements and have also build in a special algorithm to track the maximum power point of solar panels. Bypass diodes may cause appearance of local maxima on power-voltage curve when the panel surface is illuminated irregularly. In this case traditional maximum power point tracking algorithms can find only a local maximum power point. In this article the hybrid maximum power point search algorithm is presented. The main goal of the proposed method is a combination of two algorithms: a method that use temperature sensors to track maximum power point in partial shading conditions and a method that use illumination sensor to track maximum power point in equal illumination conditions. In comparison to another methods, the proposed algorithm uses correlation functions to determinate the relationship between values of illumination and temperature sensors and the corresponding values of current and voltage in maximum power point. In partial shading condition the algorithm calculates local maximum power points bases on the value of temperature and the correlation function and after that measures the value of power on each of calculated point choose those with have biggest value, and on its base run the perturb and observe search algorithm. In case of equal illumination algorithm calculate the maximum power point bases on the illumination value and the correlation function and on its base run the perturb and observe algorithm. In addition, the proposed method uses a special coefficient modification of correlation functions algorithm. This sub
[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.
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
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.
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.
Three Dimensional Defect Reconstruction Using State Space Search and Woodbury's Substructure Method
NASA Astrophysics Data System (ADS)
Liu, X.; Deng, Y.; Li, Y.; Udpa, L.; Udpa, S. S.
2010-02-01
This paper introduces a model-based approach to reconstruct the three-dimensional defect profiles using eddy-current heat exchanger tube inspection signals. The method uses a Woodbury's substructure finite element forward model to simulate the underlying physics, a state space defect representation, and a tree search algorithm to solve the inverse problem. The advantage of the substructure method is that it divides the whole solution domain into two substructures and only the region of interest (ROI) with dramatic material changes will be updated in each iterative step. Since the number of elements inside the ROI is very small compared with the number of elements in the entire mesh, the computational effort needed in both LU factorization and coefficient matrix assembly is reduced. Therefore, the execution time is reduced significantly making the inversion very efficient. The initial inversion results are presented to confirm the validity of the approach.
"The Gaze Heuristic:" Biography of an Adaptively Rational Decision Process.
Hamlin, Robert P
2017-02-21
This article is a case study that describes the natural and human history of the gaze heuristic. The gaze heuristic is an interception heuristic that utilizes a single input (deviation from a constant angle of approach) repeatedly as a task is performed. Its architecture, advantages, and limitations are described in detail. A history of the gaze heuristic is then presented. In natural history, the gaze heuristic is the only known technique used by predators to intercept prey. In human history the gaze heuristic was discovered accidentally by Royal Air Force (RAF) fighter command just prior to World War II. As it was never discovered by the Luftwaffe, the technique conferred a decisive advantage upon the RAF throughout the war. After the end of the war in America, German technology was combined with the British heuristic to create the Sidewinder AIM9 missile, the most successful autonomous weapon ever built. There are no plans to withdraw it or replace its guiding gaze heuristic. The case study demonstrates that the gaze heuristic is a specific heuristic type that takes a single best input at the best time (take the best(2) ). Its use is an adaptively rational response to specific, rapidly evolving decision environments that has allowed those animals/humans/machines who use it to survive, prosper, and multiply relative to those who do not.
Include heuristics in protection systems
Kobyakov, A.I. )
1993-02-01
Automatic systems based on interlock principles are the most popular method of protecting plants from hazards. Nevertheless, such systems have specific shortcomings. The major one comes from the fact that protection controls are activated at the stage of break down mode development, and not at the moments of pre-fault status origin. It is possible to design protection controls that account for information relating to pre-fault status, causes, locations, and potential danger severity. A method of recreating automatic protection systems (APS) with functioning and structural organization is based on the accepted strategy of potentially hazardous plant protection. APS features these basic functions: pre-fault status classification and diagnostic providing protection controls that depend on pre-fault status type and cause, and suppression process analysis and protection controls correction. The system functions as a parallel/series process. Pre-fault status location data with related classification and diagnostics are based on current startup information. A protection control vector is formed that guarantees pre-fault status suppression. This paper describes these features.
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.
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
Search Space Characterization for a Telescope Scheduling Application
NASA Technical Reports Server (NTRS)
Bresina, John; Drummond, Mark; Swanson, Keith; Friedland, Peter (Technical Monitor)
1994-01-01
This paper presents a technique for statistically characterizing a search space and demonstrates the use of this technique within a practical telescope scheduling application. The characterization provides the following: (i) an estimate of the search space size, (ii) a scaling technique for multi-attribute objective functions and search heuristics, (iii) a "quality density function" for schedules in a search space, (iv) a measure of a scheduler's performance, and (v) support for constructing and tuning search heuristics. This paper describes the random sampling algorithm used to construct this characterization and explains how it can be used to produce this information. As an example, we include a comparative analysis of an heuristic dispatch scheduler and a look-ahead scheduler that performs greedy search.
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.
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.
NASA Astrophysics Data System (ADS)
Gao, Shangce; Cao, Qiping; Vairappan, Catherine; Zhang, Jianchen; Tang, Zheng
This paper describes an improved local search method for synthesizing arbitrary Multiple-Valued Logic (MVL) function. In our approach, the MVL function is mapped from its algebraic presentation (sum-of-products form) on a multiple-layered network based on the functional completeness property. The output of the network is evaluated based on two metrics of correctness and optimality. A local search embedded with chaotic dynamics is utilized to train the network in order to minimize the MVL functions. With the characteristics of pseudo-randomness, ergodicity and irregularity, both the search sequence and solution neighbourhood generated by chaotic variables enables the system to avoid local minimum settling and improves the solution quality. Simulation results based on 2-variable 4-valued MVL functions and some other large instances also show that the improved local search learning algorithm outperforms the traditional methods in terms of the correctness and the average number of product terms required to realize a given MVL function.
Exact and heuristic algorithms for weighted cluster editing.
Rahmann, Sven; Wittkop, Tobias; Baumbach, Jan; Martin, Marcel; Truss, Anke; Böcker, Sebastian
2007-01-01
Clustering objects according to given similarity or distance values is a ubiquitous problem in computational biology with diverse applications, e.g., in defining families of orthologous genes, or in the analysis of microarray experiments. While there exists a plenitude of methods, many of them produce clusterings that can be further improved. "Cleaning up" initial clusterings can be formalized as projecting a graph on the space of transitive graphs; it is also known as the cluster editing or cluster partitioning problem in the literature. In contrast to previous work on cluster editing, we allow arbitrary weights on the similarity graph. To solve the so-defined weighted transitive graph projection problem, we present (1) the first exact fixed-parameter algorithm, (2) a polynomial-time greedy algorithm that returns the optimal result on a well-defined subset of "close-to-transitive" graphs and works heuristically on other graphs, and (3) a fast heuristic that uses ideas similar to those from the Fruchterman-Reingold graph layout algorithm. We compare quality and running times of these algorithms on both artificial graphs and protein similarity graphs derived from the 66 organisms of the COG dataset.
Analysis of methods for growth detection in the search for extraterrestrial life.
Merek, E L; Oyama, V I
1968-05-01
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.
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.
A method in search of a theory: peer education and health promotion.
Turner, G; Shepherd, J
1999-04-01
Peer education has grown in popularity and practice in recent years in the field of health promotion. However, advocates of peer education rarely make reference to theories in their rationale for particular projects. In this paper the authors review a selection of commonly cited theories, and examine to what extent they have value and relevance to peer education in health promotion. Beginning from an identification of 10 claims made for peer education, each theory is examined in terms of the scope of the theory and evidence to support it in practice. The authors conclude that, whilst most theories have something to offer towards an explanation of why peer education might be effective, most theories are limited in scope and there is little empirical evidence in health promotion practice to support them. Peer education would seem to be a method in search of a theory rather than the application of theory to practice.
In search of blood--detection of minute particles using spectroscopic methods.
De Wael, K; Lepot, L; Gason, F; Gilbert, B
2008-08-25
An examination protocol for rapid detection of remnants of blood particles on garments of suspects in bloody murder cases is described. Microparticles of blood are sampled along with fibres and hairs using the tape lifting method. The tapings are searched with a low power microscope for red particles with morphology similar to blood. Presumed blood traces are further examined using microspectrophotometry on the cut out piece of taping. The typical visible spectrum of haemoglobin is characteristic for blood. Alternatively Raman spectroscopy can be used to measure the characteristic vibrational spectrum of haemoglobin. At a later stage, these particles may be removed from the piece of taping in order to extract the blood and attempt to obtain a genetic profile.
NASA Astrophysics Data System (ADS)
Bennett, Joseph W.; Rabe, Karin M.
2012-11-01
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(Sb1/2Mn1/2)O3 as a candidate semiconducting ferroelectric; (2) polar derivatives of schafarzikite MSb2O4; and (3) ferroelectric semiconductors with formula M2P2(S,Se)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.
FLASHFLOOD: A 3D Field-based similarity search and alignment method for flexible molecules
NASA Astrophysics Data System (ADS)
Pitman, Michael C.; Huber, Wolfgang K.; Horn, Hans; Krämer, Andreas; Rice, Julia E.; Swope, William C.
2001-07-01
A three-dimensional field-based similarity search and alignment method for flexible molecules is introduced. The conformational space of a flexible molecule is represented in terms of fragments and torsional angles of allowed conformations. A user-definable property field is used to compute features of fragment pairs. Features are generalizations of CoMMA descriptors (Silverman, B.D. and Platt, D.E., J. Med. Chem., 39 (1996) 2129.) that characterize local regions of the property field by its local moments. The features are invariant under coordinate system transformations. Features taken from a query molecule are used to form alignments with fragment pairs in the database. An assembly algorithm is then used to merge the fragment pairs into full structures, aligned to the query. Key to the method is the use of a context adaptive descriptor scaling procedure as the basis for similarity. This allows the user to tune the weights of the various feature components based on examples relevant to the particular context under investigation. The property fields may range from simple, phenomenological fields, to fields derived from quantum mechanical calculations. We apply the method to the dihydrofolate/methotrexate benchmark system, and show that when one injects relevant contextual information into the descriptor scaling procedure, better results are obtained more efficiently. We also show how the method works and include computer times for a query from a database that represents approximately 23 million conformers of seventeen flexible molecules.
NASA Astrophysics Data System (ADS)
Pasam, Gopi Krishna; Manohar, T. Gowri
2016-09-01
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.
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…
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…
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.
FocusHeuristics - expression-data-driven network optimization and disease gene prediction.
Ernst, Mathias; Du, Yang; Warsow, Gregor; Hamed, Mohamed; Endlich, Nicole; Endlich, Karlhans; Murua Escobar, Hugo; Sklarz, Lisa-Madeleine; Sender, Sina; Junghanß, Christian; Möller, Steffen; Fuellen, Georg; Struckmann, Stephan
2017-02-16
To identify genes contributing to disease phenotypes remains a challenge for bioinformatics. Static knowledge on biological networks is often combined with the dynamics observed in gene expression levels over disease development, to find markers for diagnostics and therapy, and also putative disease-modulatory drug targets and drugs. The basis of current methods ranges from a focus on expression-levels (Limma) to concentrating on network characteristics (PageRank, HITS/Authority Score), and both (DeMAND, Local Radiality). We present an integrative approach (the FocusHeuristics) that is thoroughly evaluated based on public expression data and molecular disease characteristics provided by DisGeNet. The FocusHeuristics combines three scores, i.e. the log fold change and another two, based on the sum and difference of log fold changes of genes/proteins linked in a network. A gene is kept when one of the scores to which it contributes is above a threshold. Our FocusHeuristics is both, a predictor for gene-disease-association and a bioinformatics method to reduce biological networks to their disease-relevant parts, by highlighting the dynamics observed in expression data. The FocusHeuristics is slightly, but significantly better than other methods by its more successful identification of disease-associated genes measured by AUC, and it delivers mechanistic explanations for its choice of genes.
FocusHeuristics – expression-data-driven network optimization and disease gene prediction
Ernst, Mathias; Du, Yang; Warsow, Gregor; Hamed, Mohamed; Endlich, Nicole; Endlich, Karlhans; Murua Escobar, Hugo; Sklarz, Lisa-Madeleine; Sender, Sina; Junghanß, Christian; Möller, Steffen; Fuellen, Georg; Struckmann, Stephan
2017-01-01
To identify genes contributing to disease phenotypes remains a challenge for bioinformatics. Static knowledge on biological networks is often combined with the dynamics observed in gene expression levels over disease development, to find markers for diagnostics and therapy, and also putative disease-modulatory drug targets and drugs. The basis of current methods ranges from a focus on expression-levels (Limma) to concentrating on network characteristics (PageRank, HITS/Authority Score), and both (DeMAND, Local Radiality). We present an integrative approach (the FocusHeuristics) that is thoroughly evaluated based on public expression data and molecular disease characteristics provided by DisGeNet. The FocusHeuristics combines three scores, i.e. the log fold change and another two, based on the sum and difference of log fold changes of genes/proteins linked in a network. A gene is kept when one of the scores to which it contributes is above a threshold. Our FocusHeuristics is both, a predictor for gene-disease-association and a bioinformatics method to reduce biological networks to their disease-relevant parts, by highlighting the dynamics observed in expression data. The FocusHeuristics is slightly, but significantly better than other methods by its more successful identification of disease-associated genes measured by AUC, and it delivers mechanistic explanations for its choice of genes. PMID:28205611
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.
Kromin, A A; Ignatova, Yu P
2014-02-01
A method for registration of the sniffing component of the search behavior in rabbits subjected to food deprivation is suggested. Pulsed activities of the muscles controlling the movements of the wings of the nostrils and the pressure in the nasal cavity are recorded simultaneously. The method allows accurate artifact-free registration of the time and amplitude parameters of the sniffing component of the search behavior. The registration is realized on an MP150 programmed complex, consisting of EMG 100C biopotential amplifiers and Samba 202 intracavitary pressure recorder. The method allows synchronous real-time registration of pulsed activities of the muscles setting in motion the wings of the nostrils and the changes in the intranasal pressure in the course of search behavior of animals under conditions of food deprivation without limiting their locomotor activity.
Heuristics for test recognition using contextual information
NASA Astrophysics Data System (ADS)
Baraghimian, Tony
1995-01-01
Competitive electronic imaging systems are emerging due to rapidly declining processing power and storage costs. Imaging converts information on paper to electronic pictures. For applications involving large quantities of paper documents, the resulting pictures are further processed by automated character recognition systems, resulting in a text representation of the original document. Current character recognition accuracy varies from one implementation to the next, and greatly depends on each particular application. We define a set of information fusion rules for combining character recognition system output. The combined result has a higher character recognition accuracy and lower error rate than either of the individual recognizer outputs taken separately. This new set of fusion heuristics takes advantage of the following information from multiple text string recognition systems simultaneously: (1) multiple hypotheses and associated confidences for each character in a text string; (2) multiple text string segmentation hypotheses; (3) separate or combined hypotheses for both uppercase and lowercase alphabetic characters; and (4) overall text string hypotheses and associated confidences. Traditionally, only the last of these four information groups is used for fusion of multiple classifications within character recognition systems. We report on a nationally sponsored character recognition benchmark, with results indicating increased accuracy using the heuristic rules described.
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.
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.
DISCOVER: a feature-based discriminative method for motif search in complex genomes
Fu, Wenjie; Ray, Pradipta; Xing, Eric P.
2009-01-01
Motivation: Identifying transcription factor binding sites (TFBSs) encoding complex regulatory signals in metazoan genomes remains a challenging problem in computational genomics. Due to degeneracy of nucleotide content among binding site instances or motifs, and intricate ‘grammatical organization’ of motifs within cis-regulatory modules (CRMs), extant pattern matching-based in silico motif search methods often suffer from impractically high false positive rates, especially in the context of analyzing large genomic datasets, and noisy position weight matrices which characterize binding sites. Here, we try to address this problem by using a framework to maximally utilize the information content of the genomic DNA in the region of query, taking cues from values of various biologically meaningful genetic and epigenetic factors in the query region such as clade-specific evolutionary parameters, presence/absence of nearby coding regions, etc. We present a new method for TFBS prediction in metazoan genomes that utilizes both the CRM architecture of sequences and a variety of features of individual motifs. Our proposed approach is based on a discriminative probabilistic model known as conditional random fields that explicitly optimizes the predictive probability of motif presence in large sequences, based on the joint effect of all such features. Results: This model overcomes weaknesses in earlier methods based on less effective statistical formalisms that are sensitive to spurious signals in the data. We evaluate our method on both simulated CRMs and real Drosophila sequences in comparison with a wide spectrum of existing models, and outperform the state of the art by 22% in F1 score. Availability and Implementation: The code is publicly available at http://www.sailing.cs.cmu.edu/discover.html. Contact: epxing@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19478006
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…
Individual Heuristics and the Dynamics of Cooperation in Large Groups.
ERIC Educational Resources Information Center
Messick, David M.; Liebrand, Wim B. G.
1995-01-01
Computer simulations are described in which pairs of simulated individuals in groups play a prisoner's dilemma game, with the choice to cooperate determined by one of three simple heuristics. Results reveal that the prevalence of cooperation depends on the heuristic used, value of the payoff, and the social comparison process. (SLD)
Use of Statistical Heuristics in Everyday Inductive Reasoning.
ERIC Educational Resources Information Center
Nisbett, Richard E.; And Others
1983-01-01
In everyday reasoning, people use statistical heuristics (judgmental tools that are rough intuitive equivalents of statistical principles). Use of statistical heuristics is more likely when (1) sampling is clear, (2) the role of chance is clear, (3) statistical reasoning is normative for the event, or (4) the subject has had training in…
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 ...
Does the inherence heuristic take us to psychological essentialism?
Marmodoro, Anna; Murphy, Robin A; Baker, A G
2014-10-01
We argue that the claim that essence-based causal explanations emerge, hydra-like, from an inherence heuristic is incomplete. No plausible mechanism for the transition from concrete properties, or cues, to essences is provided. Moreover, the fundamental shotgun and storytelling mechanisms of the inherence heuristic are not clearly enough specified to distinguish them, developmentally, from associative or causal networks.
Azad, Abdus Salam; Islam, Md Monirul; Chakraborty, Saikat
2017-01-27
The vehicle routing problem (VRP) is a widely studied combinatorial optimization problem. We introduce a variant of the multidepot and periodic VRP (MDPVRP) and propose a heuristic initialized stochastic memetic algorithm to solve it. The main challenge in designing such an algorithm for a large combinatorial optimization problem is to avoid premature convergence by maintaining a balance between exploration and exploitation of the search space. We employ intelligent initialization and stochastic learning to address this challenge. The intelligent initialization technique constructs a population by a mix of random and heuristic generated solutions. The stochastic learning enhances the solutions' quality selectively using simulated annealing with a set of random and heuristic operators. The hybridization of randomness and greediness in the initialization and learning process helps to maintain the balance between exploration and exploitation. Our proposed algorithm has been tested extensively on the existing benchmark problems and outperformed the baseline algorithms by a large margin. We further compared our results with that of the state-of-the-art algorithms working under MDPVRP formulation and found a significant improvement over their results.
A grammar based methodology for structural motif finding in ncRNA database search.
Quest, Daniel; Tapprich, William; Ali, Hesham
2007-01-01
In recent years, sequence database searching has been conducted through local alignment heuristics, pattern-matching, and comparison of short statistically significant patterns. While these approaches have unlocked many clues as to sequence relationships, they are limited in that they do not provide context-sensitive searching capabilities (e.g. considering pseudoknots, protein binding positions, and complementary base pairs). Stochastic grammars (hidden Markov models HMMs and stochastic context-free grammars SCFG) do allow for flexibility in terms of local context, but the context comes at the cost of increased computational complexity. In this paper we introduce a new grammar based method for searching for RNA motifs that exist within a conserved RNA structure. Our method constrains computational complexity by using a chain of topology elements. Through the use of a case study we present the algorithmic approach and benchmark our approach against traditional methods.
NASA Astrophysics Data System (ADS)
Akhmedova, Sh; Semenkin, E.
2017-02-01
Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.
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
Heuristics: foundations for a novel approach to medical decision making.
Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V
2015-03-01
Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.
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.
Thermodynamic ground state of MgB{sub 6} predicted from first principles structure search methods
Wang, Hui; LeBlanc, K. A.; Gao, Bo; Yao, Yansun
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.
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.
Approach to design neural cryptography: a generalized architecture and a heuristic rule.
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.
Regularity of free boundaries a heuristic retro
Caffarelli, Luis A.; Shahgholian, Henrik
2015-01-01
This survey concerns regularity theory of a few free boundary problems that have been developed in the past half a century. Our intention is to bring up different ideas and techniques that constitute the fundamentals of the theory. We shall discuss four different problems, where approaches are somewhat different in each case. Nevertheless, these problems can be divided into two groups: (i) obstacle and thin obstacle problem; (ii) minimal surfaces, and cavitation flow of a perfect fluid. In each case, we shall only discuss the methodology and approaches, giving basic ideas and tools that have been specifically designed and tailored for that particular problem. The survey is kept at a heuristic level with mainly geometric interpretation of the techniques and situations in hand. PMID:26261372
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
2001-03-01
employs a meta-heuristic, Scatter Search, to guide the search of the multi-scenario solution space obtained by the evaluations of CFAM, the model currently used to respond to single theater scenario objectives. A Visual Basic
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
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
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.
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
Relevancy Ranking of Satellite Dataset Search Results
NASA Technical Reports Server (NTRS)
Lynnes, Christopher; Quinn, Patrick; Norton, James
2017-01-01
As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.
Climate change on the Colorado River: a method to search for robust management strategies
NASA Astrophysics Data System (ADS)
Keefe, R.; Fischbach, J. R.
2010-12-01
The Colorado River is a principal source of water for the seven Basin States, providing approximately 16.5 maf per year to users in the southwestern United States and Mexico. Though the dynamics of the river ensure Upper Basin users a reliable supply of water, the three Lower Basin states (California, Nevada, and Arizona) are in danger of delivery interruptions as Upper Basin demand increases and climate change threatens to reduce future streamflows. In light of the recent drought and uncertain effects of climate change on Colorado River flows, we evaluate the performance of a suite of policies modeled after the shortage sharing agreement adopted in December 2007 by the Department of the Interior. We build on the current literature by using a simplified model of the Lower Colorado River to consider future streamflow scenarios given climate change uncertainty. We also generate different scenarios of parametric consumptive use growth in the Upper Basin and evaluate alternate management strategies in light of these uncertainties. Uncertainty associated with climate change is represented with a multi-model ensemble from the literature, using a nearest neighbor perturbation to increase the size of the ensemble. We use Robust Decision Making to compare near-term or long-term management strategies across an ensemble of plausible future scenarios with the goal of identifying one or more approaches that are robust to alternate assumptions about the future. This method entails using search algorithms to quantitatively identify vulnerabilities that may threaten a given strategy (including the current operating policy) and characterize key tradeoffs between strategies under different scenarios.
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.
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.
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
Methods for Documenting Systematic Review Searches: A Discussion of Common Issues
ERIC Educational Resources Information Center
Rader, Tamara; Mann, Mala; Stansfield, Claire; Cooper, Chris; Sampson, Margaret
2014-01-01
Introduction: As standardized reporting requirements for systematic reviews are being adopted more widely, review authors are under greater pressure to accurately record their search process. With careful planning, documentation to fulfill the Preferred Reporting Items for Systematic Reviews and Meta-Analyses requirements can become a valuable…
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 and algorithmic processing in English, mathematics, and science education.
Sharps, Matthew J; Hess, Adam B; Price-Sharps, Jana L; Teh, Jane
2008-01-01
Many college students experience difficulties in basic academic skills. Recent research suggests that much of this difficulty may lie in heuristic competency--the ability to use and successfully manage general cognitive strategies. In the present study, the authors evaluated this possibility. They compared participants' performance on a practice California Basic Educational Skills Test and on a series of questions in the natural sciences with heuristic and algorithmic performance on a series of mathematics and reading comprehension exercises. Heuristic competency in mathematics was associated with better scores in science and mathematics. Verbal and algorithmic skills were associated with better reading comprehension. These results indicate the importance of including heuristic training in educational contexts and highlight the importance of a relatively domain-specific approach to questions of cognition in higher education.
Impact of heuristics in clustering large biological networks.
Shafin, Md Kishwar; Kabir, Kazi Lutful; Ridwan, Iffatur; Anannya, Tasmiah Tamzid; Karim, Rashid Saadman; Hoque, Mohammad Mozammel; Rahman, M Sohel
2015-12-01
Traditional clustering algorithms often exhibit poor performance for large networks. On the contrary, greedy algorithms are found to be relatively efficient while uncovering functional modules from large biological networks. The quality of the clusters produced by these greedy techniques largely depends on the underlying heuristics employed. Different heuristics based on different attributes and properties perform differently in terms of the quality of the clusters produced. This motivates us to design new heuristics for clustering large networks. In this paper, we have proposed two new heuristics and analyzed the performance thereof after incorporating those with three different combinations in a recently celebrated greedy clustering algorithm named SPICi. We have extensively analyzed the effectiveness of these new variants. The results are found to be promising.
Novels as a Source for Heuristics about Interpersonal Communication.
ERIC Educational Resources Information Center
Kougl, Kathleen Mary
1983-01-01
Examines the interpersonal communication of main characters in three novels. Concludes that the heuristic propositions that emerge from this study might be useful in the study and understanding of real life interpersonal experiences. (PD)
Adabor, Emmanuel S; Acquaah-Mensah, George K; Oduro, Francis T
2015-02-01
Bayesian Networks have been used for the inference of transcriptional regulatory relationships among genes, and are valuable for obtaining biological insights. However, finding optimal Bayesian Network (BN) is NP-hard. Thus, heuristic approaches have sought to effectively solve this problem. In this work, we develop a hybrid search method combining Simulated Annealing with a Greedy Algorithm (SAGA). SAGA explores most of the search space by undergoing a two-phase search: first with a Simulated Annealing search and then with a Greedy search. Three sets of background-corrected and normalized microarray datasets were used to test the algorithm. BN structure learning was also conducted using the datasets, and other established search methods as implemented in BANJO (Bayesian Network Inference with Java Objects). The Bayesian Dirichlet Equivalence (BDe) metric was used to score the networks produced with SAGA. SAGA predicted transcriptional regulatory relationships among genes in networks that evaluated to higher BDe scores with high sensitivities and specificities. Thus, the proposed method competes well with existing search algorithms for Bayesian Network structure learning of transcriptional regulatory networks.
A heuristic model of sensory adaptation.
McBurney, Donald H; Balaban, Carey D
2009-11-01
Adaptation is a universal process in organisms as diverse as bacteria and humans, and across the various senses. This article proposes a simple, heuristic, mathematical model containing tonic and phasic processes. The model demonstrates properties not commonly associated with adaptation, such as increased sensitivity to changes, range shifting, and phase lead. Changes in only four parameters permit the model to predict empirical psychophysical data from different senses. The relatively prolonged time courses of responses to oral and topical capsaicin are used to illustrate and validate this mathematical modeling approach for different stimulus profiles. Other examples of phenomena elucidated by this modeling approach include the time courses of taste sensation, brightness perception, loudness perception, cross-adaptation to oral irritants, and cutaneous mechanoreception. It also predicts such apparently unrelated phenomena as perceived alcohol intoxication, habituation, and drug tolerance. Because the integration of phasic and tonic components is a conservative, highly efficacious solution to a ubiquitous biological challenge, sensory adaptation is seen as an evolutionary adaptation, and as a prominent feature of Mother Nature's small bag of tricks.
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".
NASA Astrophysics Data System (ADS)
Suharsono; Nurdian, S. W.; Palupi, I. R.
2016-11-01
Relocating hypocenter is a way to improve the velocity model of the subsurface. One of the method is Grid Search. To perform the distribution of the velocity in subsurface by tomography method, it is used the result of relocating hypocenter to be a reference for subsurface analysis in volcanic and major structural patterns, such as in Central Java. The main data of this study is the earthquake data recorded from 1952 to 2012 with the P wave number is 9162, the number of events is 2426 were recorded by 30 stations located in the vicinity of Central Java. Grid search method has some advantages they are: it can relocate the hypocenter more accurate because this method is dividing space lattice model into blocks, and each grid block can only be occupied by one point hypocenter. Tomography technique is done by travel time data that has had relocated with inversion pseudo bending method. Grid search relocated method show that the hypocenter's depth is shallower than before and the direction is to the south, the hypocenter distribution is modeled into the subduction zone between the continent of Eurasia with the Indo-Australian with an average angle of 14 °. The tomography results show the low velocity value is contained under volcanoes with value of -8% to -10%, then the pattern of the main fault structure in Central Java can be description by the results of tomography at high velocity that is from 8% to 10% with the direction is northwest and northeast-southwest.
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
Neural basis of scientific innovation induced by heuristic prototype.
Luo, Junlong; Li, Wenfu; 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.
NASA Astrophysics Data System (ADS)
Mohamed, Nur Syarafina; Mamat, Mustafa; Rivaie, Mohd
2016-11-01
Conjugate gradient (CG) methods are one of the tools in optimization. Due to its low computational memory requirement, this method is used in solving several of nonlinear unconstrained optimization problems from designs, economics, physics and engineering. In this paper, a new modification of CG family coefficient (βk) is proposed and posses global convergence under exact line search direction. Numerical experimental results based on the number of iterations and central processing unit (CPU) time show that the new βk performs better than some other well known CG methods under some standard test functions.
ParAlign: a parallel sequence alignment algorithm for rapid and sensitive database searches.
Rognes, T
2001-04-01
There is a need for faster and more sensitive algorithms for sequence similarity searching in view of the rapidly increasing amounts of genomic sequence data available. Parallel processing capabilities in the form of the single instruction, multiple data (SIMD) technology are now available in common microprocessors and enable a single microprocessor to perform many operations in parallel. The ParAlign algorithm has been specifically designed to take advantage of this technology. The new algorithm initially exploits parallelism to perform a very rapid computation of the exact optimal ungapped alignment score for all diagonals in the alignment matrix. Then, a novel heuristic is employed to compute an approximate score of a gapped alignment by combining the scores of several diagonals. This approximate score is used to select the most interesting database sequences for a subsequent Smith-Waterman alignment, which is also parallelised. The resulting method represents a substantial improvement compared to existing heuristics. The sensitivity and specificity of ParAlign was found to be as good as Smith-Waterman implementations when the same method for computing the statistical significance of the matches was used. In terms of speed, only the significantly less sensitive NCBI BLAST 2 program was found to outperform the new approach. Online searches are available at http://dna.uio.no/search/
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.
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.
Hiroyasu, Tomoyuki; Miyabe, Yota; Yokouchi, Hisatake
2011-01-01
Here, we propose a training data selection method using a Support Vector Machine (SVM) to predict the effects of anticancer drugs. Conventionally, SVM is used for distinguishing between several types of data. However, in the method proposed here, the SVM is used to distinguish areas with only one or two types of data. The proposed method treats training data selection as an optimization problem and involves application of a genetic algorithm (GA). Moreover, GA with local search was applied to find the solution as the target problem was difficult to find. The composition method of GA for proposed method was examined. To determine its effectiveness, the proposed method was applied to an artificial anticancer drug data set. The verification results showed that the proposed method can be used to create a verifiable and predictable discriminant function by training data selection.
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.
Wang, Jian; Evans, Julian R G
2005-01-01
This paper describes the design, construction, and operation of the London University Search Instrument (LUSI) which was recently commissioned to create and test combinatorial libraries of ceramic compositions. The instrument uses commercially available powders, milled as necessary to create thick-film libraries by ink-jet printing. Multicomponent mixtures are prepared by well plate reformatting of ceramic inks. The library tiles are robotically loaded into a flatbed furnace and, when fired, transferred to a 2-axis high-resolution measurement table fitted with a hot plate where measurements of, for example, optical or electrical properties can be made. Data are transferred to a dedicated high-performance computer. The possibilities for remote interrogation and search steering are discussed.
Benschop, Corina C G; van der Beek, Cornelis P; Meiland, Hugo C; van Gorp, Ankie G M; Westen, Antoinette A; Sijen, Titia
2011-08-01
To analyze DNA samples with very low DNA concentrations, various methods have been developed that sensitize short tandem repeat (STR) typing. Sensitized DNA typing is accompanied by stochastic amplification effects, such as allele drop-outs and drop-ins. Therefore low template (LT) DNA profiles are interpreted with care. One can either try to infer the genotype by a consensus method that uses alleles confirmed in replicate analyses, or one can use a statistical model to evaluate the strength of the evidence in a direct comparison with a known DNA profile. In this study we focused on the first strategy and we show that the procedure by which the consensus profile is assembled will affect genotyping reliability. In order to gain insight in the roles of replicate number and requested level of reproducibility, we generated six independent amplifications of samples of known donors. The LT methods included both increased cycling and enhanced capillary electrophoresis (CE) injection [1]. Consensus profiles were assembled from two to six of the replications using four methods: composite (include all alleles), n-1 (include alleles detected in all but one replicate), n/2 (include alleles detected in at least half of the replicates) and 2× (include alleles detected twice). We compared the consensus DNA profiles with the DNA profile of the known donor, studied the stochastic amplification effects and examined the effect of the consensus procedure on DNA database search results. From all these analyses we conclude that the accuracy of LT DNA typing and the efficiency of database searching improve when the number of replicates is increased and the consensus method is n/2. The most functional number of replicates within this n/2 method is four (although a replicate number of three suffices for samples showing >25% of the alleles in standard STR typing). This approach was also the optimal strategy for the analysis of 2-person mixtures, although modified search strategies may be
Lipkovich, Ilya; Dmitrienko, Alex; Denne, Jonathan; Enas, Gregory
2011-09-20
We propose a novel recursive partitioning method for identifying subgroups of subjects with enhanced treatment effects based on a differential effect search algorithm. The idea is to build a collection of subgroups by recursively partitioning a database into two subgroups at each parent group, such that the treatment effect within one of the two subgroups is maximized compared with the other subgroup. The process of data splitting continues until a predefined stopping condition has been satisfied. The method is similar to 'interaction tree' approaches that allow incorporation of a treatment-by-split interaction in the splitting criterion. However, unlike other tree-based methods, this method searches only within specific regions of the covariate space and generates multiple subgroups of potential interest. We develop this method and provide guidance on key topics of interest that include generating multiple promising subgroups using different splitting criteria, choosing optimal values of complexity parameters via cross-validation, and addressing Type I error rate inflation inherent in data mining applications using a resampling-based method. We evaluate the operating characteristics of the procedure using a simulation study and illustrate the method with a clinical trial example.
Evaluating Common De-Identification Heuristics for Personal Health Information
Jabbouri, Sam; Sams, Scott; Drouet, Youenn; Power, Michael
2006-01-01
Background With the growing adoption of electronic medical records, there are increasing demands for the use of this electronic clinical data in observational research. A frequent ethics board requirement for such secondary use of personal health information in observational research is that the data be de-identified. De-identification heuristics are provided in the Health Insurance Portability and Accountability Act Privacy Rule, funding agency and professional association privacy guidelines, and common practice. Objective The aim of the study was to evaluate whether the re-identification risks due to record linkage are sufficiently low when following common de-identification heuristics and whether the risk is stable across sample sizes and data sets. Methods Two methods were followed to construct identification data sets. Re-identification attacks were simulated on these. For each data set we varied the sample size down to 30 individuals, and for each sample size evaluated the risk of re-identification for all combinations of quasi-identifiers. The combinations of quasi-identifiers that were low risk more than 50% of the time were considered stable. Results The identification data sets we were able to construct were the list of all physicians and the list of all lawyers registered in Ontario, using 1% sampling fractions. The quasi-identifiers of region, gender, and year of birth were found to be low risk more than 50% of the time across both data sets. The combination of gender and region was also found to be low risk more than 50% of the time. We were not able to create an identification data set for the whole population. Conclusions Existing Canadian federal and provincial privacy laws help explain why it is difficult to create an identification data set for the whole population. That such examples of high re-identification risk exist for mainstream professions makes a strong case for not disclosing the high-risk variables and their combinations identified here
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.
Heuristic cognitive diagnosis when the Q-matrix is unknown.
Köhn, Hans-Friedrich; Chiu, Chia-Yi; Brusco, Michael J
2015-05-01
Cognitive diagnosis models of educational test performance rely on a binary Q-matrix that specifies the associations between individual test items and the cognitive attributes (skills) required to answer those items correctly. Current methods for fitting cognitive diagnosis models to educational test data and assigning examinees to proficiency classes are based on parametric estimation methods such as expectation maximization (EM) and Markov chain Monte Carlo (MCMC) that frequently encounter difficulties in practical applications. In response to these difficulties, non-parametric classification techniques (cluster analysis) have been proposed as heuristic alternatives to parametric procedures. These non-parametric classification techniques first aggregate each examinee's test item scores into a profile of attribute sum scores, which then serve as the basis for clustering examinees into proficiency classes. Like the parametric procedures, the non-parametric classification techniques require that the Q-matrix underlying a given test be known. Unfortunately, in practice, the Q-matrix for most tests is not known and must be estimated to specify the associations between items and attributes, risking a misspecified Q-matrix that may then result in the incorrect classification of examinees. This paper demonstrates that clustering examinees into proficiency classes based on their item scores rather than on their attribute sum-score profiles does not require knowledge of the Q-matrix, and results in a more accurate classification of examinees.
Identifying multiple influential spreaders by a heuristic clustering algorithm
NASA Astrophysics Data System (ADS)
Bao, Zhong-Kui; Liu, Jian-Guo; Zhang, Hai-Feng
2017-03-01
The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very "negligible". Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant.
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.
NASA Astrophysics Data System (ADS)
La Cour, Brian R.; Ostrove, Corey I.
2017-01-01
This paper describes a novel approach to solving unstructured search problems using a classical, signal-based emulation of a quantum computer. The classical nature of the representation allows one to perform subspace projections in addition to the usual unitary gate operations. Although bandwidth requirements will limit the scale of problems that can be solved by this method, it can nevertheless provide a significant computational advantage for problems of limited size. In particular, we find that, for the same number of noisy oracle calls, the proposed subspace projection method provides a higher probability of success for finding a solution than does an single application of Grover's algorithm on the same device.
NASA Astrophysics Data System (ADS)
Liu, Gia-Shie
2015-09-01
This study combines a new developed redundancy allocation heuristic approach, tabu search method, simulated annealing method and non-equilibrium simulated annealing method with a genetic algorithm to solve the system availability optimisation problem. Through four proposed combination methods applied in the initial system development period, the optimal allocations of component redundancy number, reliability level and maintenance rate can be obtained to minimise the total system cost under different configuration constraints. The sensitivity analysis is also conducted based on system weight, system volume, subsystem reliability requirement levels, the cost parameters associated with the reliability level and maintenance rate to provide very helpful information for the system design and development process. Finally, the performance comparison between four proposed combination availability optimisation methods is also implemented and the results clearly show that the combination method combining the new developed redundancy allocation heuristic approach with the genetic algorithm performs better than the other three combination methods in many aspects.
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.
NASA Astrophysics Data System (ADS)
Wei, Zeng Xin; Li, Guo Yin; Qi, Li Qun
2008-12-01
We propose two algorithms for nonconvex unconstrained optimization problems that employ Polak-Ribiere-Polyak conjugate gradient formula and new inexact line search techniques. We show that the new algorithms converge globally if the function to be minimized has Lipschitz continuous gradients. Preliminary numerical results show that the proposed methods for particularly chosen line search conditions are very promising.
ERIC Educational Resources Information Center
Putti, Alice
2011-01-01
This paper discusses student attitudes and beliefs on using the Science Writing Heuristic (SWH) in an advanced placement (AP) chemistry classroom. During the 2007 school year, the SWH was used in a class of 24 AP chemistry students. Using a Likert-type survey, student attitudes and beliefs on the process were determined. Methods for the study are…
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.
Gaussian model-based partitioning using iterated local search.
Brusco, Michael J; Shireman, Emilie; Steinley, Douglas; Brudvig, Susan; Cradit, J Dennis
2017-02-01
The emergence of Gaussian model-based partitioning as a viable alternative to K-means clustering fosters a need for discrete optimization methods that can be efficiently implemented using model-based criteria. A variety of alternative partitioning criteria have been proposed for more general data conditions that permit elliptical clusters, different spatial orientations for the clusters, and unequal cluster sizes. Unfortunately, many of these partitioning criteria are computationally demanding, which makes the multiple-restart (multistart) approach commonly used for K-means partitioning less effective as a heuristic solution strategy. As an alternative, we propose an approach based on iterated local search (ILS), which has proved effective in previous combinatorial data analysis contexts. We compared multistart, ILS and hybrid multistart-ILS procedures for minimizing a very general model-based criterion that assumes no restrictions on cluster size or within-group covariance structure. This comparison, which used 23 data sets from the classification literature, revealed that the ILS and hybrid heuristics generally provided better criterion function values than the multistart approach when all three methods were constrained to the same 10-min time limit. In many instances, these differences in criterion function values reflected profound differences in the partitions obtained.
Honda, Hidehito; Matsuka, Toshihiko; Ueda, Kazuhiro
2016-07-20
Some researchers on binary choice inference have argued that people make inferences based on simple heuristics, such as recognition, fluency, or familiarity. Others have argued that people make inferences based on available knowledge. To examine the boundary between heuristic and knowledge usage, we examine binary choice inference processes in terms of attribute substitution in heuristic use (Kahneman & Frederick, 2005). In this framework, it is predicted that people will rely on heuristic or knowledge-based inference depending on the subjective difficulty of the inference task. We conducted competitive tests of binary choice inference models representing simple heuristics (fluency and familiarity heuristics) and knowledge-based inference models. We found that a simple heuristic model (especially a familiarity heuristic model) explained inference patterns for subjectively difficult inference tasks, and that a knowledge-based inference model explained subjectively easy inference tasks. These results were consistent with the predictions of the attribute substitution framework. Issues on usage of simple heuristics and psychological processes are discussed.
High throughput heuristics for prioritizing human exposure to environmental chemicals.
Wambaugh, John F; Wang, Anran; Dionisio, Kathie L; Frame, Alicia; Egeghy, Peter; Judson, Richard; Setzer, R Woodrow
2014-11-04
The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understanding of health risks. We aim to develop a rapid heuristic method to determine potential human exposure to chemicals for application to the thousands of chemicals with little or no exposure data. We used Bayesian methodology to infer ranges of exposure consistent with biomarkers identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We performed linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using chemical descriptors and use information from multiple databases and structure-based calculators. Five descriptors are capable of explaining roughly 50% of the variability in geometric means across 106 NHANES chemicals for all the demographic groups, including children aged 6-11. We use these descriptors to estimate human exposure to 7968 chemicals, the majority of which have no other quantitative exposure prediction. For thousands of chemicals with no other information, this approach allows forecasting of average exposure intake of environmental chemicals.
CHOPIN, a heuristic model for long term transmission expansion planning
Latorre-Bayona, G. . Dept. de Ingenieria Electrica y Electronica); Perez-Arriaga, I.J. . Inst. de Investigacion Tecnologica)
1994-11-01
This paper describes the long term transmission expansion planning model CHOPIN. In CHOPIN, the network expansion is formulated as the static optimization problem of minimizing the global annual cost of electricity production, which is obtained as the sum of the annualized network investment cost, the operation cost and the reliability cost. The solution method takes advantage of the natural decomposition between the investment and operation submodels. The investment submodel is solved by a new heuristic procedure that in practice has invariably yielded the optimal plan. At the operation level CHOPIN optimizes over a multiplicity of scenarios which are characterized by the demand, the hydraulicity and the availability of components. The network is represented by any one out of four options: DC load flow (DCLF), transportation model and two hybrid models. Any of these models may consider the ohmic losses. The model is very efficient computationally; this fact was verified on test examples, as well as on the actual transmission expansion planning of the Spanish system.
Brain mechanisms of valuable scientific problem finding inspired by heuristic knowledge.
Dandan, Tong; Wenfu, Li; Tianen, Dai; Nusbaum, Howard C; Jiang, Qiu; Qinglin, Zhang
2013-08-01
Heuristics through the application of heuristic knowledge to the creation of imitation devices may be one of the most common processes in scientific innovation. In particular, heuristics suggests that innovation includes the automatic activation of heuristic knowledge and formation of novel associations between heuristic knowledge and problem situations. In this study, 76 scientific innovation problem situations were selected as materials. Among these, 36 contain related heuristic knowledge and 40 have no such information. Through functional magnetic resonance imaging, the learning-testing paradigm was used to explore the brain mechanisms of scientific problem finding inspired by heuristic knowledge. Participants were asked to find a problem on the basis of a given innovation problem situation. Two scenarios were presented: finding scientific problems with related heuristic knowledge and finding conventional problems without related heuristic knowledge. The authors assumed that the regions in the brain significantly activated by the finding scientific problems with related heuristic knowledge condition compared with the finding normal problems without related heuristic knowledge condition are relevant to the brain mechanisms of scientific problem finding inspired by heuristic knowledge. The first scenario more significantly activated the left precuneus and left angular gyrus than did the second scenario. These findings suggest that the precuneus is relevant to the successful storage and retrieval of heuristic knowledge and that the left angular gyrus is involved in the formation of novel associations between heuristic knowledge and problem situations for finding scientific problems.
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.
User Interface Problems of a Nationwide Inpatient Information System: A Heuristic Evaluation
Atashi, Alireza; Azizi, Amirabbas; Dadashi, Ali
2016-01-01
Summary Introduction While studies have shown that usability evaluation could uncover many design problems of health information systems, the usability of health information systems in developing countries using their native language is poorly studied. The objective of this study was to evaluate the usability of a nationwide inpatient information system used in many academic hospitals in Iran. Material and Methods Three trained usability evaluators independently evaluated the system using Nielsen’s 10 usability heuristics. The evaluators combined identified problems in a single list and independently rated the severity of the problems. We statistically compared the number and severity of problems identified by HIS experienced and non-experienced evaluators. Results A total of 158 usability problems were identified. After removing duplications 99 unique problems were left. The highest mismatch with usability principles was related to “Consistency and standards” heuristic (25%) and the lowest related to “Flexibility and efficiency of use” (4%). The average severity of problems ranged from 2.4 (Major problem) to 3.3 (Catastrophe problem). The experienced evaluator with HIS identified significantly more problems and gave higher severities to problems (p<0.02). Discussion Heuristic Evaluation identified a high number of usability problems in a widely used inpatient information system in many academic hospitals. These problems, if remain unsolved, may waste users’ and patients’ time, increase errors and finally threaten patient’s safety. Many of them can be fixed with simple redesign solutions such as using clear labels and better layouts. This study suggests conducting further studies to confirm the findings concerning effect of evaluator experience on the results of Heuristic Evaluation. PMID:27081409
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.
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.
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.
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.
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.
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.
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.
Petri nets SM-cover-based on heuristic coloring algorithm
NASA Astrophysics Data System (ADS)
Tkacz, Jacek; Doligalski, Michał
2015-09-01
In the paper, coloring heuristic algorithm of interpreted Petri nets is presented. Coloring is used to determine the State Machines (SM) subnets. The present algorithm reduces the Petri net in order to reduce the computational complexity and finds one of its possible State Machines cover. The proposed algorithm uses elements of interpretation of Petri nets. The obtained result may not be the best, but it is sufficient for use in rapid prototyping of logic controllers. Found SM-cover will be also used in the development of algorithms for decomposition, and modular synthesis and implementation of parallel logic controllers. Correctness developed heuristic algorithm was verified using Gentzen formal reasoning system.
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.
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.
a New Hybrid Heuristic Technique for Unit Commitment Considering Spinning Reserve Probability
NASA Astrophysics Data System (ADS)
Abdollahi, A.; Ehsan, M.; Rashidinejad, M.; Purakbari-Kasmaie, M.
2009-08-01
This paper proposes a new approach for solving generation scheduling and ramp rate constrained unit commitment with considering spinning reserve probability. In order to simulate the probability of reserve in the formulation, the estimated probability that spinning reserve is called and generated has been considered. A hybrid heuristic method between genetic algorithm and lambdad iteration method is applied to solve the problem. The proposed approach is applied to two different cases such as a 10-unit base problem without considering probability of reserve and 10-unit problem with considering probability of reserve. The results are compared with other approaches results to exhibit the superiority of the proposed approach.
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.
A method for fast database search for all k-nucleotide repeats.
Benson, G; Waterman, M S
1994-01-01
A significant portion of DNA consists of repeating patterns of various sizes, from very small (one, two and three nucleotides) to very large (over 300 nucleotides). Although the functions of these repeating regions are not well understood, they appear important for understanding the expression, regulation and evolution of DNA. For example, increases in the number of trinucleotide repeats have been associated with human genetic disease, including Fragile-X mental retardation and Huntington's disease. Repeats are also useful as a tool in mapping and identifying DNA; the number of copies of a particular pattern at a site is often variable among individuals (polymorphic) and is therefore helpful in locating genes via linkage studies and also in providing DNA fingerprints of individuals. The number of repeating regions is unknown as is the distribution of pattern sizes. It would be useful to search for such regions in the DNA database in order that they may be studied more fully. The DNA database currently consists of approximately 150 million basepairs and is growing exponentially. Therefore, any program to look for repeats must be efficient and fast. In this paper, we present some new techniques that are useful in recognizing repeating patterns and describe a new program for rapidly detecting repeat regions in the DNA database where the basic unit of the repeat has size up to 32 nucleotides. It is our hope that the examples in this paper will illustrate the unrealized diversity of repeats in DNA and that the program we have developed will be a useful tool for locating new and interesting repeats. PMID:7984436
Improved intra-block copy and motion search methods for screen content coding
NASA Astrophysics Data System (ADS)
Rapaka, Krishna; Pang, Chao; Sole, Joel; Karczewicz, Marta; Li, Bin; Xu, Jizheng
2015-09-01
Screen content video coding extension of HEVC (SCC) is being developed by Joint Collaborative Team on Video Coding (JCT-VC) of ISO/IEC MPEG and ITU-T VCEG. Screen content usually features a mix of camera captured content and a significant proportion of rendered graphics, text, or animation. These two types of content exhibit distinct characteristics requiring different compression scheme to achieve better coding efficiency. This paper presents an efficient block matching schemes for coding screen content to better capture the spatial and temporal characteristics. The proposed schemes are mainly categorized as a) hash based global region block matching for intra block copy b) selective search based local region block matching for inter frame prediction c) hash based global region block matching for inter frame prediction. In the first part, a hash-based full frame block matching algorithm is designed for intra block copy to handle the repeating patterns and large motions when the reference picture constituted already decoded samples of the current picture. In the second part, a selective local area block matching algorithm is designed for inter motion estimation to handle sharp edges, high spatial frequencies and non-monotonic error surface. In the third part, a hash based full frame block matching algorithm is designed for inter motion estimation to handle repeating patterns and large motions across the temporal reference picture. The proposed schemes are compared against HM-13.0+RExt-6.0, which is the state-of-art screen content coding. The first part provides a luma BD-rate gains of -26.6%, -15.6%, -11.4% for AI, RA and LD TGM configurations. The second part provides a luma BD-rate gains of -10.1%, -12.3% for RA and LD TGM configurations. The third part provides a luma BD-rate gains of -12.2%, -11.5% for RA and LD TGM configurations.
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
A Comparision of Heuristic Methods Used in Hierarchical Production Planning.
1979-03-01
1965). ~~~. Golovin , J. J.; “Hierarchical Integration of Planning and Control”, M.I.T., Operations Research Center, Technical Report No. 116...Nostrand Reinhold , 1978. 9. flax, A. C. and J. J. Golovin ; “Computer Based Operations Management System (COMS)” , Studieä in Operations Management (A. C...flax , ed.), North Holland—American Elsevier, 1978. 10. flax, A. C. and J. J. Golovin ; “Hierarchical Production Planning Systems”, M.I.T
ERIC Educational Resources Information Center
Brown, K. M.; Elliott, S. J.; Leatherdale, S. T.; Robertson-Wilson, J.
2015-01-01
The environments in which population health interventions occur shape both their implementation and outcomes. Hence, when evaluating these interventions, we must explore both intervention content and context. Mixed methods (integrating quantitative and qualitative methods) provide this opportunity. However, although criteria exist for establishing…
Heuristic Strategies: An Aid for Solving Verbal Mathematical Problems.
ERIC Educational Resources Information Center
Giordano, Gerard
1992-01-01
Because of the importance of problem-solving skills in mathematics instruction of children with learning disabilities, this article offers guidance on teaching heuristic global strategies, including use of analogy, annotating problems, detail analysis, deletion of details, detail sorting, symbolizing operations, and designating formulas. (DB)
Heuristic Model Of The Composite Quality Index Of Environmental Assessment
NASA Astrophysics Data System (ADS)
Khabarov, A. N.; Knyaginin, A. A.; Bondarenko, D. V.; Shepet, I. P.; Korolkova, L. N.
2017-01-01
The goal of the paper is to present the heuristic model of the composite environmental quality index based on the integrated application of the elements of utility theory, multidimensional scaling, expert evaluation and decision-making. The composite index is synthesized in linear-quadratic form, it provides higher adequacy of the results of the assessment preferences of experts and decision-makers.
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.
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…
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…
Promotion of Heuristic Literacy in a Regular Mathematics Classroom
ERIC Educational Resources Information Center
Koichu, Boris; Berman, Abraham; Moore, Michael
2004-01-01
Applying and adapting a variety of appropriate heuristic strategies is one of the accepted standards of problem solving (NCTM, 2000). Thinking through a solution to a non-routine mathematical task, experts in problem solving call into play many sophisticated strategies (almost) without conscious efforts, while novices need to be taught how to do…
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…
Heuristic and Linear Models of Judgment: Matching Rules and Environments
ERIC Educational Resources Information Center
Hogarth, Robin M.; Karelaia, Natalia
2007-01-01
Much research has highlighted incoherent implications of judgmental heuristics, yet other findings have demonstrated high correspondence between predictions and outcomes. At the same time, judgment has been well modeled in the form of as if linear models. Accepting the probabilistic nature of the environment, the authors use statistical tools to…
Heuristics and NCLB Standardized Tests: A Convenient Lie
ERIC Educational Resources Information Center
Dodge, Arnold
2009-01-01
The No Child Left Behind Act of 2001 requires public schools in the United States to test students in grades 3-8. The author argues that this mandate has been supported by the public, in part, because of the "availability heuristic," a phenomenon which occurs when people assess the probability of an event by the ease with which instances…
Use of the Competing-Hypotheses Heuristic to Reduce "Pseudodiagnosticity."
ERIC Educational Resources Information Center
Wolf, Fredric M. And Others
1988-01-01
The efficacy of an educational intervention in teaching medical students to select optimal diagnostic data consistent with the competing-hypotheses heuristic and Bayes' theorem when solving clinical problems was examined. The results suggest that some problem-solving skills can be enhanced or learned independent of the acquisition of content…
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
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.
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,…
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…
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…
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.
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' understanding of…
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…
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.
Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method.
Toropova, Mariya A; Toropov, Andrey A; Raška, Ivan; Rašková, Mária
2015-09-01
Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral). The considerable influence of the presence of rings of various types with respect to the above endpoint has been detected. The mechanistic interpretation and the domain of applicability of the QSARs are discussed. Methods to select new potential gamma-secretase inhibitors are suggested.
NASA Astrophysics Data System (ADS)
Astone, Pia; Colla, Alberto; D'Antonio, Sabrina; Frasca, Sergio; Palomba, Cristiano
2014-08-01
In this paper we present a hierarchical data analysis pipeline for all-sky searches of continuous gravitational wave signals, like those emitted by spinning neutron stars asymmetric with respect to the rotation axis, with unknown position, rotational frequency, and spin-down. The core of the pipeline is an incoherent step based on a particularly efficient implementation of the Hough transform, which we call frequency-Hough, that maps the data time-frequency plane to the source frequency and spin-down plane for each fixed direction in the sky. Theoretical ROCs and sensitivity curves are computed and the dependency on various thresholds is discussed. A comparison of the sensitivity loss with respect to an "optimal" method is also presented. Several other novelties, with respect to other wide-parameter analysis pipelines, are also outlined. They concern, in particular, the construction of the grid in the parameter space, with over-resolution in frequency and parameter refinement, candidate selection, and various data cleaning steps that are introduced to improve search sensitivity and rejection of false candidates.
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,…
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…
Heuristic Research: A New Perspective on Ethics and Problems in Adult Education Research.
ERIC Educational Resources Information Center
Beckstrom, Edward S.
1993-01-01
Heuristic research is a highly autobiographical investigation of one's experience with a question or problem. This article examines the basic concepts and processes of heuristic research (in adult education), including self-dialog, tacit knowing, inverted perspective, intuition, indwelling, and focusing. Heuristic research design phases involve…
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
2009-06-01
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.
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.
Sakai, Kent; Koyama, Nobuhiro; Fukuda, Takashi; Mori, Yukiko; Onaka, Hiroyasu; Tomoda, Hiroshi
2012-01-01
Staphyloxanthin, a yellow pigment produced by methicillin-resistant Staphylococcus aureus (MRSA), is a virulent factor escaping from the host immune system. A new screening method for inhibitors of staphyloxanthin production by MRSA was established using paper disks. By this screening method, inhibitors of staphyloxanthin production were selected from the natural product library (ca. 300) and from actinomycete culture broths (ca. 1000). From the natural product library, four known inhibitors of lipid metabolism, cerulenin, dihydrobisvertinol, xanthohumol and zaragozic acid, were found to inhibit staphyloxanthin production; however, typical antibiotics used clinically, including vancomycin, had no effect on staphyloxanthin production. From actinomycete culture broths, two known anthraquinones, 6-deoxy-8-O-methylrabelomycin and tetrangomycin, were found to inhibit staphyloxanthin production by MRSA in the paper disk assay. These results suggested that this screening method is useful and effective to find compounds targeting staphyloxanthin production, leading to a new type of chemotherapeutics against MRSA infection.
Sweeney, J J
1999-04-20
Part II of the Protocol of the Comprehensive Test Ban Treaty prescribes the use of geophysical methods such as active seismic surveys and electrical conductivity measurements to search for and locate underground anomalies, including cavities and rubble zones, during the continuation phase of an on-site inspection. In this paper the application of spontaneous potential, magnetotelluric, active seismic, and gas sampling studies at the US Nevada Test Site associated with underground nuclear explosions will be described and discussed in the context of on-site inspections. Spontaneous potential and E-field ratio telluric methods were found to be effective in some geologic settings but not in others. An example of gas sampling is shown for which radiogenic gas was detected several years after detonation. The case study of the application of active seismic methods illustrates limitations imposed by the use of relatively simple systems in the field. Detection of a deeply-buried cavity or rubble zone will be difficult; results from the application of only a single method will likely be ambiguous. Best results will come from the synthesis of results from a number of widely-varying methods.
Searching transients in large-scale surveys. A method based on the Abbe value
NASA Astrophysics Data System (ADS)
Mowlavi, N.
2014-08-01
Aims: A new method is presented to identify transient candidates in large-scale surveys based on the variability pattern in their light curves. Methods: The method is based on the Abbe value, Ab, that estimates the smoothness of a light curve, and on a newly introduced value called the excess Abbe and denoted excessAb, that estimates the regularity of the light curve variability pattern over the duration of the observations. Results: Based on simulated light curves, transients are shown to occupy a specific region in the {diagram} diagram, distinct from sources presenting pulsating-like features in their light curves or having featureless light curves. The method is tested on real light curves taken from EROS-2 and OGLE-II surveys in a 0.50° × 0.17° field of the sky in the Large Magellanic Cloud centered at RA(J2000) = 5h25m56.5s and Dec(J2000) = -69d29m43.3s. The method identifies 43 EROS-2 transient candidates out of a total of 1300 variable stars, and 19 more OGLE-II candidates, 10 of which do not have any EROS-2 variable star matches and which would need further confirmation to assess their reliability. The efficiency of the method is further tested by comparing the list of transient candidates with known Be stars in the literature. It is shown that all Be stars known in the studied field of view with detectable bursts or outbursts are successfully extracted by the method. In addition, four new transient candidates displaying bursts and/or outbursts are found in the field, of which at least two are good new Be candidates. Conclusions: The new method proves to be a potentially powerful tool to extract transient candidates from large-scale multi-epoch surveys. The better the photometric measurement uncertainties are, the cleaner the list of detected transient candidates is. In addition, the diagram diagram is shown to be a good diagnostic tool to check the data quality of multi-epoch photometric surveys. A trend of instrumental and/or data reduction origin
Trusting the Method: An Ethnographic Search for Policy in Practice in an Australian Primary School
ERIC Educational Resources Information Center
Robinson, Sarah
2008-01-01
The apparent simplicity of ethnographic methods--studying people in their normal life setting, going beyond what might be said in surveys and interviews to observe everyday practices--is deceptive. Anthropological knowledge is gained through fieldwork and through pursuing a reflexive flexible approach. This study carried out in a non-government…
The Tabu Search Procedure: An Alternative to the Variable Selection Methods
ERIC Educational Resources Information Center
Mills, Jamie, D.; Olejnik, Stephen, F.; Marcoulides, George, A.
2005-01-01
The effectiveness of the Tabu variable selection algorithm, to identify predictor variables related to a criterion variable, is compared with the stepwise variable selection method and the all possible regression approach. Considering results obtained from previous research, Tabu is more successful in identifying relevant variables than the…
Not Available
1994-09-01
The bibliography contains citations concerning field projects and supporting research on petroleum recovery and reservoir technology. Recovery agents and methods are discussed including responsive copolymers, microemulsions, surfactants, steam injection, gas injection, miscible displacement, and thermal processes. Reservoir modeling, simulation, and performance are examined. (Contains 250 citations and includes a subject term index and title list.)
Application of tabu search to deterministic and stochastic optimization problems
NASA Astrophysics Data System (ADS)
Gurtuna, Ozgur
During the past two decades, advances in computer science and operations research have resulted in many new optimization methods for tackling complex decision-making problems. One such method, tabu search, forms the basis of this thesis. Tabu search is a very versatile optimization heuristic that can be used for solving many different types of optimization problems. Another research area, real options, has also gained considerable momentum during the last two decades. Real options analysis is emerging as a robust and powerful method for tackling decision-making problems under uncertainty. Although the theoretical foundations of real options are well-established and significant progress has been made in the theory side, applications are lagging behind. A strong emphasis on practical applications and a multidisciplinary approach form the basic rationale of this thesis. The fundamental concepts and ideas behind tabu search and real options are investigated in order to provide a concise overview of the theory supporting both of these two fields. This theoretical overview feeds into the design and development of algorithms that are used to solve three different problems. The first problem examined is a deterministic one: finding the optimal servicing tours that minimize energy and/or duration of missions for servicing satellites around Earth's orbit. Due to the nature of the space environment, this problem is modeled as a time-dependent, moving-target optimization problem. Two solution methods are developed: an exhaustive method for smaller problem instances, and a method based on tabu search for larger ones. The second and third problems are related to decision-making under uncertainty. In the second problem, tabu search and real options are investigated together within the context of a stochastic optimization problem: option valuation. By merging tabu search and Monte Carlo simulation, a new method for studying options, Tabu Search Monte Carlo (TSMC) method, is