Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

PubMed

Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

2018-07-01

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

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.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

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

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

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.

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1995-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies, and analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans is presented. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc. that must occur during the assembly, and handles nonreversible as well as reversible assembly tasks through backward assembly planning. In order to increase the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space.

PubMed

Kalathil, Shaeen; Elias, Elizabeth

2015-11-01

This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB) using canonic signed digit (CSD) coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB.

Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space

PubMed Central

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

Horizontal decomposition of data table for finding one reduct

NASA Astrophysics Data System (ADS)

Hońko, Piotr

2018-04-01

Attribute reduction, being one of the most essential tasks in rough set theory, is a challenge for data that does not fit in the available memory. This paper proposes new definitions of attribute reduction using horizontal data decomposition. Algorithms for computing superreduct and subsequently exact reducts of a data table are developed and experimentally verified. In the proposed approach, the size of subtables obtained during the decomposition can be arbitrarily small. Reducts of the subtables are computed independently from one another using any heuristic method for finding one reduct. Compared with standard attribute reduction methods, the proposed approach can produce superreducts that usually inconsiderably differ from an exact reduct. The approach needs comparable time and much less memory to reduce the attribute set. The method proposed for removing unnecessary attributes from superreducts executes relatively fast for bigger databases.

Memory-Based Simple Heuristics as Attribute Substitution: Competitive Tests of Binary Choice Inference Models.

PubMed

Honda, Hidehito; Matsuka, Toshihiko; Ueda, Kazuhiro

2017-05-01

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. Copyright © 2016 Cognitive Science Society, Inc.

Balancing antagonistic time and resource utilization constraints in over-subscribed scheduling problems

NASA Technical Reports Server (NTRS)

Smith, Stephen F.; Pathak, Dhiraj K.

1991-01-01

In this paper, we report work aimed at applying concepts of constraint-based problem structuring and multi-perspective scheduling to an over-subscribed scheduling problem. Previous research has demonstrated the utility of these concepts as a means for effectively balancing conflicting objectives in constraint-relaxable scheduling problems, and our goal here is to provide evidence of their similar potential in the context of HST observation scheduling. To this end, we define and experimentally assess the performance of two time-bounded heuristic scheduling strategies in balancing the tradeoff between resource setup time minimization and satisfaction of absolute time constraints. The first strategy considered is motivated by dispatch-based manufacturing scheduling research, and employs a problem decomposition that concentrates local search on minimizing resource idle time due to setup activities. The second is motivated by research in opportunistic scheduling and advocates a problem decomposition that focuses attention on the goal activities that have the tightest temporal constraints. Analysis of experimental results gives evidence of differential superiority on the part of each strategy in different problem solving circumstances. A composite strategy based on recognition of characteristics of the current problem solving state is then defined and tested to illustrate the potential benefits of constraint-based problem structuring and multi-perspective scheduling in over-subscribe scheduling problems.

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

2012-10-01

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms wemore » have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.« less

Familiarity and Recollection in Heuristic Decision Making

PubMed Central

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.

PubMed

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. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1992-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies is presented. The planning system analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. Additionally, the planning handles nonreversible, as well as reversible, assembly tasks through backward assembly planning. In order to decrease the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

A linguistic geometry for space applications

NASA Technical Reports Server (NTRS)

Stilman, Boris

1994-01-01

We develop a formal theory, the so-called Linguistic Geometry, in order to discover the inner properties of human expert heuristics, which were successful in a certain class of complex control systems, and apply them to different systems. This research relies on the formalization of search heuristics of high-skilled human experts which allow for the decomposition of complex system into the hierarchy of subsystems, and thus solve intractable problems reducing the search. The hierarchy of subsystems is represented as a hierarchy of formal attribute languages. This paper includes a formal survey of the Linguistic Geometry, and new example of a solution of optimization problem for the space robotic vehicles. This example includes actual generation of the hierarchy of languages, some details of trajectory generation and demonstrates the drastic reduction of search in comparison with conventional search algorithms.

Identification of Shearer Cutting Patterns Using Vibration Signals Based on a Least Squares Support Vector Machine with an Improved Fruit Fly Optimization Algorithm

PubMed Central

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Liu, Ze; Xu, Jing

2016-01-01

Shearers play an important role in fully mechanized coal mining face and accurately identifying their cutting pattern is very helpful for improving the automation level of shearers and ensuring the safety of coal mining. The least squares support vector machine (LSSVM) has been proven to offer strong potential in prediction and classification issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. In this paper, an improved fly optimization algorithm (IFOA) to optimize the parameters of LSSVM was presented and the LSSVM coupled with IFOA (IFOA-LSSVM) was used to identify the shearer cutting pattern. The vibration acceleration signals of five cutting patterns were collected and the special state features were extracted based on the ensemble empirical mode decomposition (EEMD) and the kernel function. Some examples on the IFOA-LSSVM model were further presented and the results were compared with LSSVM, PSO-LSSVM, GA-LSSVM and FOA-LSSVM models in detail. The comparison results indicate that the proposed approach was feasible, efficient and outperformed the others. Finally, an industrial application example at the coal mining face was demonstrated to specify the effect of the proposed system. PMID:26771615

Assessing the use of cognitive heuristic representativeness in clinical reasoning.

PubMed

Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca

2008-11-06

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

PubMed Central

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140

Focus of attention in an activity-based scheduler

NASA Technical Reports Server (NTRS)

Sadeh, Norman; Fox, Mark S.

1989-01-01

Earlier research in job shop scheduling has demonstrated the advantages of opportunistically combining order-based and resource-based scheduling techniques. An even more flexible approach is investigated where each activity is considered a decision point by itself. Heuristics to opportunistically select the next decision point on which to focus attention (i.e., variable ordering heuristics) and the next decision to be tried at this point (i.e., value ordering heuristics) are described that probabilistically account for both activity precedence and resource requirement interactions. Preliminary experimental results indicate that the variable ordering heuristic greatly increases search efficiency. While least constraining value ordering heuristics have been advocated in the literature, the experimental results suggest that other value ordering heuristics combined with our variable-ordering heuristic can produce much better schedules without significantly increasing search.

A dynamic scheduling algorithm for singe-arm two-cluster tools with flexible processing times

NASA Astrophysics Data System (ADS)

Li, Xin; Fung, Richard Y. K.

2018-02-01

This article presents a dynamic algorithm for job scheduling in two-cluster tools producing multi-type wafers with flexible processing times. Flexible processing times mean that the actual times for processing wafers should be within given time intervals. The objective of the work is to minimize the completion time of the newly inserted wafer. To deal with this issue, a two-cluster tool is decomposed into three reduced single-cluster tools (RCTs) in a series based on a decomposition approach proposed in this article. For each single-cluster tool, a dynamic scheduling algorithm based on temporal constraints is developed to schedule the newly inserted wafer. Three experiments have been carried out to test the dynamic scheduling algorithm proposed, comparing with the results the 'earliest starting time' heuristic (EST) adopted in previous literature. The results show that the dynamic algorithm proposed in this article is effective and practical.

Mixed Integer Programming Model and Incremental Optimization for Delivery and Storage Planning Using Truck Terminals

NASA Astrophysics Data System (ADS)

Sakakibara, Kazutoshi; Tian, Yajie; Nishikawa, Ikuko

We discuss the planning of transportation by trucks over a multi-day period. Each truck collects loads from suppliers and delivers them to assembly plants or a truck terminal. By exploiting the truck terminal as a temporal storage, we aim to increase the load ratio of each truck and to minimize the lead time for transportation. In this paper, we show a mixed integer programming model which represents each product explicitly, and discuss the decomposition of the problem into a problem of delivery and storage, and a problem of vehicle routing. Based on this model, we propose a relax-and-fix type heuristic in which decision variables are fixed one by one by mathematical programming techniques such as branch-and-bound methods.

Constraint-based integration of planning and scheduling for space-based observatory management

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Steven F.

1994-01-01

Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized.

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…

Automated detection of heuristics and biases among pathologists in a computer-based system.

PubMed

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.

Incompressible inelasticity as an essential ingredient for the validity of the kinematic decomposition F =FeFi

NASA Astrophysics Data System (ADS)

Reina, Celia; Conti, Sergio

2017-10-01

The multiplicative decomposition of the total deformation F =FeFi between an elastic (Fe) and an inelastic component (Fi) is standard in the modeling of many irreversible processes such as plasticity, growth, thermoelasticity, viscoelasticty or phase transformations. The heuristic argument for such kinematic assumption is based on the chain rule for the compatible scenario (CurlFi = 0) where the individual deformation tensors are gradients of deformation mappings, i.e. F = D φ = D (φe ∘φi) = (Dφe) ∘φi (Dφi) =FeFi . Yet, the conditions for its validity in the general incompatible case (CurlFi ≠ 0) has so far remained uncertain. We show in this paper that detFi = 1 and CurlFi bounded are necessary and sufficient conditions for the validity of F =FeFi for a wide range of inelastic processes. In particular, in the context of crystal plasticity, we demonstrate via rigorous homogenization from discrete dislocations to the continuum level in two dimensions, that the volume preserving property of the mechanistics of dislocation glide, combined with a finite dislocation density, is sufficient to deliver F =FeFp at the continuum scale. We then generalize this result to general two-dimensional inelastic processes that may be described at a lower dimensional scale via a multiplicative decomposition while exhibiting a finite density of incompatibilities. The necessity of the conditions detFi = 1 and CurlFi bounded for such systems is demonstrated via suitable counterexamples.

Deriving a Set of Privacy Specific Heuristics for the Assessment of PHRs (Personal Health Records).

PubMed

Furano, Riccardo F; Kushniruk, Andre; Barnett, Jeff

2017-01-01

With the emergence of personal health record (PHR) platforms becoming more widely available, this research focused on the development of privacy heuristics to assess PHRs regarding privacy. Existing sets of heuristics are typically not application specific and do not address patient-centric privacy as a main concern prior to undergoing PHR procurement. A set of privacy specific heuristics were developed based on a scoping review of the literature. An internet-based commercially available, vendor specific PHR application was evaluated using the derived set of privacy specific heuristics. The proposed set of privacy specific derived heuristics is explored in detail in relation to ISO 29100. The assessment of the internet-based commercially available, vendor specific PHR application indicated numerous violations. These violations were noted within the study. It is argued that the new derived privacy heuristics should be used in addition to Nielsen's well-established set of heuristics. Privacy specific heuristics could be used to assess PHR portal system-level privacy mechanisms in the procurement process of a PHR application and may prove to be a beneficial form of assessment to prevent the selection of a PHR platform with a poor privacy specific interface design.

Sequence-based heuristics for faster annotation of non-coding RNA families.

PubMed

Weinberg, Zasha; Ruzzo, Walter L

2006-01-01

Non-coding RNAs (ncRNAs) are functional RNA molecules that do not code for proteins. Covariance Models (CMs) are a useful statistical tool to find new members of an ncRNA gene family in a large genome database, using both sequence and, importantly, RNA secondary structure information. Unfortunately, CM searches are extremely slow. Previously, we created rigorous filters, which provably sacrifice none of a CM's accuracy, while making searches significantly faster for virtually all ncRNA families. However, these rigorous filters make searches slower than heuristics could be. In this paper we introduce profile HMM-based heuristic filters. We show that their accuracy is usually superior to heuristics based on BLAST. Moreover, we compared our heuristics with those used in tRNAscan-SE, whose heuristics incorporate a significant amount of work specific to tRNAs, where our heuristics are generic to any ncRNA. Performance was roughly comparable, so we expect that our heuristics provide a high-quality solution that--unlike family-specific solutions--can scale to hundreds of ncRNA families. The source code is available under GNU Public License at the supplementary web site.

Combination of graph heuristics in producing initial solution of curriculum based course timetabling problem

NASA Astrophysics Data System (ADS)

Wahid, Juliana; Hussin, Naimah Mohd

2016-08-01

The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution. This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions. The graph heuristics were set as single and combination of two heuristics. In addition, several ways of assigning courses into room and timeslot are implemented. All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced. The result shows that combination of saturation degree followed by largest degree heuristic produce the highest number of population of initial solutions. The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions.

Learning to improve iterative repair scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene

1992-01-01

This paper presents a general learning method for dynamically selecting between repair heuristics in an iterative repair scheduling system. The system employs a version of explanation-based learning called Plausible Explanation-Based Learning (PEBL) that uses multiple examples to confirm conjectured explanations. The basic approach is to conjecture contradictions between a heuristic and statistics that measure the quality of the heuristic. When these contradictions are confirmed, a different heuristic is selected. To motivate the utility of this approach we present an empirical evaluation of the performance of a scheduling system with respect to two different repair strategies. We show that the scheduler that learns to choose between the heuristics outperforms the same scheduler with any one of two heuristics alone.

Memory-Based Simple Heuristics as Attribute Substitution: Competitive Tests of Binary Choice Inference Models

ERIC Educational Resources Information Center

Honda, Hidehito; Matsuka, Toshihiko; Ueda, Kazuhiro

2017-01-01

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…

Influence maximization based on partial network structure information: A comparative analysis on seed selection heuristics

NASA Astrophysics Data System (ADS)

Erkol, Şirag; Yücel, Gönenç

In this study, the problem of seed selection is investigated. This problem is mainly treated as an optimization problem, which is proved to be NP-hard. There are several heuristic approaches in the literature which mostly use algorithmic heuristics. These approaches mainly focus on the trade-off between computational complexity and accuracy. Although the accuracy of algorithmic heuristics are high, they also have high computational complexity. Furthermore, in the literature, it is generally assumed that complete information on the structure and features of a network is available, which is not the case in most of the times. For the study, a simulation model is constructed, which is capable of creating networks, performing seed selection heuristics, and simulating diffusion models. Novel metric-based seed selection heuristics that rely only on partial information are proposed and tested using the simulation model. These heuristics use local information available from nodes in the synthetically created networks. The performances of heuristics are comparatively analyzed on three different network types. The results clearly show that the performance of a heuristic depends on the structure of a network. A heuristic to be used should be selected after investigating the properties of the network at hand. More importantly, the approach of partial information provided promising results. In certain cases, selection heuristics that rely only on partial network information perform very close to similar heuristics that require complete network data.

Acceleration of aircraft-level Traffic Flow Management

NASA Astrophysics Data System (ADS)

Rios, Joseph Lucio

This dissertation describes novel approaches to solving large-scale, high fidelity, aircraft-level Traffic Flow Management scheduling problems. Depending on the methods employed, solving these problems to optimality can take longer than the length of the planning horizon in question. Research in this domain typically focuses on the quality of the modeling used to describe the problem and the benefits achieved from the optimized solution, often treating computational aspects as secondary or tertiary. The work presented here takes the complementary view and considers the computational aspect as the primary concern. To this end, a previously published model for solving this Traffic Flow Management scheduling problem is used as starting point for this study. The model proposed by Bertsimas and Stock-Patterson is a binary integer program taking into account all major resource capacities and the trajectories of each flight to decide which flights should be held in which resource for what amount of time in order to satisfy all capacity requirements. For large instances, the solve time using state-of-the-art solvers is prohibitive for use within a potential decision support tool. With this dissertation, however, it will be shown that solving can be achieved in reasonable time for instances of real-world size. Five other techniques developed and tested for this dissertation will be described in detail. These are heuristic methods that provide good results. Performance is measured in terms of runtime and "optimality gap." We then describe the most successful method presented in this dissertation: Dantzig-Wolfe Decomposition. Results indicate that a parallel implementation of Dantzig-Wolfe Decomposition optimally solves the original problem in much reduced time and with better integrality and smaller optimality gap than any of the heuristic methods or state-of-the-art, commercial solvers. The solution quality improves in every measureable way as the number of subproblems solved in parallel increases. A maximal decomposition provides the best results of any method tested. The convergence qualities of Dantzig-Wolfe Decomposition have been criticized in the past, so we examine what makes the Bertsimas-Stock Patterson model so amenable to use of this method. These mathematical qualities of the model are generalized to provide guidance on other problems that may benefit from massively parallel Dantzig-Wolfe Decomposition. This result, together with the development of the software, and the experimental results indicating the feasibility of real-time, nationwide Traffic Flow Management scheduling represent the major contributions of this dissertation.

Perceived breast cancer risk: heuristic reasoning and search for a dominance structure.

PubMed

Katapodi, Maria C; Facione, Noreen C; Humphreys, Janice C; Dodd, Marylin J

2005-01-01

Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied logic. The availability, simulation, representativeness, affect, and perceived control heuristics, and search for a dominance structure were commonly used for making risk assessments. Risk assessments were based on experiences with an abnormal breast symptom, experiences with affected family members and friends, beliefs about living a healthy lifestyle, and trust in health providers. Assessment of the potential threat of a breast symptom was facilitated by the search for a dominance structure. Experiences with family members and friends were incorporated into risk assessments through the availability, simulation, representativeness, and affect heuristics. Mistrust in health providers led to an inappropriate dependence on the perceived control heuristic. Identified heuristics appear to create predictable biases and suggest that perceived breast cancer risk is based on common cognitive patterns.

Usability Study and Heuristic Evaluation of the Applied Robotics for Installations and Base Operations (ARIBO) Driverless Vehicle Reservation Application ARIBO Mobile

DTIC Science & Technology

2017-03-01

ARL-TN-0814 ● MAR 2017 US Army Research Laboratory Usability Study and Heuristic Evaluation of the Applied Robotics for...ARL-TN-0814 ● MAR 2017 US Army Research Laboratory Usability Study and Heuristic Evaluation of the Applied Robotics for...Heuristic Evaluation of the Applied Robotics for Installations and Base Operations (ARIBO) Driverless Vehicle Reservation Application ARIBO Mobile 5a

On orbital allotments for geostationary satellites

NASA Technical Reports Server (NTRS)

Gonsalvez, David J. A.; Reilly, Charles H.; Mount-Campbell, Clark A.

1986-01-01

The following satellite synthesis problem is addressed: communication satellites are to be allotted positions on the geostationary arc so that interference does not exceed a given acceptable level by enforcing conservative pairwise satellite separation. A desired location is specified for each satellite, and the objective is to minimize the sum of the deviations between the satellites' prescribed and desired locations. Two mixed integer programming models for the satellite synthesis problem are presented. Four solution strategies, branch-and-bound, Benders' decomposition, linear programming with restricted basis entry, and a switching heuristic, are used to find solutions to example synthesis problems. Computational results indicate the switching algorithm yields solutions of good quality in reasonable execution times when compared to the other solution methods. It is demonstrated that the switching algorithm can be applied to synthesis problems with the objective of minimizing the largest deviation between a prescribed location and the corresponding desired location. Furthermore, it is shown that the switching heuristic can use no conservative, location-dependent satellite separations in order to satisfy interference criteria.

Learning Low-Rank Decomposition for Pan-Sharpening With Spatial-Spectral Offsets.

PubMed

Yang, Shuyuan; Zhang, Kai; Wang, Min

2017-08-25

Finding accurate injection components is the key issue in pan-sharpening methods. In this paper, a low-rank pan-sharpening (LRP) model is developed from a new perspective of offset learning. Two offsets are defined to represent the spatial and spectral differences between low-resolution multispectral and high-resolution multispectral (HRMS) images, respectively. In order to reduce spatial and spectral distortions, spatial equalization and spectral proportion constraints are designed and cast on the offsets, to develop a spatial and spectral constrained stable low-rank decomposition algorithm via augmented Lagrange multiplier. By fine modeling and heuristic learning, our method can simultaneously reduce spatial and spectral distortions in the fused HRMS images. Moreover, our method can efficiently deal with noises and outliers in source images, for exploring low-rank and sparse characteristics of data. Extensive experiments are taken on several image data sets, and the results demonstrate the efficiency of the proposed LRP.

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy.

PubMed

Blumenthal-Barby, J S; Krieger, Heather

2015-05-01

The role of cognitive biases and heuristics in medical decision making is of growing interest. The purpose of this study was to determine whether studies on cognitive biases and heuristics in medical decision making are based on actual or hypothetical decisions and are conducted with populations that are representative of those who typically make the medical decision; to categorize the types of cognitive biases and heuristics found and whether they are found in patients or in medical personnel; and to critically review the studies based on standard methodological quality criteria. Data sources were original, peer-reviewed, empirical studies on cognitive biases and heuristics in medical decision making found in Ovid Medline, PsycINFO, and the CINAHL databases published in 1980-2013. Predefined exclusion criteria were used to identify 213 studies. During data extraction, information was collected on type of bias or heuristic studied, respondent population, decision type, study type (actual or hypothetical), study method, and study conclusion. Of the 213 studies analyzed, 164 (77%) were based on hypothetical vignettes, and 175 (82%) were conducted with representative populations. Nineteen types of cognitive biases and heuristics were found. Only 34% of studies (n = 73) investigated medical personnel, and 68% (n = 145) confirmed the presence of a bias or heuristic. Each methodological quality criterion was satisfied by more than 50% of the studies, except for sample size and validated instruments/questions. Limitations are that existing terms were used to inform search terms, and study inclusion criteria focused strictly on decision making. Most of the studies on biases and heuristics in medical decision making are based on hypothetical vignettes, raising concerns about applicability of these findings to actual decision making. Biases and heuristics have been underinvestigated in medical personnel compared with patients. © The Author(s) 2014.

A heuristic neural network initialization scheme for modeling nonlinear functions in engineering mechanics: continuous development

NASA Astrophysics Data System (ADS)

Pei, Jin-Song; Mai, Eric C.

2007-04-01

This paper introduces a continuous effort towards the development of a heuristic initialization methodology for constructing multilayer feedforward neural networks to model nonlinear functions. In this and previous studies that this work is built upon, including the one presented at SPIE 2006, the authors do not presume to provide a universal method to approximate arbitrary functions, rather the focus is given to the development of a rational and unambiguous initialization procedure that applies to the approximation of nonlinear functions in the specific domain of engineering mechanics. The applications of this exploratory work can be numerous including those associated with potential correlation and interpretation of the inner workings of neural networks, such as damage detection. The goal of this study is fulfilled by utilizing the governing physics and mathematics of nonlinear functions and the strength of the sigmoidal basis function. A step-by-step graphical procedure utilizing a few neural network prototypes as "templates" to approximate commonly seen memoryless nonlinear functions of one or two variables is further developed in this study. Decomposition of complex nonlinear functions into a summation of some simpler nonlinear functions is utilized to exploit this prototype-based initialization methodology. Training examples are presented to demonstrate the rationality and effciency of the proposed methodology when compared with the popular Nguyen-Widrow initialization algorithm. Future work is also identfied.

Trends Concerning Four Misconceptions in Students' Intuitively-Based Probabilistic Reasoning Sourced in the Heuristic of Representativeness

ERIC Educational Resources Information Center

Kustos, Paul Nicholas

2010-01-01

Student difficulty in the study of probability arises in intuitively-based misconceptions derived from heuristics. One such heuristic, the one of note for this research study, is that of representativeness, in which an individual informally assesses the probability of an event based on the degree to which the event is similar to the sample from…

Using heuristic evaluations to assess the safety of health information systems.

PubMed

Carvalho, Christopher J; Borycki, Elizabeth M; Kushniruk, Andre W

2009-01-01

Health information systems (HISs) are typically seen as a mechanism for reducing medical errors. There is, however, evidence to prove that technology may actually be the cause of errors. As a result, it is crucial to fully test any system prior to its implementation. At present, evidence-based evaluation heuristics do not exist for assessing aspects of interface design that lead to medical errors. A three phase study was conducted to develop evidence-based heuristics for evaluating interfaces. Phase 1 consisted of a systematic review of the literature. In Phase 2 a comprehensive list of 33 evaluation heuristics was developed based on the review that could be used to test for potential technology induced errors. Phase 3 involved applying these healthcare specific heuristics to evaluate a HIS.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Using Heuristic Task Analysis to Create Web-Based Instructional Design Theory

ERIC Educational Resources Information Center

Fiester, Herbert R.

2010-01-01

The first purpose of this study was to identify procedural and heuristic knowledge used when creating web-based instruction. The second purpose of this study was to develop suggestions for improving the Heuristic Task Analysis process, a technique for eliciting, analyzing, and representing expertise in cognitively complex tasks. Three expert…

Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm.

PubMed

Agarwal, Krishna; Macháň, Radek; Prasad, Dilip K

2018-03-21

Localization microscopy and multiple signal classification algorithm use temporal stack of image frames of sparse emissions from fluorophores to provide super-resolution images. Localization microscopy localizes emissions in each image independently and later collates the localizations in all the frames, giving same weight to each frame irrespective of its signal-to-noise ratio. This results in a bias towards frames with low signal-to-noise ratio and causes cluttered background in the super-resolved image. User-defined heuristic computational filters are employed to remove a set of localizations in an attempt to overcome this bias. Multiple signal classification performs eigen-decomposition of the entire stack, irrespective of the relative signal-to-noise ratios of the frames, and uses a threshold to classify eigenimages into signal and null subspaces. This results in under-representation of frames with low signal-to-noise ratio in the signal space and over-representation in the null space. Thus, multiple signal classification algorithms is biased against frames with low signal-to-noise ratio resulting into suppression of the corresponding fluorophores. This paper presents techniques to automatically debias localization microscopy and multiple signal classification algorithm of these biases without compromising their resolution and without employing heuristics, user-defined criteria. The effect of debiasing is demonstrated through five datasets of invitro and fixed cell samples.

Automated Design of Quantum Circuits

NASA Technical Reports Server (NTRS)

Williams, Colin P.; Gray, Alexander G.

2000-01-01

In order to design a quantum circuit that performs a desired quantum computation, it is necessary to find a decomposition of the unitary matrix that represents that computation in terms of a sequence of quantum gate operations. To date, such designs have either been found by hand or by exhaustive enumeration of all possible circuit topologies. In this paper we propose an automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem. We demonstrate the method on the task of discovering quantum circuit designs for quantum teleportation. We show that to find a given known circuit design (one which was hand-crafted by a human), the method considers roughly an order of magnitude fewer designs than naive enumeration. In addition, the method finds novel circuit designs superior to those previously known.

Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

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…

Use of Heuristics to Facilitate Scientific Discovery Learning in a Simulation Learning Environment in a Physics Domain

ERIC Educational Resources Information Center

Veermans, Koen; van Joolingen, Wouter; de Jong, Ton

2006-01-01

This article describes a study into the role of heuristic support in facilitating discovery learning through simulation-based learning. The study compares the use of two such learning environments in the physics domain of collisions. In one learning environment (implicit heuristics) heuristics are only used to provide the learner with guidance…

Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures

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 broad sense, of meta-heuristics, and describe free-accessible software frameworks which can be used to make easier the implementation of these algorithms.

The Effectiveness of Local Culture-Based Mathematical Heuristic-KR Learning towards Enhancing Student's Creative Thinking Skill

ERIC Educational Resources Information Center

Tandiseru, Selvi Rajuaty

2015-01-01

The problem in this research is the lack of creative thinking skills of students. One of the learning models that is expected to enhance student's creative thinking skill is the local culture-based mathematical heuristic-KR learning model (LC-BMHLM). Heuristic-KR is a learning model which was introduced by Krulik and Rudnick (1995) that is the…

Heuristic decision making in medicine

PubMed Central

Marewski, Julian N.; Gigerenzer, Gerd

2012-01-01

Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care. PMID:22577307

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 decision making in medicine.

PubMed

Marewski, Julian N; Gigerenzer, Gerd

2012-03-01

Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care.

Proportional reasoning as a heuristic-based process: time constraint and dual task considerations.

PubMed

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.

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

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.

QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm.

PubMed

Bao, Ying; Lei, Weimin; Zhang, Wei; Zhan, Yuzhuo

2016-01-01

At present, to realize or improve the quality of experience (QoE) is a major goal for network media transmission service, and QoE evaluation is the basis for adjusting the transmission control mechanism. Therefore, a kind of QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm is proposed in this paper, which is concentrated on service score calculation at the server side. The server side collects network transmission quality of service (QoS) parameter, node location data, and user expectation value from client feedback information. Then it manages the historical data in database through the "big data" process mode, and predicts user score according to heuristic rules. On this basis, it completes fuzzy clustering analysis, and generates service QoE score and management message, which will be finally fed back to clients. Besides, this paper mainly discussed service evaluation generative rules, heuristic evaluation rules and fuzzy clustering analysis methods, and presents service-based QoE evaluation processes. The simulation experiments have verified the effectiveness of QoE collaborative evaluation method based on fuzzy clustering heuristic rules.

Analytic and heuristic processes in the detection and resolution of conflict.

PubMed

Ferreira, Mário B; Mata, André; Donkin, Christopher; Sherman, Steven J; Ihmels, Max

2016-10-01

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dual-process models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and single-process accounts, which are discussed.

Topology Optimization - Engineering Contribution to Architectural Design

NASA Astrophysics Data System (ADS)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one-material problems.

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.

Analytically derived switching functions for exact H2+ eigenstates

NASA Astrophysics Data System (ADS)

Thorson, W. R.; Kimura, M.; Choi, J. H.; Knudson, S. K.

1981-10-01

Electron translation factors (ETF's) appropriate for slow atomic collisions may be constructed using switching functions. In this paper we derive a set of switching functions for the H2+ system by an analytical "two-center decomposition" of the exact molecular eigenstates. These switching functions are closely approximated by the simple form f=bη, where η is the "angle variable" of prolate spheroidal coordinates. For given united atom angular momentum quantum numbers (l,m), the characteristic parameter blm depends only on the quantity c2=-ɛR22, where ɛ is the electronic binding energy and R the internuclear distance in a.u. The resulting parameters are in excellent agreement with those found in our earlier work by a heuristic "optimization" scheme based on a study of coupling matrix-element behavior for a number of H2+ states. An approximate extension to asymmetric cases (HeH2+) has also been made. Nonadiabatic couplings based on these switching functions have been used in recent close-coupling calculations for H+-H(1s) collisions and He2+-H(1s) collisions at energies 1.0-20 keV.

Clinical decision-making by midwives: managing case complexity.

PubMed

Cioffi, J; Markham, R

1997-02-01

In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.

Heuristic Processes in Ratings of Leader Behavior: Assessing Item-Induced Availability Biases.

ERIC Educational Resources Information Center

Binning, John F.; Fernandez, Guadalupe

Since observers' memory-based ratings of organizational phenomena provide data in research and decision-making contexts, bias in observers' judgments must be examined. A study was conducted to explore the extent to which leader behavior ratings are more generally biased by the availability heuristic. The availability heuristic is operative when a…

The Generation and Resemblance Heuristics in Face Recognition: Cooperation and Competition

ERIC Educational Resources Information Center

Kleider, Heather M.; Goldinger, Stephen D.

2006-01-01

Like all probabilistic decisions, recognition memory judgments are based on inferences about the strength and quality of stimulus familiarity. In recent articles, B. W. A. Whittlesea and J. Leboe (2000; J. Leboe & B. W. A. Whittlesea, 2002) proposed that such memory decisions entail various heuristics, similar to well-known heuristics in overt…

Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations.

PubMed

Ryan, Jason C; Banerjee, Ashis Gopal; Cummings, Mary L; Roy, Nicholas

2014-06-01

Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.

New insights into diversification of hyper-heuristics.

PubMed

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.

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

PubMed

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Utility functions and resource management in an oversubscribed heterogeneous computing environment

DOE PAGES

Khemka, Bhavesh; Friese, Ryan; Briceno, Luis Diego; ...

2014-09-26

We model an oversubscribed heterogeneous computing system where tasks arrive dynamically and a scheduler maps the tasks to machines for execution. The environment and workloads are based on those being investigated by the Extreme Scale Systems Center at Oak Ridge National Laboratory. Utility functions that are designed based on specifications from the system owner and users are used to create a metric for the performance of resource allocation heuristics. Each task has a time-varying utility (importance) that the enterprise will earn based on when the task successfully completes execution. We design multiple heuristics, which include a technique to drop lowmore » utility-earning tasks, to maximize the total utility that can be earned by completing tasks. The heuristics are evaluated using simulation experiments with two levels of oversubscription. The results show the benefit of having fast heuristics that account for the importance of a task and the heterogeneity of the environment when making allocation decisions in an oversubscribed environment. Furthermore, the ability to drop low utility-earning tasks allow the heuristics to tolerate the high oversubscription as well as earn significant utility.« less

Optimizing Controlling-Value-Based Power Gating with Gate Count and Switching Activity

NASA Astrophysics Data System (ADS)

Chen, Lei; Kimura, Shinji

In this paper, a new heuristic algorithm is proposed to optimize the power domain clustering in controlling-value-based (CV-based) power gating technology. In this algorithm, both the switching activity of sleep signals (p) and the overall numbers of sleep gates (gate count, N) are considered, and the sum of the product of p and N is optimized. The algorithm effectively exerts the total power reduction obtained from the CV-based power gating. Even when the maximum depth is kept to be the same, the proposed algorithm can still achieve power reduction approximately 10% more than that of the prior algorithms. Furthermore, detailed comparison between the proposed heuristic algorithm and other possible heuristic algorithms are also presented. HSPICE simulation results show that over 26% of total power reduction can be obtained by using the new heuristic algorithm. In addition, the effect of dynamic power reduction through the CV-based power gating method and the delay overhead caused by the switching of sleep transistors are also shown in this paper.

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…

Requirements analysis, domain knowledge, and design

NASA Technical Reports Server (NTRS)

Potts, Colin

1988-01-01

Two improvements to current requirements analysis practices are suggested: domain modeling, and the systematic application of analysis heuristics. Domain modeling is the representation of relevant application knowledge prior to requirements specification. Artificial intelligence techniques may eventually be applicable for domain modeling. In the short term, however, restricted domain modeling techniques, such as that in JSD, will still be of practical benefit. Analysis heuristics are standard patterns of reasoning about the requirements. They usually generate questions of clarification or issues relating to completeness. Analysis heuristics can be represented and therefore systematically applied in an issue-based framework. This is illustrated by an issue-based analysis of JSD's domain modeling and functional specification heuristics. They are discussed in the context of the preliminary design of simple embedded systems.

Evaluating a Web-Based Interface for Internet Telemedicine

NASA Technical Reports Server (NTRS)

Lathan, Corinna E.; Newman, Dava J.; Sebrechts, Marc M.; Doarn, Charles R.

1997-01-01

The objective is to introduce the usability engineering methodology, heuristic evaluation, to the design and development of a web-based telemedicine system. Using a set of usability criteria, or heuristics, one evaluator examined the Spacebridge to Russia web-site for usability problems. Thirty-four usability problems were found in this preliminary study and all were assigned a severity rating. The value of heuristic analysis in the iterative design of a system is shown because the problems can be fixed before deployment of a system and the problems are of a different nature than those found by actual users of the system. It was therefore determined that there is potential value of heuristic evaluation paired with user testing as a strategy for optimal system performance design.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

PubMed

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-08-01

RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.

Automated discovery of local search heuristics for satisfiability testing.

PubMed

Fukunaga, Alex S

2008-01-01

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.

Inhibitory mechanism of the matching heuristic in syllogistic reasoning.

PubMed

Tse, Ping Ping; Moreno Ríos, Sergio; García-Madruga, Juan Antonio; Bajo Molina, María Teresa

2014-11-01

A number of heuristic-based hypotheses have been proposed to explain how people solve syllogisms with automatic processes. In particular, the matching heuristic employs the congruency of the quantifiers in a syllogism—by matching the quantifier of the conclusion with those of the two premises. When the heuristic leads to an invalid conclusion, successful solving of these conflict problems requires the inhibition of automatic heuristic processing. Accordingly, if the automatic processing were based on processing the set of quantifiers, no semantic contents would be inhibited. The mental model theory, however, suggests that people reason using mental models, which always involves semantic processing. Therefore, whatever inhibition occurs in the processing implies the inhibition of the semantic contents. We manipulated the validity of the syllogism and the congruency of the quantifier of its conclusion with those of the two premises according to the matching heuristic. A subsequent lexical decision task (LDT) with related words in the conclusion was used to test any inhibition of the semantic contents after each syllogistic evaluation trial. In the LDT, the facilitation effect of semantic priming diminished after correctly solved conflict syllogisms (match-invalid or mismatch-valid), but was intact after no-conflict syllogisms. The results suggest the involvement of an inhibitory mechanism of semantic contents in syllogistic reasoning when there is a conflict between the output of the syntactic heuristic and actual validity. Our results do not support a uniquely syntactic process of syllogistic reasoning but fit with the predictions based on mental model theory. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamic Resource Management for Parallel Tasks in an Oversubscribed Energy-Constrained Heterogeneous Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Koenig, Gregory A; Machovec, Dylan

2016-01-01

Abstract: The worth of completing parallel tasks is modeled using utility functions, which monotonically-decrease with time and represent the importance and urgency of a task. These functions define the utility earned by a task at the time of its completion. The performance of such a system is measured as the total utility earned by all completed tasks over some interval of time (e.g., 24 hours). To maximize system performance when scheduling dynamically arriving parallel tasks onto a high performance computing (HPC) system that is oversubscribed and energy-constrained, we have designed, analyzed, and compared different heuristic techniques. Four utility-aware heuristics (i.e.,more » Max Utility, Max Utility-per-Time, Max Utility-per-Resource, and Max Utility-per-Energy), three FCFS-based heuristics (Conservative Backfilling, EASY Backfilling, and FCFS with Multiple Queues), and a Random heuristic were examined in this study. A technique that is often used with the FCFS-based heuristics is the concept of a permanent reservation. We compare the performance of permanent reservations with temporary place-holders to demonstrate the advantages that place-holders can provide. We also present a novel energy filtering technique that constrains the maximum energy-per-resource used by each task. We conducted a simulation study to evaluate the performance of these heuristics and techniques in an energy-constrained oversubscribed HPC environment. With place-holders, energy filtering, and dropping tasks with low potential utility, our utility-aware heuristics are able to significantly outperform the existing FCFS-based techniques.« less

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.

Does the inherence heuristic take us to psychological essentialism?

PubMed

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.

The Memory State Heuristic: A Formal Model Based on Repeated Recognition Judgments

ERIC Educational Resources Information Center

Castela, Marta; Erdfelder, Edgar

2017-01-01

The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e.,…

Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

NASA Astrophysics Data System (ADS)

Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

2017-03-01

Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

PubMed

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model for the design of distributed data bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ram, S.

This research focuses on developing a model to solve the File Allocation Problem (FAP). The model integrates two major design issues, namely Concurrently Control and Data Distribution. The central node locking mechanism is incorporated in developing a nonlinear integer programming model. Two solution algorithms are proposed, one of which was implemented in FORTRAN.V. The allocation of data bases and programs are examined using this heuristic. Several decision rules were also formulated based on the results of the heuristic. A second more comprehensive heuristic was proposed, based on the knapsack problem. The development and implementation of this algorithm has been leftmore » as a topic for future research.« less

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.

Using tree diversity to compare phylogenetic heuristics.

PubMed

Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L

2009-04-29

Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees-especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest.

A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems.

PubMed

Kheiri, Ahmed; Keedwell, Ed

2017-01-01

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 article, 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.

Multi-objective Decision Based Available Transfer Capability in Deregulated Power System Using Heuristic Approaches

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.

Usability of a patient education and motivation tool using heuristic evaluation.

PubMed

Joshi, Ashish; Arora, Mohit; Dai, Liwei; Price, Kathleen; Vizer, Lisa; Sears, Andrew

2009-11-06

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. 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. 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. 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 for aesthetic and minimalist design (median severity = 2), 4 violations for help users recognize, diagnose, and recover from errors (median severity = 3), and 4 violations for help and documentation (median severity = 4). We describe the heuristic evaluation method employed to assess the usability of PEMT, a method which uncovers heuristic violations in the interface design in a quick and efficient manner. Bringing together usability experts and health professionals to evaluate a computer-mediated patient education program can help to identify problems in a timely manner. This makes this method particularly well suited to the iterative design process when developing other computer-mediated health education programs. Heuristic evaluations provided a means to assess the user interface of PEMT.

Usability of a Patient Education and Motivation Tool Using Heuristic Evaluation

PubMed Central

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 for aesthetic and minimalist design (median severity = 2), 4 violations for help users recognize, diagnose, and recover from errors (median severity = 3), and 4 violations for help and documentation (median severity = 4). Conclusion We describe the heuristic evaluation method employed to assess the usability of PEMT, a method which uncovers heuristic violations in the interface design in a quick and efficient manner. Bringing together usability experts and health professionals to evaluate a computer-mediated patient education program can help to identify problems in a timely manner. This makes this method particularly well suited to the iterative design process when developing other computer-mediated health education programs. Heuristic evaluations provided a means to assess the user interface of PEMT. PMID:19897458

It looks easy! Heuristics for combinatorial optimization problems.

PubMed

Chronicle, Edward P; MacGregor, James N; Ormerod, Thomas C; Burr, Alistair

2006-04-01

Human performance on instances of computationally intractable optimization problems, such as the travelling salesperson problem (TSP), can be excellent. We have proposed a boundary-following heuristic to account for this finding. We report three experiments with TSPs where the capacity to employ this heuristic was varied. In Experiment 1, participants free to use the heuristic produced solutions significantly closer to optimal than did those prevented from doing so. Experiments 2 and 3 together replicated this finding in larger problems and demonstrated that a potential confound had no effect. In all three experiments, performance was closely matched by a boundary-following model. The results implicate global rather than purely local processes. Humans may have access to simple, perceptually based, heuristics that are suited to some combinatorial optimization tasks.

A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems.

PubMed

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.

Semiclassical approach to atomic decoherence by gravitational waves

NASA Astrophysics Data System (ADS)

Quiñones, D. A.; Varcoe, B. T. H.

2018-01-01

A new heuristic model of interaction of an atomic system with a gravitational wave (GW) is proposed. In it, the GW alters the local electromagnetic field of the atomic nucleus, as perceived by the electron, changing the state of the system. The spectral decomposition of the wave function is calculated, from which the energy is obtained. The results suggest a shift in the difference of the atomic energy levels, which will induce a small detuning to a resonant transition. The detuning increases with the quantum numbers of the levels, making the effect more prominent for Rydberg states. We performed calculations on the Rabi oscillations of atomic transitions, estimating how they would vary as a result of the proposed effect.

A Sharp methodology for VLSI layout

NASA Astrophysics Data System (ADS)

Bapat, Shekhar

1993-01-01

The layout problem for VLSI circuits is recognized as a very difficult problem and has been traditionally decomposed into the several seemingly independent sub-problems of placement, global routing, and detailed routing. Although this structure achieves a reduction in programming complexity, it is also typically accompanied by a reduction in solution quality. Most current placement research recognizes that the separation is artificial, and that the placement and routing problems should be solved ideally in tandem. We propose a new interconnection model, Sharp and an associated partitioning algorithm. The Sharp interconnection model uses a partitioning shape that roughly resembles the musical sharp 'number sign' and makes extensive use of pre-computed rectilinear Steiner trees. The model is designed to generate strategic routing information along with the partitioning results. Additionally, the Sharp model also generates estimates of the routing congestion. We also propose the Sharp layout heuristic that solves the layout problem in its entirety. The Sharp layout heuristic makes extensive use of the Sharp partitioning model. The use of precomputed Steiner tree forms enables the method to model accurately net characteristics. For example, the Steiner tree forms can model both the length of the net and more importantly its route. In fact, the tree forms are also appropriate for modeling the timing delays of nets. The Sharp heuristic works to minimize both the total layout area by minimizing total net length (thus reducing the total wiring area), and the congestion imbalances in the various channels (thus reducing the unused or wasted channel area). Our heuristic uses circuit element movements amongst the different partitioning blocks and selection of alternate minimal Steiner tree forms to achieve this goal. The objective function for the algorithm can be modified readily to include other important circuit constraints like propagation delays. The layout technique first computes a very high-level approximation of the layout solution (i.e., the positions of the circuit elements and the associated net routes). The approximate solution is alternately refined, objective function. The technique creates well defined sub-problems and offers intermediary steps that can be solved in parallel, as well as a parallel mechanism to merge the sub-problem solutions.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

PubMed

MacGillivray, Brian H

2017-08-01

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.

Storage Costs and Heuristics Interact to Produce Patterns of Aphasic Sentence Comprehension Performance

PubMed Central

Clark, David Glenn

2012-01-01

Background: Despite general agreement that aphasic individuals exhibit difficulty understanding complex sentences, the nature of sentence complexity itself is unresolved. In addition, aphasic individuals appear to make use of heuristic strategies for understanding sentences. This research is a comparison of predictions derived from two approaches to the quantification of sentence complexity, one based on the hierarchical structure of sentences, and the other based on dependency locality theory (DLT). Complexity metrics derived from these theories are evaluated under various assumptions of heuristic use. Method: A set of complexity metrics was derived from each general theory of sentence complexity and paired with assumptions of heuristic use. Probability spaces were generated that summarized the possible patterns of performance across 16 different sentence structures. The maximum likelihood of comprehension scores of 42 aphasic individuals was then computed for each probability space and the expected scores from the best-fitting points in the space were recorded for comparison to the actual scores. Predictions were then compared using measures of fit quality derived from linear mixed effects models. Results: All three of the metrics that provide the most consistently accurate predictions of patient scores rely on storage costs based on the DLT. Patients appear to employ an Agent–Theme heuristic, but vary in their tendency to accept heuristically generated interpretations. Furthermore, the ability to apply the heuristic may be degraded in proportion to aphasia severity. Conclusion: DLT-derived storage costs provide the best prediction of sentence comprehension patterns in aphasia. Because these costs are estimated by counting incomplete syntactic dependencies at each point in a sentence, this finding suggests that aphasia is associated with reduced availability of cognitive resources for maintaining these dependencies. PMID:22590462

Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance.

PubMed

Clark, David Glenn

2012-01-01

Despite general agreement that aphasic individuals exhibit difficulty understanding complex sentences, the nature of sentence complexity itself is unresolved. In addition, aphasic individuals appear to make use of heuristic strategies for understanding sentences. This research is a comparison of predictions derived from two approaches to the quantification of sentence complexity, one based on the hierarchical structure of sentences, and the other based on dependency locality theory (DLT). Complexity metrics derived from these theories are evaluated under various assumptions of heuristic use. A set of complexity metrics was derived from each general theory of sentence complexity and paired with assumptions of heuristic use. Probability spaces were generated that summarized the possible patterns of performance across 16 different sentence structures. The maximum likelihood of comprehension scores of 42 aphasic individuals was then computed for each probability space and the expected scores from the best-fitting points in the space were recorded for comparison to the actual scores. Predictions were then compared using measures of fit quality derived from linear mixed effects models. All three of the metrics that provide the most consistently accurate predictions of patient scores rely on storage costs based on the DLT. Patients appear to employ an Agent-Theme heuristic, but vary in their tendency to accept heuristically generated interpretations. Furthermore, the ability to apply the heuristic may be degraded in proportion to aphasia severity. DLT-derived storage costs provide the best prediction of sentence comprehension patterns in aphasia. Because these costs are estimated by counting incomplete syntactic dependencies at each point in a sentence, this finding suggests that aphasia is associated with reduced availability of cognitive resources for maintaining these dependencies.

A hop count based heuristic routing protocol for mobile delay tolerant networks.

PubMed

You, Lei; Li, Jianbo; Wei, Changjiang; Dai, Chenqu; Xu, Jixing; Hu, Lejuan

2014-01-01

Routing in delay tolerant networks (DTNs) is a challenge since it must handle network partitioning, long delays, and dynamic topology. Meanwhile, routing protocols of the traditional mobile ad hoc networks (MANETs) cannot work well due to the failure of its assumption that most network connections are available. In this paper, we propose a hop count based heuristic routing protocol by utilizing the information carried by the peripatetic packets in the network. A heuristic function is defined to help in making the routing decision. We formally define a custom operation for square matrices so as to transform the heuristic value calculation into matrix manipulation. Finally, the performance of our proposed algorithm is evaluated by the simulation results, which show the advantage of such self-adaptive routing protocol in the diverse circumstance of DTNs.

A Hop Count Based Heuristic Routing Protocol for Mobile Delay Tolerant Networks

PubMed Central

Wei, Changjiang; Dai, Chenqu; Xu, Jixing; Hu, Lejuan

2014-01-01

Routing in delay tolerant networks (DTNs) is a challenge since it must handle network partitioning, long delays, and dynamic topology. Meanwhile, routing protocols of the traditional mobile ad hoc networks (MANETs) cannot work well due to the failure of its assumption that most network connections are available. In this paper, we propose a hop count based heuristic routing protocol by utilizing the information carried by the peripatetic packets in the network. A heuristic function is defined to help in making the routing decision. We formally define a custom operation for square matrices so as to transform the heuristic value calculation into matrix manipulation. Finally, the performance of our proposed algorithm is evaluated by the simulation results, which show the advantage of such self-adaptive routing protocol in the diverse circumstance of DTNs. PMID:25110736

Impact of heuristics in clustering large biological networks.

PubMed

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new Nawaz-Enscore-Ham-based heuristic for permutation flow-shop problems with bicriteria of makespan and machine idle time

NASA Astrophysics Data System (ADS)

Liu, Weibo; Jin, Yan; Price, Mark

2016-10-01

A new heuristic based on the Nawaz-Enscore-Ham algorithm is proposed in this article for solving a permutation flow-shop scheduling problem. A new priority rule is proposed by accounting for the average, mean absolute deviation, skewness and kurtosis, in order to fully describe the distribution style of processing times. A new tie-breaking rule is also introduced for achieving effective job insertion with the objective of minimizing both makespan and machine idle time. Statistical tests illustrate better solution quality of the proposed algorithm compared to existing benchmark heuristics.

Efficient Network Coding-Based Loss Recovery for Reliable Multicast in Wireless Networks

NASA Astrophysics Data System (ADS)

Chi, Kaikai; Jiang, Xiaohong; Ye, Baoliu; Horiguchi, Susumu

Recently, network coding has been applied to the loss recovery of reliable multicast in wireless networks [19], where multiple lost packets are XOR-ed together as one packet and forwarded via single retransmission, resulting in a significant reduction of bandwidth consumption. In this paper, we first prove that maximizing the number of lost packets for XOR-ing, which is the key part of the available network coding-based reliable multicast schemes, is actually a complex NP-complete problem. To address this limitation, we then propose an efficient heuristic algorithm for finding an approximately optimal solution of this optimization problem. Furthermore, we show that the packet coding principle of maximizing the number of lost packets for XOR-ing sometimes cannot fully exploit the potential coding opportunities, and we then further propose new heuristic-based schemes with a new coding principle. Simulation results demonstrate that the heuristic-based schemes have very low computational complexity and can achieve almost the same transmission efficiency as the current coding-based high-complexity schemes. Furthermore, the heuristic-based schemes with the new coding principle not only have very low complexity, but also slightly outperform the current high-complexity ones.

Development of heuristic bias detection in elementary school.

PubMed

De Neys, Wim; Feremans, Vicky

2013-02-01

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 presented with child-friendly versions of classic base-rate problems in which a cued heuristic response could be inconsistent or consistent with the base rates. After each problem children were asked to indicate their subjective response confidence to assess their bias detection skills. Results indicated that 6th graders showed a clear confidence decrease when they gave a heuristic response that conflicted with the base rates. However, this confidence decrease was not observed for 3rd graders, suggesting that they did not yet acknowledge that their judgment was not fully warranted. Implications for the development of efficient training programs and the debate on human rationality are discussed. (c) 2013 APA, all rights reserved.

Using Empirical Mode Decomposition to process Marine Magnetotelluric Data

NASA Astrophysics Data System (ADS)

Chen, J.; Jegen, M. D.; Heincke, B. H.; Moorkamp, M.

2014-12-01

The magnetotelluric (MT) data always exhibits nonstationarities due to variations of source mechanisms causing MT variations on different time and spatial scales. An additional non-stationary component is introduced through noise, which is particularly pronounced in marine MT data through motion induced noise caused by time-varying wave motion and currents. We present a new heuristic method for dealing with the non-stationarity of MT time series based on Empirical Mode Decomposition (EMD). The EMD method is used in combination with the derived instantaneous spectra to determine impedance estimates. The procedure is tested on synthetic and field MT data. In synthetic tests the reliability of impedance estimates from EMD-based method is compared to the synthetic responses of a 1D layered model. To examine how estimates are affected by noise, stochastic stationary and non-stationary noise are added on the time series. Comparisons reveal that estimates by the EMD-based method are generally more stable than those by simple Fourier analysis. Furthermore, the results are compared to those derived by a commonly used Fourier-based MT data processing software (BIRRP), which incorporates additional sophisticated robust estimations to deal with noise issues. It is revealed that the results from both methods are already comparable, even though no robust estimate procedures are implemented in the EMD approach at present stage. The processing scheme is then applied to marine MT field data. Testing is performed on short, relatively quiet segments of several data sets, as well as on long segments of data with many non-stationary noise packages. Compared to BIRRP, the new method gives comparable or better impedance estimates, furthermore, the estimates are extended to lower frequencies and less noise biased estimates with smaller error bars are obtained at high frequencies. The new processing methodology represents an important step towards deriving a better resolved Earth model to greater depth underneath the seafloor.

Impact of Blended Learning Environments Based on Algo-Heuristic Theory on Some Variables

ERIC Educational Resources Information Center

Aygün, Mustafa; Korkmaz, Özgen

2012-01-01

In this study, the effects of Algo-Heuristic Theory based blended learning environments on students' computer skills in their preparation of presentations, levels of attitudes towards computers, and levels of motivation regarding the information technology course were investigated. The research sample was composed of 71 students. A semi-empirical…

Exact and Heuristic Algorithms for Runway Scheduling

NASA Technical Reports Server (NTRS)

Malik, Waqar A.; Jung, Yoon C.

2016-01-01

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

PubMed Central

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-01-01

Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465

Paranoid thinking as a heuristic.

PubMed

Preti, Antonio; Cella, Matteo

2010-08-01

Paranoid thinking can be viewed as a human heuristic used by individuals to deal with uncertainty during stressful situations. Under stress, individuals are likely to emphasize the threatening value of neutral stimuli and increase the reliance on paranoia-based heuristic to interpreter events and guide their decisions. Paranoid thinking can also be activated by stress arising from the possibility of losing a good opportunity; this may result in an abnormal allocation of attentional resources to social agents. A better understanding of the interplay between cognitive heuristics and emotional processes may help to detect situations in which paranoid thinking is likely to exacerbate and improve intervention for individuals with delusional disorders.

How Smart Do You Need to Be to Get It Wrong? The Role of Cognitive Capacity in the Development of Heuristic-Based Judgment

ERIC Educational Resources Information Center

Morsanyi, Kinga; Handley, Simon J.

2008-01-01

We examined the relationship between cognitive capacity and heuristic responding on four types of reasoning and decision-making tasks. A total of 84 children, between 5 years 2 months and 11 years 7 months of age, participated in the study. There was a marked increase in heuristic responding with age that was related to increases in cognitive…

A Heuristic Decision Making Model to Mitigate Adverse Consequences in a Network Centric Warfare/Sense and Respond System

DTIC Science & Technology

2005-05-01

made. 4. Do military decision makers identify / analyze adverse consequences presently? Few do based on this research and most don’t do it effectively ...A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM...ENS/05-01 A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM

Unified heuristics to solve routing problem of reverse logistics in sustainable supply chain

NASA Astrophysics Data System (ADS)

Anbuudayasankar, S. P.; Ganesh, K.; Lenny Koh, S. C.; Mohandas, K.

2010-03-01

A reverse logistics problem, motivated by many real-life applications, is examined where bottles/cans in which products are delivered from a processing depot to customers in one period are available for return to the depot in the following period. The picked-up bottles/cans need to be adjusted in the place of delivery load. This problem is termed as simultaneous delivery and pick-up problem with constrained capacity (SDPC). We develop three unified heuristics based on extended branch and bound heuristic, genetic algorithm and simulated annealing to solve SDPC. These heuristics are also designed to solve standard travelling salesman problem (TSP) and TSP with simultaneous delivery and pick-up (TSDP). We tested the heuristics on standard, derived and randomly generated datasets of TSP, TSDP and SDPC and obtained satisfying results with high convergence in reasonable time.

Evidence-based Heuristics for Evaluating Demands on eHealth Literacy and Usability in a Mobile Consumer Health Application.

PubMed

Monkman, Helen; Griffith, Janessa; Kushniruk, Andre W

2015-01-01

Heuristic evaluations have proven to be valuable for identifying usability issues in systems. Commonly used sets of heuritics exist; however, they may not always be the most suitable, given the specific goal of the analysis. One such example is seeking to evaluate the demands on eHealth literacy and usability of consumer health information systems. In this study, eight essential heuristics and three optional heuristics subsumed from the evidence on eHealth/health literacy and usability were tested for their utility in assessing a mobile blood pressure tracking application (app). This evaluation revealed a variety of ways the design of the app could both benefit and impede users with limited eHealth literacy. This study demonstrated the utility of a low-cost, single evaluation approach for identifying both eHealth literacy and usability issues based on existing evidence in the literature.

Can the inherence heuristic explain vitalistic reasoning?

PubMed

Bastian, Brock

2014-10-01

Inherence is an important component of psychological essentialism. By drawing on vitalism as a way in which to explain this link, however, the authors appear to conflate causal explanations based on fixed features with those based on general causal forces. The disjuncture between these two types of explanatory principles highlights potential new avenues for the inherence heuristic.

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.

Scheduling and rescheduling with iterative repair

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Daun, Brian; Deale, Michael

1992-01-01

This paper describes the GERRY scheduling and rescheduling system being applied to coordinate Space Shuttle Ground Processing. The system uses constraint-based iterative repair, a technique that starts with a complete but possibly flawed schedule and iteratively improves it by using constraint knowledge within repair heuristics. In this paper we explore the tradeoff between the informedness and the computational cost of several repair heuristics. We show empirically that some knowledge can greatly improve the convergence speed of a repair-based system, but that too much knowledge, such as the knowledge embodied within the MIN-CONFLICTS lookahead heuristic, can overwhelm a system and result in degraded performance.

Efficient partitioning and assignment on programs for multiprocessor execution

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1993-01-01

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Propagation and wavefront ambiguity of linear nondiffracting beams

NASA Astrophysics Data System (ADS)

Grunwald, R.; Bock, M.

2014-02-01

Ultrashort-pulsed Bessel and Airy beams in free space are often interpreted as "linear light bullets". Usually, interconnected intensity profiles are considered a "propagation" along arbitrary pathways which can even follow curved trajectories. A more detailed analysis, however, shows that this picture gives an adequate description only in situations which do not require to consider the transport of optical signals or causality. To also cover these special cases, a generalization of the terms "beam" and "propagation" is necessary. The problem becomes clearer by representing the angular spectra of the propagating wave fields by rays or Poynting vectors. It is known that quasi-nondiffracting beams can be described as caustics of ray bundles. Their decomposition into Poynting vectors by Shack-Hartmann sensors indicates that, in the frame of their classical definition, the corresponding local wavefronts are ambiguous and concepts based on energy density are not appropriate to describe the propagation completely. For this reason, quantitative parameters like the beam propagation factor have to be treated with caution as well. For applications like communication or optical computing, alternative descriptions are required. A heuristic approach based on vector field based information transport and Fourier analysis is proposed here. Continuity and discontinuity of far field distributions in space and time are discussed. Quantum aspects of propagation are briefly addressed.

Précis of Simple heuristics that make us smart.

PubMed

Todd, P M; Gigerenzer, G

2000-10-01

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.

Put a limit on it: The protective effects of scarcity heuristics when self-control is low

PubMed Central

Cheung, Tracy TL; Kroese, Floor M; Fennis, Bob M; De Ridder, Denise TD

2015-01-01

Low self-control is a state in which consumers are assumed to be vulnerable to making impulsive choices that hurt long-term goals. Rather than increasing self-control, the current research exploits the tendency for heuristic-based thinking in low self-control by employing scarcity heuristics to promote better consumption choices. Results indicate that consumers low in self-control especially benefited and selected more healthy choices when marketed as “scarce” (Study 1), and that a demand (vs supply) scarcity heuristic was most effective in promoting utilitarian products (Study 2) suggests low self-control involves both an enhanced reward orientation and increased tendency to conform to descriptive norms. PMID:28070377

A two-stage stochastic rule-based model to determine pre-assembly buffer content

NASA Astrophysics Data System (ADS)

Gunay, Elif Elcin; Kula, Ufuk

2018-01-01

This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decides the spare vehicle quantities, where the second stage model recovers the scrambled sequence respect to pre-defined rules. The problem is solved by sample average approximation (SAA) algorithm. We conduct a numerical study to compare the solutions of heuristic model with optimal ones and provide following insights: (i) as the mismatch between paint entrance and scheduled sequence decreases, the rule-based heuristic model recovers the scrambled sequence as good as the optimal resequencing model, (ii) the rule-based model is more sensitive to the mismatch between the paint entrance and scheduled sequences for recovering the scrambled sequence, (iii) as the defect rate increases, the difference in recovery effectiveness between rule-based heuristic and optimal solutions increases, (iv) as buffer capacity increases, the recovery effectiveness of the optimization model outperforms heuristic model, (v) as expected the rule-based model holds more inventory than the optimization model.

Response demands and the recruitment of heuristic strategies in syllogistic reasoning.

PubMed

Reverberi, Carlo; Rusconi, Patrice; Paulesu, Eraldo; Cherubini, Paolo

2009-03-01

Two experiments investigated whether dealing with a homogeneous subset of syllogisms with time-constrained responses encouraged participants to develop and use heuristics for abstract (Experiment 1) and thematic (Experiment 2) syllogisms. An atmosphere-based heuristic accounted for most responses with both abstract and thematic syllogisms. With thematic syllogisms, a weaker effect of a belief heuristic was also observed, mainly where the correct response was inconsistent with the atmosphere of the premises. Analytic processes appear to have played little role in the time-constrained condition, whereas their involvement increased in a self-paced, unconstrained condition. From a dual-process perspective, the results further specify how task demands affect the recruitment of heuristic and analytic systems of reasoning. Because the syllogisms and experimental procedure were the same as those used in a previous neuroimaging study by Goel, Buchel, Frith, and Dolan (2000), the result also deepen our understanding of the cognitive processes investigated by that study.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

PubMed

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

PubMed Central

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505

A health literacy and usability heuristic evaluation of a mobile consumer health application.

PubMed

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.

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.

Reasoning heuristics across the psychosis continuum: the contribution of hypersalient evidence-hypothesis matches.

PubMed

Balzan, Ryan; Delfabbro, Paul; Galletly, Cherrie; Woodward, Todd

2012-01-01

Hypersalience of evidence-hypothesis matches has recently been proposed as the cognitive mechanism responsible for the cognitive biases which, in turn, may contribute to the formation and maintenance of delusions. However, the construct lacks empirical support. The current paper investigates the possibility that individuals with delusions are hypersalient to evidence-hypothesis matches using a series of cognitive tasks designed to elicit the representativeness and availability reasoning heuristics. It was hypothesised that hypersalience of evidence-hypothesis matches may increase a person's propensity to rely on judgements of representativeness (i.e., when the probability of an outcome is based on its similarity with its parent population) and availability (i.e., estimates of frequency based on the ease with which relevant events come to mind). A total of 75 participants (25 diagnosed with schizophrenia with a history of delusions; 25 nonclinical delusion-prone; 25 nondelusion-prone controls) completed four heuristics tasks based on the original Tversky and Kahnemann experiments. These included two representativeness tasks ("coin-toss" random sequence task; "lawyer-engineer" base-rates task) and two availability tasks ("famous-names" and "letter-frequency" tasks). The results across these four heuristics tasks showed that participants with schizophrenia were more susceptible than nonclinical groups to both the representativeness and availability reasoning heuristics. These results suggest that delusional ideation is linked to a hypersalience of evidence-hypothesis matches. The theoretical implications of this cognitive mechanism on the formation and maintenance of delusions are discussed.

Heuristic Evaluation on Mobile Interfaces: A New Checklist

PubMed Central

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

Negations in syllogistic reasoning: evidence for a heuristic-analytic conflict.

PubMed

Stupple, Edward J N; Waterhouse, Eleanor F

2009-08-01

An experiment utilizing response time measures was conducted to test dominant processing strategies in syllogistic reasoning with the expanded quantifier set proposed by Roberts (2005). Through adding negations to existing quantifiers it is possible to change problem surface features without altering logical validity. Biases based on surface features such as atmosphere, matching, and the probability heuristics model (PHM; Chater & Oaksford, 1999; Wetherick & Gilhooly, 1995) would not be expected to show variance in response latencies, but participant responses should be highly sensitive to changes in the surface features of the quantifiers. In contrast, according to analytic accounts such as mental models theory and mental logic (e.g., Johnson-Laird & Byrne, 1991; Rips, 1994) participants should exhibit increased response times for negated premises, but not be overly impacted upon by the surface features of the conclusion. Data indicated that the dominant response strategy was based on a matching heuristic, but also provided evidence of a resource-demanding analytic procedure for dealing with double negatives. The authors propose that dual-process theories offer a stronger account of these data whereby participants employ competing heuristic and analytic strategies and fall back on a heuristic response when analytic processing fails.

Identifying a set of influential spreaders in complex networks

NASA Astrophysics Data System (ADS)

Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

2016-06-01

Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency.

Sparse Gaussian elimination with controlled fill-in on a shared memory multiprocessor

NASA Technical Reports Server (NTRS)

Alaghband, Gita; Jordan, Harry F.

1989-01-01

It is shown that in sparse matrices arising from electronic circuits, it is possible to do computations on many diagonal elements simultaneously. A technique for obtaining an ordered compatible set directly from the ordered incompatible table is given. The ordering is based on the Markowitz number of the pivot candidates. This technique generates a set of compatible pivots with the property of generating few fills. A novel heuristic algorithm is presented that combines the idea of an order-compatible set with a limited binary tree search to generate several sets of compatible pivots in linear time. An elimination set for reducing the matrix is generated and selected on the basis of a minimum Markowitz sum number. The parallel pivoting technique presented is a stepwise algorithm and can be applied to any submatrix of the original matrix. Thus, it is not a preordering of the sparse matrix and is applied dynamically as the decomposition proceeds. Parameters are suggested to obtain a balance between parallelism and fill-ins. Results of applying the proposed algorithms on several large application matrices using the HEP multiprocessor (Kowalik, 1985) are presented and analyzed.

Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Russell W

This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositionsmore » which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.« less

Heuristic evaluation of eNote: an electronic notes system.

PubMed

Bright, Tiffani J; Bakken, Suzanne; Johnson, Stephen B

2006-01-01

eNote is an electronic health record (EHR) system based on semi-structured narrative documents. A heuristic evaluation was conducted with a sample of five usability experts. eNote performed highly in: 1)consistency with standards and 2)recognition rather than recall. eNote needs improvement in: 1)help and documentation, 2)aesthetic and minimalist design, 3)error prevention, 4)helping users recognize, diagnosis, and recover from errors, and 5)flexibility and efficiency of use. The heuristic evaluation was an efficient method of evaluating our interface.

SHRIF, a General-Purpose System for Heuristic Retrieval of Information and Facts, Applied to Medical Knowledge Processing.

ERIC Educational Resources Information Center

Findler, Nicholas V.; And Others

1992-01-01

Describes SHRIF, a System for Heuristic Retrieval of Information and Facts, and the medical knowledge base that was used in its development. Highlights include design decisions; the user-machine interface, including the language processor; and the organization of the knowledge base in an artificial intelligence (AI) project like this one. (57…

A new graph-based method for pairwise global network alignment

PubMed Central

Klau, Gunnar W

2009-01-01

Background In addition to component-based comparative approaches, network alignments provide the means to study conserved network topology such as common pathways and more complex network motifs. Yet, unlike in classical sequence alignment, the comparison of networks becomes computationally more challenging, as most meaningful assumptions instantly lead to NP-hard problems. Most previous algorithmic work on network alignments is heuristic in nature. Results We introduce the graph-based maximum structural matching formulation for pairwise global network alignment. We relate the formulation to previous work and prove NP-hardness of the problem. Based on the new formulation we build upon recent results in computational structural biology and present a novel Lagrangian relaxation approach that, in combination with a branch-and-bound method, computes provably optimal network alignments. The Lagrangian algorithm alone is a powerful heuristic method, which produces solutions that are often near-optimal and – unlike those computed by pure heuristics – come with a quality guarantee. Conclusion Computational experiments on the alignment of protein-protein interaction networks and on the classification of metabolic subnetworks demonstrate that the new method is reasonably fast and has advantages over pure heuristics. Our software tool is freely available as part of the LISA library. PMID:19208162

Heuristic evaluation of infusion pumps: implications for patient safety in Intensive Care Units.

PubMed

Graham, Mark J; Kubose, Tate K; Jordan, Desmond; Zhang, Jiajie; Johnson, Todd R; Patel, Vimla L

2004-11-01

The goal of this research was to use a heuristic evaluation methodology to uncover design and interface deficiencies of infusion pumps that are currently in use in Intensive Care Units (ICUs). Because these infusion systems cannot be readily replaced due to lease agreements and large-scale institutional purchasing procedures, we argue that it is essential to systematically identify the existing usability problems so that the possible causes of errors can be better understood, passed on to the end-users (e.g., critical care nurses), and used to make policy recommendations. Four raters conducted the heuristic evaluation of the three-channel infusion pump interface. Three raters had a cognitive science background as well as experience with the heuristic evaluation methodology. The fourth rater was a veteran critical care nurse who had extensive experience operating the pumps. The usability experts and the domain expert independently evaluated the user interface and physical design of the infusion pump and generated a list of heuristic violations based upon a set of 14 heuristics developed in previous research. The lists were compiled and then rated on the severity of the violation. From 14 usability heuristics considered in this evaluation of the Infusion Pump, there were 231 violations. Two heuristics, "Consistency" and "Language", were found to have the most violations. The one with fewest violations was "Document". While some heuristic evaluation categories had more violations than others, the most severe ones were not confined to one type. The Primary interface location (e.g., where loading the pump, changing doses, and confirming drug settings takes place) had the most occurrences of heuristic violations. We believe that the Heuristic Evaluation methodology provides a simple and cost-effective approach to discovering medical device deficiencies that affect a patient's general well being. While this methodology provides information for the infusion pump designs of the future, it also identifies important insights concerning equipment that is currently in use in critical care environments.

How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

PubMed

Lecca, Paola

2018-01-01

We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of drug release, we point out how Monte Carlo heuristics can be integrated in an evolutionary algorithmic approach to infer the mode of MCS best fitting the observed data, and thus the observed release kinetics.•The software implementing the method is written in R language, the free most used language in the bioinformaticians community.

Hybridisations of Variable Neighbourhood Search and Modified Simplex Elements to Harmony Search and Shuffled Frog Leaping Algorithms for Process Optimisations

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.

Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.

PubMed

Richie, Megan; Josephson, S Andrew

2018-01-01

Construct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained significance for students (Version A, M = 7.28, SD = 3.46; Version B, M = 5.82, SD = 3.22), t(153) = 2.67, p = .008, and residents (Version A, M = 7.19, SD = 3.24; Version B, M = 5.56, SD = 2.72), t(77) = 2.32, p = .02, but not attendings. Authors developed an instrument to isolate and quantify bias produced by the availability and representativeness heuristics, and illustrated the utility of their instrument by demonstrating decreased heuristic bias within medical contexts at higher training levels.

Triplet supertree heuristics for the tree of life

PubMed Central

Lin, Harris T; Burleigh, J Gordon; Eulenstein, Oliver

2009-01-01

Background There is much interest in developing fast and accurate supertree methods to infer the tree of life. Supertree methods combine smaller input trees with overlapping sets of taxa to make a comprehensive phylogenetic tree that contains all of the taxa in the input trees. The intrinsically hard triplet supertree problem takes a collection of input species trees and seeks a species tree (supertree) that maximizes the number of triplet subtrees that it shares with the input trees. However, the utility of this supertree problem has been limited by a lack of efficient and effective heuristics. Results We introduce fast hill-climbing heuristics for the triplet supertree problem that perform a step-wise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. To realize time efficient heuristics we designed the first nontrivial algorithms for two standard search problems, which greatly improve on the time complexity to the best known (naïve) solutions by a factor of n and n2 (the number of taxa in the supertree). These algorithms enable large-scale supertree analyses based on the triplet supertree problem that were previously not possible. We implemented hill-climbing heuristics that are based on our new algorithms, and in analyses of two published supertree data sets, we demonstrate that our new heuristics outperform other standard supertree methods in maximizing the number of triplets shared with the input trees. Conclusion With our new heuristics, the triplet supertree problem is now computationally more tractable for large-scale supertree analyses, and it provides a potentially more accurate alternative to existing supertree methods. PMID:19208181

The normalization heuristic: an untested hypothesis that may misguide medical decisions.

PubMed

Aberegg, Scott K; O'Brien, James M

2009-06-01

Medical practice is increasingly informed by the evidence from randomized controlled trials. When such evidence is not available, clinical hypotheses based on pathophysiological reasoning and common sense guide clinical decision making. One commonly utilized general clinical hypothesis is the assumption that normalizing abnormal laboratory values and physiological parameters will lead to improved patient outcomes. We refer to the general use of this clinical hypothesis to guide medical therapeutics as the "normalization heuristic". In this paper, we operationally define this heuristic and discuss its limitations as a rule of thumb for clinical decision making. We review historical and contemporaneous examples of normalization practices as empirical evidence for the normalization heuristic and to highlight its frailty as a guide for clinical decision making.

What is behind the priority heuristic? A mathematical analysis and comment on Brandstätter, Gigerenzer, and Hertwig (2006).

PubMed

Rieger, Marc Oliver; Wang, Mei

2008-01-01

Comments on the article by E. Brandstätter, G. Gigerenzer, and R. Hertwig. The authors discuss the priority heuristic, a recent model for decisions under risk. They reanalyze the experimental validity of this approach and discuss how these results compare with cumulative prospect theory, the currently most established model in behavioral economics. They also discuss how general models for decisions under risk based on a heuristic approach can be understood mathematically to gain some insight in their limitations. They finally consider whether the priority heuristic model can lead to some understanding of the decision process of individuals or whether it is better seen as an as-if model. (c) 2008 APA, all rights reserved

Fourth Graders' Heuristic Problem-Solving Behavior.

ERIC Educational Resources Information Center

Lee, Kil S.

1982-01-01

Eight boys and eight girls from a rural elementary school participated in the investigation. Specific heuristics were adopted from Polya; and the students selected represented two substages of Piaget's concrete operational stage. Five hypotheses were generated, based on observed results and the study's theoretical rationale. (MP)

Redundancy checking algorithms based on parallel novel extension rule

NASA Astrophysics Data System (ADS)

Liu, Lei; Yang, Yang; Li, Guangli; Wang, Qi; Lü, Shuai

2017-05-01

Redundancy checking (RC) is a key knowledge reduction technology. Extension rule (ER) is a new reasoning method, first presented in 2003 and well received by experts at home and abroad. Novel extension rule (NER) is an improved ER-based reasoning method, presented in 2009. In this paper, we first analyse the characteristics of the extension rule, and then present a simple algorithm for redundancy checking based on extension rule (RCER). In addition, we introduce MIMF, a type of heuristic strategy. Using the aforementioned rule and strategy, we design and implement RCHER algorithm, which relies on MIMF. Next we design and implement an RCNER (redundancy checking based on NER) algorithm based on NER. Parallel computing greatly accelerates the NER algorithm, which has weak dependence among tasks when executed. Considering this, we present PNER (parallel NER) and apply it to redundancy checking and necessity checking. Furthermore, we design and implement the RCPNER (redundancy checking based on PNER) and NCPPNER (necessary clause partition based on PNER) algorithms as well. The experimental results show that MIMF significantly influences the acceleration of algorithm RCER in formulae on a large scale and high redundancy. Comparing PNER with NER and RCPNER with RCNER, the average speedup can reach up to the number of task decompositions when executed. Comparing NCPNER with the RCNER-based algorithm on separating redundant formulae, speedup increases steadily as the scale of the formulae is incrementing. Finally, we describe the challenges that the extension rule will be faced with and suggest possible solutions.

Operational Planning of Channel Airlift Missions Using Forecasted Demand

DTIC Science & Technology

2013-03-01

tailored to the specific problem ( Metaheuristics , 2005). As seen in the section Cargo Loading Algorithm , heuristic methods are often iterative...that are equivalent to the forecasted cargo amount. The simulated pallets are then used in a heuristic cargo loading algorithm . The loading... algorithm places cargo onto available aircraft (based on real schedules) given the date and the destination and outputs statistics based on the aircraft ton

A Simulation of Readiness-Based Sparing Policies

DTIC Science & Technology

2017-06-01

variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the...available in the optimization tools. 14. SUBJECT TERMS readiness-based sparing, discrete event simulation, optimization, multi-indenture...variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Neural basis of scientific innovation induced by heuristic prototype.

PubMed

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.

Neural Basis of Scientific Innovation Induced by Heuristic Prototype

PubMed Central

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

Memory-based decision-making with heuristics: evidence for a controlled activation of memory representations.

PubMed

Khader, Patrick H; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rösler, Frank

2011-11-01

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 activating long-term memory representations of only those attributes that are necessary for the decision. However, from behavioral studies alone, it is unclear whether using heuristics is indeed associated with limited memory search. The present study tested this assumption by monitoring the activation of specific long-term-memory representations with fMRI while participants made memory-based decisions using the "take-the-best" heuristic. For different decision trials, different numbers and types of information had to be retrieved and processed. The attributes consisted of visual information known to be represented in different parts of the posterior cortex. We found that the amount of information required for a decision was mirrored by a parametric activation of the dorsolateral PFC. Such a parametric pattern was also observed in all posterior areas, suggesting that activation was not limited to those attributes required for a decision. However, the posterior increases were systematically modulated by the relative importance of the information for making a decision. These findings suggest that memory-based decision-making is mediated by the dorsolateral PFC, which selectively controls posterior storage areas. In addition, the systematic modulations of the posterior activations indicate a selective boosting of activation of decision-relevant attributes.

Toward a More Usable Home-Based Video Telemedicine System: A Heuristic Evaluation of the Clinician User Interfaces of Home-Based Video Telemedicine Systems

PubMed Central

Welch, Brandon; Brinda, FNU

2017-01-01

Background Telemedicine is the use of technology to provide and support health care when distance separates the clinical service and the patient. Home-based telemedicine systems involve the use of such technology for medical support and care connecting the patient from the comfort of their homes with the clinician. In order for such a system to be used extensively, it is necessary to understand not only the issues faced by the patients in using them but also the clinician. Objectives The aim of this study was to conduct a heuristic evaluation of 4 telemedicine software platforms—Doxy.me, Polycom, Vidyo, and VSee—to assess possible problems and limitations that could affect the usability of the system from the clinician’s perspective. Methods It was found that 5 experts individually evaluated all four systems using Nielsen’s list of heuristics, classifying the issues based on a severity rating scale. Results A total of 46 unique problems were identified by the experts. The heuristics most frequently violated were visibility of system status and Error prevention amounting to 24% (11/46 issues) each. Esthetic and minimalist design was second contributing to 13% (6/46 issues) of the total errors. Conclusions Heuristic evaluation coupled with a severity rating scale was found to be an effective method for identifying problems with the systems. Prioritization of these problems based on the rating provides a good starting point for resolving the issues affecting these platforms. There is a need for better transparency and a more streamlined approach for how physicians use telemedicine systems. Visibility of the system status and speaking the users’ language are keys for achieving this. PMID:28438724

Autobiographical Elaboration Reduces Memory Distortion: Cognitive Operations and the Distinctiveness Heuristic

ERIC Educational Resources Information Center

McDonough, Ian M.; Gallo, David A.

2008-01-01

Retrieval monitoring enhances episodic memory accuracy. For instance, false recognition is reduced when participants base their decisions on more distinctive recollections, a retrieval monitoring process called the distinctiveness heuristic. The experiments reported here tested the hypothesis that autobiographical elaboration during study (i.e.,…

Testing a videogame intervention to recalibrate physician heuristics in trauma triage: study protocol for a randomized controlled trial.

PubMed

Mohan, Deepika; Rosengart, Matthew R; Fischhoff, Baruch; Angus, Derek C; Farris, Coreen; Yealy, Donald M; Wallace, David J; Barnato, Amber E

2016-11-11

Between 30 and 40 % of patients with severe injuries receive treatment at non-trauma centers (under-triage), largely because of physician decision making. Existing interventions to improve triage by physicians ignore the role that intuition (heuristics) plays in these decisions. One such heuristic is to form an initial impression based on representativeness (how typical does a patient appear of one with severe injuries). We created a video game (Night Shift) to recalibrate physician's representativeness heuristic in trauma triage. We developed Night Shift in collaboration with emergency medicine physicians, trauma surgeons, behavioral scientists, and game designers. Players take on the persona of Andy Jordan, an emergency medicine physician, who accepts a new job in a small town. Through a series of cases that go awry, they gain experience with the contextual cues that distinguish patients with minor and severe injuries (based on the theory of analogical encoding) and receive emotionally-laden feedback on their performance (based on the theory of narrative engagement). The planned study will compare the effect of Night Shift with that of an educational program on physician triage decisions and on physician heuristics. Psychological theory predicts that cognitive load increases reliance on heuristics, thereby increasing the under-triage rate when heuristics are poorly calibrated. We will randomize physicians (n = 366) either to play the game or to review an educational program, and will assess performance using a validated virtual simulation. The validated simulation includes both control and cognitive load conditions. We will compare rates of under-triage after exposure to the two interventions (primary outcome) and will compare the effect of cognitive load on physicians' under-triage rates (secondary outcome). We hypothesize that: a) physicians exposed to Night Shift will have lower rates of under-triage compared to those exposed to the educational program, and b) cognitive load will not degrade triage performance among physicians exposed to Night Shift as much as it will among those exposed to the educational program. Serious games offer a new approach to the problem of poorly-calibrated heuristics in trauma triage. The results of this trial will contribute to the understanding of physician quality improvement and the efficacy of video games as behavioral interventions. clinicaltrials.gov; NCT02857348 ; August 2, 2016.

Incorporating metacognition into morbidity and mortality rounds: The next frontier in quality improvement.

PubMed

Katz, David; Detsky, Allan S

2016-02-01

This Perspective proposes the introduction of metacognition (thinking about thinking) into the existing format of hospital-based morbidity and mortality rounds. It is placed in the context of historical movements to advance quality improvement by expanding the spectrum of the causes of medical error from systems-based issues to flawed human decision-making capabilities. We suggest that the current approach that focuses on systems-based issues can be improved by exploiting the opportunities to educate physicians about predictable errors committed by reliance on cognitive heuristics. In addition, because the field of educating clinicians about cognitive heuristics has shown mixed results, this proposal represents fertile ground for further research. Educating clinicians about cognitive heuristics may improve metacognition and perhaps be the next frontier in quality improvement. © 2015 Society of Hospital Medicine.

Fast optimization of multipump Raman amplifiers based on a simplified wavelength and power budget heuristic

NASA Astrophysics Data System (ADS)

de O. Rocha, Helder R.; Castellani, Carlos E. S.; Silva, Jair A. L.; Pontes, Maria J.; Segatto, Marcelo E. V.

2015-01-01

We report a simple budget heuristic for a fast optimization of multipump Raman amplifiers based on the reallocation of the pump wavelengths and the optical powers. A set of different optical fibers are analyzed as the Raman gain medium, and a four-pump amplifier setup is optimized for each of them in order to achieve ripples close to 1 dB and gains up to 20 dB in the C band. Later, a comparison between our proposed heuristic and a multiobjective optimization based on a nondominated sorting genetic algorithm is made, highlighting the fact that our new approach can give similar solutions after at least an order of magnitude fewer iterations. The results shown in this paper can potentially pave the way for real-time optimization of multipump Raman amplifier systems.

Solving Inverse Kinematics of Robot Manipulators by Means of Meta-Heuristic Optimisation

NASA Astrophysics Data System (ADS)

Wichapong, Kritsada; Bureerat, Sujin; Pholdee, Nantiwat

2018-05-01

This paper presents the use of meta-heuristic algorithms (MHs) for solving inverse kinematics of robot manipulators based on using forward kinematic. Design variables are joint angular displacements used to move a robot end-effector to the target in the Cartesian space while the design problem is posed to minimize error between target points and the positions of the robot end-effector. The problem is said to be a dynamic problem as the target points always changed by a robot user. Several well established MHs are used to solve the problem and the results obtained from using different meta-heuristics are compared based on the end-effector error and searching speed of the algorithms. From the study, the best performer will be obtained for setting as the baseline for future development of MH-based inverse kinematic solving.

Neural substrates of similarity and rule-based strategies in judgment

PubMed Central

von Helversen, Bettina; Karlsson, Linnea; Rasch, Björn; Rieskamp, Jörg

2014-01-01

Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI), we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved. PMID:25360099

The probability heuristics model of syllogistic reasoning.

PubMed

Chater, N; Oaksford, M

1999-03-01

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic. Copyright 1999 Academic Press.

A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

NASA Astrophysics Data System (ADS)

Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

2017-06-01

With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

Community-aware task allocation for social networked multiagent systems.

PubMed

Wang, Wanyuan; Jiang, Yichuan

2014-09-01

In this paper, we propose a novel community-aware task allocation model for social networked multiagent systems (SN-MASs), where the agent' cooperation domain is constrained in community and each agent can negotiate only with its intracommunity member agents. Under such community-aware scenarios, we prove that it remains NP-hard to maximize system overall profit. To solve this problem effectively, we present a heuristic algorithm that is composed of three phases: 1) task selection: select the desirable task to be allocated preferentially; 2) allocation to community: allocate the selected task to communities based on a significant task-first heuristics; and 3) allocation to agent: negotiate resources for the selected task based on a nonoverlap agent-first and breadth-first resource negotiation mechanism. Through the theoretical analyses and experiments, the advantages of our presented heuristic algorithm and community-aware task allocation model are validated. 1) Our presented heuristic algorithm performs very closely to the benchmark exponential brute-force optimal algorithm and the network flow-based greedy algorithm in terms of system overall profit in small-scale applications. Moreover, in the large-scale applications, the presented heuristic algorithm achieves approximately the same overall system profit, but significantly reduces the computational load compared with the greedy algorithm. 2) Our presented community-aware task allocation model reduces the system communication cost compared with the previous global-aware task allocation model and improves the system overall profit greatly compared with the previous local neighbor-aware task allocation model.

Three hybridization models based on local search scheme for job shop scheduling problem

NASA Astrophysics Data System (ADS)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Singh, Surya Prakash

2017-11-01

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10-30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine-cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.

Why some women have an optimistic or a pessimistic bias about their breast cancer risk: experiences, heuristics, and knowledge of risk factors.

PubMed

Katapodi, Maria C; Dodd, Marylin J; Facione, Noreen C; Humphreys, Janice C; Lee, Kathryn A

2010-01-01

Perceived risk to a health problem is formed by inferential rules called heuristics and by comparative judgments that assess how one's risk compares to the risk of others. The purpose of this cross-sectional, community-based survey was to examine how experiences with breast cancer, knowledge of risk factors, and specific heuristics inform risk judgments for oneself, for friends/peers, and comparative judgments for breast cancer (risk friends/peers - risk self). We recruited an English-speaking, multicultural (57% nonwhite) sample of 184 middle-aged (47 + or - 12 years old), well-educated women. Fifty percent of participants perceived that their breast cancer risk was the same as the risk of their friends/peers; 10% were pessimistic (risk friends/peers - risk self < 0), whereas 40% were optimistic (risk friends/peers - risk self > 0). Family history of breast cancer and worry informed risk judgments for oneself. The availability and cultural heuristics specific for black women informed risk judgments for friends/peers. Knowledge of risk factors and interactions of knowledge with the availability, representativeness, and simulation heuristics informed comparative judgments (risk friends/peers - risk self). We discuss cognitive mechanisms with which experiences, knowledge, and heuristics influence comparative breast cancer risk judgments. Risk communication interventions should assess knowledge deficits, contextual variables, and specific heuristics that activate differential information processing mechanisms.

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.

A new impedance accounting for short- and long-range effects in mixed substructured formulations of nonlinear problems

NASA Astrophysics Data System (ADS)

Negrello, Camille; Gosselet, Pierre; Rey, Christian

2018-05-01

An efficient method for solving large nonlinear problems combines Newton solvers and Domain Decomposition Methods (DDM). In the DDM framework, the boundary conditions can be chosen to be primal, dual or mixed. The mixed approach presents the advantage to be eligible for the research of an optimal interface parameter (often called impedance) which can increase the convergence rate. The optimal value for this parameter is often too expensive to be computed exactly in practice: an approximate version has to be sought for, along with a compromise between efficiency and computational cost. In the context of parallel algorithms for solving nonlinear structural mechanical problems, we propose a new heuristic for the impedance which combines short and long range effects at a low computational cost.

From Faddeev-Kulish to LSZ. Towards a non-perturbative description of colliding electrons

NASA Astrophysics Data System (ADS)

Dybalski, Wojciech

2017-12-01

In a low energy approximation of the massless Yukawa theory (Nelson model) we derive a Faddeev-Kulish type formula for the scattering matrix of N electrons and reformulate it in LSZ terms. To this end, we perform a decomposition of the infrared finite Dollard modifier into clouds of real and virtual photons, whose infrared divergencies mutually cancel. We point out that in the original work of Faddeev and Kulish the clouds of real photons are omitted, and consequently their wave-operators are ill-defined on the Fock space of free electrons. To support our observations, we compare our final LSZ expression for N = 1 with a rigorous non-perturbative construction due to Pizzo. While our discussion contains some heuristic steps, they can be formulated as clear-cut mathematical conjectures.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis.

PubMed

Pieterse, Arwen H; de Vries, Marieke

2013-09-01

Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic-based VCMs. To critically analyse the suitability of the 'take the best' (TTB) and 'tallying' fast and frugal heuristics in the context of patient decision making. Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. The specific nature of patient preference-sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. © 2011 John Wiley & Sons Ltd.

Systematic Heuristic Evaluation of Computerized Consultation Order Templates: Clinicians' and Human Factors Engineers' Perspectives.

PubMed

Savoy, April; Patel, Himalaya; Flanagan, Mindy E; Weiner, Michael; Russ, Alissa L

2017-08-01

We assessed the usability of consultation order templates and identified problems to prioritize in design efforts for improving referral communication. With a sample of 26 consultation order templates, three evaluators performed a usability heuristic evaluation. The evaluation used 14 domain-independent heuristics and the following three supplemental references: 1 new domain-specific heuristic, 6 usability goals, and coded clinicians' statements regarding ease of use for 10 sampled templates. Evaluators found 201 violations, a mean of 7.7 violations per template. Minor violations outnumbered major violations almost twofold, 115 (57%) to 62 (31%). Approximately 68% of violations were linked to 5 heuristics: aesthetic and minimalist design (17%), error prevention (16%), consistency and standards (14%), recognition rather than recall (11%), and meet referrers' information needs (10%). Severe violations were attributed mostly to meet referrers' information needs and recognition rather than recall. Recorded violations yielded potential negative consequences for efficiency, effectiveness, safety, learnability, and utility. Evaluators and clinicians demonstrated 80% agreement in usability assessment. Based on frequency and severity of usability heuristic violations, the consultation order templates reviewed may impede clinical efficiency and risk patient safety. Results support the following design considerations: communicate consultants' requirements, facilitate information seeking, and support communication. While the most frequent heuristic violations involved interaction design and presentation, the most severe violations lacked information desired by referring clinicians. Violations related to templates' inability to support referring clinicians' information needs had the greatest potential negative impact on efficiency and safety usability goals. Heuristics should be prioritized in future design efforts.

Take the first heuristic, self-efficacy, and decision-making in sport.

PubMed

Hepler, Teri J; Feltz, Deborah L

2012-06-01

Can taking the first (TTF) option in decision-making lead to the best decisions in sports contexts? And, is one's decision-making self-efficacy in that context linked to TTF decisions? The purpose of this study was to examine the role of the TTF heuristic and self-efficacy in decision-making on a simulated sports task. Undergraduate and graduate students (N = 72) participated in the study and performed 13 trials in each of two video-based basketball decision tasks. One task required participants to verbally generate options before making a final decision on what to do next, while the other task simply asked participants to make a decision regarding the next move as quickly as possible. Decision-making self-efficacy was assessed using a 10-item questionnaire comprising various aspects of decision-making in basketball. Participants also rated their confidence in the final decision. Results supported many of the tenets of the TTF heuristic, such that people used the heuristic on a majority of the trials (70%), earlier generated options were better than later ones, first options were meaningfully generated, and final options were meaningfully selected. Results did not support differences in dynamic inconsistency or decision confidence based on the number of options. Findings also supported the link between self-efficacy and the TTF heuristic. Participants with higher self-efficacy beliefs used TTF more frequently and generated fewer options than those with low self-efficacy. Thus, not only is TTF an important heuristic when making decisions in dynamic, time-pressure situations, but self-efficacy plays an influential role in TTF.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

PubMed

Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

PubMed Central

2011-01-01

Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology. PMID:21989196

A benders decomposition approach to multiarea stochastic distributed utility planning

NASA Astrophysics Data System (ADS)

McCusker, Susan Ann

Until recently, small, modular generation and storage options---distributed resources (DRs)---have been installed principally in areas too remote for economic power grid connection and sensitive applications requiring backup capacity. Recent regulatory changes and DR advances, however, have lead utilities to reconsider the role of DRs. To a utility facing distribution capacity bottlenecks or uncertain load growth, DRs can be particularly valuable since they can be dispersed throughout the system and constructed relatively quickly. DR value is determined by comparing its costs to avoided central generation expenses (i.e., marginal costs) and distribution investments. This requires a comprehensive central and local planning and production model, since central system marginal costs result from system interactions over space and time. This dissertation develops and applies an iterative generalized Benders decomposition approach to coordinate models for optimal DR evaluation. Three coordinated models exchange investment, net power demand, and avoided cost information to minimize overall expansion costs. Local investment and production decisions are made by a local mixed integer linear program. Central system investment decisions are made by a LP, and production costs are estimated by a stochastic multi-area production costing model with Kirchhoff's Voltage and Current Law constraints. The nested decomposition is a new and unique method for distributed utility planning that partitions the variables twice to separate local and central investment and production variables, and provides upper and lower bounds on expected expansion costs. Kirchhoff's Voltage Law imposes nonlinear, nonconvex constraints that preclude use of LP if transmission capacity is available in a looped transmission system. This dissertation develops KVL constraint approximations that permit the nested decomposition to consider new transmission resources, while maintaining linearity in the three individual models. These constraints are presented as a heuristic for the given examples; future research will investigate conditions for convergence. A ten-year multi-area example demonstrates the decomposition approach and suggests the ability of DRs and new transmission to modify capacity additions and production costs by changing demand and power flows. Results demonstrate that DR and new transmission options may lead to greater capacity additions, but resulting production cost savings more than offset extra capacity costs.

Integration Framework of Process Planning based on Resource Independent Operation Summary to Support Collaborative Manufacturing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulvatunyou, Boonserm; Wysk, Richard A.; Cho, Hyunbo

2004-06-01

In today's global manufacturing environment, manufacturing functions are distributed as never before. Design, engineering, fabrication, and assembly of new products are done routinely in many different enterprises scattered around the world. Successful business transactions require the sharing of design and engineering data on an unprecedented scale. This paper describes a framework that facilitates the collaboration of engineering tasks, particularly process planning and analysis, to support such globalized manufacturing activities. The information models of data and the software components that integrate those information models are described. The integration framework uses an Integrated Product and Process Data (IPPD) representation called a Resourcemore » Independent Operation Summary (RIOS) to facilitate the communication of business and manufacturing requirements. Hierarchical process modeling, process planning decomposition and an augmented AND/OR directed graph are used in this representation. The Resource Specific Process Planning (RSPP) module assigns required equipment and tools, selects process parameters, and determines manufacturing costs based on two-level hierarchical RIOS data. The shop floor knowledge (resource and process knowledge) and a hybrid approach (heuristic and linear programming) to linearize the AND/OR graph provide the basis for the planning. Finally, a prototype system is developed and demonstrated with an exemplary part. Java and XML (Extensible Markup Language) are used to ensure software and information portability.« less

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 interviewees seemed to view chemical reactions as macroscopic reassembling processes where favorability was related to the perceived ease with which reactants broke apart or products formed. Students also expressed spurious chemical assumptions based on the misinterpretation and overgeneralization of periodicity and electronegativity. Our findings suggest the need to create more opportunities for college chemistry students to monitor their thinking, develop and apply analytical ways of reasoning, and evaluate the effectiveness of shortcut reasoning procedures in different contexts.

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

ERIC Educational Resources Information Center

Renkl, Alexander; Hilbert, Tatjana; Schworm, Silke

2009-01-01

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies…

The Heuristic Sandbox: Developing Teacher Know-How through Play in simSchool

ERIC Educational Resources Information Center

Hopper, Susan B.

2018-01-01

simSchool is a game-based, virtual, and interactive tool that allows pre-service teachers to acquire new skills while constructing knowledge through experimentation with learning situations. Pre-service teachers develop know-how--or heuristic knowledge--through repeated practice in the "Personality Plus Higher-Order Thinking" module to…

Balancing Self-Directed Learning with Expert Mentoring: The Science Writing Heuristic Approach

ERIC Educational Resources Information Center

Shelley, Mack; Fostvedt, Luke; Gonwa-Reeves, Christopher; Baenziger, Joan; McGill, Michael; Seefeld, Ashley; Hand, Brian; Therrien, William; Taylor, Jonte; Villanueva, Mary Grace

2012-01-01

This study focuses on the implementation of the Science Writing Heuristic (SWH) curriculum (Hand, 2007), which combines current understandings of learning as a cognitive and negotiated process with the techniques of argument-based inquiry, critical thinking skills, and writing to strengthen student outcomes. Success of SWH is dependent on the…

One-Reason Decision Making Unveiled: A Measurement Model of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Erdfelder, Edgar; Pohl, Rudiger F.

2010-01-01

The fast-and-frugal recognition heuristic (RH) theory provides a precise process description of comparative judgments. It claims that, in suitable domains, judgments between pairs of objects are based on recognition alone, whereas further knowledge is ignored. However, due to the confound between recognition and further knowledge, previous…

Web-Based Family Life Education: Spotlight on User Experience

ERIC Educational Resources Information Center

Doty, Jennifer; Doty, Matthew; Dwrokin, Jodi

2011-01-01

Family Life Education (FLE) websites can benefit from the field of user experience, which makes technology easy to use. A heuristic evaluation of five FLE sites was performed using Neilson's heuristics, guidelines for making sites user friendly. Greater site complexity resulted in more potential user problems. Sites most frequently had problems…

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.

Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

PubMed

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

Testing process predictions of models of risky choice: a quantitative model comparison approach

PubMed Central

Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

2013-01-01

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

Design and usability of heuristic-based deliberation tools for women facing amniocentesis.

PubMed

Durand, Marie-Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2012-03-01

Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. © 2011 Blackwell Publishing Ltd.

A multi-stage heuristic algorithm for matching problem in the modified miniload automated storage and retrieval system of e-commerce

NASA Astrophysics Data System (ADS)

Wang, Wenrui; Wu, Yaohua; Wu, Yingying

2016-05-01

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can't fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

Strategy selection in cue-based decision making.

PubMed

Bryant, David J

2014-06-01

People can make use of a range of heuristic and rational, compensatory strategies to perform a multiple-cue judgment task. It has been proposed that people are sensitive to the amount of cognitive effort required to employ decision strategies. Experiment 1 employed a dual-task methodology to investigate whether participants' preference for heuristic versus compensatory decision strategies can be altered by increasing the cognitive demands of the task. As indicated by participants' decision times, a secondary task interfered more with the performance of a heuristic than compensatory decision strategy but did not affect the proportions of participants using either type of strategy. A stimulus set effect suggested that the conjunction of cue salience and cue validity might play a determining role in strategy selection. The results of Experiment 2 indicated that when a perceptually salient cue was also the most valid, the majority of participants preferred a single-cue heuristic strategy. Overall, the results contradict the view that heuristics are more likely to be adopted when a task is made more cognitively demanding. It is argued that people employ 2 learning processes during training, one an associative learning process in which cue-outcome associations are developed by sampling multiple cues, and another that involves the sequential examination of single cues to serve as a basis for a single-cue heuristic.

The fallacy of financial heuristics.

PubMed

Langabeer, James

2007-01-01

In turbulent times, the financial policies and decisions about cash and debt make or break hospitals' financial condition. Decisions about whether to continue saving cash or reduce debt burdens are probably the most vital policy decision for the hospital CFO. Unfortunately, my research shows that most administrators are relying on judgment, or best-guess heuristics to address these policy issues. This article explores one of the most common heuristics in health finance-ratios gauging debt and cash on hand. The subject is explored through the research and analysis of over 40 hospitals in a very competitive marketplace-the boroughs of New York City. Analyses of financial strength, through various statistical models, were conducted to explore the linkages between traditional heuristics and long-term economic results. Data were collected for 30 operational and financial indicators. Findings suggest that organizations require different cash-debt positions based on their overall financial health, and that a one-number heuristic does not fit all. Extremely financially constrained hospitals (those approaching bankruptcy conditions) should be building free cash flow and minimizing debt service, while financially secure hospitals need to minimize cash on hand while reducing debt. If all hospitals continue to try to meet an arbitrary days of cash heuristic, this simplification could cripple an organization. A much more effective metric requires each organization to model decisions more comprehensively.

Smart strategies for doctors and doctors-in-training: heuristics in medicine.

PubMed

Wegwarth, Odette; Gaissmaier, Wolfgang; Gigerenzer, Gerd

2009-08-01

How do doctors make sound decisions when confronted with probabilistic data, time pressures and a heavy workload? One theory that has been embraced by many researchers is based on optimisation, which emphasises the need to integrate all information in order to arrive at sound decisions. This notion makes heuristics, which use less than complete information, appear as second-best strategies. In this article, we challenge this pessimistic view of heuristics. We introduce two medical problems that involve decision making to the reader: one concerns coronary care issues and the other macrolide prescriptions. In both settings, decision-making tools grounded in the principles of optimisation and heuristics, respectively, have been developed to assist doctors in making decisions. We explain the structure of each of these tools and compare their performance in terms of their facilitation of correct predictions. For decisions concerning both the coronary care unit and the prescribing of macrolides, we demonstrate that sacrificing information does not necessarily imply a forfeiting of predictive accuracy, but can sometimes even lead to better decisions. Subsequently, we discuss common misconceptions about heuristics and explain when and why ignoring parts of the available information can lead to the making of more robust predictions. Heuristics are neither good nor bad per se, but, if applied in situations to which they have been adapted, can be helpful companions for doctors and doctors-in-training. This, however, requires that heuristics in medicine be openly discussed, criticised, refined and then taught to doctors-in-training rather than being simply dismissed as harmful or irrelevant. A more uniform use of explicit and accepted heuristics has the potential to reduce variations in diagnoses and to improve medical care for patients.

Approach to design neural cryptography: a generalized architecture and a heuristic rule.

PubMed

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.

A Heuristic Bioinspired for 8-Piece Puzzle

NASA Astrophysics Data System (ADS)

Machado, M. O.; Fabres, P. A.; Melo, J. C. L.

2017-10-01

This paper investigates a mathematical model inspired by nature, and presents a Meta-Heuristic that is efficient in improving the performance of an informed search, when using strategy A * using a General Search Tree as data structure. The work hypothesis suggests that the investigated meta-heuristic is optimal in nature and may be promising in minimizing the computational resources required by an objective-based agent in solving high computational complexity problems (n-part puzzle) as well as In the optimization of objective functions for local search agents. The objective of this work is to describe qualitatively the characteristics and properties of the mathematical model investigated, correlating the main concepts of the A * function with the significant variables of the metaheuristic used. The article shows that the amount of memory required to perform this search when using the metaheuristic is less than using the A * function to evaluate the nodes of a general search tree for the eight-piece puzzle. It is concluded that the meta-heuristic must be parameterized according to the chosen heuristic and the level of the tree that contains the possible solutions to the chosen problem.

On the psychology of the recognition heuristic: retrieval primacy as a key determinant of its use.

PubMed

Pachur, Thorsten; Hertwig, Ralph

2006-09-01

The recognition heuristic is a prime example of a boundedly rational mind tool that rests on an evolved capacity, recognition, and exploits environmental structures. When originally proposed, it was conjectured that no other probabilistic cue reverses the recognition-based inference (D. G. Goldstein & G. Gigerenzer, 2002). More recent studies challenged this view and gave rise to the argument that recognition enters inferences just like any other probabilistic cue. By linking research on the heuristic with research on recognition memory, the authors argue that the retrieval of recognition information is not tantamount to the retrieval of other probabilistic cues. Specifically, the retrieval of subjective recognition precedes that of an objective probabilistic cue and occurs at little to no cognitive cost. This retrieval primacy gives rise to 2 predictions, both of which have been empirically supported: Inferences in line with the recognition heuristic (a) are made faster than inferences inconsistent with it and (b) are more prevalent under time pressure. Suspension of the heuristic, in contrast, requires additional time, and direct knowledge of the criterion variable, if available, can trigger such suspension. Copyright 2006 APA

Boolean Reasoning and Informed Search in the Minimization of Logic Circuits

DTIC Science & Technology

1992-03-01

motivation of this project as well as a definition of the problem. The scope of the effort was presented, as well as the assumptions found to be...in the resulting formula than the expansion-based product operation. The primary motive for using the expansion-based product versus a cross-product...eliminant is formed is the least-binate-variable heuristic described in Chapter 2. The motivation for this heuristic was illustrated in Example 3.3. The

Perspectives of young Chinese Singaporean women on seeking and processing information to decide about vaccinating against human papillomavirus.

PubMed

Basnyat, Iccha; Lim, Cheryl

2017-07-06

Human papillomavirus (HPV) vaccination uptake in Singapore is low among young women. Low uptake has been found to be linked to low awareness. Thus, this study aimed to understand active and passive vaccine information-seeking behavior. Furthermore, guided by the Elaboration Likelihood Model (ELM), this study examined young women's (aged 21-26 years) processing of information they acquired in their decision to get vaccinated. ELM postulates that information processing could be through the central (i.e., logic-based) or peripheral (i.e., heuristic-based) route. Twenty-six in-depth interviews were conducted from January to March 2016. Data were analyzed using thematic analysis. Two meta-themes-information acquisition and vaccination decision-revealed the heuristic-based information processing was employed. These young women acquired information passively within their social network and actively in healthcare settings. However, they used heuristic cues, such as closeness and trust, to process the information. Similarly, vaccination decisions revealed that women relied on heuristic cues, such as sense of belonging and validation among peers and source credibility and likability in medical settings, in their decision to get vaccinated. The findings of this study highlight that intervention efforts should focus on strengthening social support among personal networks to increase the uptake of the vaccine.

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

PubMed Central

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

PubMed

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

On the Psychology of the Recognition Heuristic: Retrieval Primacy as a Key Determinant of Its Use

ERIC Educational Resources Information Center

Pachur, Thorsten; Hertwig, Ralph

2006-01-01

The recognition heuristic is a prime example of a boundedly rational mind tool that rests on an evolved capacity, recognition, and exploits environmental structures. When originally proposed, it was conjectured that no other probabilistic cue reverses the recognition-based inference (D. G. Goldstein & G. Gigerenzer, 2002). More recent studies…

Heuristic Chemistry--A Qualitative Study on Teaching Domain-Specific Strategies for the Six-Electron Case

ERIC Educational Resources Information Center

Graulich, Nicole; Tiemann, Rudiger; Schreiner, Peter R.

2012-01-01

We investigate the efficiency of domain-specific heuristic strategies in mastering and predicting pericyclic six-electron rearrangements. Based on recent research findings on these types of reactions a new concept has been developed that should help students identify and describe six-electron rearrangements more readily in complex molecules. The…

Heuristics for Planning University Study at a Distance.

ERIC Educational Resources Information Center

Dodds, Agnes E.; Lawrence, Jeanette A.

A model to describe how adults work on university courses at a distance from campus was developed at an Australian university. The model was designed to describe how students define the task/goal and plan their study, based on G. Ploya's (1957) Heuristic and A. Newell's and H. A. Simon's (1972) General Problem Solver. Verbal reports were obtained…

Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Pohl, Rudiger F.

2009-01-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

Dictionary-Based Tensor Canonical Polyadic Decomposition

NASA Astrophysics Data System (ADS)

Cohen, Jeremy Emile; Gillis, Nicolas

2018-04-01

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

Toward a More Usable Home-Based Video Telemedicine System: A Heuristic Evaluation of the Clinician User Interfaces of Home-Based Video Telemedicine Systems.

PubMed

Agnisarman, Sruthy; Narasimha, Shraddhaa; Chalil Madathil, Kapil; Welch, Brandon; Brinda, Fnu; Ashok, Aparna; McElligott, James

2017-04-24

Telemedicine is the use of technology to provide and support health care when distance separates the clinical service and the patient. Home-based telemedicine systems involve the use of such technology for medical support and care connecting the patient from the comfort of their homes with the clinician. In order for such a system to be used extensively, it is necessary to understand not only the issues faced by the patients in using them but also the clinician. The aim of this study was to conduct a heuristic evaluation of 4 telemedicine software platforms-Doxy.me, Polycom, Vidyo, and VSee-to assess possible problems and limitations that could affect the usability of the system from the clinician's perspective. It was found that 5 experts individually evaluated all four systems using Nielsen's list of heuristics, classifying the issues based on a severity rating scale. A total of 46 unique problems were identified by the experts. The heuristics most frequently violated were visibility of system status and Error prevention amounting to 24% (11/46 issues) each. Esthetic and minimalist design was second contributing to 13% (6/46 issues) of the total errors. Heuristic evaluation coupled with a severity rating scale was found to be an effective method for identifying problems with the systems. Prioritization of these problems based on the rating provides a good starting point for resolving the issues affecting these platforms. There is a need for better transparency and a more streamlined approach for how physicians use telemedicine systems. Visibility of the system status and speaking the users' language are keys for achieving this. ©Sruthy Agnisarman, Shraddhaa Narasimha, Kapil Chalil Madathil, Brandon Welch, FNU Brinda, Aparna Ashok, James McElligott. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 24.04.2017.

Leveraging social system networks in ubiquitous high-data-rate health systems.

PubMed

Massey, Tammara; Marfia, Gustavo; Stoelting, Adam; Tomasi, Riccardo; Spirito, Maurizio A; Sarrafzadeh, Majid; Pau, Giovanni

2011-05-01

Social system networks with high data rates and limited storage will discard data if the system cannot connect and upload the data to a central server. We address the challenge of limited storage capacity in mobile health systems during network partitions with a heuristic that achieves efficiency in storage capacity by modifying the granularity of the medical data during long intercontact periods. Patterns in the connectivity, reception rate, distance, and location are extracted from the social system network and leveraged in the global algorithm and online heuristic. In the global algorithm, the stochastic nature of the data is modeled with maximum likelihood estimation based on the distribution of the reception rates. In the online heuristic, the correlation between system position and the reception rate is combined with patterns in human mobility to estimate the intracontact and intercontact time. The online heuristic performs well with a low data loss of 2.1%-6.1%.

Re-visions of rationality?

PubMed

Newell, Ben R

2005-01-01

The appeal of simple algorithms that take account of both the constraints of human cognitive capacity and the structure of environments has been an enduring theme in cognitive science. A novel version of such a boundedly rational perspective views the mind as containing an 'adaptive toolbox' of specialized cognitive heuristics suited to different problems. Although intuitively appealing, when this version was proposed, empirical evidence for the use of such heuristics was scant. I argue that in the light of empirical studies carried out since then, it is time this 'vision of rationality' was revised. An alternative view based on integrative models rather than collections of heuristics is proposed.

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

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 expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids: a critical analysis

PubMed Central

Pieterse, Arwen H.; de Vries, Marieke

2011-01-01

Abstract Background  Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference‐sensitive health‐care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic‐based VCMs. Objective  To critically analyse the suitability of the ‘take the best’ (TTB) and ‘tallying’ fast and frugal heuristics in the context of patient decision making. Strategy  Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. Conclusion  The specific nature of patient preference‐sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. PMID:21902770

How do people judge risks: availability heuristic, affect heuristic, or both?

PubMed

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.

Heuristic evaluation of online COPD respiratory therapy and education video resource center.

PubMed

Stellefson, Michael; Chaney, Beth; Chaney, Don

2014-10-01

Abstract Purpose: Because of limited accessibility to pulmonary rehabilitation programs, patients with chronic obstructive pulmonary disease (COPD) are infrequently provided with patient education resources. To help educate patients with COPD on how to live a better life with diminished breathing capacity, we developed a novel social media resource center containing COPD respiratory therapy and education videos called "COPDFlix." A heuristic evaluation of COPDFlix was conducted as part of a larger study to determine whether the prototype was successful in adhering to formal Web site usability guidelines for older adults. A purposive sample of three experts, with expertise in Web design and health communications technology, was recruited (a) to identify usability violations and (b) to propose solutions to improve the functionality of the COPDFlix prototype. Each expert evaluated 18 heuristics in four categories of task-based criteria (i.e., interaction and navigation, information architecture, presentation design, and information design). Seventy-six subcriteria across these four categories were assessed. Quantitative ratings and qualitative comments from each expert were compiled into a single master list, noting the violated heuristic and type/location of problem(s). Sixty-one usability violations were identified across the 18 heuristics. Evaluators rated the majority of heuristic subcriteria as either a "minor hindrance" (n=32) or "no problem" (n=132). Moreover, only 2 of the 18 heuristic categories were noted as "major" violations, with mean severity scores of ≥3. Mixed-methods data analysis helped the multidisciplinary research team to categorize and prioritize usability problems and solutions, leading to 26 discrete design modifications within the COPDFlix prototype.

Estimating the relative weights of visual and auditory tau versus heuristic-based cues for time-to-contact judgments in realistic, familiar scenes by older and younger adults.

PubMed

Keshavarz, Behrang; Campos, Jennifer L; DeLucia, Patricia R; Oberfeld, Daniel

2017-04-01

Estimating time to contact (TTC) involves multiple sensory systems, including vision and audition. Previous findings suggested that the ratio of an object's instantaneous optical size/sound intensity to its instantaneous rate of change in optical size/sound intensity (τ) drives TTC judgments. Other evidence has shown that heuristic-based cues are used, including final optical size or final sound pressure level. Most previous studies have used decontextualized and unfamiliar stimuli (e.g., geometric shapes on a blank background). Here we evaluated TTC estimates by using a traffic scene with an approaching vehicle to evaluate the weights of visual and auditory TTC cues under more realistic conditions. Younger (18-39 years) and older (65+ years) participants made TTC estimates in three sensory conditions: visual-only, auditory-only, and audio-visual. Stimuli were presented within an immersive virtual-reality environment, and cue weights were calculated for both visual cues (e.g., visual τ, final optical size) and auditory cues (e.g., auditory τ, final sound pressure level). The results demonstrated the use of visual τ as well as heuristic cues in the visual-only condition. TTC estimates in the auditory-only condition, however, were primarily based on an auditory heuristic cue (final sound pressure level), rather than on auditory τ. In the audio-visual condition, the visual cues dominated overall, with the highest weight being assigned to visual τ by younger adults, and a more equal weighting of visual τ and heuristic cues in older adults. Overall, better characterizing the effects of combined sensory inputs, stimulus characteristics, and age on the cues used to estimate TTC will provide important insights into how these factors may affect everyday behavior.

Exact and heuristic algorithms for Space Information Flow.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing; Li, Zongpeng

2018-01-01

Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm.

Dramatic Consequences: Integrating Rhetorical Performance across the Disciplines and Curriculum

ERIC Educational Resources Information Center

Marquez, Loren

2015-01-01

Just as WAC pedagogy and writing studies both stress the ways that writing and communication practices can act as both heuristics and products of genre-based, discipline- specific knowledge, in much the same way, performance, too, can be used as a heuristic and as a product and should be more fully explored in WAC theory and pedagogy. This article…

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.

Slime moulds use heuristics based on within-patch experience to decide when to leave.

PubMed

Latty, Tanya; Beekman, Madeleine

2015-04-15

Animals foraging in patchy, non-renewing or slowly renewing environments must make decisions about how long to remain within a patch. Organisms can use heuristics ('rules of thumb') based on available information to decide when to leave the patch. Here, we investigated proximate patch-departure heuristics in two species of giant, brainless amoeba: the slime moulds Didymium bahiense and Physarum polycephalum. We explicitly tested the importance of information obtained through experience by eliminating chemosensory cues of patch quality. In P. polycephalum, patch departure was influenced by the consumption of high, and to a much lesser extent low, quality food items such that engulfing a food item increased patch-residency time. Physarum polycephalum also tended to forage for longer in darkened, 'safe' patches. In D. bahiense, engulfment of any food item increased patch residency irrespective of that food item's quality. Exposure to light had no effect on the patch-residency time of D. bahiense. Given that these organisms lack a brain, our results illustrate how the use of simple heuristics can give the impression that individuals make sophisticated foraging decisions. © 2015. Published by The Company of Biologists Ltd.

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.

Toward a physiology of dual-process reasoning and judgment: lemonade, willpower, and expensive rule-based analysis.

PubMed

Masicampo, E J; Baumeister, Roy F

2008-03-01

This experiment used the attraction effect to test the hypothesis that ingestion of sugar can reduce reliance on intuitive, heuristic-based decision making. In the attraction effect, a difficult choice between two options is swayed by the presence of a seemingly irrelevant "decoy" option. We replicated this effect and the finding that the effect increases when people have depleted their mental resources performing a previous self-control task. Our hypothesis was based on the assumption that effortful processes require and consume relatively large amounts of glucose (brain fuel), and that this use of glucose is why people use heuristic strategies after exerting self-control. Before performing any tasks, some participants drank lemonade sweetened with sugar, which restores blood glucose, whereas others drank lemonade containing a sugar substitute. Only lemonade with sugar reduced the attraction effect. These results show one way in which the body (blood glucose) interacts with the mind (self-control and reliance on heuristics).

Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD).

PubMed

Khowaja, Kamran; Salim, Siti Salwah; Asemi, Adeleh

2015-01-01

In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen's set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen's heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system.

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

PubMed

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

Evaluating Heuristics for Planning Effective and Efficient Inspections

NASA Technical Reports Server (NTRS)

Shull, Forrest J.; Seaman, Carolyn B.; Diep, Madeline M.; Feldmann, Raimund L.; Godfrey, Sara H.; Regardie, Myrna

2010-01-01

A significant body of knowledge concerning software inspection practice indicates that the value of inspections varies widely both within and across organizations. Inspection effectiveness and efficiency can be measured in numerous ways, and may be affected by a variety of factors such as Inspection planning, the type of software, the developing organization, and many others. In the early 1990's, NASA formulated heuristics for inspection planning based on best practices and early NASA inspection data. Over the intervening years, the body of data from NASA inspections has grown. This paper describes a multi-faceted exploratory analysis performed on this · data to elicit lessons learned in general about conducting inspections and to recommend improvements to the existing heuristics. The contributions of our results include support for modifying some of the original inspection heuristics (e.g. Increasing the recommended page rate), evidence that Inspection planners must choose between efficiency and effectiveness, as a good tradeoff between them may not exist, and Identification of small subsets of inspections for which new inspection heuristics are needed. Most Importantly, this work illustrates the value of collecting rich data on software Inspections, and using it to gain insight into, and Improve, inspection practice.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems

NASA Astrophysics Data System (ADS)

Abtahi, Amir-Reza; Bijari, Afsane

2017-03-01

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.

Heuristic and analytic processes in reasoning: an event-related potential study of belief bias.

PubMed

Banks, Adrian P; Hope, Christopher

2014-03-01

Human reasoning involves both heuristic and analytic processes. This study of belief bias in relational reasoning investigated whether the two processes occur serially or in parallel. Participants evaluated the validity of problems in which the conclusions were either logically valid or invalid and either believable or unbelievable. Problems in which the conclusions presented a conflict between the logically valid response and the believable response elicited a more positive P3 than problems in which there was no conflict. This shows that P3 is influenced by the interaction of belief and logic rather than either of these factors on its own. These findings indicate that belief and logic influence reasoning at the same time, supporting models in which belief-based and logical evaluations occur in parallel but not theories in which belief-based heuristic evaluations precede logical analysis.

Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD)

PubMed Central

Khowaja, Kamran; Salim, Siti Salwah

2015-01-01

In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen’s set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen’s heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system. PMID:26196385

Heuristics of reasoning and analogy in children's visual perspective taking.

PubMed

Yaniv, I; Shatz, M

1990-10-01

We propose that children's reasoning about others' visual perspectives is guided by simple heuristics based on a perceiver's line of sight and salient features of the object met by that line. In 3 experiments employing a 2-perceiver analogy task, children aged 3-6 were generally better able to reproduce a perceiver's perspective if a visual cue in the perceiver's line of sight sufficed to distinguish it from alternatives. Children had greater difficulty when the task hinged on attending to configural cues. Availability of distinctive cues affixed on the objects' sides facilitated solution of the symmetrical orientations. These and several other related findings reported in the literature are traced to children's reliance on heuristics of reasoning.

How smart do you need to be to get it wrong? The role of cognitive capacity in the development of heuristic-based judgment.

PubMed

Morsanyi, Kinga; Handley, Simon J

2008-01-01

We examined the relationship between cognitive capacity and heuristic responding on four types of reasoning and decision-making tasks. A total of 84 children, between 5 years 2 months and 11 years 7 months of age, participated in the study. There was a marked increase in heuristic responding with age that was related to increases in cognitive capacity. These findings are inconsistent with the predominant dual-process accounts of reasoning and decision making as applied to development. We offer an alternative explanation of the findings, considering them in the context of recent claims concerning the role of working memory in contextualized reasoning.

Heuristic Evaluation of Online COPD Respiratory Therapy and Education Video Resource Center

PubMed Central

Chaney, Beth; Chaney, Don

2014-01-01

Abstract Purpose: Because of limited accessibility to pulmonary rehabilitation programs, patients with chronic obstructive pulmonary disease (COPD) are infrequently provided with patient education resources. To help educate patients with COPD on how to live a better life with diminished breathing capacity, we developed a novel social media resource center containing COPD respiratory therapy and education videos called “COPDFlix.” Methodology: A heuristic evaluation of COPDFlix was conducted as part of a larger study to determine whether the prototype was successful in adhering to formal Web site usability guidelines for older adults. A purposive sample of three experts, with expertise in Web design and health communications technology, was recruited (a) to identify usability violations and (b) to propose solutions to improve the functionality of the COPDFlix prototype. Each expert evaluated 18 heuristics in four categories of task-based criteria (i.e., interaction and navigation, information architecture, presentation design, and information design). Seventy-six subcriteria across these four categories were assessed. Quantitative ratings and qualitative comments from each expert were compiled into a single master list, noting the violated heuristic and type/location of problem(s). Results: Sixty-one usability violations were identified across the 18 heuristics. Evaluators rated the majority of heuristic subcriteria as either a “minor hindrance” (n=32) or “no problem” (n=132). Moreover, only 2 of the 18 heuristic categories were noted as “major” violations, with mean severity scores of ≥3. Conclusions: Mixed-methods data analysis helped the multidisciplinary research team to categorize and prioritize usability problems and solutions, leading to 26 discrete design modifications within the COPDFlix prototype. PMID:24650318

Scaling for the SOL/separatrix χ ⊥ following from the heuristic drift model for the power scrape-off layer width

NASA Astrophysics Data System (ADS)

Huber, A.; Chankin, A. V.

2017-06-01

A simple two-point representation of the tokamak scrape-off layer (SOL) in the conduction limited regime, based on the parallel and perpendicular energy balance equations in combination with the heat flux width predicted by a heuristic drift-based model, was used to derive a scaling for the cross-field thermal diffusivity {χ }\\perp . For fixed plasma shape and neglecting weak power dependence indexes 1/8, the scaling {χ }\\perp \\propto {P}{{S}{{O}}{{L}}}/(n{B}θ {R}2) is derived.

Establishing usability heuristics for heuristics evaluation in a specific domain: Is there a consensus?

PubMed

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

The affect heuristic in occupational safety.

PubMed

Savadori, Lucia; Caovilla, Jessica; Zaniboni, Sara; Fraccaroli, Franco

2015-07-08

The affect heuristic is a rule of thumb according to which, in the process of making a judgment or decision, people use affect as a cue. If a stimulus elicits positive affect then risks associated to that stimulus are viewed as low and benefits as high; conversely, if the stimulus elicits negative affect, then risks are perceived as high and benefits as low. The basic tenet of this study is that affect heuristic guides worker's judgment and decision making in a risk situation. The more the worker likes her/his organization the less she/he will perceive the risks as high. A sample of 115 employers and 65 employees working in small family agricultural businesses completed a questionnaire measuring perceived safety costs, psychological safety climate, affective commitment and safety compliance. A multi-sample structural analysis supported the thesis that safety compliance can be explained through an affect-based heuristic reasoning, but only for employers. Positive affective commitment towards their family business reduced employers' compliance with safety procedures by increasing the perceived cost of implementing them.

Approaches to eliminate waste and reduce cost for recycling glass.

PubMed

Chao, Chien-Wen; Liao, Ching-Jong

2011-12-01

In recent years, the issue of environmental protection has received considerable attention. This paper adds to the literature by investigating a scheduling problem in the manufacturing of a glass recycling factory in Taiwan. The objective is to minimize the sum of the total holding cost and loss cost. We first represent the problem as an integer programming (IP) model, and then develop two heuristics based on the IP model to find near-optimal solutions for the problem. To validate the proposed heuristics, comparisons between optimal solutions from the IP model and solutions from the current method are conducted. The comparisons involve two problem sizes, small and large, where the small problems range from 15 to 45 jobs, and the large problems from 50 to 100 jobs. Finally, a genetic algorithm is applied to evaluate the proposed heuristics. Computational experiments show that the proposed heuristics can find good solutions in a reasonable time for the considered problem. Copyright © 2011 Elsevier Ltd. All rights reserved.

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

PubMed

Biswas, Surama; Acharyya, Sriyankar

2016-06-01

Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

Determining the optimal number of Kanban in multi-products supply chain system

NASA Astrophysics Data System (ADS)

Widyadana, G. A.; Wee, H. M.; Chang, Jer-Yuan

2010-02-01

Kanban, a key element of just-in-time system, is a re-order card or signboard giving instruction or triggering the pull system to manufacture or supply a component based on actual usage of material. There are two types of Kanban: production Kanban and withdrawal Kanban. This study uses optimal and meta-heuristic methods to determine the Kanban quantity and withdrawal lot sizes in a supply chain system. Although the mix integer programming method gives an optimal solution, it is not time efficient. For this reason, the meta-heuristic methods are suggested. In this study, a genetic algorithm (GA) and a hybrid of genetic algorithm and simulated annealing (GASA) are used. The study compares the performance of GA and GASA with that of the optimal method using MIP. The given problems show that both GA and GASA result in a near optimal solution, and they outdo the optimal method in term of run time. In addition, the GASA heuristic method gives a better performance than the GA heuristic method.

Heuristic algorithms for the minmax regret flow-shop problem with interval processing times.

PubMed

Ćwik, Michał; Józefczyk, Jerzy

2018-01-01

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.

Using scenarios and personas to enhance the effectiveness of heuristic usability evaluations for older adults and their care team.

PubMed

Kneale, Laura; Mikles, Sean; Choi, Yong K; Thompson, Hilaire; Demiris, George

2017-09-01

Using heuristics to evaluate user experience is a common methodology for human-computer interaction studies. One challenge of this method is the inability to tailor results towards specific end-user needs. This manuscript reports on a method that uses validated scenarios and personas of older adults and care team members to enhance heuristics evaluations of the usability of commercially available personal health records for homebound older adults. Our work extends the Chisnell and Redish heuristic evaluation methodology by using a protocol that relies on multiple expert reviews of each system. It further standardizes the heuristic evaluation process through the incorporation of task-based scenarios. We were able to use the modified version of the Chisnell and Redish heuristic evaluation methodology to identify potential usability challenges of two commercially available personal health record systems. This allowed us to: (1) identify potential usability challenges for specific types of users, (2) describe improvements that would be valuable to all end-users of the system, and (3) better understand how the interactions of different users may vary within a single personal health record. The methodology described in this paper may help designers of consumer health information technology tools, such as personal health records, understand the needs of diverse end-user populations. Such methods may be particularly helpful when designing systems for populations that are difficult to recruit for end-user evaluations through traditional methods. Copyright © 2017 Elsevier Inc. All rights reserved.

More than one way to see it: Individual heuristics in avian visual computation

PubMed Central

Ravignani, Andrea; Westphal-Fitch, Gesche; Aust, Ulrike; Schlumpp, Martin M.; Fitch, W. Tecumseh

2015-01-01

Comparative pattern learning experiments investigate how different species find regularities in sensory input, providing insights into cognitive processing in humans and other animals. Past research has focused either on one species’ ability to process pattern classes or different species’ performance in recognizing the same pattern, with little attention to individual and species-specific heuristics and decision strategies. We trained and tested two bird species, pigeons (Columba livia) and kea (Nestor notabilis, a parrot species), on visual patterns using touch-screen technology. Patterns were composed of several abstract elements and had varying degrees of structural complexity. We developed a model selection paradigm, based on regular expressions, that allowed us to reconstruct the specific decision strategies and cognitive heuristics adopted by a given individual in our task. Individual birds showed considerable differences in the number, type and heterogeneity of heuristic strategies adopted. Birds’ choices also exhibited consistent species-level differences. Kea adopted effective heuristic strategies, based on matching learned bigrams to stimulus edges. Individual pigeons, in contrast, adopted an idiosyncratic mix of strategies that included local transition probabilities and global string similarity. Although performance was above chance and quite high for kea, no individual of either species provided clear evidence of learning exactly the rule used to generate the training stimuli. Our results show that similar behavioral outcomes can be achieved using dramatically different strategies and highlight the dangers of combining multiple individuals in a group analysis. These findings, and our general approach, have implications for the design of future pattern learning experiments, and the interpretation of comparative cognition research more generally. PMID:26113444

Teaching dermatoscopy of pigmented skin tumours to novices: comparison of analytic vs. heuristic approach.

PubMed

Tschandl, P; Kittler, H; Schmid, K; Zalaudek, I; Argenziano, G

2015-06-01

There are two strategies to approach the dermatoscopic diagnosis of pigmented skin tumours, namely the verbal-based analytic and the more visual-global heuristic method. It is not known if one or the other is more efficient in teaching dermatoscopy. To compare two teaching methods in short-term training of dermatoscopy to medical students. Fifty-seven medical students in the last year of the curriculum were given a 1-h lecture of either the heuristic- or the analytic-based teaching of dermatoscopy. Before and after this session, they were shown the same 50 lesions and asked to diagnose them and rate for chance of malignancy. Test lesions consisted of melanomas, basal cell carcinomas, nevi, seborrhoeic keratoses, benign vascular tumours and dermatofibromas. Performance measures were diagnostic accuracy regarding malignancy as measured by the area under the curves of receiver operating curves (range: 0-1), as well as per cent correct diagnoses (range: 0-100%). Diagnostic accuracy as well as per cent correct diagnoses increased by +0.21 and +32.9% (heuristic teaching) and +0.19 and +35.7% (analytic teaching) respectively (P for all <0.001). Neither for diagnostic accuracy (P = 0.585), nor for per cent correct diagnoses (P = 0.298) was a difference between the two groups. Short-term training of dermatoscopy to medical students allows significant improvement in diagnostic abilities. Choosing a heuristic or analytic method does not have an influence on this effect in short training using common pigmented skin lesions. © 2014 European Academy of Dermatology and Venereology.

A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB).

PubMed

Shirazi, Mohammadali; Dhavala, Soma Sekhar; Lord, Dominique; Geedipally, Srinivas Reddy

2017-10-01

Safety analysts usually use post-modeling methods, such as the Goodness-of-Fit statistics or the Likelihood Ratio Test, to decide between two or more competitive distributions or models. Such metrics require all competitive distributions to be fitted to the data before any comparisons can be accomplished. Given the continuous growth in introducing new statistical distributions, choosing the best one using such post-modeling methods is not a trivial task, in addition to all theoretical or numerical issues the analyst may face during the analysis. Furthermore, and most importantly, these measures or tests do not provide any intuitions into why a specific distribution (or model) is preferred over another (Goodness-of-Logic). This paper ponders into these issues by proposing a methodology to design heuristics for Model Selection based on the characteristics of data, in terms of descriptive summary statistics, before fitting the models. The proposed methodology employs two analytic tools: (1) Monte-Carlo Simulations and (2) Machine Learning Classifiers, to design easy heuristics to predict the label of the 'most-likely-true' distribution for analyzing data. The proposed methodology was applied to investigate when the recently introduced Negative Binomial Lindley (NB-L) distribution is preferred over the Negative Binomial (NB) distribution. Heuristics were designed to select the 'most-likely-true' distribution between these two distributions, given a set of prescribed summary statistics of data. The proposed heuristics were successfully compared against classical tests for several real or observed datasets. Not only they are easy to use and do not need any post-modeling inputs, but also, using these heuristics, the analyst can attain useful information about why the NB-L is preferred over the NB - or vice versa- when modeling data. Copyright © 2017 Elsevier Ltd. All rights reserved.

BCI Control of Heuristic Search Algorithms

PubMed Central

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 cognitive systems. PMID:28197092

BCI Control of Heuristic Search Algorithms.

PubMed

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 cognitive systems.

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…

Accessible methods for the dynamic time-scale decomposition of biochemical systems.

PubMed

Surovtsova, Irina; Simus, Natalia; Lorenz, Thomas; König, Artjom; Sahle, Sven; Kummer, Ursula

2009-11-01

The growing complexity of biochemical models asks for means to rationally dissect the networks into meaningful and rather independent subnetworks. Such foregoing should ensure an understanding of the system without any heuristics employed. Important for the success of such an approach is its accessibility and the clarity of the presentation of the results. In order to achieve this goal, we developed a method which is a modification of the classical approach of time-scale separation. This modified method as well as the more classical approach have been implemented for time-dependent application within the widely used software COPASI. The implementation includes different possibilities for the representation of the results including 3D-visualization. The methods are included in COPASI which is free for academic use and available at www.copasi.org. irina.surovtsova@bioquant.uni-heidelberg.de Supplementary data are available at Bioinformatics online.

A single cognitive heuristic process meets the complexity of domain-specific moral heuristics.

PubMed

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).

How Does the Science Writing Heuristic Approach Affect Students' Performances of Different Academic Achievement Levels? A Case for High School Chemistry

ERIC Educational Resources Information Center

Kingir, Sevgi; Geban, Omer; Gunel, Murat

2012-01-01

This study investigates the effects of the Science Writing Heuristic (SWH), known as an argumentation-based science inquiry approach, on Grade 9 students' performance on a post-test in relation to their academic achievement levels. Four intact classes taught by 2 chemistry teachers from a Turkish public high school were selected for the study; one…

The Role of Young Hoosier Book Award Nominees in the Classroom: Using Approaches to Multicultural Education as a Lens for Evaluating Literature

ERIC Educational Resources Information Center

Marks, Shaylyn Barrie

2013-01-01

This study demonstrates the need for the integration of multiculturalism in the K-12 curriculum as well as provides a heuristic based on the work conducted by Sleeter and Grant (2009) to evaluate literature for level of multiculturalism. In the study, the researcher uses an evaluate heuristic to critically analyze and evaluation ten of the books…

A multilevel probabilistic beam search algorithm for the shortest common supersequence problem.

PubMed

Gallardo, José E

2012-01-01

The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this problem based on the use at different levels of a probabilistic variant of a classical heuristic known as Beam Search. The proposed algorithm is empirically analysed and compared to current approaches in the literature. Experiments show that it provides better quality solutions in a reasonable time for medium and large instances of the problem. For very large instances, our heuristic also provides better solutions, but required execution times may increase considerably.

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.

How cognitive heuristics can explain social interactions in spatial movement.

PubMed

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. © 2016 The Author(s).

How cognitive heuristics can explain social interactions in spatial movement

PubMed Central

Köster, Gerta

2016-01-01

The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as ‘stop if another step would lead to a collision’ or ‘follow the person in front’. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. PMID:27581483

Decision heuristic or preference? Attribute non-attendance in discrete choice problems.

PubMed

Heidenreich, Sebastian; Watson, Verity; Ryan, Mandy; Phimister, Euan

2018-01-01

This paper investigates if respondents' choice to not consider all characteristics of a multiattribute health service may represent preferences. Over the last decade, an increasing number of studies account for attribute non-attendance (ANA) when using discrete choice experiments to elicit individuals' preferences. Most studies assume such behaviour is a heuristic and therefore uninformative. This assumption may result in misleading welfare estimates if ANA reflects preferences. This is the first paper to assess if ANA is a heuristic or genuine preference without relying on respondents' self-stated motivation and the first study to explore this question within a health context. Based on findings from cognitive psychology, we expect that familiar respondents are less likely to use a decision heuristic to simplify choices than unfamiliar respondents. We employ a latent class model of discrete choice experiment data concerned with National Health Service managers' preferences for support services that assist with performance concerns. We present quantitative and qualitative evidence that in our study ANA mostly represents preferences. We also show that wrong assumptions about ANA result in inadequate welfare measures that can result in suboptimal policy advice. Future research should proceed with caution when assuming that ANA is a heuristic. Copyright © 2017 John Wiley & Sons, Ltd.

Testing Bayesian and heuristic predictions of mass judgments of colliding objects

PubMed Central

Sanborn, Adam N.

2014-01-01

Mass judgments of colliding objects have been used to explore people's understanding of the physical world because they are ecologically relevant, yet people display biases that are most easily explained by a small set of heuristics. Recent work has challenged the heuristic explanation, by producing the same biases from a model that copes with perceptual uncertainty by using Bayesian inference with a prior based on the correct combination rules from Newtonian mechanics (noisy Newton). Here I test the predictions of the leading heuristic model (Gilden and Proffitt, 1989) against the noisy Newton model using a novel manipulation of the standard mass judgment task: making one of the objects invisible post-collision. The noisy Newton model uses the remaining information to predict above-chance performance, while the leading heuristic model predicts chance performance when one or the other final velocity is occluded. An experiment using two different types of occlusion showed better-than-chance performance and response patterns that followed the predictions of the noisy Newton model. The results demonstrate that people can make sensible physical judgments even when information critical for the judgment is missing, and that a Bayesian model can serve as a guide in these situations. Possible algorithmic-level accounts of this task that more closely correspond to the noisy Newton model are explored. PMID:25206345

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.

Test Scheduling for Core-Based SOCs Using Genetic Algorithm Based Heuristic Approach

NASA Astrophysics Data System (ADS)

Giri, Chandan; Sarkar, Soumojit; Chattopadhyay, Santanu

This paper presents a Genetic algorithm (GA) based solution to co-optimize test scheduling and wrapper design for core based SOCs. Core testing solutions are generated as a set of wrapper configurations, represented as rectangles with width equal to the number of TAM (Test Access Mechanism) channels and height equal to the corresponding testing time. A locally optimal best-fit heuristic based bin packing algorithm has been used to determine placement of rectangles minimizing the overall test times, whereas, GA has been utilized to generate the sequence of rectangles to be considered for placement. Experimental result on ITC'02 benchmark SOCs shows that the proposed method provides better solutions compared to the recent works reported in the literature.

Optimisation of flight dynamic control based on many-objectives meta-heuristic: a comparative study

NASA Astrophysics Data System (ADS)

Bureerat, Sujin; Pholdee, Nantiwat; Radpukdee, Thana

2018-05-01

Development of many objective meta-heuristics (MnMHs) is a currently interesting topic as they are suitable to real applications of optimisation problems which usually require many ob-jectives. However, most of MnMHs have been mostly developed and tested based on stand-ard testing functions while the use of MnMHs to real applications is rare. Therefore, in this work, MnMHs are applied for optimisation design of flight dynamic control. The design prob-lem is posed to find control gains for minimising; the control effort, the spiral root, the damp-ing in roll root, sideslip angle deviation, and maximising; the damping ratio of the dutch-roll complex pair, the dutch-roll frequency, bank angle at pre-specified times 1 seconds and 2.8 second subjected to several constraints based on Military Specifications (1969) requirement. Several established many-objective meta-heuristics (MnMHs) are used to solve the problem while their performances are compared. With this research work, performance of several MnMHs for flight control is investigated. The results obtained will be the baseline for future development of flight dynamic and control.

Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

PubMed

Al-Khatib, Ra'ed M; Rashid, Nur'Aini Abdul; Abdullah, Rosni

2011-08-01

The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

Heuristic evaluation of paper-based Web pages: a simplified inspection usability methodology.

PubMed

Allen, Mureen; Currie, Leanne M; Bakken, Suzanne; Patel, Vimla L; Cimino, James J

2006-08-01

Online medical information, when presented to clinicians, must be well-organized and intuitive to use, so that the clinicians can conduct their daily work efficiently and without error. It is essential to actively seek to produce good user interfaces that are acceptable to the user. This paper describes the methodology used to develop a simplified heuristic evaluation (HE) suitable for the evaluation of screen shots of Web pages, the development of an HE instrument used to conduct the evaluation, and the results of the evaluation of the aforementioned screen shots. In addition, this paper presents examples of the process of categorizing problems identified by the HE and the technological solutions identified to resolve these problems. Four usability experts reviewed 18 paper-based screen shots and made a total of 108 comments. Each expert completed the task in about an hour. We were able to implement solutions to approximately 70% of the violations. Our study found that a heuristic evaluation using paper-based screen shots of a user interface was expeditious, inexpensive, and straightforward to implement.

Improving delivery routes using combined heuristic and optimization in a consumer goods distribution company

NASA Astrophysics Data System (ADS)

Wibisono, E.; Santoso, A.; Sunaryo, M. A.

2017-11-01

XYZ is a distributor of various consumer goods products. The company plans its delivery routes daily and in order to obtain route construction in a short amount of time, it simplifies the process by assigning drivers based on geographic regions. This approach results in inefficient use of vehicles leading to imbalance workloads. In this paper, we propose a combined method involving heuristic and optimization to obtain better solutions in acceptable computation time. The heuristic is based on a time-oriented, nearest neighbor (TONN) to form clusters if the number of locations is higher than a certain value. The optimization part uses a mathematical modeling formulation based on vehicle routing problem that considers heterogeneous vehicles, time windows, and fixed costs (HVRPTWF) and is used to solve routing problem in clusters. A case study using data from one month of the company’s operations is analyzed, and data from one day of operations are detailed in this paper. The analysis shows that the proposed method results in 24% cost savings on that month, but it can be as high as 54% in a day.

Climate fails to predict wood decomposition at regional scales

Treesearch

Mark A. Bradford; Robert J. Warren; Petr Baldrian; Thomas W. Crowther; Daniel S. Maynard; Emily E. Oldfield; William R. Wieder; Stephen A. Wood; Joshua R. King

2014-01-01

Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2, 3, 4, 5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on...

Heuristic-based scheduling algorithm for high level synthesis

NASA Technical Reports Server (NTRS)

Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye

1992-01-01

A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.

Understanding place and health: a heuristic for using administrative data.

PubMed

Frohlich, Katherine L; Dunn, James R; McLaren, Lindsay; Shiell, Alan; Potvin, Louise; Hawe, Penelope; Dassa, Clément; Thurston, Wilfreda E

2007-06-01

The increasing availability, use and limitations of administrative data for place-based population health research, and a lack of theory development, created the context for the current paper. We developed a heuristic to interrogate administrative data sets and to help us develop explanatory pathways for linking place and health. Guided by a worked example, we argue that some items in administrative data sets lend themselves to multiple theories, creating problems of inference owing to the implications of using inductive versus deductive reasoning during the research process, and that certain types of theories are privileged when used administrative data bases.

Wishful Thinking? Inside the Black Box of Exposure Assessment.

PubMed

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-05-01

Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts' assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the 'black box' of exposure assessment. A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; 'intensity'; 'probability'; 'agent'; 'process'; and 'duration' of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Wishful Thinking? Inside the Black Box of Exposure Assessment

PubMed Central

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-01-01

Background: Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts’ assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the ‘black box’ of exposure assessment. Methods: A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Results: Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; ‘intensity’; ‘probability’; ‘agent’; ‘process’; and ‘duration’ of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. Conclusion: In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. PMID:26764244

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…

The order and priority of research and design method application within an assistive technology new product development process: a summative content analysis of 20 case studies.

PubMed

Torrens, George Edward

2018-01-01

Summative content analysis was used to define methods and heuristics from each case study. The review process was in two parts: (1) A literature review to identify conventional research methods and (2) a summative content analysis of published case studies, based on the identified methods and heuristics to suggest an order and priority of where and when were used. Over 200 research and design methods and design heuristics were identified. From the review of the 20 case studies 42 were identified as being applied. The majority of methods and heuristics were applied in phase two, market choice. There appeared a disparity between the limited numbers of methods frequently used, under 10 within the 20 case studies, when hundreds were available. Implications for Rehabilitation The communication highlights a number of issues that have implication for those involved in assistive technology new product development: •The study defined over 200 well-established research and design methods and design heuristics that are available for use by those who specify and design assistive technology products, which provide a comprehensive reference list for practitioners in the field; •The review within the study suggests only a limited number of research and design methods are regularly used by industrial design focused assistive technology new product developers; and, •Debate is required within the practitioners working in this field to reflect on how a wider range of potentially more effective methods and heuristics may be incorporated into daily working practice.

More than one way to see it: Individual heuristics in avian visual computation.

PubMed

Ravignani, Andrea; Westphal-Fitch, Gesche; Aust, Ulrike; Schlumpp, Martin M; Fitch, W Tecumseh

2015-10-01

Comparative pattern learning experiments investigate how different species find regularities in sensory input, providing insights into cognitive processing in humans and other animals. Past research has focused either on one species' ability to process pattern classes or different species' performance in recognizing the same pattern, with little attention to individual and species-specific heuristics and decision strategies. We trained and tested two bird species, pigeons (Columba livia) and kea (Nestor notabilis, a parrot species), on visual patterns using touch-screen technology. Patterns were composed of several abstract elements and had varying degrees of structural complexity. We developed a model selection paradigm, based on regular expressions, that allowed us to reconstruct the specific decision strategies and cognitive heuristics adopted by a given individual in our task. Individual birds showed considerable differences in the number, type and heterogeneity of heuristic strategies adopted. Birds' choices also exhibited consistent species-level differences. Kea adopted effective heuristic strategies, based on matching learned bigrams to stimulus edges. Individual pigeons, in contrast, adopted an idiosyncratic mix of strategies that included local transition probabilities and global string similarity. Although performance was above chance and quite high for kea, no individual of either species provided clear evidence of learning exactly the rule used to generate the training stimuli. Our results show that similar behavioral outcomes can be achieved using dramatically different strategies and highlight the dangers of combining multiple individuals in a group analysis. These findings, and our general approach, have implications for the design of future pattern learning experiments, and the interpretation of comparative cognition research more generally. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

The development of a culture of problem solving with secondary students through heuristic strategies

NASA Astrophysics Data System (ADS)

Eisenmann, Petr; Novotná, Jarmila; Přibyl, Jiří; Břehovský, Jiří

2015-12-01

The article reports the results of a longitudinal research study conducted in three mathematics classes in Czech schools with 62 pupils aged 12-18 years. The pupils were exposed to the use of selected heuristic strategies in mathematical problem solving for a period of 16 months. This was done through solving problems where the solution was the most efficient if heuristic strategies were used. The authors conducted a two-dimensional classification of the use of heuristic strategies based on the work of Pólya (2004) and Schoenfeld (1985). We developed a tool that allows for the description of a pupil's ability to solve problems. Named, the Culture of Problem Solving (CPS), this tool consists of four components: intelligence, text comprehension, creativity and the ability to use existing knowledge. The pupils' success rate in problem solving and the changes in some of the CPS factors pre- and post-experiment were monitored. The pupils appeared to considerably improve in the creativity component. In addition, the results indicate a positive change in the students' attitude to problem solving. As far as the teachers participating in the experiment are concerned, a significant change was in their teaching style to a more constructivist, inquiry-based approach, as well as their willingness to accept a student's non-standard approach to solving a problem. Another important outcome of the research was the identification of the heuristic strategies that can be taught via long-term guided solutions of suitable problems and those that cannot. Those that can be taught include systematic experimentation, guess-check-revise and introduction of an auxiliary element. Those that cannot be taught (or can only be taught with difficulty) include the strategies of specification and generalization and analogy.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Conflict and bias in heuristic judgment.

PubMed

Bhatia, Sudeep

2017-02-01

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. We tested this prediction in experiments involving judgments of argument strength and word frequency, and found that participants are more likely to avoid heuristic bias and respond correctly in settings with 2 incorrect heuristic response options compared with similar settings with only 1 heuristic response option. Our results provide strong evidence for conflict as a mechanism influencing the interaction between heuristic and deliberative thought, and illustrate how accuracy can be increased through simple changes to the response sets offered to participants. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem.

PubMed

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.

Research and application of a novel hybrid air quality early-warning system: A case study in China.

PubMed

Li, Chen; Zhu, Zhijie

2018-06-01

As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency. Copyright © 2018 Elsevier B.V. All rights reserved.

Edge compression techniques for visualization of dense directed graphs.

PubMed

Dwyer, Tim; Henry Riche, Nathalie; Marriott, Kim; Mears, Christopher

2013-12-01

We explore the effectiveness of visualizing dense directed graphs by replacing individual edges with edges connected to 'modules'-or groups of nodes-such that the new edges imply aggregate connectivity. We only consider techniques that offer a lossless compression: that is, where the entire graph can still be read from the compressed version. The techniques considered are: a simple grouping of nodes with identical neighbor sets; Modular Decomposition which permits internal structure in modules and allows them to be nested; and Power Graph Analysis which further allows edges to cross module boundaries. These techniques all have the same goal--to compress the set of edges that need to be rendered to fully convey connectivity--but each successive relaxation of the module definition permits fewer edges to be drawn in the rendered graph. Each successive technique also, we hypothesize, requires a higher degree of mental effort to interpret. We test this hypothetical trade-off with two studies involving human participants. For Power Graph Analysis we propose a novel optimal technique based on constraint programming. This enables us to explore the parameter space for the technique more precisely than could be achieved with a heuristic. Although applicable to many domains, we are motivated by--and discuss in particular--the application to software dependency analysis.

A knowledge-based system for patient image pre-fetching in heterogeneous database environments--modeling, design, and evaluation.

PubMed

Wei, C P; Hu, P J; Sheng, O R

2001-03-01

When performing primary reading on a newly taken radiological examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation or comparison purposes. Support of such image references is of clinical importance and may have significant effects on radiologists' examination reading efficiency, service quality, and work satisfaction. To effectively support such image reference needs, we proposed and developed a knowledge-based patient image pre-fetching system, addressing several challenging requirements of the application that include representation and learning of image reference heuristics and management of data-intensive knowledge inferencing. Moreover, the system demands an extensible and maintainable architecture design capable of effectively adapting to a dynamic environment characterized by heterogeneous and autonomous data source systems. In this paper, we developed a synthesized object-oriented entity- relationship model, a conceptual model appropriate for representing radiologists' prior image reference heuristics that are heuristic oriented and data intensive. We detailed the system architecture and design of the knowledge-based patient image pre-fetching system. Our architecture design is based on a client-mediator-server framework, capable of coping with a dynamic environment characterized by distributed, heterogeneous, and highly autonomous data source systems. To adapt to changes in radiologists' patient prior image reference heuristics, ID3-based multidecision-tree induction and CN2-based multidecision induction learning techniques were developed and evaluated. Experimentally, we examined effects of the pre-fetching system we created on radiologists' examination readings. Preliminary results show that the knowledge-based patient image pre-fetching system more accurately supports radiologists' patient prior image reference needs than the current practice adopted at the study site and that radiologists may become more efficient, consultatively effective, and better satisfied when supported by the pre-fetching system than when relying on the study site's pre-fetching practice.

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.

A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique

NASA Astrophysics Data System (ADS)

Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.

2018-04-01

Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.

Neural correlates of strategic reasoning during competitive games.

PubMed

Seo, Hyojung; Cai, Xinying; Donahue, Christopher H; Lee, Daeyeol

2014-10-17

Although human and animal behaviors are largely shaped by reinforcement and punishment, choices in social settings are also influenced by information about the knowledge and experience of other decision-makers. During competitive games, monkeys increased their payoffs by systematically deviating from a simple heuristic learning algorithm and thereby countering the predictable exploitation by their computer opponent. Neurons in the dorsomedial prefrontal cortex (dmPFC) signaled the animal's recent choice and reward history that reflected the computer's exploitative strategy. The strength of switching signals in the dmPFC also correlated with the animal's tendency to deviate from the heuristic learning algorithm. Therefore, the dmPFC might provide control signals for overriding simple heuristic learning algorithms based on the inferred strategies of the opponent. Copyright © 2014, American Association for the Advancement of Science.

Maximum likelihood of phylogenetic networks.

PubMed

Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir

2006-11-01

Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree. Implementation of the criteria as well as heuristics and hardness proofs are available from the authors upon request. Hardness proofs can also be downloaded at http://www.cs.tau.ac.il/~tamirtul/MLNET/Supp-ML.pdf

Heuristic method of fabricating counter electrodes in dye-sensitized solar cells based on a PEDOT:PSS layer as a catalytic material

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.

When decision heuristics and science collide.

PubMed

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.

Path integration mediated systematic search: a Bayesian model.

PubMed

Vickerstaff, Robert J; Merkle, Tobias

2012-08-21

The systematic search behaviour is a backup system that increases the chances of desert ants finding their nest entrance after foraging when the path integrator has failed to guide them home accurately enough. Here we present a mathematical model of the systematic search that is based on extensive behavioural studies in North African desert ants Cataglyphis fortis. First, a simple search heuristic utilising Bayesian inference and a probability density function is developed. This model, which optimises the short-term nest detection probability, is then compared to three simpler search heuristics and to recorded search patterns of Cataglyphis ants. To compare the different searches a method to quantify search efficiency is established as well as an estimate of the error rate in the ants' path integrator. We demonstrate that the Bayesian search heuristic is able to automatically adapt to increasing levels of positional uncertainty to produce broader search patterns, just as desert ants do, and that it outperforms the three other search heuristics tested. The searches produced by it are also arguably the most similar in appearance to the ant's searches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

NASA Astrophysics Data System (ADS)

Zhu, Wei; Timmermans, Harry

2011-06-01

Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may simplify the decision problem using heuristics. Pedestrian behavior in shopping streets is an example. We therefore propose a modeling framework for pedestrian shopping behavior incorporating principles of bounded rationality. We extend three classical heuristic rules (conjunctive, disjunctive and lexicographic rule) by introducing threshold heterogeneity. The proposed models are implemented using data on pedestrian behavior in Wang Fujing Street, the city center of Beijing, China. The models are estimated and compared with multinomial logit models and mixed logit models. Results show that the heuristic models are the best for all the decisions that are modeled. Validation tests are carried out through multi-agent simulation by comparing simulated spatio-temporal agent behavior with the observed pedestrian behavior. The predictions of heuristic models are slightly better than those of the multinomial logit models.

Strategy selection as rational metareasoning.

PubMed

Lieder, Falk; Griffiths, Thomas L

2017-11-01

Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question of how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy's performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to arithmetic by capturing the variability of people's strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and 4 new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the 2 poles of the debate about human rationality by integrating heuristics and biases with learning and rationality. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

We favor formal models of heuristics rather than lists of loose dichotomies: a reply to Evans and Over

PubMed Central

Gigerenzer, Gerd

2009-01-01

In their comment on Marewski et al. (good judgments do not require complex cognition, 2009) Evans and Over (heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer, 2009) conjectured that heuristics can often lead to biases and are not error free. This is a most surprising critique. The computational models of heuristics we have tested allow for quantitative predictions of how many errors a given heuristic will make, and we and others have measured the amount of error by analysis, computer simulation, and experiment. This is clear progress over simply giving heuristics labels, such as availability, that do not allow for quantitative comparisons of errors. Evans and Over argue that the reason people rely on heuristics is the accuracy-effort trade-off. However, the comparison between heuristics and more effortful strategies, such as multiple regression, has shown that there are many situations in which a heuristic is more accurate with less effort. Finally, we do not see how the fast and frugal heuristics program could benefit from a dual-process framework unless the dual-process framework is made more precise. Instead, the dual-process framework could benefit if its two “black boxes” (Type 1 and Type 2 processes) were substituted by computational models of both heuristics and other processes. PMID:19784854

Heuristic decision making.

PubMed

Gigerenzer, Gerd; Gaissmaier, Wolfgang

2011-01-01

As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.

"The Gaze Heuristic:" Biography of an Adaptively Rational Decision Process.

PubMed

Hamlin, Robert P

2017-04-01

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. Copyright © 2017 Cognitive Science Society, Inc.

Reconsidering "evidence" for fast-and-frugal heuristics.

PubMed

Hilbig, Benjamin E

2010-12-01

In several recent reviews, authors have argued for the pervasive use of fast-and-frugal heuristics in human judgment. They have provided an overview of heuristics and have reiterated findings corroborating that such heuristics can be very valid strategies leading to high accuracy. They also have reviewed previous work that implies that simple heuristics are actually used by decision makers. Unfortunately, concerning the latter point, these reviews appear to be somewhat incomplete. More important, previous conclusions have been derived from investigations that bear some noteworthy methodological limitations. I demonstrate these by proposing a new heuristic and provide some novel critical findings. Also, I review some of the relevant literature often not-or only partially-considered. Overall, although some fast-and-frugal heuristics indeed seem to predict behavior at times, there is little to no evidence for others. More generally, the empirical evidence available does not warrant the conclusion that heuristics are pervasively used.

VHP - An environment for the remote visualization of heuristic processes

NASA Technical Reports Server (NTRS)

Crawford, Stuart L.; Leiner, Barry M.

1991-01-01

A software system called VHP is introduced which permits the visualization of heuristic algorithms on both resident and remote hardware platforms. The VHP is based on the DCF tool for interprocess communication and is applicable to remote algorithms which can be on different types of hardware and in languages other than VHP. The VHP system is of particular interest to systems in which the visualization of remote processes is required such as robotics for telescience applications.

Remarks on a New Possible Discretization Scheme for Gauge Theories

NASA Astrophysics Data System (ADS)

Magnot, Jean-Pierre

2018-03-01

We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.

POCO-MOEA: Using Evolutionary Algorithms to Solve the Controller Placement Problem

DTIC Science & Technology

2016-03-24

to gather data on POCO-MOEA performance to a series of iv model networks. The algorithm’s behavior is then evaluated and compared to ex- haustive... evaluation of a third heuristic based on a Multi 3 Objective Evolutionary Algorithm (MOEA). This heuristic is modeled after one of the most well known MOEAs...researchers to extend into more realistic evaluations of the performance characteristics of SDN controllers, such as the use of simulators or live

An approach to combining heuristic and qualitative reasoning in an expert system

NASA Technical Reports Server (NTRS)

Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

1988-01-01

An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

Remarks on a New Possible Discretization Scheme for Gauge Theories

NASA Astrophysics Data System (ADS)

Magnot, Jean-Pierre

2018-07-01

We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.

Scope of Various Random Number Generators in Ant System Approach for TSP

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2007-01-01

Experimented on heuristic, based on an ant system approach for traveling Salesman problem, are several quasi and pseudo-random number generators. This experiment is to explore if any particular generator is most desirable. Such an experiment on large samples has the potential to rank the performance of the generators for the foregoing heuristic. This is just to seek an answer to the controversial performance ranking of the generators in probabilistic/statically sense.

Cultural heuristics in risk assessment of HIV/AIDS.

PubMed

Bailey, Ajay; Hutter, Inge

2006-01-01

Behaviour change models in HIV prevention tend to consider that risky sexual behaviours reflect risk assessments and that by changing risk assessments behaviour can be changed. Risk assessment is however culturally constructed. Individuals use heuristics or bounded cognitive devices derived from broader cultural meaning systems to rationalize uncertainty. In this study, we identify some of the cultural heuristics used by migrant men in Goa, India to assess their risk of HIV infection from different sexual partners. Data derives from a series of in-depth interviews and a locally informed survey. Cultural heuristics identified include visual heuristics, heuristics of gender roles, vigilance and trust. The paper argues that, for more culturally informed HIV/AIDS behaviour change interventions, knowledge of cultural heuristics is essential.

Fast or Frugal, but Not Both: Decision Heuristics Under Time Pressure

PubMed Central

2017-01-01

Heuristics are simple, yet effective, strategies that people use to make decisions. Because heuristics do not require all available information, they are thought to be easy to implement and to not tax limited cognitive resources, which has led heuristics to be characterized as fast-and-frugal. We question this monolithic conception of heuristics by contrasting the cognitive demands of two popular heuristics, Tallying and Take-the-Best. We contend that heuristics that are frugal in terms of information usage may not always be fast because of the attentional control required to implement this focus in certain contexts. In support of this hypothesis, we find that Take-the-Best, while being more frugal in terms of information usage, is slower to implement and fares worse under time pressure manipulations than Tallying. This effect is then reversed when search costs for Take-the-Best are reduced by changing the format of the stimuli. These findings suggest that heuristics are heterogeneous and should be unpacked according to their cognitive demands to determine the circumstances a heuristic best applies. PMID:28557503

Fast or frugal, but not both: Decision heuristics under time pressure.

PubMed

Bobadilla-Suarez, Sebastian; Love, Bradley C

2018-01-01

Heuristics are simple, yet effective, strategies that people use to make decisions. Because heuristics do not require all available information, they are thought to be easy to implement and to not tax limited cognitive resources, which has led heuristics to be characterized as fast-and-frugal. We question this monolithic conception of heuristics by contrasting the cognitive demands of two popular heuristics, Tallying and Take-the-Best. We contend that heuristics that are frugal in terms of information usage may not always be fast because of the attentional control required to implement this focus in certain contexts. In support of this hypothesis, we find that Take-the-Best, while being more frugal in terms of information usage, is slower to implement and fares worse under time pressure manipulations than Tallying. This effect is then reversed when search costs for Take-the-Best are reduced by changing the format of the stimuli. These findings suggest that heuristics are heterogeneous and should be unpacked according to their cognitive demands to determine the circumstances a heuristic best applies. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Heuristics for Relevancy Ranking of Earth Dataset Search Results

NASA Astrophysics Data System (ADS)

Lynnes, C.; Quinn, P.; Norton, J.

2016-12-01

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.

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.

Varying execution discipline to increase performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, P.L.; Maccabe, A.B.

1993-12-22

This research investigates the relationship between execution discipline and performance. The hypothesis has two parts: 1. Different execution disciplines exhibit different performance for different computations, and 2. These differences can be effectively predicted by heuristics. A machine model is developed that can vary its execution discipline. That is, the model can execute a given program using either the control-driven, data-driven or demand-driven execution discipline. This model is referred to as a ``variable-execution-discipline`` machine. The instruction set for the model is the Program Dependence Web (PDW). The first part of the hypothesis will be tested by simulating the execution of themore » machine model on a suite of computations, based on the Livermore Fortran Kernel (LFK) Test (a.k.a. the Livermore Loops), using all three execution disciplines. Heuristics are developed to predict relative performance. These heuristics predict (a) the execution time under each discipline for one iteration of each loop and (b) the number of iterations taken by that loop; then the heuristics use those predictions to develop a prediction for the execution of the entire loop. Similar calculations are performed for branch statements. The second part of the hypothesis will be tested by comparing the results of the simulated execution with the predictions produced by the heuristics. If the hypothesis is supported, then the door is open for the development of machines that can vary execution discipline to increase performance.« less

Web-based Education for Low-literate Parents in Neonatal Intensive Care Unit: Development of a Website and Heuristic Evaluation and Usability Testing

PubMed Central

Choi, Jeungok; Bakken, Suzanne

2010-01-01

Purpose Low health literacy has been associated with poor health-related outcomes. The purposes are to report the development of a website for low-literate parents in the Neonatal Intensive Care Unit (NICU), and the findings of heuristic evaluation and a usability testing of this website. Methods To address low literacy of NICU parents, multimedia educational Website using visual aids (e.g., pictographs, photographs), voice-recorded text message in addition to a simplified text was developed. The text was created at the 5th grade readability level. The heuristic evaluation was conducted by three usability experts using 10 heuristics. End-users’ performance was measured by counting the time spent completing tasks and number of errors, as well as recording users’ perception of ease of use and usefulness (PEUU) in a sample of 10 NICU parents. Results Three evaluators identified 82 violations across the 10 heuristics. All violations, however, received scores <2, indicating minor usability problems. Participants’ time to complete task varies from 81.2 seconds (SD=30.9) to 2.2 seconds (SD=1.3). Participants rated the Website as easy to use and useful (PEUU Mean= 4.52, SD=0.53). Based on the participants’ comments, appropriate modifications were made. Discussion and Conclusions Different types of visuals on the Website were well accepted by low-literate users and agreement of visuals with text improved understanding of the educational materials over that with text alone. The findings suggest that using concrete and realistic pictures and pictographs with clear captions would maximize the benefit of visuals. One emerging theme was “simplicity” in design (e.g., limited use of colors, one font type and size), content (e.g., avoid lengthy text), and technical features (e.g., limited use of pop-ups). The heuristic evaluation by usability experts and the usability test with actual users provided complementary expertise, which can give a richer assessment of a design for low literacy Website. These results facilitated design modification and implementation of solutions by categorizing and prioritizing the usability problems. PMID:20617546

Web-based education for low-literate parents in Neonatal Intensive Care Unit: development of a website and heuristic evaluation and usability testing.

PubMed

Choi, Jeungok; Bakken, Suzanne

2010-08-01

Low health literacy has been associated with poor health-related outcomes. The purposes are to report the development of a website for low-literate parents in the Neonatal Intensive Care Unit (NICU), and the findings of heuristic evaluation and a usability testing of this website. To address low literacy of NICU parents, multimedia educational Website using visual aids (e.g., pictographs, photographs), voice-recorded text message in addition to a simplified text was developed. The text was created at the 5th grade readability level. The heuristic evaluation was conducted by three usability experts using 10 heuristics. End-users' performance was measured by counting the time spent completing tasks and number of errors, as well as recording users' perception of ease of use and usefulness (PEUU) in a sample of 10 NICU parents. Three evaluators identified 82 violations across the 10 heuristics. All violations, however, received scores <2, indicating minor usability problems. Participants' time to complete task varies from 81.2 s (SD = 30.9) to 2.2 s (SD = 1.3). Participants rated the Website as easy to use and useful (PEUU mean = 4.52, SD = 0.53). Based on the participants' comments, appropriate modifications were made. Different types of visuals on the Website were well accepted by low-literate users and agreement of visuals with text improved understanding of the educational materials over that with text alone. The findings suggest that using concrete and realistic pictures and pictographs with clear captions would maximize the benefit of visuals. One emerging theme was "simplicity" in design (e.g., limited use of colors, one font type and size), content (e.g., avoid lengthy text), and technical features (e.g., limited use of pop-ups). The heuristic evaluation by usability experts and the usability test with actual users provided complementary expertise, which can give a richer assessment of a design for low literacy Website. These results facilitated design modification and implementation of solutions by categorizing and prioritizing the usability problems.

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

Reexamining our bias against heuristics.

PubMed

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.

Not so fast! (and not so frugal!): rethinking the recognition heuristic.

PubMed

Oppenheimer, Daniel M

2003-11-01

The 'fast and frugal' approach to reasoning (Gigerenzer, G., & Todd, P. M. (1999). Simple heuristics that make us smart. New York: Oxford University Press) claims that individuals use non-compensatory strategies in judgment--the idea that only one cue is taken into account in reasoning. The simplest and most important of these heuristics postulates that judgment sometimes relies solely on recognition. However, the studies that have investigated usage of the recognition heuristic have confounded recognition with other cues that could also lead to similar judgments. This paper tests whether mere recognition is actually driving the findings in support of the recognition heuristic. Two studies provide evidence that judgments do not conform to the recognition heuristic when these confounds are accounted for. Implications for the study of simple heuristics are discussed.

The E-health Literacy Demands of Australia's My Health Record: A Heuristic Evaluation of Usability.

PubMed

Walsh, Louisa; Hemsley, Bronwyn; Allan, Meredith; Adams, Natalie; Balandin, Susan; Georgiou, Andrew; Higgins, Isabel; McCarthy, Shaun; Hill, Sophie

2017-01-01

My Health Record is Australia's electronic personal health record system, which was introduced in July 2012. As of August 2017, approximately 21 percent of Australia's total population was registered to use My Health Record. Internationally, usability issues have been shown to negatively influence the uptake and use of electronic health record systems, and this scenario may particularly affect people who have low e-health literacy. It is likely that usability issues are negatively affecting the uptake and use of My Health Record in Australia. To identify potential e-health literacy-related usability issues within My Health Record through a heuristic evaluation method. Between September 14 and October 12, 2016, three of the authors conducted a heuristic evaluation of the two consumer-facing components of My Health Record-the information website and the electronic health record itself. These two components were evaluated against two sets of heuristics-the Health Literacy Online checklist and the Monkman Heuristics. The Health Literacy Online checklist and Monkman Heuristics are evidence-based checklists of web design elements with a focus on design for audiences with low health literacy. During this heuristic evaluation, the investigators individually navigated through the consumer-facing components of My Health Record, recording instances where the My Health Record did not conform to the checklist criteria. After the individual evaluations were completed, the investigators conferred and aggregated their results. From this process, a list of usability violations was constructed. When evaluated against the Health Literacy Online Checklist, the information website demonstrated violations in 12 of 35 criteria, and the electronic health record demonstrated violations in 16 of 35 criteria. When evaluated against the Monkman Heuristics, the information website demonstrated violations in 7 of 11 criteria, and the electronic health record demonstrated violations in 9 of 11 criteria. The identified violations included usability issues with the reading levels used within My Health Record, the graphic design elements, the layout of web pages, and a lack of images and audiovisual tools to support learning. Other important usability issues included a lack of translated resources, difficulty using accessibility tools, and complexity of the registration processes. My Health Record is an important piece of technology that has the potential to facilitate better communication between consumers and their health providers. However, this heuristic evaluation demonstrated that many usability-related elements of My Health Record cater poorly to users at risk of having low e-health literacy. Usability issues have been identified as an important barrier to use of personal health records internationally, and the findings of this heuristic evaluation demonstrate that usability issues may be substantial barriers to the uptake and use of My Health Record.

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

NASA Astrophysics Data System (ADS)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.

PubMed

Naso, David; Turchiano, Biagio

2005-04-01

In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.

Aiding USAF/UPT (Undergraduate Pilot Training) Aircrew Scheduling Using Network Flow Models.

DTIC Science & Technology

1986-06-01

51 3.4 Heuristic Modifications ............ 55 CHAPTER 4 STUDENT SCHEDULING PROBLEM (LEVEL 2) 4.0 Introduction 4.01 Constraints ............. 60 4.02...Covering" Complete Enumeration . . .. . 71 4.14 Heuristics . ............. 72 4.2 Heuristic Method for the Level 2 Problem 4.21 Step I ............... 73...4.22 Step 2 ............... 74 4.23 Advantages to the Heuristic Method. .... .. 78 4.24 Problems with the Heuristic Method. . ... 79 :,., . * CHAPTER5

Approximation algorithms for the min-power symmetric connectivity problem

NASA Astrophysics Data System (ADS)

Plotnikov, Roman; Erzin, Adil; Mladenovic, Nenad

2016-10-01

We consider the NP-hard problem of synthesis of optimal spanning communication subgraph in a given arbitrary simple edge-weighted graph. This problem occurs in the wireless networks while minimizing the total transmission power consumptions. We propose several new heuristics based on the variable neighborhood search metaheuristic for the approximation solution of the problem. We have performed a numerical experiment where all proposed algorithms have been executed on the randomly generated test samples. For these instances, on average, our algorithms outperform the previously known heuristics.

Kepler: Analogies in the search for the law of refraction.

PubMed

Cardona, Carlos Alberto

2016-10-01

This paper examines the methodology used by Kepler to discover a quantitative law of refraction. The aim is to argue that this methodology follows a heuristic method based on the following two Pythagorean principles: (1) sameness is made known by sameness, and (2) harmony arises from establishing a limit to what is unlimited. We will analyse some of the author's proposed analogies to find the aforementioned law and argue that the investigation's heuristic pursues such principles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.

DETECTORS AND EXPERIMENTAL METHODS: Heuristic approach for peak regions estimation in gamma-ray spectra measured by a NaI detector

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.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

PubMed

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.

Heuristic-based information acquisition and decision making among pilots.

PubMed

Wiggins, Mark W; Bollwerk, Sandra

2006-01-01

This research was designed to examine the impact of heuristic-based approaches to the acquisition of task-related information on the selection of an optimal alternative during simulated in-flight decision making. The work integrated features of naturalistic and normative decision making and strategies of information acquisition within a computer-based, decision support framework. The study comprised two phases, the first of which involved familiarizing pilots with three different heuristic-based strategies of information acquisition: frequency, elimination by aspects, and majority of confirming decisions. The second stage enabled participants to choose one of the three strategies of information acquisition to resolve a fourth (choice) scenario. The results indicated that task-oriented experience, rather than the information acquisition strategies, predicted the selection of the optimal alternative. It was also evident that of the three strategies available, the elimination by aspects information acquisition strategy was preferred by most participants. It was concluded that task-oriented experience, rather than the process of information acquisition, predicted task accuracy during the decision-making task. It was also concluded that pilots have a preference for one particular approach to information acquisition. Applications of outcomes of this research include the development of decision support systems that adapt to the information-processing capabilities and preferences of users.

A proven knowledge-based approach to prioritizing process information

NASA Technical Reports Server (NTRS)

Corsberg, Daniel R.

1991-01-01

Many space-related processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect is rapid analysis of the changing process information. During a disturbance, this task can overwhelm humans as well as computers. Humans deal with this by applying heuristics in determining significant information. A simple, knowledge-based approach to prioritizing information is described. The approach models those heuristics that humans would use in similar circumstances. The approach described has received two patents and was implemented in the Alarm Filtering System (AFS) at the Idaho National Engineering Laboratory (INEL). AFS was first developed for application in a nuclear reactor control room. It has since been used in chemical processing applications, where it has had a significant impact on control room environments. The approach uses knowledge-based heuristics to analyze data from process instrumentation and respond to that data according to knowledge encapsulated in objects and rules. While AFS cannot perform the complete diagnosis and control task, it has proven to be extremely effective at filtering and prioritizing information. AFS was used for over two years as a first level of analysis for human diagnosticians. Given the approach's proven track record in a wide variety of practical applications, it should be useful in both ground- and space-based systems.

Evaluating the usability of an interactive, bi-lingual, touchscreen-enabled breastfeeding educational programme: application of Nielson's heuristics.

PubMed

Joshi, Ashish; Perin, Douglas M Puricelli; Amadi, Chioma; Trout, Kate

2015-03-05

The study purpose was to conduct heuristic evaluation of an interactive, bilingual touchscreen-enabled breastfeeding educational programme for Hispanic women living in rural settings in Nebraska. Three raters conducted the evaluation during May 2013 using principles of Nielson's heuristics. A total of 271 screens were evaluated and included: interface (n = 5), programme sections (n = 223) and educational content (n = 43). A total of 97 heuristic violations were identified and were mostly related to interface (8 violations/5 screens) and programme components (89 violations/266 screens). The most common heuristic violations reported were recognition rather than recall (62%, n = 60), consistency and standards (14%, n = 14) and match between the system and real world (9%, n = 9). Majority of the heuristic violations had minor usability issues (73%, n = 71). The only grade 4 heuristic violation reported was due to the visibility of system status in the assessment modules. The results demonstrated that the system was more consistent with Nielsen's usability heuristics. With Nielsen's usability heuristics, it is possible to identify problems in a timely manner, and help facilitate the identification and prioritisation of problems needing urgent attention at an earlier stage before the final deployment of the system.

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

PubMed

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.

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems

PubMed Central

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

Hyper-heuristics with low level parameter adaptation.

PubMed

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.

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.

Is creative insight task-specific? A coordinate-based meta-analysis of neuroimaging studies on insightful problem solving.

PubMed

Shen, Wangbing; Yuan, Yuan; Liu, Chang; Zhang, Xiaojiang; Luo, Jing; Gong, Zhe

2016-12-01

The question of whether creative insight varies across problem types has recently come to the forefront of studies of creative cognition. In the present study, to address the nature of creative insight, the coordinate-based activation likelihood estimation (ALE) technique was utilized to individually conduct three quantitative meta-analyses of neuroimaging experiments that used the compound remote associate (CRA) task, the prototype heuristic (PH) task and the Chinese character chunk decomposition (CCD) task. These tasks were chosen because they are frequently used to uncover the neurocognitive correlates of insight. Our results demonstrated that creative insight reliably activates largely non-overlapping brain regions across task types, with the exception of some shared regions: the CRA task mainly relied on the right parahippocampal gyrus, the superior frontal gyrus and the inferior frontal gyrus; the PH task primarily depended on the right middle occipital gyrus (MOG), the bilateral superior parietal lobule/precuneus, the left inferior parietal lobule, the left lingual gyrus and the left middle frontal gyrus; and the CCD task activated a broad cerebral network consisting of most dorsolateral and medial prefrontal regions, frontoparietal regions and the right MOG. These results provide the first neural evidence of the task dependence of creative insight. The implications of these findings for resolving conflict surrounding the different theories of creative cognition and for defining insight as a set of heterogeneous processes are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Distributed and decentralized state estimation in gas networks as distributed parameter systems.

PubMed

Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry

2015-09-01

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline networks. In the construction of local models, due to the existence of common states and interconnections among the subsystems, the assimilation and prediction steps of the Kalman filter are modified to take the overlapping and external states into account. However, dynamic Riccati equation for each subsystem is constructed based on the local model, which introduces a maximum error of 5% in the estimated standard deviation of the states in the benchmarks studied in this paper. The performance of the proposed methodology has been shown based on the comparison of its accuracy and computational demands against their counterparts in centralized Kalman filter for two viable benchmarks. In a real life network, it is shown that while the accuracy is not significantly decreased, the real-time factor of the state estimation is increased by a factor of 10. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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.…

Ideology in Writing Instruction: Reconsidering Invention Heuristics.

ERIC Educational Resources Information Center

Byard, Vicki

Modern writing textbooks tend to offer no heuristics, treat heuristics as if they do not have different impacts on inquiry, or take the view that heuristics are ideologically neutral pedagogies. Yet theory about language demonstrates that ideological neutrality is impossible. Any use of language in attempting to represent reality will inevitably…

An Effective Exercise for Teaching Cognitive Heuristics

ERIC Educational Resources Information Center

Swinkels, Alan

2003-01-01

This article describes a brief heuristics demonstration and offers suggestions for personalizing examples of heuristics by making them relevant to students. Students complete a handout asking for 4 judgments illustrative of such heuristics. The decisions are cast in the context of students' daily lives at their particular university. After the…

A practical material decomposition method for x-ray dual spectral computed tomography.

PubMed

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

Fairness heuristics and substitutability effects: inferring the fairness of outcomes, procedures, and interpersonal treatment when employees lack clear information.

PubMed

Qin, Xin; Ren, Run; Zhang, Zhi-Xue; Johnson, Russell E

2015-05-01

Employees routinely make judgments of 3 kinds of justice (i.e., distributive, procedural, and interactional), yet they may lack clear information to do so. This research examines how justice judgments are formed when clear information about certain types of justice is unavailable or ambiguous. Drawing from fairness heuristic theory, as well as more general theories of cognitive heuristics, we predict that when information for 1 type of justice is unclear (i.e., low in justice clarity), people infer its fairness based on other types of justice with clear information (i.e., high in justice clarity). Results across 3 studies employing different designs (correlational vs. experimental), samples (employees vs. students), and measures (proxy vs. direct) provided support for the proposed substitutability effects, especially when inferences were based on clear interactional justice information. Moreover, we found that substitutability effects were more likely to occur when employees had high (vs. low) need for cognitive closure. We conclude by discussing the theoretical contributions and practical implications of our findings. (c) 2015 APA, all rights reserved).

Derived heuristics-based consistent optimization of material flow in a gold processing plant

NASA Astrophysics Data System (ADS)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Comparison of Decisions Quality of Heuristic Methods with Limited Depth-First Search Techniques in the Graph Shortest Path Problem

NASA Astrophysics Data System (ADS)

Vatutin, Eduard

2017-12-01

The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.

Double-Group Particle Swarm Optimization and Its Application in Remote Sensing Image Segmentation

PubMed Central

Shen, Liang; Huang, Xiaotao; Fan, Chongyi

2018-01-01

Particle Swarm Optimization (PSO) is a well-known meta-heuristic. It has been widely used in both research and engineering fields. However, the original PSO generally suffers from premature convergence, especially in multimodal problems. In this paper, we propose a double-group PSO (DG-PSO) algorithm to improve the performance. DG-PSO uses a double-group based evolution framework. The individuals are divided into two groups: an advantaged group and a disadvantaged group. The advantaged group works according to the original PSO, while two new strategies are developed for the disadvantaged group. The proposed algorithm is firstly evaluated by comparing it with the other five popular PSO variants and two state-of-the-art meta-heuristics on various benchmark functions. The results demonstrate that DG-PSO shows a remarkable performance in terms of accuracy and stability. Then, we apply DG-PSO to multilevel thresholding for remote sensing image segmentation. The results show that the proposed algorithm outperforms five other popular algorithms in meta-heuristic-based multilevel thresholding, which verifies the effectiveness of the proposed algorithm. PMID:29724013

Double-Group Particle Swarm Optimization and Its Application in Remote Sensing Image Segmentation.

PubMed

Shen, Liang; Huang, Xiaotao; Fan, Chongyi

2018-05-01

Particle Swarm Optimization (PSO) is a well-known meta-heuristic. It has been widely used in both research and engineering fields. However, the original PSO generally suffers from premature convergence, especially in multimodal problems. In this paper, we propose a double-group PSO (DG-PSO) algorithm to improve the performance. DG-PSO uses a double-group based evolution framework. The individuals are divided into two groups: an advantaged group and a disadvantaged group. The advantaged group works according to the original PSO, while two new strategies are developed for the disadvantaged group. The proposed algorithm is firstly evaluated by comparing it with the other five popular PSO variants and two state-of-the-art meta-heuristics on various benchmark functions. The results demonstrate that DG-PSO shows a remarkable performance in terms of accuracy and stability. Then, we apply DG-PSO to multilevel thresholding for remote sensing image segmentation. The results show that the proposed algorithm outperforms five other popular algorithms in meta-heuristic-based multilevel thresholding, which verifies the effectiveness of the proposed algorithm.

Through-wall image enhancement using fuzzy and QR decomposition.

PubMed

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

QR decomposition and fuzzy logic based scheme is proposed for through-wall image enhancement. QR decomposition is less complex compared to singular value decomposition. Fuzzy inference engine assigns weights to different overlapping subspaces. Quantitative measures and visual inspection are used to analyze existing and proposed techniques.

Adaptive Fourier decomposition based ECG denoising.

PubMed

Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

2016-10-01

A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer.

PubMed

Evans, Jonathan St B T; Over, David E

2010-05-01

Marewski, Gaissmaier and Gigerenzer (2009) present a review of research on fast and frugal heuristics, arguing that complex problems are best solved by simple heuristics, rather than the application of knowledge and logical reasoning. We argue that the case for such heuristics is overrated. First, we point out that heuristics can often lead to biases as well as effective responding. Second, we show that the application of logical reasoning can be both necessary and relatively simple. Finally, we argue that the evidence for a logical reasoning system that co-exists with simpler heuristic forms of thinking is overwhelming. Not only is it implausible a priori that we would have evolved such a system that is of no use to us, but extensive evidence from the literature on dual processing in reasoning and judgement shows that many problems can only be solved when this form of reasoning is used to inhibit and override heuristic thinking.

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,…

Heuristics Made Easy: An Effort-Reduction Framework

ERIC Educational Resources Information Center

Shah, Anuj K.; Oppenheimer, Daniel M.

2008-01-01

In this article, the authors propose a new framework for understanding and studying heuristics. The authors posit that heuristics primarily serve the purpose of reducing the effort associated with a task. As such, the authors propose that heuristics can be classified according to a small set of effort-reduction principles. The authors use this…

Heuristic Diagrams as a Tool to Teach History of Science

ERIC Educational Resources Information Center

Chamizo, Jose A.

2012-01-01

The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The…

A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices.

PubMed

Brusco, Michael; Steinley, Douglas

2011-10-01

Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where the goal is to identify partitions for the row and column objects such that the clusters of the row and column objects form blocks that are either complete (all 1s) or null (all 0s) to the greatest extent possible. Multiple restarts of an object relocation heuristic that seeks to minimize the number of inconsistencies (i.e., 1s in null blocks and 0s in complete blocks) with ideal block structure is the predominant approach for tackling this problem. As an alternative, we propose a fast and effective implementation of tabu search. Computational comparisons across a set of 48 large network matrices revealed that the new tabu-search heuristic always provided objective function values that were better than those of the relocation heuristic when the two methods were constrained to the same amount of computation time.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Heuristic reasoning and cognitive biases: Are they hindrances to judgments and decision making in orthodontics?

PubMed

Hicks, E Preston; Kluemper, G Thomas

2011-03-01

Studies show that our brains use 2 modes of reasoning: heuristic (intuitive, automatic, implicit processing) and analytic (deliberate, rule-based, explicit processing). The use of intuition often dominates problem solving when innovative, creative thinking is required. Under conditions of uncertainty, we default to an even greater reliance on the heuristic processing. In health care settings and other such environments of increased importance, this mode becomes problematic. Since choice heuristics are quickly constructed from fragments of memory, they are often biased by prior evaluations of and preferences for the alternatives being considered. Therefore, a rigorous and systematic decision process notwithstanding, clinical judgments under uncertainty are often flawed by a number of unwitting biases. Clinical orthodontics is as vulnerable to this fundamental failing in the decision-making process as any other health care discipline. Several of the more common cognitive biases relevant to clinical orthodontics are discussed in this article. By raising awareness of these sources of cognitive errors in our clinical decision making, our intent was to equip the clinician to take corrective action to avoid them. Our secondary goal was to expose this important area of empirical research and encourage those with expertise in the cognitive sciences to explore, through further research, the possible relevance and impact of cognitive heuristics and biases on the accuracy of orthodontic judgments and decision making. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Detecting false positive sequence homology: a machine learning approach.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

Cue reliability and a landmark stability heuristic determine relative weighting between egocentric and allocentric visual information in memory-guided reach.

PubMed

Byrne, Patrick A; Crawford, J Douglas

2010-06-01

It is not known how egocentric visual information (location of a target relative to the self) and allocentric visual information (location of a target relative to external landmarks) are integrated to form reach plans. Based on behavioral data from rodents and humans we hypothesized that the degree of stability in visual landmarks would influence the relative weighting. Furthermore, based on numerous cue-combination studies we hypothesized that the reach system would act like a maximum-likelihood estimator (MLE), where the reliability of both cues determines their relative weighting. To predict how these factors might interact we developed an MLE model that weighs egocentric and allocentric information based on their respective reliabilities, and also on an additional stability heuristic. We tested the predictions of this model in 10 human subjects by manipulating landmark stability and reliability (via variable amplitude vibration of the landmarks and variable amplitude gaze shifts) in three reach-to-touch tasks: an egocentric control (reaching without landmarks), an allocentric control (reaching relative to landmarks), and a cue-conflict task (involving a subtle landmark "shift" during the memory interval). Variability from all three experiments was used to derive parameters for the MLE model, which was then used to simulate egocentric-allocentric weighting in the cue-conflict experiment. As predicted by the model, landmark vibration--despite its lack of influence on pointing variability (and thus allocentric reliability) in the control experiment--had a strong influence on egocentric-allocentric weighting. A reduced model without the stability heuristic was unable to reproduce this effect. These results suggest heuristics for extrinsic cue stability are at least as important as reliability for determining cue weighting in memory-guided reaching.

Design and usability of heuristic‐based deliberation tools for women facing amniocentesis

PubMed Central

Durand, Marie‐Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2011-01-01

Abstract Background  Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health‐care decisions), fast and frugal decision‐making strategies (heuristics) may perform better than complex rules of reasoning. Objective  To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). Design  The ‘Take The Best’ heuristic (i.e. selection of a ‘most important reason’) and ‘The Tallying’ integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web‐based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health‐care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of ‘your most important reason’ (Take The Best) and ‘weighing it up’ (Tallying). Results  Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health‐care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that ‘weighing it up’ and ‘your most important reason’ were not appropriate when facing such a difficult and emotional decision. Conclusion  Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real‐world decisions about amniocentesis. PMID:21241434

Fast or Frugal, but Not Both: Decision Heuristics under Time Pressure

ERIC Educational Resources Information Center

Bobadilla-Suarez, Sebastian; Love, Bradley C.

2018-01-01

Heuristics are simple, yet effective, strategies that people use to make decisions. Because heuristics do not require all available information, they are thought to be easy to implement and to not tax limited cognitive resources, which has led heuristics to be characterized as fast-and-frugal. We question this monolithic conception of heuristics…

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…

Why Heuristics Work.

PubMed

Gigerenzer, Gerd

2008-01-01

The adaptive toolbox is a Darwinian-inspired theory that conceives of the mind as a modular system that is composed of heuristics, their building blocks, and evolved capacities. The study of the adaptive toolbox is descriptive and analyzes the selection and structure of heuristics in social and physical environments. The study of ecological rationality is prescriptive and identifies the structure of environments in which specific heuristics either succeed or fail. Results have been used for designing heuristics and environments to improve professional decision making in the real world. © 2008 Association for Psychological Science.

Heuristic status polling

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN; Ratterman, Joseph D [Rochester, MN

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.

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.

Heuristics: foundations for a novel approach to medical decision making.

PubMed

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.

Hybrid Decompositional Verification for Discovering Failures in Adaptive Flight Control Systems

NASA Technical Reports Server (NTRS)

Thompson, Sarah; Davies, Misty D.; Gundy-Burlet, Karen

2010-01-01

Adaptive flight control systems hold tremendous promise for maintaining the safety of a damaged aircraft and its passengers. However, most currently proposed adaptive control methodologies rely on online learning neural networks (OLNNs), which necessarily have the property that the controller is changing during the flight. These changes tend to be highly nonlinear, and difficult or impossible to analyze using standard techniques. In this paper, we approach the problem with a variant of compositional verification. The overall system is broken into components. Undesirable behavior is fed backwards through the system. Components which can be solved using formal methods techniques explicitly for the ranges of safe and unsafe input bounds are treated as white box components. The remaining black box components are analyzed with heuristic techniques that try to predict a range of component inputs that may lead to unsafe behavior. The composition of these component inputs throughout the system leads to overall system test vectors that may elucidate the undesirable behavior

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Self-organization in a distributed coordination game through heuristic rules

NASA Astrophysics Data System (ADS)

Agarwal, Shubham; Ghosh, Diptesh; Chakrabarti, Anindya S.

2016-12-01

In this paper, we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, N agents play a coordination game repeatedly, which has exactly N pure strategy Nash equilibria, and all of the equilibria are equally preferred by the agents. The problem is to select one equilibrium out of N possible equilibria in the least number of attempts. We propose a number of heuristic rules based on reinforcement learning to solve the coordination problem. We see that the agents self-organize into clusters with varying intensities depending on the heuristic rule applied, although all clusters but one are transitory in most cases. Finally, we characterize a trade-off in terms of the time requirement to achieve a degree of stability in strategies versus the efficiency of such a solution.

A novel heuristic algorithm for capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

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.

Heuristics and Cognitive Error in Medical Imaging.

PubMed

Itri, Jason N; Patel, Sohil H

2018-05-01

The field of cognitive science has provided important insights into mental processes underlying the interpretation of imaging examinations. Despite these insights, diagnostic error remains a major obstacle in the goal to improve quality in radiology. In this article, we describe several types of cognitive bias that lead to diagnostic errors in imaging and discuss approaches to mitigate cognitive biases and diagnostic error. Radiologists rely on heuristic principles to reduce complex tasks of assessing probabilities and predicting values into simpler judgmental operations. These mental shortcuts allow rapid problem solving based on assumptions and past experiences. Heuristics used in the interpretation of imaging studies are generally helpful but can sometimes result in cognitive biases that lead to significant errors. An understanding of the causes of cognitive biases can lead to the development of educational content and systematic improvements that mitigate errors and improve the quality of care provided by radiologists.

Heuristics for the Hodgkin-Huxley system.

PubMed

Hoppensteadt, Frank

2013-09-01

Hodgkin and Huxley (HH) discovered that voltages control ionic currents in nerve membranes. This led them to describe electrical activity in a neuronal membrane patch in terms of an electronic circuit whose characteristics were determined using empirical data. Due to the complexity of this model, a variety of heuristics, including relaxation oscillator circuits and integrate-and-fire models, have been used to investigate activity in neurons, and these simpler models have been successful in suggesting experiments and explaining observations. Connections between most of the simpler models had not been made clear until recently. Shown here are connections between these heuristics and the full HH model. In particular, we study a new model (Type III circuit): It includes the van der Pol-based models; it can be approximated by a simple integrate-and-fire model; and it creates voltages and currents that correspond, respectively, to the h and V components of the HH system. Copyright © 2012 Elsevier Inc. All rights reserved.

Task Assignment Heuristics for Parallel and Distributed CFD Applications

NASA Technical Reports Server (NTRS)

Lopez-Benitez, Noe; Djomehri, M. Jahed; Biswas, Rupak

2003-01-01

This paper proposes a task graph (TG) model to represent a single discrete step of multi-block overset grid computational fluid dynamics (CFD) applications. The TG model is then used to not only balance the computational workload across the overset grids but also to reduce inter-grid communication costs. We have developed a set of task assignment heuristics based on the constraints inherent in this class of CFD problems. Two basic assignments, the smallest task first (STF) and the largest task first (LTF), are first presented. They are then systematically costs. To predict the performance of the proposed task assignment heuristics, extensive performance evaluations are conducted on a synthetic TG with tasks defined in terms of the number of grid points in predetermined overlapping grids. A TG derived from a realistic problem with eight million grid points is also used as a test case.

A human reliability based usability evaluation method for safety-critical software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boring, R. L.; Tran, T. Q.; Gertman, D. I.

2006-07-01

Boring and Gertman (2005) introduced a novel method that augments heuristic usability evaluation methods with that of the human reliability analysis method of SPAR-H. By assigning probabilistic modifiers to individual heuristics, it is possible to arrive at the usability error probability (UEP). Although this UEP is not a literal probability of error, it nonetheless provides a quantitative basis to heuristic evaluation. This method allows one to seamlessly prioritize and identify usability issues (i.e., a higher UEP requires more immediate fixes). However, the original version of this method required the usability evaluator to assign priority weights to the final UEP, thusmore » allowing the priority of a usability issue to differ among usability evaluators. The purpose of this paper is to explore an alternative approach to standardize the priority weighting of the UEP in an effort to improve the method's reliability. (authors)« less

Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.

2015-03-01

In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.

Capturing molecular multimode relaxation processes in excitable gases based on decomposition of acoustic relaxation spectra

NASA Astrophysics Data System (ADS)

Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng

2017-08-01

Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.

Extracting fingerprint of wireless devices based on phase noise and multiple level wavelet decomposition

NASA Astrophysics Data System (ADS)

Zhao, Weichen; Sun, Zhuo; Kong, Song

2016-10-01

Wireless devices can be identified by the fingerprint extracted from the signal transmitted, which is useful in wireless communication security and other fields. This paper presents a method that extracts fingerprint based on phase noise of signal and multiple level wavelet decomposition. The phase of signal will be extracted first and then decomposed by multiple level wavelet decomposition. The statistic value of each wavelet coefficient vector is utilized for constructing fingerprint. Besides, the relationship between wavelet decomposition level and recognition accuracy is simulated. And advertised decomposition level is revealed as well. Compared with previous methods, our method is simpler and the accuracy of recognition remains high when Signal Noise Ratio (SNR) is low.

How the twain can meet: Prospect theory and models of heuristics in risky choice.

PubMed

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. Copyright © 2017 Elsevier Inc. All rights reserved.

Conflict monitoring in dual process theories of thinking.

PubMed

De Neys, Wim; Glumicic, Tamara

2008-03-01

Popular dual process theories have characterized human thinking as an interplay between an intuitive-heuristic and demanding-analytic reasoning process. Although monitoring the output of the two systems for conflict is crucial to avoid decision making errors there are some widely different views on the efficiency of the process. Kahneman [Kahneman, D. (2002). Maps of bounded rationality: A perspective on intuitive judgement and choice. Nobel Prize Lecture. Retrieved January 11, 2006, from: http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahnemann-lecture.pdf] and Evans [Evans, J. St. B. T. (1984). Heuristic and analytic processing in reasoning. British Journal of Psychology, 75, 451-468], for example, claim that the monitoring of the heuristic system is typically quite lax whereas others such as Sloman [Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3-22] and Epstein [Epstein, S. (1994). Integration of the cognitive and psychodynamic unconscious. American Psychologists, 49, 709-724] claim it is flawless and people typically experience a struggle between what they "know" and "feel" in case of a conflict. The present study contrasted these views. Participants solved classic base rate neglect problems while thinking aloud. In these problems a stereotypical description cues a response that conflicts with the response based on the analytic base rate information. Verbal protocols showed no direct evidence for an explicitly experienced conflict. As Kahneman and Evans predicted, participants hardly ever mentioned the base rates and seemed to base their judgment exclusively on heuristic reasoning. However, more implicit measures of conflict detection such as participants' retrieval of the base rate information in an unannounced recall test, decision making latencies, and the tendency to review the base rates indicated that the base rates had been thoroughly processed. On control problems where base rates and description did not conflict this was not the case. Results suggest that whereas the popular characterization of conflict detection as an actively experienced struggle can be questioned there is nevertheless evidence for Sloman's and Epstein's basic claim about the flawless operation of the monitoring. Whenever the base rates and description disagree people will detect this conflict and consequently redirect attention towards a deeper processing of the base rates. Implications for the dual process framework and the rationality debate are discussed.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

The recognition heuristic: a review of theory and tests.

PubMed

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).

Cognitive load during route selection increases reliance on spatial heuristics.

PubMed

Brunyé, Tad T; Martis, Shaina B; Taylor, Holly A

2018-05-01

Planning routes from maps involves perceiving the symbolic environment, identifying alternate routes and applying explicit strategies and implicit heuristics to select an option. Two implicit heuristics have received considerable attention, the southern route preference and initial segment strategy. This study tested a prediction from decision-making theory that increasing cognitive load during route planning will increase reliance on these heuristics. In two experiments, participants planned routes while under conditions of minimal (0-back) or high (2-back) working memory load. In Experiment 1, we examined how memory load impacts the southern route heuristic. In Experiment 2, we examined how memory load impacts the initial segment heuristic. Results replicated earlier results demonstrating a southern route preference (Experiment 1) and initial segment strategy (Experiment 2) and further demonstrated that evidence for heuristic reliance is more likely under conditions of concurrent working memory load. Furthermore, the extent to which participants maintained efficient route selection latencies in the 2-back condition predicted the magnitude of this effect. Together, results demonstrate that working memory load increases the application of heuristics during spatial decision making, particularly when participants attempt to maintain quick decisions while managing concurrent task demands.

Ozone decomposition

PubMed Central

Batakliev, Todor; Georgiev, Vladimir; Anachkov, Metody; Rakovsky, Slavcho

2014-01-01

Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers). Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates. PMID:26109880

Minimizing makespan in a two-stage flow shop with parallel batch-processing machines and re-entrant jobs

NASA Astrophysics Data System (ADS)

Huang, J. D.; Liu, J. J.; Chen, Q. X.; Mao, N.

2017-06-01

Against a background of heat-treatment operations in mould manufacturing, a two-stage flow-shop scheduling problem is described for minimizing makespan with parallel batch-processing machines and re-entrant jobs. The weights and release dates of jobs are non-identical, but job processing times are equal. A mixed-integer linear programming model is developed and tested with small-scale scenarios. Given that the problem is NP hard, three heuristic construction methods with polynomial complexity are proposed. The worst case of the new constructive heuristic is analysed in detail. A method for computing lower bounds is proposed to test heuristic performance. Heuristic efficiency is tested with sets of scenarios. Compared with the two improved heuristics, the performance of the new constructive heuristic is superior.

Heuristic Diagrams as a Tool to Teach History of Science

NASA Astrophysics Data System (ADS)

Chamizo, José A.

2012-05-01

The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The left side originally related in Gowin's Vee with philosophies, theories, models, laws or regularities now agrees with Toulmin's concepts (language, models as representation techniques and application procedures). Mexican science teachers without experience in science education research used the heuristic diagram to learn about the history of chemistry considering also in the left side two different historical times: past and present. Through a semantic differential scale teachers' attitude to the heuristic diagram was evaluated and its usefulness was demonstrated.

The E-health Literacy Demands of Australia's My Health Record: A Heuristic Evaluation of Usability

PubMed Central

Walsh, Louisa; Hemsley, Bronwyn; Allan, Meredith; Adams, Natalie; Balandin, Susan; Georgiou, Andrew; Higgins, Isabel; McCarthy, Shaun; Hill, Sophie

2017-01-01

Background My Health Record is Australia's electronic personal health record system, which was introduced in July 2012. As of August 2017, approximately 21 percent of Australia's total population was registered to use My Health Record. Internationally, usability issues have been shown to negatively influence the uptake and use of electronic health record systems, and this scenario may particularly affect people who have low e-health literacy. It is likely that usability issues are negatively affecting the uptake and use of My Health Record in Australia. Objective To identify potential e-health literacy–related usability issues within My Health Record through a heuristic evaluation method. Methods Between September 14 and October 12, 2016, three of the authors conducted a heuristic evaluation of the two consumer-facing components of My Health Record—the information website and the electronic health record itself. These two components were evaluated against two sets of heuristics—the Health Literacy Online checklist and the Monkman Heuristics. The Health Literacy Online checklist and Monkman Heuristics are evidence-based checklists of web design elements with a focus on design for audiences with low health literacy. During this heuristic evaluation, the investigators individually navigated through the consumer-facing components of My Health Record, recording instances where the My Health Record did not conform to the checklist criteria. After the individual evaluations were completed, the investigators conferred and aggregated their results. From this process, a list of usability violations was constructed. Results When evaluated against the Health Literacy Online Checklist, the information website demonstrated violations in 12 of 35 criteria, and the electronic health record demonstrated violations in 16 of 35 criteria. When evaluated against the Monkman Heuristics, the information website demonstrated violations in 7 of 11 criteria, and the electronic health record demonstrated violations in 9 of 11 criteria. The identified violations included usability issues with the reading levels used within My Health Record, the graphic design elements, the layout of web pages, and a lack of images and audiovisual tools to support learning. Other important usability issues included a lack of translated resources, difficulty using accessibility tools, and complexity of the registration processes. Conclusion My Health Record is an important piece of technology that has the potential to facilitate better communication between consumers and their health providers. However, this heuristic evaluation demonstrated that many usability-related elements of My Health Record cater poorly to users at risk of having low e-health literacy. Usability issues have been identified as an important barrier to use of personal health records internationally, and the findings of this heuristic evaluation demonstrate that usability issues may be substantial barriers to the uptake and use of My Health Record. PMID:29118683

The design and implementation of signal decomposition system of CL multi-wavelet transform based on DSP builder

NASA Astrophysics Data System (ADS)

Huang, Yan; Wang, Zhihui

2015-12-01

With the development of FPGA, DSP Builder is widely applied to design system-level algorithms. The algorithm of CL multi-wavelet is more advanced and effective than scalar wavelets in processing signal decomposition. Thus, a system of CL multi-wavelet based on DSP Builder is designed for the first time in this paper. The system mainly contains three parts: a pre-filtering subsystem, a one-level decomposition subsystem and a two-level decomposition subsystem. It can be converted into hardware language VHDL by the Signal Complier block that can be used in Quartus II. After analyzing the energy indicator, it shows that this system outperforms Daubenchies wavelet in signal decomposition. Furthermore, it has proved to be suitable for the implementation of signal fusion based on SoPC hardware, and it will become a solid foundation in this new field.

Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice.

PubMed

Riva, Silvia; Monti, Marco; Antonietti, Alessandro

2011-01-01

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. 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. 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. 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. 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 for current medical education, which has to prepare competent health specialists to orientate and support the choices of their patients.

Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice

PubMed Central

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 for current medical education, which has to prepare competent health specialists to orientate and support the choices of their patients. PMID:23745077

PathEdEx – Uncovering High-explanatory Visual Diagnostics Heuristics Using Digital Pathology and Multiscale Gaze Data

PubMed Central

Shin, Dmitriy; Kovalenko, Mikhail; Ersoy, Ilker; Li, Yu; Doll, Donald; Shyu, Chi-Ren; Hammer, Richard

2017-01-01

Background: Visual heuristics of pathology diagnosis is a largely unexplored area where reported studies only provided a qualitative insight into the subject. Uncovering and quantifying pathology visual and nonvisual diagnostic patterns have great potential to improve clinical outcomes and avoid diagnostic pitfalls. Methods: Here, we present PathEdEx, an informatics computational framework that incorporates whole-slide digital pathology imaging with multiscale gaze-tracking technology to create web-based interactive pathology educational atlases and to datamine visual and nonvisual diagnostic heuristics. Results: We demonstrate the capabilities of PathEdEx for mining visual and nonvisual diagnostic heuristics using the first PathEdEx volume of a hematopathology atlas. We conducted a quantitative study on the time dynamics of zooming and panning operations utilized by experts and novices to come to the correct diagnosis. We then performed association rule mining to determine sets of diagnostic factors that consistently result in a correct diagnosis, and studied differences in diagnostic strategies across different levels of pathology expertise using Markov chain (MC) modeling and MC Monte Carlo simulations. To perform these studies, we translated raw gaze points to high-explanatory semantic labels that represent pathology diagnostic clues. Therefore, the outcome of these studies is readily transformed into narrative descriptors for direct use in pathology education and practice. Conclusion: PathEdEx framework can be used to capture best practices of pathology visual and nonvisual diagnostic heuristics that can be passed over to the next generation of pathologists and have potential to streamline implementation of precision diagnostics in precision medicine settings. PMID:28828200

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.

PathEdEx - Uncovering High-explanatory Visual Diagnostics Heuristics Using Digital Pathology and Multiscale Gaze Data.

PubMed

Shin, Dmitriy; Kovalenko, Mikhail; Ersoy, Ilker; Li, Yu; Doll, Donald; Shyu, Chi-Ren; Hammer, Richard

2017-01-01

Visual heuristics of pathology diagnosis is a largely unexplored area where reported studies only provided a qualitative insight into the subject. Uncovering and quantifying pathology visual and nonvisual diagnostic patterns have great potential to improve clinical outcomes and avoid diagnostic pitfalls. Here, we present PathEdEx, an informatics computational framework that incorporates whole-slide digital pathology imaging with multiscale gaze-tracking technology to create web-based interactive pathology educational atlases and to datamine visual and nonvisual diagnostic heuristics. We demonstrate the capabilities of PathEdEx for mining visual and nonvisual diagnostic heuristics using the first PathEdEx volume of a hematopathology atlas. We conducted a quantitative study on the time dynamics of zooming and panning operations utilized by experts and novices to come to the correct diagnosis. We then performed association rule mining to determine sets of diagnostic factors that consistently result in a correct diagnosis, and studied differences in diagnostic strategies across different levels of pathology expertise using Markov chain (MC) modeling and MC Monte Carlo simulations. To perform these studies, we translated raw gaze points to high-explanatory semantic labels that represent pathology diagnostic clues. Therefore, the outcome of these studies is readily transformed into narrative descriptors for direct use in pathology education and practice. PathEdEx framework can be used to capture best practices of pathology visual and nonvisual diagnostic heuristics that can be passed over to the next generation of pathologists and have potential to streamline implementation of precision diagnostics in precision medicine settings.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

Automating the packing heuristic design process with genetic programming.

PubMed

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.

Optimism in the face of uncertainty supported by a statistically-designed multi-armed bandit algorithm.

PubMed

Kamiura, Moto; Sano, Kohei

2017-10-01

The principle of optimism in the face of uncertainty is known as a heuristic in sequential decision-making problems. Overtaking method based on this principle is an effective algorithm to solve multi-armed bandit problems. It was defined by a set of some heuristic patterns of the formulation in the previous study. The objective of the present paper is to redefine the value functions of Overtaking method and to unify the formulation of them. The unified Overtaking method is associated with upper bounds of confidence intervals of expected rewards on statistics. The unification of the formulation enhances the universality of Overtaking method. Consequently we newly obtain Overtaking method for the exponentially distributed rewards, numerically analyze it, and show that it outperforms UCB algorithm on average. The present study suggests that the principle of optimism in the face of uncertainty should be regarded as the statistics-based consequence of the law of large numbers for the sample mean of rewards and estimation of upper bounds of expected rewards, rather than as a heuristic, in the context of multi-armed bandit problems. Copyright © 2017 Elsevier B.V. All rights reserved.

The Recognition Heuristic: A Review of Theory and Tests

PubMed Central

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

Heuristic Bayesian segmentation for discovery of coexpressed genes within genomic regions.

PubMed

Pehkonen, Petri; Wong, Garry; Törönen, Petri

2010-01-01

Segmentation aims to separate homogeneous areas from the sequential data, and plays a central role in data mining. It has applications ranging from finance to molecular biology, where bioinformatics tasks such as genome data analysis are active application fields. In this paper, we present a novel application of segmentation in locating genomic regions with coexpressed genes. We aim at automated discovery of such regions without requirement for user-given parameters. In order to perform the segmentation within a reasonable time, we use heuristics. Most of the heuristic segmentation algorithms require some decision on the number of segments. This is usually accomplished by using asymptotic model selection methods like the Bayesian information criterion. Such methods are based on some simplification, which can limit their usage. In this paper, we propose a Bayesian model selection to choose the most proper result from heuristic segmentation. Our Bayesian model presents a simple prior for the segmentation solutions with various segment numbers and a modified Dirichlet prior for modeling multinomial data. We show with various artificial data sets in our benchmark system that our model selection criterion has the best overall performance. The application of our method in yeast cell-cycle gene expression data reveals potential active and passive regions of the genome.

Recipient design in human communication: simple heuristics or perspective taking?

PubMed

Blokpoel, Mark; van Kesteren, Marlieke; Stolk, Arjen; Haselager, Pim; Toni, Ivan; van Rooij, Iris

2012-01-01

Humans have a remarkable capacity for tuning their communicative behaviors to different addressees, a phenomenon also known as recipient design. It remains unclear how this tuning of communicative behavior is implemented during live human interactions. Classical theories of communication postulate that recipient design involves perspective taking, i.e., the communicator selects her behavior based on her hypotheses about beliefs and knowledge of the recipient. More recently, researchers have argued that perspective taking is computationally too costly to be a plausible mechanism in everyday human communication. These researchers propose that computationally simple mechanisms, or heuristics, are exploited to perform recipient design. Such heuristics may be able to adapt communicative behavior to an addressee with no consideration for the addressee's beliefs and knowledge. To test whether the simpler of the two mechanisms is sufficient for explaining the "how" of recipient design we studied communicators' behaviors in the context of a non-verbal communicative task (the Tacit Communication Game, TCG). We found that the specificity of the observed trial-by-trial adjustments made by communicators is parsimoniously explained by perspective taking, but not by simple heuristics. This finding is important as it suggests that humans do have a computationally efficient way of taking beliefs and knowledge of a recipient into account.

Recipient design in human communication: simple heuristics or perspective taking?

PubMed Central

Blokpoel, Mark; van Kesteren, Marlieke; Stolk, Arjen; Haselager, Pim; Toni, Ivan; van Rooij, Iris

2012-01-01

Humans have a remarkable capacity for tuning their communicative behaviors to different addressees, a phenomenon also known as recipient design. It remains unclear how this tuning of communicative behavior is implemented during live human interactions. Classical theories of communication postulate that recipient design involves perspective taking, i.e., the communicator selects her behavior based on her hypotheses about beliefs and knowledge of the recipient. More recently, researchers have argued that perspective taking is computationally too costly to be a plausible mechanism in everyday human communication. These researchers propose that computationally simple mechanisms, or heuristics, are exploited to perform recipient design. Such heuristics may be able to adapt communicative behavior to an addressee with no consideration for the addressee's beliefs and knowledge. To test whether the simpler of the two mechanisms is sufficient for explaining the “how” of recipient design we studied communicators' behaviors in the context of a non-verbal communicative task (the Tacit Communication Game, TCG). We found that the specificity of the observed trial-by-trial adjustments made by communicators is parsimoniously explained by perspective taking, but not by simple heuristics. This finding is important as it suggests that humans do have a computationally efficient way of taking beliefs and knowledge of a recipient into account. PMID:23055960

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

NASA Astrophysics Data System (ADS)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

Hybrid glowworm swarm optimization for task scheduling in the cloud environment

NASA Astrophysics Data System (ADS)

Zhou, Jing; Dong, Shoubin

2018-06-01

In recent years many heuristic algorithms have been proposed to solve task scheduling problems in the cloud environment owing to their optimization capability. This article proposes a hybrid glowworm swarm optimization (HGSO) based on glowworm swarm optimization (GSO), which uses a technique of evolutionary computation, a strategy of quantum behaviour based on the principle of neighbourhood, offspring production and random walk, to achieve more efficient scheduling with reasonable scheduling costs. The proposed HGSO reduces the redundant computation and the dependence on the initialization of GSO, accelerates the convergence and more easily escapes from local optima. The conducted experiments and statistical analysis showed that in most cases the proposed HGSO algorithm outperformed previous heuristic algorithms to deal with independent tasks.

Money earlier or later? Simple heuristics explain intertemporal choices better than delay discounting does.

PubMed

Ericson, Keith M Marzilli; White, John Myles; Laibson, David; Cohen, Jonathan D

2015-06-01

Heuristic models have been proposed for many domains involving choice. We conducted an out-of-sample, cross-validated comparison of heuristic models of intertemporal choice (which can account for many of the known intertemporal choice anomalies) and discounting models. Heuristic models outperformed traditional utility-discounting models, including models of exponential and hyperbolic discounting. The best-performing models predicted choices by using a weighted average of absolute differences and relative percentage differences of the attributes of the goods in a choice set. We concluded that heuristic models explain time-money trade-off choices in experiments better than do utility-discounting models. © The Author(s) 2015.

Money Earlier or Later? Simple Heuristics Explain Intertemporal Choices Better than Delay Discounting1

PubMed Central

Marzilli Ericson, Keith M.; White, John Myles; Laibson, David; Cohen, Jonathan D.

2015-01-01

Heuristic models have been proposed for many domains of choice. We compare heuristic models of intertemporal choice, which can account for many of the known intertemporal choice anomalies, to discounting models. We conduct an out-of-sample, cross-validated comparison of intertemporal choice models. Heuristic models outperform traditional utility discounting models, including models of exponential and hyperbolic discounting. The best performing models predict choices by using a weighted average of absolute differences and relative (percentage) differences of the attributes of the goods in a choice set. We conclude that heuristic models explain time-money tradeoff choices in experiments better than utility discounting models. PMID:25911124

ENVIRONMENTAL ASSESSMENT OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS

EPA Science Inventory

This report summarizes laboratory-scale, pilot-scale, and field performance data on BCD (Base Catalyzed Decomposition) and technology, collected to date by various governmental, academic, and private organizations.

Heuristics and Problem Solving.

ERIC Educational Resources Information Center

Abel, Charles F.

2003-01-01

Defines heuristics as cognitive "rules of thumb" that can help problem solvers work more efficiently and effectively. Professors can use a heuristic model of problem solving to guide students in all disciplines through the steps of problem-solving. (SWM)

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

PubMed Central

Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun

2017-01-01

This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank-(L1,L2,·) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method. PMID:28448431

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array.

PubMed

Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun

2017-04-27

This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- ( L 1 , L 2 , · ) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method.

An Intelligent Pattern Recognition System Based on Neural Network and Wavelet Decomposition for Interpretation of Heart Sounds

DTIC Science & Technology

2001-10-25

wavelet decomposition of signals and classification using neural network. Inputs to the system are the heart sound signals acquired by a stethoscope in a...Proceedings. pp. 415–418, 1990. [3] G. Ergun, “An intelligent diagnostic system for interpretation of arterpartum fetal heart rate tracings based on ANNs and...AN INTELLIGENT PATTERN RECOGNITION SYSTEM BASED ON NEURAL NETWORK AND WAVELET DECOMPOSITION FOR INTERPRETATION OF HEART SOUNDS I. TURKOGLU1, A

An adaptive toolbox approach to the route to expertise in sport.

PubMed

de Oliveira, Rita F; Lobinger, Babett H; Raab, Markus

2014-01-01

Expertise is characterized by fast decision-making which is highly adaptive to new situations. Here we propose that athletes use a toolbox of heuristics which they develop on their route to expertise. The development of heuristics occurs within the context of the athletes' natural abilities, past experiences, developed skills, and situational context, but does not pertain to any of these factors separately. This is a novel approach because it integrates separate factors into a comprehensive heuristic description. The novelty of this approach lies within the integration of separate factors determining expertise into a comprehensive heuristic description. It is our contention that talent identification methods and talent development models should therefore be geared toward the assessment and development of specific heuristics. Specifically, in addition to identifying and developing separate natural abilities and skills as per usual, heuristics should be identified and developed. The application of heuristics to talent and expertise models can bring the field one step away from dichotomized models of nature and nurture toward a comprehensive approach to the route to expertise.

Heuristic thinking makes a chemist smart.

PubMed

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.

An adaptive toolbox approach to the route to expertise in sport

PubMed Central

de Oliveira, Rita F.; Lobinger, Babett H.; Raab, Markus

2014-01-01

Expertise is characterized by fast decision-making which is highly adaptive to new situations. Here we propose that athletes use a toolbox of heuristics which they develop on their route to expertise. The development of heuristics occurs within the context of the athletes’ natural abilities, past experiences, developed skills, and situational context, but does not pertain to any of these factors separately. This is a novel approach because it integrates separate factors into a comprehensive heuristic description. The novelty of this approach lies within the integration of separate factors determining expertise into a comprehensive heuristic description. It is our contention that talent identification methods and talent development models should therefore be geared toward the assessment and development of specific heuristics. Specifically, in addition to identifying and developing separate natural abilities and skills as per usual, heuristics should be identified and developed. The application of heuristics to talent and expertise models can bring the field one step away from dichotomized models of nature and nurture toward a comprehensive approach to the route to expertise. PMID:25071673

Generation of structural topologies using efficient technique based on sorted compliances

NASA Astrophysics Data System (ADS)

Mazur, Monika; Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2018-01-01

Topology optimization, although well recognized is still widely developed. It has gained recently more attention since large computational ability become available for designers. This process is stimulated simultaneously by variety of emerging, innovative optimization methods. It is observed that traditional gradient-based mathematical programming algorithms, in many cases, are replaced by novel and e cient heuristic methods inspired by biological, chemical or physical phenomena. These methods become useful tools for structural optimization because of their versatility and easy numerical implementation. In this paper engineering implementation of a novel heuristic algorithm for minimum compliance topology optimization is discussed. The performance of the topology generator is based on implementation of a special function utilizing information of compliance distribution within the design space. With a view to cope with engineering problems the algorithm has been combined with structural analysis system Ansys.

Heuristics Reasoning in Diagnostic Judgment.

ERIC Educational Resources Information Center

O'Neill, Eileen S.

1995-01-01

Describes three heuristics--short-cut mental strategies that streamline information--relevant to diagnostic reasoning: accessibility, similarity, and anchoring and adjustment. Analyzes factors thought to influence heuristic reasoning and presents interventions to be tested for nursing practice and education. (JOW)

Fluency heuristic: a model of how the mind exploits a by-product of information retrieval.

PubMed

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. (c) 2008 APA, all rights reserved.

Steganography based on pixel intensity value decomposition

NASA Astrophysics Data System (ADS)

Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

2014-05-01

This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

Aggregate age-at-marriage patterns from individual mate-search heuristics.

PubMed

Todd, Peter M; Billari, Francesco C; Simão, Jorge

2005-08-01

The distribution of age at first marriage shows well-known strong regularities across many countries and recent historical periods. We accounted for these patterns by developing agent-based models that simulate the aggregate behavior of individuals who are searching for marriage partners. Past models assumed fully rational agents with complete knowledge of the marriage market; our simulated agents used psychologically plausible simple heuristic mate search rules that adjust aspiration levels on the basis of a sequence of encounters with potential partners. Substantial individual variation must be included in the models to account for the demographically observed age-at-marriage patterns.

Scope of Various Random Number Generators in ant System Approach for TSP

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2007-01-01

Experimented on heuristic, based on an ant system approach for traveling salesman problem, are several quasi- and pseudo-random number generators. This experiment is to explore if any particular generator is most desirable. Such an experiment on large samples has the potential to rank the performance of the generators for the foregoing heuristic. This is mainly to seek an answer to the controversial issue "which generator is the best in terms of quality of the result (accuracy) as well as cost of producing the result (time/computational complexity) in a probabilistic/statistical sense."

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

A New Approach of evaluating the damage in simply-supported reinforced concrete beam by Local mean decomposition (LMD)

NASA Astrophysics Data System (ADS)

Zhang, Xuebing; Liu, Ning; Xi, Jiaxin; Zhang, Yunqi; Zhang, Wenchun; Yang, Peipei

2017-08-01

How to analyze the nonstationary response signals and obtain vibration characters is extremely important in the vibration-based structural diagnosis methods. In this work, we introduce a more reasonable time-frequency decomposition method termed local mean decomposition (LMD) to instead the widely-used empirical mode decomposition (EMD). By employing the LMD method, one can derive a group of component signals, each of which is more stationary, and then analyze the vibration state and make the assessment of structural damage of a construction or building. We illustrated the effectiveness of LMD by a synthetic data and an experimental data recorded in a simply-supported reinforced concrete beam. Then based on the decomposition results, an elementary method of damage diagnosis was proposed.

Applying heuristic evaluation to improve the usability of a telemedicine system.

PubMed

Tang, Zhihua; Johnson, Todd R; Tindall, R Douglas; Zhang, Jiajie

2006-02-01

The development of a telemedicine system should not only take advantage of technological advances but also pay close attention to users and the human issues involved. In this paper we examine the utility of heuristic evaluation in improving the usability of a digital emergency medical services (EMS) system equipped on an ambulance. The digital EMS system used advanced communication technologies to help remotely located trauma specialists gain access to patient data in real-time and direct life-saving measures in a timely fashion. To improve its usability, three experts inspected prototypes of the system according to 14 software usability heuristics. The analyses revealed information on the prevalence, severity, and nature of heuristic violations in the user interface design. The results were subsequently utilized to guide the iterative software design process. A comparison between two consecutive prototypes showed that the second design had only half as many usability violations as the first prototype and had considerable improvement in a number of usability heuristic categories. The validity of heuristic evaluation was examined in an ethnographic study of paramedics using a prototype of the system in their work environment. Users' task performances partially verified heuristic evaluation results. However, they also revealed problems that were not identified in heuristic evaluation but only became prominent during field observation. In conclusion, we argue that usability should be given high priority in the development of a telemedicine system, and that heuristic evaluation can be an effective and efficient way to identify usability problems in the early stage of software development.

Climate adaptation heuristics and the science/policy divide

DOE PAGES

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

Water/cortical bone decomposition: A new approach in dual energy CT imaging for bone marrow oedema detection. A feasibility study.

PubMed

Biondi, M; Vanzi, E; De Otto, G; Banci Buonamici, F; Belmonte, G M; Mazzoni, L N; Guasti, A; Carbone, S F; Mazzei, M A; La Penna, A; Foderà, E; Guerreri, D; Maiolino, A; Volterrani, L

2016-12-01

Many studies aimed at validating the application of Dual Energy Computed Tomography (DECT) in clinical practice where conventional CT is not exhaustive. An example is given by bone marrow oedema detection, in which DECT based on water/calcium (W/Ca) decomposition was applied. In this paper a new DECT approach, based on water/cortical bone (W/CB) decomposition, was investigated. Eight patients suffering from marrow oedema were scanned with MRI and DECT. Two-materials density decomposition was performed in ROIs corresponding to normal bone marrow and oedema. These regions were drawn on DECT images using MRI informations. Both W/Ca and W/CB were considered as material basis. Scatter plots of W/Ca and W/CB concentrations were made for each ROI in order to evaluate if oedema could be distinguished from normal bone marrow. Thresholds were defined on the scatter plots in order to produce DECT images where oedema regions were highlighted through color maps. The agreement between these images and MR was scored by two expert radiologists. For all the patients, the best scores were obtained using W/CB density decomposition. In all cases, DECT color map images based on W/CB decomposition showed better agreement with MR in bone marrow oedema identification with respect to W/Ca decomposition. This result encourages further studies in order to evaluate if DECT based on W/CB decomposition could be an alternative technique to MR, which would be important when short scanning duration is relevant, as in the case of aged or traumatic patients. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

PubMed

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.

A manpower scheduling heuristic for aircraft maintenance application

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Sze, Jeeu-Fong; Chiew, Kang-Leng

2012-09-01

This research studies a manpower scheduling for aircraft maintenance, focusing on in-flight food loading operation. A group of loading teams with flexible shifts is required to deliver and upload packaged meals from the ground kitchen to aircrafts in multiple trips. All aircrafts must be served within predefined time windows. The scheduling process takes into account of various constraints such as meal break allocation, multi-trip traveling and food exposure time limit. Considering the aircrafts movement and predefined maximum working hours for each loading team, the main objective of this study is to form an efficient roster by assigning a minimum number of loading teams to the aircrafts. We proposed an insertion based heuristic to generate the solutions in a short period of time for large instances. This proposed algorithm is implemented in various stages for constructing trips due to the presence of numerous constraints. The robustness and efficiency of the algorithm is demonstrated in computational results. The results show that the insertion heuristic more efficiently outperforms the company's current practice.

Multi-Criteria Optimization of the Deployment of a Grid for Rural Electrification Based on a Heuristic Method

NASA Astrophysics Data System (ADS)

Ortiz-Matos, L.; Aguila-Tellez, A.; Hincapié-Reyes, R. C.; González-Sanchez, J. W.

2017-07-01

In order to design electrification systems, recent mathematical models solve the problem of location, type of electrification components, and the design of possible distribution microgrids. However, due to the amount of points to be electrified increases, the solution to these models require high computational times, thereby becoming unviable practice models. This study posed a new heuristic method for the electrification of rural areas in order to solve the problem. This heuristic algorithm presents the deployment of rural electrification microgrids in the world, by finding routes for optimal placement lines and transformers in transmission and distribution microgrids. The challenge is to obtain a display with equity in losses, considering the capacity constraints of the devices and topology of the land at minimal economic cost. An optimal scenario ensures the electrification of all neighbourhoods to a minimum investment cost in terms of the distance between electric conductors and the amount of transformation devices.

Analytic and heuristic processing influences on adolescent reasoning and decision-making.

PubMed

Klaczynski, P A

2001-01-01

The normative/descriptive gap is the discrepancy between actual reasoning and traditional standards for reasoning. The relationship between age and the normative/descriptive gap was examined by presenting adolescents with a battery of reasoning and decision-making tasks. Middle adolescents (N = 76) performed closer to normative ideals than early adolescents (N = 66), although the normative/descriptive gap was large for both groups. Correlational analyses revealed that (1) normative responses correlated positively with each other, (2) nonnormative responses were positively interrelated, and (3) normative and nonnormative responses were largely independent. Factor analyses suggested that performance was based on two processing systems. The "analytic" system operates on "decontextualized" task representations and underlies conscious, computational reasoning. The "heuristic" system operates on "contextualized," content-laden representations and produces "cognitively cheap" responses that sometimes conflict with traditional norms. Analytic processing was more clearly linked to age and to intelligence than heuristic processing. Implications for cognitive development, the competence/performance issue, and rationality are discussed.

Spinal meningioma, aortic aneurysms and the missing link of observation: the anchoring heuristic approach.

PubMed

Floros, Nikolaos; Papadakis, Marios; Schelzig, Hubert; Oberhuber, Alexander

2018-03-10

Over the last three decades, the development of systematic and protocol-based algorithms, and advances in available diagnostic tests have become the indispensable parts of practising medicine. Naturally, despite the implementation of meticulous protocols involving diagnostic tests or even trials of empirical therapies, the cause of one's symptoms may still not be obvious. We herein report a case of chronic back pain, which took about 5 years to get accurately diagnosed. The case challenges the diagnostic assumptions and sets ground of discussion for the diagnostic reasoning pitfalls and heuristic biases that mislead the caring physicians and cost years of low quality of life to our patient. This case serves as an example of how anchoring heuristics can interfere in the diagnostic process of a complex and rare entity when combined with a concurrent potentially life-threatening condition. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH.

PubMed

Volk, Jochen; Herrmann, Torsten; Wüthrich, Kurt

2008-07-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

Robust Frequency-Domain Constrained Feedback Design via a Two-Stage Heuristic Approach.

PubMed

Li, Xianwei; Gao, Huijun

2015-10-01

Based on a two-stage heuristic method, this paper is concerned with the design of robust feedback controllers with restricted frequency-domain specifications (RFDSs) for uncertain linear discrete-time systems. Polytopic uncertainties are assumed to enter all the system matrices, while RFDSs are motivated by the fact that practical design specifications are often described in restricted finite frequency ranges. Dilated multipliers are first introduced to relax the generalized Kalman-Yakubovich-Popov lemma for output feedback controller synthesis and robust performance analysis. Then a two-stage approach to output feedback controller synthesis is proposed: at the first stage, a robust full-information (FI) controller is designed, which is used to construct a required output feedback controller at the second stage. To improve the solvability of the synthesis method, heuristic iterative algorithms are further formulated for exploring the feedback gain and optimizing the initial FI controller at the individual stage. The effectiveness of the proposed design method is finally demonstrated by the application to active control of suspension systems.

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Interpreting Quantifier Scope Ambiguity: Evidence of Heuristic First, Algorithmic Second Processing

PubMed Central

Dwivedi, Veena D.

2013-01-01

The present work suggests that sentence processing requires both heuristic and algorithmic processing streams, where the heuristic processing strategy precedes the algorithmic phase. This conclusion is based on three self-paced reading experiments in which the processing of two-sentence discourses was investigated, where context sentences exhibited quantifier scope ambiguity. Experiment 1 demonstrates that such sentences are processed in a shallow manner. Experiment 2 uses the same stimuli as Experiment 1 but adds questions to ensure deeper processing. Results indicate that reading times are consistent with a lexical-pragmatic interpretation of number associated with context sentences, but responses to questions are consistent with the algorithmic computation of quantifier scope. Experiment 3 shows the same pattern of results as Experiment 2, despite using stimuli with different lexical-pragmatic biases. These effects suggest that language processing can be superficial, and that deeper processing, which is sensitive to structure, only occurs if required. Implications for recent studies of quantifier scope ambiguity are discussed. PMID:24278439

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

NASA Astrophysics Data System (ADS)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN

EPA Science Inventory

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 ...

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

Artificial Intelligence Techniques: Applications for Courseware Development.

ERIC Educational Resources Information Center

Dear, Brian L.

1986-01-01

Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

Applying heuristic inquiry to nurse migration from the UK to Australia.

PubMed

Vafeas, Caroline; Hendricks, Joyce

2017-01-23

Background Heuristic inquiry is a research approach that improves understanding of the essence of an experience. This qualitative method relies on researchers' ability to discover and interpret their own experience while exploring those of others. Aim To present a discussion of heuristic inquiry's methodology and its application to the experience of nurse migration. Discussion The researcher's commitment to the research is central to heuristic inquiry. It is immersive, reflective, reiterative and a personally-affecting method of gathering knowledge. Researchers are acknowledged as the only people who can validate the findings of the research by exploring their own experiences while also examining those of others with the same experiences to truly understand the phenomena being researched. This paper presents the ways in which the heuristic process guides this discovery in relation to traditional research steps. Conclusion Heuristic inquiry is an appropriate method for exploring nurses' experiences of migration because nurse researchers can tell their own stories and it brings understanding of themselves and the phenomenon as experienced by others. Implications for practice Although not a popular method in nursing research, heuristic inquiry offers a depth of exploration and understanding that may not be revealed by other methods.

An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation

PubMed Central

Yan, Honghang; Deng, Fang; Sun, Jian; Chen, Jie

2014-01-01

In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition of N subparts and reduces the training time to 1N and memory cost to 1N, has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. PMID:25232912

Acid and alkali effects on the decomposition of HMX molecule: a computational study.

PubMed

Zhang, Chaoyang; Li, Yuzhen; Xiong, Ying; Wang, Xiaolin; Zhou, Mingfei

2011-11-03

The stored and wasted explosives are usually in an acid or alkali environment, leading to the importance of exploring the acid and alkali effects on the decomposition mechanism of explosives. The acid and alkali effects on the decomposition of HMX molecule in gaseous state and in aqueous solution at 298 K are studied using quantum chemistry and molecular force field calculations. The results show that both H(+) and OH(-) make the decomposition in gaseous state energetically favorable. However, the effect of H(+) is much different from that of OH(-) in aqueous solution: OH(-) can accelerate the decomposition but H(+) cannot. The difference is mainly caused by the large aqueous solvation energy difference between H(+) and OH(-). The results confirm that the dissociation of HMX is energetically favored only in the base solutions, in good agreement with previous HMX base hydrolysis experimental observations. The different acid and alkali effects on the HMX decomposition are dominated by the large aqueous solvation energy difference between H(+) and OH(-).

A knowledge-based tool for multilevel decomposition of a complex design problem

NASA Technical Reports Server (NTRS)

Rogers, James L.

1989-01-01

Although much work has been done in applying artificial intelligence (AI) tools and techniques to problems in different engineering disciplines, only recently has the application of these tools begun to spread to the decomposition of complex design problems. A new tool based on AI techniques has been developed to implement a decomposition scheme suitable for multilevel optimization and display of data in an N x N matrix format.

Smooth Constrained Heuristic Optimization of a Combinatorial Chemical Space

DTIC Science & Technology

2015-05-01

ARL-TR-7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...

Heuristic approach to Satellite Range Scheduling with Bounds using Lagrangian Relaxation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Nathanael J. K.; Arguello, Bryan; Nozick, Linda Karen

This paper focuses on scheduling antennas to track satellites using a heuristic method. In order to validate the performance of the heuristic, bounds are developed using Lagrangian relaxation. The performance of the algorithm is established using several illustrative problems.

Heuristic decision-making about research participation in children with cystic fibrosis.

PubMed

Christofides, Emily; Dobson, Jennifer A; Solomon, Melinda; Waters, Valerie; O'Doherty, Kieran C

2016-08-01

Traditional perspectives on informed consent assume that when faced with decisions about whether to participate in research, individuals behave according to principles of classical rationality, taking into account all available information to weigh risks and benefits to come to a decision that is optimal for them. However, theoretical and empirical research in psychology suggests that people may not make decisions in this way. Less is known about decision-making processes as they pertain to participating in biomedical research, particularly when the participants are children. We sought to better understand research decision processes especially in children who tend to participate extensively in research due to chronic illness. To learn more about children's decision-making in this context, we interviewed 19 young patients with cystic fibrosis (male n = 7; female n = 12) aged 8-18 years (M = 13 years) at a children's hospital in Canada between April and August 2013. We found that participants generally had a default approach to participation decisions, which they attributed to their parents' attitudes to research, experiences of having grown up participating in research, trusting the researchers, and wanting to help. Most of our participants made the decision to participate in research based on a heuristic with a baseline to say "yes", subject to change based on aspects of the research or particular preferences. In particular, concerns with the procedure, unwillingness to talk about cystic fibrosis, logistical challenges, and perceptions of risk all influenced the decision, as did the perceived importance or personal relevance of the research. Our study illustrates that rather than conducting risk/benefit analyses, participants tended to adopt a heuristic-like approach, consistent with decision theories that view heuristic decision-making as ecologically rational. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Ambivalence--a key concept in gerontology? Elements of heuristics exemplified by identity formation in old age].

PubMed

Lüscher, Kurt; Haller, Miriam

2016-01-01

Ambivalence is a widely used concept in gerontology, mostly used in the common sense meaning. We propose that an elaborated notion based on the historical and systematic analysis, reveals important theoretical, methodological and practical potentials of the idea of ambivalence for the study of aging. We exemplify this view by proposing a heuristic perspective for the analysis of processes to constitute and reconstitute identities in old age using a model based on a multidimensional understanding of ambivalence. Ambivalence is defined as referring to the experiences of vacillating between polar contradictions of feeling, thinking, wanting and social structures in the search for the sense and meaning of social relationships, facts and texts, which are important for unfolding and altering facets of the self and agency.

An iterative bidirectional heuristic placement algorithm for solving the two-dimensional knapsack packing problem

NASA Astrophysics Data System (ADS)

Shiangjen, Kanokwatt; Chaijaruwanich, Jeerayut; Srisujjalertwaja, Wijak; Unachak, Prakarn; Somhom, Samerkae

2018-02-01

This article presents an efficient heuristic placement algorithm, namely, a bidirectional heuristic placement, for solving the two-dimensional rectangular knapsack packing problem. The heuristic demonstrates ways to maximize space utilization by fitting the appropriate rectangle from both sides of the wall of the current residual space layer by layer. The iterative local search along with a shift strategy is developed and applied to the heuristic to balance the exploitation and exploration tasks in the solution space without the tuning of any parameters. The experimental results on many scales of packing problems show that this approach can produce high-quality solutions for most of the benchmark datasets, especially for large-scale problems, within a reasonable duration of computational time.

Cultural-based particle swarm for dynamic optimisation problems

NASA Astrophysics Data System (ADS)

Daneshyari, Moayed; Yen, Gary G.

2012-07-01

Many practical optimisation problems are with the existence of uncertainties, among which a significant number belong to the dynamic optimisation problem (DOP) category in which the fitness function changes through time. In this study, we propose the cultural-based particle swarm optimisation (PSO) to solve DOP problems. A cultural framework is adopted incorporating the required information from the PSO into five sections of the belief space, namely situational, temporal, domain, normative and spatial knowledge. The stored information will be adopted to detect the changes in the environment and assists response to the change through a diversity-based repulsion among particles and migration among swarms in the population space, and also helps in selecting the leading particles in three different levels, personal, swarm and global levels. Comparison of the proposed heuristics over several difficult dynamic benchmark problems demonstrates the better or equal performance with respect to most of other selected state-of-the-art dynamic PSO heuristics.

Direct heuristic dynamic programming for damping oscillations in a large power system.

PubMed

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

A Symposium on Heuristic Teaching.

ERIC Educational Resources Information Center

Snow, Richard E., Ed.

In order to explore diverse philosophical, psychological, and pedagogical views on the concept of heuristic teaching and the question whether basic teaching skills can be "content free," a symposium on the subject of heuristic teaching was organized with resource papers being requested from scholars representing several disciplines and…

Study on the decomposition of trace benzene over V2O5-WO3 ...

EPA Pesticide Factsheets

Commercial and laboratory-prepared V2O5–WO3/TiO2-based catalysts with different compositions were tested for catalytic decomposition of chlorobenzene （ClBz） in simulated flue gas. Resonance enhanced multiphoton ionization-time of flight mass spectrometry (REMPI-TOFMS) was employed to measure real-time, trace concentrations of ClBz contained in the flue gas before and after the catalyst. The effects of various parameters, including vanadium content of the catalyst, the catalyst support, as well as the reaction temperature on decomposition of ClBz were investigated. The results showed that the ClBz decomposition efficiency was significantly enhanced when nano-TiO2 instead of conventional TiO2 was used as the catalyst support. No promotion effects were found in the ClBz decomposition process when the catalysts were wet-impregnated with CuO and CeO2. Tests with different concentrations (1,000, 500, and 100 ppb) of ClBz showed that ClBz-decomposition efficiency decreased with increasing concentration, unless active sites were plentiful. A comparison between ClBz and benzene decomposition on the V2O5–WO3/TiO2-based catalyst and the relative kinetics analysis showed that two different active sites were likely involved in the decomposition mechanism and the V=O and V-O-Ti groups may only work for the degradation of the phenyl group and the benzene ring rather than the C-Cl bond. V2O5-WO3/TiO2 based catalysts, that have been used for destruction of a wide variet

Heuristic errors in clinical reasoning.

PubMed

Rylander, Melanie; Guerrasio, Jeannette

2016-08-01

Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.

The power of simplicity: a fast-and-frugal heuristics approach to performance science.

PubMed

Raab, Markus; Gigerenzer, Gerd

2015-01-01

Performance science is a fairly new multidisciplinary field that integrates performance domains such as sports, medicine, business, and the arts. To give its many branches a structure and its research a direction, it requires a theoretical framework. We demonstrate the applications of this framework with examples from sport and medicine. Because performance science deals mainly with situations of uncertainty rather than known risks, the needed framework can be provided by the fast-and-frugal heuristics approach. According to this approach, experts learn to rely on heuristics in an adaptive way in order to make accurate decisions. We investigate the adaptive use of heuristics in three ways: the descriptive study of the heuristics in the cognitive "adaptive toolbox;" the prescriptive study of their "ecological rationality," that is, the characterization of the situations in which a given heuristic works; and the engineering study of "intuitive design," that is, the design of transparent aids for making better decisions.

The power of simplicity: a fast-and-frugal heuristics approach to performance science

PubMed Central

Raab, Markus; Gigerenzer, Gerd

2015-01-01

Performance science is a fairly new multidisciplinary field that integrates performance domains such as sports, medicine, business, and the arts. To give its many branches a structure and its research a direction, it requires a theoretical framework. We demonstrate the applications of this framework with examples from sport and medicine. Because performance science deals mainly with situations of uncertainty rather than known risks, the needed framework can be provided by the fast-and-frugal heuristics approach. According to this approach, experts learn to rely on heuristics in an adaptive way in order to make accurate decisions. We investigate the adaptive use of heuristics in three ways: the descriptive study of the heuristics in the cognitive “adaptive toolbox;” the prescriptive study of their “ecological rationality,” that is, the characterization of the situations in which a given heuristic works; and the engineering study of “intuitive design,” that is, the design of transparent aids for making better decisions. PMID:26579051

Hostile Work Environment: What Communication Administrators and Educators Can Learn from Communication-based Law.

ERIC Educational Resources Information Center

Newburger, Craig

2001-01-01

Presents a consideration of sexual harassment laws that are intended to underscore the variety of heuristic possibilities offered by inquiry into communication-based laws, for both communication administrators and educators. Concludes that communication administration, communication education, and evolving communication-based legal standards and…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preston, Benjamin L.; Mustelin, Johanna; Maloney, Megan C.

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

Internal Medicine residents use heuristics to estimate disease probability.

PubMed

Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin

2015-01-01

Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. We randomized 55 Internal Medicine residents to different versions of four clinical vignettes and asked them to estimate probabilities of target conditions. We manipulated the clinical data for each vignette to be consistent with either 1) using a representative heuristic, by adding non-discriminating prototypical clinical features of the target condition, or 2) using anchoring with adjustment heuristic, by providing a high or low anchor for the target condition. When presented with additional non-discriminating data the odds of diagnosing the target condition were increased (odds ratio (OR) 2.83, 95% confidence interval [1.30, 6.15], p = 0.009). Similarly, the odds of diagnosing the target condition were increased when a high anchor preceded the vignette (OR 2.04, [1.09, 3.81], p = 0.025). Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.

Synthesis Polarimetry Calibration

NASA Astrophysics Data System (ADS)

Moellenbrock, George

2017-10-01

Synthesis instrumental polarization calibration fundamentals for both linear (ALMA) and circular (EVLA) feed bases are reviewed, with special attention to the calibration heuristics supported in CASA. Practical problems affecting modern instruments are also discussed.

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.

Development a heuristic method to locate and allocate the medical centers to minimize the earthquake relief operation time.

PubMed

Aghamohammadi, Hossein; Saadi Mesgari, Mohammad; Molaei, Damoon; Aghamohammadi, Hasan

2013-01-01

Location-allocation is a combinatorial optimization problem, and is defined as Non deterministic Polynomial Hard (NP) hard optimization. Therefore, solution of such a problem should be shifted from exact to heuristic or Meta heuristic due to the complexity of the problem. Locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster management so that developing a proper method will reduce the time of relief operation and will consequently decrease the number of fatalities. This paper presents the development of a heuristic method based on two nested genetic algorithms to optimize this location allocation problem by using the abilities of Geographic Information System (GIS). In the proposed method, outer genetic algorithm is applied to the location part of the problem and inner genetic algorithm is used to optimize the resource allocation. The final outcome of implemented method includes the spatial location of new required medical centers. The method also calculates that how many of the injuries at each demanding point should be taken to any of the existing and new medical centers as well. The results of proposed method showed high performance of designed structure to solve a capacitated location-allocation problem that may arise in a disaster situation when injured people has to be taken to medical centers in a reasonable time.

Adaptive neuro-heuristic hybrid model for fruit peel defects detection.

PubMed

Woźniak, Marcin; Połap, Dawid

2018-02-01

Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the development of adaptive method based on fusion of proposed novel neural architecture and heuristic search into one co-working solution. We propose a developed neural network architecture that adapts to processed input co-working with heuristic method used to precisely detect areas of interest. Input images are first decomposed into segments. This is to make processing easier, since in smaller images (decomposed segments) developed Adaptive Artificial Neural Network (AANN) processes less information what makes numerical calculations more precise. For each segment a descriptor vector is composed to be presented to the proposed AANN architecture. Evaluation is run adaptively, where the developed AANN adapts to inputs and their features by composed architecture. After evaluation, selected segments are forwarded to heuristic search, which detects areas of interest. As a result the system returns the image with pixels located over peel damages. Presented experimental research results on the developed solution are discussed and compared with other commonly used methods to validate the efficacy and the impact of the proposed fusion in the system structure and training process on classification results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Abstract Mindsets Increase Believability of Spatially Distant Online Messages

PubMed Central

Sungur, Hande; Hartmann, Tilo; van Koningsbruggen, Guido M.

2016-01-01

Growing evidence from online credibility research reveals that online users rely on heuristic processes to evaluate the credibility of online information. The current paper, which is based on the construal level theory (CLT), proposes that congruency between the psychological distance of a stimulus and the way it is mentally construed can act as a heuristic for believability. According to CLT, psychologically close (e.g., spatially, temporally, socially) stimuli are represented concretely whereas psychologically distant stimuli are represented abstractly. The level of mental construals and the psychological distance of information have been shown to influence people’s truth judgments in offline contexts. This study tests whether congruency between the construal level of people’s mindsets (abstract vs. concrete) and the psychological distance implied in an online message (far vs. close) enhances message believability. By partially confirming CLT predictions, we found that believability of an online news item about a distant location increased when people maintained an abstract mindset rather than a concrete one. The effect of a concrete mindset on believability was not significant for the close psychological distance condition. Our findings provide initial evidence that congruency between the construal level of people’s mindsets and psychological distance cues in online messages can act as a heuristic for believability. We discuss the potential of applying the CLT framework to the growing literature on online cognitive heuristics in the area of online information credibility. PMID:27468272

The Probability Heuristics Model of Syllogistic Reasoning.

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

Early stage litter decomposition across biomes

Treesearch

Ika Djukic; Sebastian Kepfer-Rojas; Inger Kappel Schmidt; Klaus Steenberg Larsen; Claus Beier; Björn Berg; Kris Verheyen; Adriano Caliman; Alain Paquette; Alba Gutiérrez-Girón; Alberto Humber; Alejandro Valdecantos; Alessandro Petraglia; Heather Alexander; Algirdas Augustaitis; Amélie Saillard; Ana Carolina Ruiz Fernández; Ana I. Sousa; Ana I. Lillebø; Anderson da Rocha Gripp; André-Jean Francez; Andrea Fischer; Andreas Bohner; Andrey Malyshev; Andrijana Andrić; Andy Smith; Angela Stanisci; Anikó Seres; Anja Schmidt; Anna Avila; Anne Probst; Annie Ouin; Anzar A. Khuroo; Arne Verstraeten; Arely N. Palabral-Aguilera; Artur Stefanski; Aurora Gaxiola; Bart Muys; Bernard Bosman; Bernd Ahrends; Bill Parker; Birgit Sattler; Bo Yang; Bohdan Juráni; Brigitta Erschbamer; Carmen Eugenia Rodriguez Ortiz; Casper T. Christiansen; E. Carol Adair; Céline Meredieu; Cendrine Mony; Charles A. Nock; Chi-Ling Chen; Chiao-Ping Wang; Christel Baum; Christian Rixen; Christine Delire; Christophe Piscart; Christopher Andrews; Corinna Rebmann; Cristina Branquinho; Dana Polyanskaya; David Fuentes Delgado; Dirk Wundram; Diyaa Radeideh; Eduardo Ordóñez-Regil; Edward Crawford; Elena Preda; Elena Tropina; Elli Groner; Eric Lucot; Erzsébet Hornung; Esperança Gacia; Esther Lévesque; Evanilde Benedito; Evgeny A. Davydov; Evy Ampoorter; Fabio Padilha Bolzan; Felipe Varela; Ferdinand Kristöfel; Fernando T. Maestre; Florence Maunoury-Danger; Florian Hofhansl; Florian Kitz; Flurin Sutter; Francisco Cuesta; Francisco de Almeida Lobo; Franco Leandro de Souza; Frank Berninger; Franz Zehetner; Georg Wohlfahrt; George Vourlitis; Geovana Carreño-Rocabado; Gina Arena; Gisele Daiane Pinha; Grizelle González; Guylaine Canut; Hanna Lee; Hans Verbeeck; Harald Auge; Harald Pauli; Hassan Bismarck Nacro; Héctor A. Bahamonde; Heike Feldhaar; Heinke Jäger; Helena C. Serrano; Hélène Verheyden; Helge Bruelheide; Henning Meesenburg; Hermann Jungkunst; Hervé Jactel; Hideaki Shibata; Hiroko Kurokawa; Hugo López Rosas; Hugo L. Rojas Villalobos; Ian Yesilonis; Inara Melece; Inge Van Halder; Inmaculada García Quirós; Isaac Makelele; Issaka Senou; István Fekete; Ivan Mihal; Ivika Ostonen; Jana Borovská; Javier Roales; Jawad Shoqeir; Jean-Christophe Lata; Jean-Paul Theurillat; Jean-Luc Probst; Jess Zimmerman; Jeyanny Vijayanathan; Jianwu Tang; Jill Thompson; Jiří Doležal; Joan-Albert Sanchez-Cabeza; Joël Merlet; Joh Henschel; Johan Neirynck; Johannes Knops; John Loehr; Jonathan von Oppen; Jónína Sigríður Þorláksdóttir; Jörg Löffler; José-Gilberto Cardoso-Mohedano; José-Luis Benito-Alonso; Jose Marcelo Torezan; Joseph C. Morina; Juan J. Jiménez; Juan Dario Quinde; Juha Alatalo; Julia Seeber; Jutta Stadler; Kaie Kriiska; Kalifa Coulibaly; Karibu Fukuzawa; Katalin Szlavecz; Katarína Gerhátová; Kate Lajtha; Kathrin Käppeler; Katie A. Jennings; Katja Tielbörger; Kazuhiko Hoshizaki; Ken Green; Lambiénou Yé; Laryssa Helena Ribeiro Pazianoto; Laura Dienstbach; Laura Williams; Laura Yahdjian; Laurel M. Brigham; Liesbeth van den Brink; Lindsey Rustad; al. et

2018-01-01

Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies...

Thermal decomposition of high-nitrogen energetic compounds: TAGzT and GUzT

NASA Astrophysics Data System (ADS)

Hayden, Heather F.

The U.S. Navy is exploring high-nitrogen compounds as burning-rate additives to meet the growing demands of future high-performance gun systems. Two high-nitrogen compounds investigated as potential burning-rate additives are bis(triaminoguanidinium) 5,5-azobitetrazolate (TAGzT) and bis(guanidinium) 5,5'-azobitetrazolate (GUzT). Small-scale tests showed that formulations containing TAGzT exhibit significant increases in the burning rates of RDX-based gun propellants. However, when GUzT, a similarly structured molecule was incorporated into the formulation, there was essentially no effect on the burning rate of the propellant. Through the use of simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) and Fourier-Transform ion cyclotron resonance (FTICR) mass spectrometry methods, an investigation of the underlying chemical and physical processes that control the thermal decomposition behavior of TAGzT and GUzT alone and in the presence of RDX, was conducted. The objective was to determine why GUzT is not as good a burning-rate enhancer in RDX-based gun propellants as compared to TAGzT. The results show that TAGzT is an effective burning-rate modifier in the presence of RDX because the decomposition of TAGzT alters the initial stages of the decomposition of RDX. Hydrazine, formed in the decomposition of TAGzT, reacts faster with RDX than RDX can decompose itself. The reactions occur at temperatures below the melting point of RDX and thus the TAGzT decomposition products react with RDX in the gas phase. Although there is no hydrazine formed in the decomposition of GUzT, amines formed in the decomposition of GUzT react with aldehydes, formed in the decomposition of RDX, resulting in an increased reaction rate of RDX in the presence of GUzT. However, GUzT is not an effective burning-rate modifier because its decomposition does not alter the initial gas-phase decomposition of RDX. The decomposition of GUzT occurs at temperatures above the melting point of RDX. Therefore, the decomposition of GUzT affects reactions that are dominant in the liquid phase of RDX. Although GUzT is not an effective burning-rate modifier, features of its decomposition where the reaction between amines formed in the decomposition of GUzT react with the aldehydes, formed in the decomposition of RDX, may have implications from an insensitive-munitions perspective.

Optimizing a multi-product closed-loop supply chain using NSGA-II, MOSA, and MOPSO meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Babaveisi, Vahid; Paydar, Mohammad Mahdi; Safaei, Abdul Sattar

2018-07-01

This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products. Since three objective functions are considered, a multi-objective solution methodology can be advantageous. Therefore, several approaches have been studied and an NSGA-II algorithm is first utilized, and then the results are validated using an MOSA and MOPSO algorithms. Priority-based encoding, which is used in all the algorithms, is the core of the solution computations. To compare the performance of the meta-heuristics, random numerical instances are evaluated by four criteria involving mean ideal distance, spread of non-dominance solution, the number of Pareto solutions, and CPU time. In order to enhance the performance of the algorithms, Taguchi method is used for parameter tuning. Finally, sensitivity analyses are performed and the computational results are presented based on the sensitivity analyses in parameter tuning.

Optimizing a multi-product closed-loop supply chain using NSGA-II, MOSA, and MOPSO meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Babaveisi, Vahid; Paydar, Mohammad Mahdi; Safaei, Abdul Sattar

2017-07-01

This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products. Since three objective functions are considered, a multi-objective solution methodology can be advantageous. Therefore, several approaches have been studied and an NSGA-II algorithm is first utilized, and then the results are validated using an MOSA and MOPSO algorithms. Priority-based encoding, which is used in all the algorithms, is the core of the solution computations. To compare the performance of the meta-heuristics, random numerical instances are evaluated by four criteria involving mean ideal distance, spread of non-dominance solution, the number of Pareto solutions, and CPU time. In order to enhance the performance of the algorithms, Taguchi method is used for parameter tuning. Finally, sensitivity analyses are performed and the computational results are presented based on the sensitivity analyses in parameter tuning.

A subjective framework for seat comfort based on a heuristic multi criteria decision making technique and anthropometry.

PubMed

Fazlollahtabar, Hamed

2010-12-01

Consumer expectations for automobile seat comfort continue to rise. With this said, it is evident that the current automobile seat comfort development process, which is only sporadically successful, needs to change. In this context, there has been growing recognition of the need for establishing theoretical and methodological automobile seat comfort. On the other hand, seat producer need to know the costumer's required comfort to produce based on their interests. The current research methodologies apply qualitative approaches due to anthropometric specifications. The most significant weakness of these approaches is the inexact extracted inferences. Despite the qualitative nature of the consumer's preferences there are some methods to transform the qualitative parameters into numerical value which could help seat producer to improve or enhance their products. Nonetheless this approach would help the automobile manufacturer to provide their seats from the best producer regarding to the consumers idea. In this paper, a heuristic multi criteria decision making technique is applied to make consumers preferences in the numeric value. This Technique is combination of Analytical Hierarchy Procedure (AHP), Entropy method, and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A case study is conducted to illustrate the applicability and the effectiveness of the proposed heuristic approach. Copyright © 2010 Elsevier Ltd. All rights reserved.

When less is not always more: stereotype knowledge and reasoning development.

PubMed

De Neys, Wim; Vanderputte, Karolien

2011-03-01

Developmental studies on heuristics and biases have reported controversial findings suggesting that children sometimes reason more logically than do adults. We addressed the controversy by testing the impact of children's knowledge of the heuristic stereotypes that are typically cued in these studies. Five-year-old preschoolers and 8-year-old children were tested with a card game version of the classic base-rate task. Problems were based on stereotypes that were familiar or unfamiliar for preschoolers. We also manipulated whether the cued stereotypical response was consistent (no-conflict problems) or inconsistent (conflict problems) with the correct analytic response that was cued in the problem. Results showed that an age-related performance decrease on the conflict problems was accompanied by an age-related performance increase on the no-conflict problems. These age effects were most pronounced for problems that adopted stereotypes that were unfamiliar for the 5-year-old preschoolers. When preschoolers were familiar with the stereotypes, their performance also started being affected. Findings support the claim that previously reported age-related performance decreases on classic reasoning tasks need to be attributed to the increased need to deal with tempting heuristics and not to a decrease in analytic thinking skills per se. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows

PubMed Central

Jawarneh, Sana; Abdullah, Salwani

2015-01-01

This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon’s 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results. PMID:26132158

Near-Optimal Tracking Control of Mobile Robots Via Receding-Horizon Dual Heuristic Programming.

PubMed

Lian, Chuanqiang; Xu, Xin; Chen, Hong; He, Haibo

2016-11-01

Trajectory tracking control of wheeled mobile robots (WMRs) has been an important research topic in control theory and robotics. Although various tracking control methods with stability have been developed for WMRs, it is still difficult to design optimal or near-optimal tracking controller under uncertainties and disturbances. In this paper, a near-optimal tracking control method is presented for WMRs based on receding-horizon dual heuristic programming (RHDHP). In the proposed method, a backstepping kinematic controller is designed to generate desired velocity profiles and the receding horizon strategy is used to decompose the infinite-horizon optimal control problem into a series of finite-horizon optimal control problems. In each horizon, a closed-loop tracking control policy is successively updated using a class of approximate dynamic programming algorithms called finite-horizon dual heuristic programming (DHP). The convergence property of the proposed method is analyzed and it is shown that the tracking control system based on RHDHP is asymptotically stable by using the Lyapunov approach. Simulation results on three tracking control problems demonstrate that the proposed method has improved control performance when compared with conventional model predictive control (MPC) and DHP. It is also illustrated that the proposed method has lower computational burden than conventional MPC, which is very beneficial for real-time tracking control.

The identification of complete domains within protein sequences using accurate E-values for semi-global alignment

PubMed Central

Kann, Maricel G.; Sheetlin, Sergey L.; Park, Yonil; Bryant, Stephen H.; Spouge, John L.

2007-01-01

The sequencing of complete genomes has created a pressing need for automated annotation of gene function. Because domains are the basic units of protein function and evolution, a gene can be annotated from a domain database by aligning domains to the corresponding protein sequence. Ideally, complete domains are aligned to protein subsequences, in a ‘semi-global alignment’. Local alignment, which aligns pieces of domains to subsequences, is common in high-throughput annotation applications, however. It is a mature technique, with the heuristics and accurate E-values required for screening large databases and evaluating the screening results. Hidden Markov models (HMMs) provide an alternative theoretical framework for semi-global alignment, but their use is limited because they lack heuristic acceleration and accurate E-values. Our new tool, GLOBAL, overcomes some limitations of previous semi-global HMMs: it has accurate E-values and the possibility of the heuristic acceleration required for high-throughput applications. Moreover, according to a standard of truth based on protein structure, two semi-global HMM alignment tools (GLOBAL and HMMer) had comparable performance in identifying complete domains, but distinctly outperformed two tools based on local alignment. When searching for complete protein domains, therefore, GLOBAL avoids disadvantages commonly associated with HMMs, yet maintains their superior retrieval performance. PMID:17596268

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

PubMed

Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Assessment of the usability of a digital learning technology prototype for monitoring intracranial pressure 1

PubMed Central

de Carvalho, Lilian Regina; Évora, Yolanda Dora Martinez; Zem-Mascarenhas, Silvia Helena

2016-01-01

ABSTRACT Objective: to assess the usability of a digital learning technology prototype as a new method for minimally invasive monitoring of intracranial pressure. Method: descriptive study using a quantitative approach on assessing the usability of a prototype based on Nielsen's ten heuristics. Four experts in the area of Human-Computer interaction participated in the study. Results: the evaluation delivered eight violated heuristics and 31 usability problems in the 32 screens of the prototype. Conclusion: the suggestions of the evaluators were critical for developing an intuitive, user-friendly interface and will be included in the final version of the digital learning technology. PMID:27579932

TORC3: Token-ring clearing heuristic for currency circulation

NASA Astrophysics Data System (ADS)

Humes, Carlos, Jr.; Lauretto, Marcelo S.; Nakano, Fábio; Pereira, Carlos A. B.; Rafare, Guilherme F. G.; Stern, Julio Michael

2012-10-01

Clearing algorithms are at the core of modern payment systems, facilitating the settling of multilateral credit messages with (near) minimum transfers of currency. Traditional clearing procedures use batch processing based on MILP - mixed-integer linear programming algorithms. The MILP approach demands intensive computational resources; moreover, it is also vulnerable to operational risks generated by possible defaults during the inter-batch period. This paper presents TORC3 - the Token-Ring Clearing Algorithm for Currency Circulation. In contrast to the MILP approach, TORC3 is a real time heuristic procedure, demanding modest computational resources, and able to completely shield the clearing operation against the participating agents' risk of default.

Knowledge-Based Systems Approach to Wilderness Fire Management.

NASA Astrophysics Data System (ADS)

Saveland, James M.

The 1988 and 1989 forest fire seasons in the Intermountain West highlight the shortcomings of current fire policy. To fully implement an optimization policy that minimizes the costs and net value change of resources affected by fire, long-range fire severity information is essential, yet lacking. This information is necessary for total mobility of suppression forces, implementing contain and confine suppression strategies, effectively dealing with multiple fire situations, scheduling summer prescribed burning, and wilderness fire management. A knowledge-based system, Delphi, was developed to help provide long-range information. Delphi provides: (1) a narrative of advice on where a fire might spread, if allowed to burn, (2) a summary of recent weather and fire danger information, and (3) a Bayesian analysis of long-range fire danger potential. Uncertainty is inherent in long-range information. Decision theory and judgment research can be used to help understand the heuristics experts use to make decisions under uncertainty, heuristics responsible both for expert performance and bias. Judgment heuristics and resulting bias are examined from a fire management perspective. Signal detection theory and receiver operating curve (ROC) analysis can be used to develop a long-range forecast to improve decisions. ROC analysis mimics some of the heuristics and compensates for some of the bias. Most importantly, ROC analysis displays a continuum of bias from which an optimum operating point can be selected. ROC analysis is especially appropriate for long-range forecasting since (1) the occurrence of possible future events is stated in terms of probability, (2) skill prediction is displayed, (3) inherent trade-offs are displayed, and (4) fire danger is explicitly defined. Statements on the probability of the energy release component of the National Fire Danger Rating System exceeding a critical value later in the fire season can be made early July in the Intermountain West. Delphi was evaluated formally and informally. Continual evaluation and feedback to update knowledge-based systems results in a repository for current knowledge, and a means to devise policy that will augment existing knowledge. Thus, knowledge-based systems can help implement adaptive resource management.

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 &…

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…

A Priori Knowledge and Heuristic Reasoning in Architectural Design.

ERIC Educational Resources Information Center

Rowe, Peter G.

1982-01-01

It is proposed that the various classes of a priori knowledge incorporated in heuristic reasoning processes exert a strong influence over architectural design activity. Some design problems require exercise of some provisional set of rules, inference, or plausible strategy which requires heuristic reasoning. A case study illustrates this concept.…

An heuristic for the study of the effects of emotion on memory.

PubMed

Whissell, C

1991-02-01

This report contains an heuristic (a systematic set of questions) addressing issues of concern in the emotion-memory literature. Four experiments (ns of 73, 24, 160, and 34) are described in terms of the heuristic and its potential for describing the literature is examined.

On Dual Processing and Heuristic Approaches to Moral Cognition

ERIC Educational Resources Information Center

Lapsley, Daniel K.; Hill, Patrick L.

2008-01-01

We examine the implications of dual-processing theories of cognition for the moral domain, with particular emphasis upon "System 1" theories: the Social Intuitionist Model (Haidt), moral heuristics (Sunstein), fast-and-frugal moral heuristics (Gigerenzer), schema accessibility (Lapsley & Narvaez) and moral expertise (Narvaez). We argue that these…

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.

The Priority Heuristic: Making Choices Without Trade-Offs

PubMed Central

Brandstätter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph

2010-01-01

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, we generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (i) Allais' paradox, (ii) risk aversion for gains if probabilities are high, (iii) risk seeking for gains if probabilities are low (lottery tickets), (iv) risk aversion for losses if probabilities are low (buying insurance), (v) risk seeking for losses if probabilities are high, (vi) certainty effect, (vii) possibility effect, and (viii) intransitivities. We test how accurately the heuristic predicts people's choices, compared to previously proposed heuristics and three modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory. PMID:16637767

Heuristic and algorithmic processing in English, mathematics, and science education.

PubMed

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.

Evaluation of the priority heuristic as a descriptive model of risky decision making: comment on Brandstätter, Gigerenzer, and Hertwig (2006).

PubMed

Birnbaum, Michael H

2008-01-01

E. Brandstätter, G. Gigerenzer, and R. Hertwig (2006) contended that their priority heuristic, a type of lexicographic semiorder model, is more accurate than cumulative prospect theory (CPT) or transfer of attention exchange (TAX) models in describing risky decisions. However, there are 4 problems with their argument. First, their heuristic is not descriptive of certain data that they did not review. Second, their analysis relied on a global index of fit, percentage of correct predictions of the modal choice. Such analyses can lead to wrong conclusions when parameters are not properly estimated from the data. When parameters are estimated from the data, CPT and TAX fit the D. Kahneman and A. Tversky (1979) data perfectly. Reanalysis shows that TAX and CPT do as well as the priority heuristic for 2 of the data sets reviewed and outperform the priority heuristic for the other 3. Third, when 2 of these sets of data are reexamined, the priority heuristic is seen to make systematic violations. Fourth, new critical implications have been devised for testing the family of lexicographic semiorders including the priority heuristic; new results with these critical tests show systematic evidence against lexicographic semiorder models. (c) 2008 APA, all rights reserved

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.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Domain Decomposition By the Advancing-Partition Method for Parallel Unstructured Grid Generation

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.; Zagaris, George

2009-01-01

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Domain Decomposition By the Advancing-Partition Method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2008-01-01

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Effects of magnesium-based hydrogen storage materials on the thermal decomposition, burning rate, and explosive heat of ammonium perchlorate-based composite solid propellant.

PubMed

Liu, Leili; Li, Jie; Zhang, Lingyao; Tian, Siyu

2018-01-15

MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 were prepared, and their structure and hydrogen storage properties were determined through X-ray photoelectron spectroscopy and thermal analyzer. The effects of MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 on the thermal decomposition, burning rate, and explosive heat of ammonium perchlorate-based composite solid propellant were subsequently studied. Results indicated that MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 can decrease the thermal decomposition peak temperature and increase the total released heat of decomposition. These compounds can improve the effect of thermal decomposition of the propellant. The burning rates of the propellant increased using Mg-based hydrogen storage materials as promoter. The burning rates of the propellant also increased using MgH 2 instead of Al in the propellant, but its explosive heat was not enlarged. Nonetheless, the combustion heat of MgH 2 was higher than that of Al. A possible mechanism was thus proposed. Copyright © 2017. Published by Elsevier B.V.

Intuitive and Deliberate Judgments Are Based on Common Principles

ERIC Educational Resources Information Center

Kruglanski, Arie W.; Gigerenzer, Gerd

2011-01-01

A popular distinction in cognitive and social psychology has been between "intuitive" and "deliberate" judgments. This juxtaposition has aligned in dual-process theories of reasoning associative, unconscious, effortless, heuristic, and suboptimal processes (assumed to foster intuitive judgments) versus rule-based, conscious, effortful, analytic,…

Automatic and controlled components of judgment and decision making.

PubMed

Ferreira, Mario B; Garcia-Marques, Leonel; Sherman, Steven J; Sherman, Jeffrey W

2006-11-01

The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., K. E. Stanovich & R. F. West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. The present authors use the process dissociation procedure (L. L. Jacoby, 1991) to provide convergent evidence validating a dual-process perspective to judgment under uncertainty based on the independent contributions of heuristic and rule-based reasoning. Process dissociations based on experimental manipulation of variables were derived from the most relevant theoretical properties typically used to contrast the two forms of reasoning. These include processing goals (Experiment 1), cognitive resources (Experiment 2), priming (Experiment 3), and formal training (Experiment 4); the results consistently support the author's perspective. They conclude that judgment under uncertainty is neither an automatic nor a controlled process but that it reflects both processes, with each making independent contributions.

Multiobjective immune algorithm with nondominated neighbor-based selection.

PubMed

Gong, Maoguo; Jiao, Licheng; Du, Haifeng; Bo, Liefeng

2008-01-01

Abstract Nondominated Neighbor Immune Algorithm (NNIA) is proposed for multiobjective optimization by using a novel nondominated neighbor-based selection technique, an immune inspired operator, two heuristic search operators, and elitism. The unique selection technique of NNIA only selects minority isolated nondominated individuals in the population. The selected individuals are then cloned proportionally to their crowding-distance values before heuristic search. By using the nondominated neighbor-based selection and proportional cloning, NNIA pays more attention to the less-crowded regions of the current trade-off front. We compare NNIA with NSGA-II, SPEA2, PESA-II, and MISA in solving five DTLZ problems, five ZDT problems, and three low-dimensional problems. The statistical analysis based on three performance metrics including the coverage of two sets, the convergence metric, and the spacing, show that the unique selection method is effective, and NNIA is an effective algorithm for solving multiobjective optimization problems. The empirical study on NNIA's scalability with respect to the number of objectives shows that the new algorithm scales well along the number of objectives.

Fixing Stellarator Magnetic Surfaces

NASA Astrophysics Data System (ADS)

Hanson, James D.

1999-11-01

Magnetic surfaces are a perennial issue for stellarators. The design heuristic of finding a magnetic field with zero perpendicular component on a specified outer surface often yields inner magnetic surfaces with very small resonant islands. However, magnetic fields in the laboratory are not design fields. Island-causing errors can arise from coil placement errors, stray external fields, and design inadequacies such as ignoring coil leads and incomplete characterization of current distributions within the coil pack. The problem addressed is how to eliminate such error-caused islands. I take a perturbation approach, where the zero order field is assumed to have good magnetic surfaces, and comes from a VMEC equilibrium. The perturbation field consists of error and correction pieces. The error correction method is to determine the correction field so that the sum of the error and correction fields gives zero island size at specified rational surfaces. It is particularly important to correctly calculate the island size for a given perturbation field. The method works well with many correction knobs, and a Singular Value Decomposition (SVD) technique is used to determine minimal corrections necessary to eliminate islands.

An optimization approach for fitting canonical tensor decompositions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunlavy, Daniel M.; Acar, Evrim; Kolda, Tamara Gibson

Tensor decompositions are higher-order analogues of matrix decompositions and have proven to be powerful tools for data analysis. In particular, we are interested in the canonical tensor decomposition, otherwise known as the CANDECOMP/PARAFAC decomposition (CPD), which expresses a tensor as the sum of component rank-one tensors and is used in a multitude of applications such as chemometrics, signal processing, neuroscience, and web analysis. The task of computing the CPD, however, can be difficult. The typical approach is based on alternating least squares (ALS) optimization, which can be remarkably fast but is not very accurate. Previously, nonlinear least squares (NLS) methodsmore » have also been recommended; existing NLS methods are accurate but slow. In this paper, we propose the use of gradient-based optimization methods. We discuss the mathematical calculation of the derivatives and further show that they can be computed efficiently, at the same cost as one iteration of ALS. Computational experiments demonstrate that the gradient-based optimization methods are much more accurate than ALS and orders of magnitude faster than NLS.« less

Simple heuristics and rules of thumb: where psychologists and behavioural biologists might meet.

PubMed

Hutchinson, John M C; Gigerenzer, Gerd

2005-05-31

The Centre for Adaptive Behaviour and Cognition (ABC) has hypothesised that much human decision-making can be described by simple algorithmic process models (heuristics). This paper explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of Take The Best for choosing between two alternatives: cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modelling is usually used to explain less detailed aspects of behaviour but might more often be redirected to investigate rules of thumb.

Internal Medicine residents use heuristics to estimate disease probability

PubMed Central

Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin

2015-01-01

Background Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. Method We randomized 55 Internal Medicine residents to different versions of four clinical vignettes and asked them to estimate probabilities of target conditions. We manipulated the clinical data for each vignette to be consistent with either 1) using a representative heuristic, by adding non-discriminating prototypical clinical features of the target condition, or 2) using anchoring with adjustment heuristic, by providing a high or low anchor for the target condition. Results When presented with additional non-discriminating data the odds of diagnosing the target condition were increased (odds ratio (OR) 2.83, 95% confidence interval [1.30, 6.15], p = 0.009). Similarly, the odds of diagnosing the target condition were increased when a high anchor preceded the vignette (OR 2.04, [1.09, 3.81], p = 0.025). Conclusions Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing. PMID:27004080

A comparative study of the A* heuristic search algorithm used to solve efficiently a puzzle game

NASA Astrophysics Data System (ADS)

Iordan, A. E.

2018-01-01

The puzzle game presented in this paper consists in polyhedra (prisms, pyramids or pyramidal frustums) which can be moved using the free available spaces. The problem requires to be found the minimum number of movements in order the game reaches to a goal configuration starting from an initial configuration. Because the problem is enough complex, the principal difficulty in solving it is given by dimension of search space, that leads to necessity of a heuristic search. The improving of the search method consists into determination of a strong estimation by the heuristic function which will guide the search process to the most promising side of the search tree. The comparative study is realized among Manhattan heuristic and the Hamming heuristic using A* search algorithm implemented in Java. This paper also presents the necessary stages in object oriented development of a software used to solve efficiently this puzzle game. The modelling of the software is achieved through specific UML diagrams representing the phases of analysis, design and implementation, the system thus being described in a clear and practical manner. With the purpose to confirm the theoretical results which demonstrates that Manhattan heuristic is more efficient was used space complexity criterion. The space complexity was measured by the number of generated nodes from the search tree, by the number of the expanded nodes and by the effective branching factor. From the experimental results obtained by using the Manhattan heuristic, improvements were observed regarding space complexity of A* algorithm versus Hamming heuristic.

Spider foraging strategy affects trophic cascades under natural and drought conditions.

PubMed

Liu, Shengjie; Chen, Jin; Gan, Wenjin; Schaefer, Douglas; Gan, Jianmin; Yang, Xiaodong

2015-07-23

Spiders can cause trophic cascades affecting litter decomposition rates. However, it remains unclear how spiders with different foraging strategies influence faunal communities, or present cascading effects on decomposition. Furthermore, increased dry periods predicted in future climates will likely have important consequences for trophic interactions in detritus-based food webs. We investigated independent and interactive effects of spider predation and drought on litter decomposition in a tropical forest floor. We manipulated densities of dominant spiders with actively hunting or sit-and-wait foraging strategies in microcosms which mimicked the tropical-forest floor. We found a positive trophic cascade on litter decomposition was triggered by actively hunting spiders under ambient rainfall, but sit-and-wait spiders did not cause this. The drought treatment reversed the effect of actively hunting spiders on litter decomposition. Under drought conditions, we observed negative trophic cascade effects on litter decomposition in all three spider treatments. Thus, reduced rainfall can alter predator-induced indirect effects on lower trophic levels and ecosystem processes, and is an example of how such changes may alter trophic cascades in detritus-based webs of tropical forests.

Spider foraging strategy affects trophic cascades under natural and drought conditions

PubMed Central

Liu, Shengjie; Chen, Jin; Gan, Wenjin; Schaefer, Douglas; Gan, Jianmin; Yang, Xiaodong

2015-01-01

Spiders can cause trophic cascades affecting litter decomposition rates. However, it remains unclear how spiders with different foraging strategies influence faunal communities, or present cascading effects on decomposition. Furthermore, increased dry periods predicted in future climates will likely have important consequences for trophic interactions in detritus-based food webs. We investigated independent and interactive effects of spider predation and drought on litter decomposition in a tropical forest floor. We manipulated densities of dominant spiders with actively hunting or sit-and-wait foraging strategies in microcosms which mimicked the tropical-forest floor. We found a positive trophic cascade on litter decomposition was triggered by actively hunting spiders under ambient rainfall, but sit-and-wait spiders did not cause this. The drought treatment reversed the effect of actively hunting spiders on litter decomposition. Under drought conditions, we observed negative trophic cascade effects on litter decomposition in all three spider treatments. Thus, reduced rainfall can alter predator-induced indirect effects on lower trophic levels and ecosystem processes, and is an example of how such changes may alter trophic cascades in detritus-based webs of tropical forests. PMID:26202370

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

Macula segmentation and fovea localization employing image processing and heuristic based clustering for automated retinal screening.

PubMed

R, GeethaRamani; Balasubramanian, Lakshmi

2018-07-01

Macula segmentation and fovea localization is one of the primary tasks in retinal analysis as they are responsible for detailed vision. Existing approaches required segmentation of retinal structures viz. optic disc and blood vessels for this purpose. This work avoids knowledge of other retinal structures and attempts data mining techniques to segment macula. Unsupervised clustering algorithm is exploited for this purpose. Selection of initial cluster centres has a great impact on performance of clustering algorithms. A heuristic based clustering in which initial centres are selected based on measures defining statistical distribution of data is incorporated in the proposed methodology. The initial phase of proposed framework includes image cropping, green channel extraction, contrast enhancement and application of mathematical closing. Then, the pre-processed image is subjected to heuristic based clustering yielding a binary map. The binary image is post-processed to eliminate unwanted components. Finally, the component which possessed the minimum intensity is finalized as macula and its centre constitutes the fovea. The proposed approach outperforms existing works by reporting that 100%,of HRF, 100% of DRIVE, 96.92% of DIARETDB0, 97.75% of DIARETDB1, 98.81% of HEI-MED, 90% of STARE and 99.33% of MESSIDOR images satisfy the 1R criterion, a standard adopted for evaluating performance of macula and fovea identification. The proposed system thus helps the ophthalmologists in identifying the macula thereby facilitating to identify if any abnormality is present within the macula region. Copyright © 2018 Elsevier B.V. All rights reserved.

Limitations of Language: Developing Arts-Based Creative Narrative in Stories of Teachers' Identities

ERIC Educational Resources Information Center

Leitch, Ruth

2006-01-01

This paper is based on a multidimensional study employing a heuristic methodology termed "creative narrative" that combines arts-based methods with narrative inquiry. Six female teachers' narratives of identity are explored through artistic, visual images to illuminate if and how they story "unconscious". The creative narratives, illuminated…