heuristic rules applied: Topics by Science.gov

Sample records for heuristic rules applied

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.
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.
Bayesian probability estimates are not necessary to make choices satisfying Bayes' rule in elementary situations.

PubMed

Domurat, Artur; Kowalczuk, Olga; Idzikowska, Katarzyna; Borzymowska, Zuzanna; Nowak-Przygodzka, Marta

2015-01-01

This paper has two aims. First, we investigate how often people make choices conforming to Bayes' rule when natural sampling is applied. Second, we show that using Bayes' rule is not necessary to make choices satisfying Bayes' rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes' rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes' rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes' rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes' rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes' rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes' rule. However, people tend to replace Bayes' rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient.
Bayesian probability estimates are not necessary to make choices satisfying Bayes’ rule in elementary situations

PubMed Central

Domurat, Artur; Kowalczuk, Olga; Idzikowska, Katarzyna; Borzymowska, Zuzanna; Nowak-Przygodzka, Marta

2015-01-01

This paper has two aims. First, we investigate how often people make choices conforming to Bayes’ rule when natural sampling is applied. Second, we show that using Bayes’ rule is not necessary to make choices satisfying Bayes’ rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes’ rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes’ rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes’ rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes’ rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes’ rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes’ rule. However, people tend to replace Bayes’ rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient. PMID:26347676
Heuristics structure and pervade formal risk assessment.

PubMed

MacGillivray, Brian H

2014-04-01

Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art. © 2013 Society for Risk Analysis.
Choice Rules and Accumulator Networks

PubMed Central

2015-01-01

This article presents a preference accumulation model that can be used to implement a number of different multi-attribute heuristic choice rules, including the lexicographic rule, the majority of confirming dimensions (tallying) rule and the equal weights rule. The proposed model differs from existing accumulators in terms of attribute representation: Leakage and competition, typically applied only to preference accumulation, are also assumed to be involved in processing attribute values. This allows the model to perform a range of sophisticated attribute-wise comparisons, including comparisons that compute relative rank. The ability of a preference accumulation model composed of leaky competitive networks to mimic symbolic models of heuristic choice suggests that these 2 approaches are not incompatible, and that a unitary cognitive model of preferential choice, based on insights from both these approaches, may be feasible. PMID:28670592
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.
More equal than others: Equity norms as an integration of cognitive heuristics and contextual cues in bargaining games.

PubMed

Civai, Claudia; Rumiati, Raffaella Ida; Rustichini, Aldo

2013-09-01

Behavior in one-shot bargaining games, like the Ultimatum Game (UG), has been interpreted as an expression of social preferences, such as inequity aversion and negative reciprocity; however, the traditional UG design limits the range of possible psychological interpretation of the results. Here, we employed three different designs for ultimatum games, finding support for a more comprehensive theory: behavior is driven by cognitive factors implementing rules such as equal splitting, speaking up for the idea that equity works as a cognitive heuristic, applicable when the environment provides no reason to behave otherwise. Instead subjects deviate from this rule when environment changes, as, for instance, when personal interest is at stake. Results show that behavior varies systematically with contextual cues, balancing the self-interest with the automatic application of the equity heuristic. Thus, the context suggests the rule to be applied in a specific situation. Copyright © 2013 Elsevier B.V. All rights reserved.
Meta-RaPS Algorithm for the Aerial Refueling Scheduling Problem

NASA Technical Reports Server (NTRS)

Kaplan, Sezgin; Arin, Arif; Rabadi, Ghaith

2011-01-01

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on multiple tankers (machines). ARSP assumes that jobs have different release times and due dates, The total weighted tardiness is used to evaluate schedule's quality. Therefore, ARSP can be modeled as a parallel machine scheduling with release limes and due dates to minimize the total weighted tardiness. Since ARSP is NP-hard, it will be more appropriate to develop a pproimate or heuristic algorithm to obtain solutions in reasonable computation limes. In this paper, Meta-Raps-ATC algorithm is implemented to create high quality solutions. Meta-RaPS (Meta-heuristic for Randomized Priority Search) is a recent and promising meta heuristic that is applied by introducing randomness to a construction heuristic. The Apparent Tardiness Rule (ATC), which is a good rule for scheduling problems with tardiness objective, is used to construct initial solutions which are improved by an exchanging operation. Results are presented for generated instances.
New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.
Augmented neural networks and problem structure-based heuristics for the bin-packing problem

NASA Astrophysics Data System (ADS)

Kasap, Nihat; Agarwal, Anurag

2012-08-01

In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.
Vervet monkeys use paths consistent with context-specific spatial movement heuristics.

PubMed

Teichroeb, Julie A

2015-10-01

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.
A conceptual review of decision making in social dilemmas: applying a logic of appropriateness.

PubMed

Weber, J Mark; Kopelman, Shirli; Messick, David M

2004-01-01

Despite decades of experimental social dilemma research, "theoretical integration has proven elusive" (Smithson & Foddy, 1999, p. 14). To advance a theory of decision making in social dilemmas, this article provides a conceptual review of the literature that applies a "logic of appropriateness" (March, 1994) framework. The appropriateness framework suggests that people making decisions ask themselves (explicitly or implicitly), "What does a person like me do in a situation like this? " This question identifies 3 significant factors: recognition and classification of the kind of situation encountered, the identity of the individual making the decision, and the application of rules or heuristics in guiding behavioral choice. In contrast with dominant rational choice models, the appropriateness framework proposed accommodates the inherently social nature of social dilemmas, and the role of rule and heuristic based processing. Implications for the interpretation of past findings and the direction of future research are discussed.
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.
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.
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.
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.
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.
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.
Modified Levenberg-Marquardt Method for RÖSSLER Chaotic System Fuzzy Modeling Training

NASA Astrophysics Data System (ADS)

Wang, Yu-Hui; Wu, Qing-Xian; Jiang, Chang-Sheng; Xue, Ya-Li; Fang, Wei

Generally, fuzzy approximation models require some human knowledge and experience. Operator's experience is involved in the mathematics of fuzzy theory as a collection of heuristic rules. The main goal of this paper is to present a new method for identifying unknown nonlinear dynamics such as Rössler system without any human knowledge. Instead of heuristic rules, the presented method uses the input-output data pairs to identify the Rössler chaotic system. The training algorithm is a modified Levenberg-Marquardt (L-M) method, which can adjust the parameters of each linear polynomial and fuzzy membership functions on line, and do not rely on experts' experience excessively. Finally, it is applied to training Rössler chaotic system fuzzy identification. Comparing this method with the standard L-M method, the convergence speed is accelerated. The simulation results demonstrate the effectiveness of the proposed method.

Expert system for identification of simultaneous and sequential reactor fuel failures with gas tagging

DOEpatents

Gross, Kenny C.

1994-01-01

Failure of a fuel element in a nuclear reactor core is determined by a gas tagging failure detection system and method. Failures are catalogued and characterized after the event so that samples of the reactor's cover gas are taken at regular intervals and analyzed by mass spectroscopy. Employing a first set of systematic heuristic rules which are applied in a transformed node space allows the number of node combinations which must be processed within a barycentric algorithm to be substantially reduced. A second set of heuristic rules treats the tag nodes of the most recent one or two leakers as "background" gases, further reducing the number of trial node combinations. Lastly, a "fuzzy" set theory formalism minimizes experimental uncertainties in the identification of the most likely volumes of tag gases. This approach allows for the identification of virtually any number of sequential leaks and up to five simultaneous gas leaks from fuel elements.
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)
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,…
Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule

NASA Astrophysics Data System (ADS)

Jin, Qinian; Wang, Wei

2018-03-01

The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.
Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

NASA Astrophysics Data System (ADS)

Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.
New insight into the comparative power of quality-control rules that use control observations within a single analytical run.

PubMed

Parvin, C A

1993-03-01

The error detection characteristics of quality-control (QC) rules that use control observations within a single analytical run are investigated. Unlike the evaluation of QC rules that span multiple analytical runs, most of the fundamental results regarding the performance of QC rules applied within a single analytical run can be obtained from statistical theory, without the need for simulation studies. The case of two control observations per run is investigated for ease of graphical display, but the conclusions can be extended to more than two control observations per run. Results are summarized in a graphical format that offers many interesting insights into the relations among the various QC rules. The graphs provide heuristic support to the theoretical conclusions that no QC rule is best under all error conditions, but the multirule that combines the mean rule and a within-run standard deviation rule offers an attractive compromise.
Sophisticated approval voting, ignorance priors, and plurality heuristics: a behavioral social choice analysis in a Thurstonian framework.

PubMed

Regenwetter, Michel; Ho, Moon-Ho R; Tsetlin, Ilia

2007-10-01

This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two types of plurality heuristics to model approval voting behavior. When using a sincere plurality heuristic, voters simplify their decision process by voting for their single favorite candidate. When using a strategic plurality heuristic, voters strategically focus their attention on the 2 front-runners and vote for their preferred candidate among these 2. Using a hierarchy of Thurstonian random utility models, the authors implemented these different decision rules and tested them statistically on 7 real world approval voting elections. They cross-validated their key findings via a psychological Internet experiment. Although a substantial number of voters used the plurality heuristic in the real elections, they did so sincerely, not strategically. Moreover, even though Thurstonian models do not force such agreement, the results show, in contrast to common wisdom about social choice rules, that the sincere social orders by Condorcet, Borda, plurality, and approval voting are identical in all 7 elections and in the Internet experiment. PsycINFO Database Record (c) 2007 APA, all rights reserved.
Normalizing biomedical terms by minimizing ambiguity and variability

PubMed Central

Tsuruoka, Yoshimasa; McNaught, John; Ananiadou, Sophia

2008-01-01

Background One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of the terms. Soft string matching is a possible solution to the problem, but its inherent heavy computational cost discourages its use when the dictionaries are large or when real time processing is required. A less computationally demanding approach is to normalize the terms by using heuristic rules, which enables us to look up a dictionary in a constant time regardless of its size. The development of good heuristic rules, however, requires extensive knowledge of the terminology in question and thus is the bottleneck of the normalization approach. Results We present a novel framework for discovering a list of normalization rules from a dictionary in a fully automated manner. The rules are discovered in such a way that they minimize the ambiguity and variability of the terms in the dictionary. We evaluated our algorithm using two large dictionaries: a human gene/protein name dictionary built from BioThesaurus and a disease name dictionary built from UMLS. Conclusions The experimental results showed that automatically discovered rules can perform comparably to carefully crafted heuristic rules in term mapping tasks, and the computational overhead of rule application is small enough that a very fast implementation is possible. This work will help improve the performance of term-concept mapping tasks in biomedical information extraction especially when good normalization heuristics for the target terminology are not fully known. PMID:18426547
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
Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

PubMed

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.
Training self‐assessment and task‐selection skills to foster self‐regulated learning: Do trained skills transfer across domains?

PubMed Central

Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J. G.; van Gog, Tamara

2018-01-01

Summary Students' ability to accurately self‐assess their performance and select a suitable subsequent learning task in response is imperative for effective self‐regulated learning. Video modeling examples have proven effective for training self‐assessment and task‐selection skills, and—importantly—such training fostered self‐regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task‐selection rule or a more general heuristic task‐selection rule in biology would transfer to self‐regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task‐selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self‐regulated learning in math. Future research should investigate how to support transfer of task‐selection skills across domains. PMID:29610547
Expert system for identification of simultaneous and sequential reactor fuel failures with gas tagging

DOEpatents

Gross, K.C.

1994-07-26

Failure of a fuel element in a nuclear reactor core is determined by a gas tagging failure detection system and method. Failures are catalogued and characterized after the event so that samples of the reactor's cover gas are taken at regular intervals and analyzed by mass spectroscopy. Employing a first set of systematic heuristic rules which are applied in a transformed node space allows the number of node combinations which must be processed within a barycentric algorithm to be substantially reduced. A second set of heuristic rules treats the tag nodes of the most recent one or two leakers as background'' gases, further reducing the number of trial node combinations. Lastly, a fuzzy'' set theory formalism minimizes experimental uncertainties in the identification of the most likely volumes of tag gases. This approach allows for the identification of virtually any number of sequential leaks and up to five simultaneous gas leaks from fuel elements. 14 figs.
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.…
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.
Algorithmic and heuristic processing of information by the nervous system.

PubMed

Restian, A

1980-01-01

Starting from the fact that the nervous system must discover the information it needs, the author describes the way it decodes the received message. The logical circuits of the nervous system, submitting the received signals to a process by means of which information brought is discovered step by step, participates in decoding the message. The received signals, as information, can be algorithmically or heuristically processed. Algorithmic processing is done according to precise rules, which must be fulfilled step by step. By algorithmic processing, one develops somatic and vegetative reflexes as blood pressure, heart frequency or water metabolism control. When it does not dispose of precise rules of information processing or when algorithmic processing needs a very long time, the nervous system must use heuristic processing. This is the feature that differentiates the human brain from the electronic computer that can work only according to some extremely precise rules. The human brain can work according to less precise rules because it can resort to trial and error operations, and because it works according to a form of logic. Working with superior order signals which represent the class of all inferior type signals from which they begin, the human brain need not perform all the operations that it would have to perform by superior type of signals. Therefore the brain tries to submit the received signals to intensive as possible superization. All informational processing, and especially heuristical processing, is accompanied by a certain affective color and the brain cannot operate without it. Emotions, passions and sentiments usually complete the lack of precision of the heuristical programmes. Finally, the author shows that informational and especially heuristical processes study can contribute to a better understanding of the transition from neurological to psychological activity.
A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

PubMed

Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

2018-06-04

Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.
Swift and Smart Decision Making: Heuristics that Work

ERIC Educational Resources Information Center

Hoy, Wayne K.; Tarter, C. J.

2010-01-01

Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…
"The Golden Rule": Only a starting point for quality care.

PubMed

Corazzini, Kirsten N; Lekan-Rutledge, Deborah; Utley-Smith, Queen; Piven, Mary L; Colón-Emeric, Cathleen S; Bailey, Donald; Ammarell, Natalie; Anderson, Ruth A

2005-01-01

The Golden Rule guides people to choose for others what they would choose for themselves. The Golden Rule is often described as 'putting yourself in someone else's shoes', or 'Do unto others as you would have them do unto you'(Baumrin 2004). The viewpoint held in the Golden Rule is noted in all the major world religions and cultures, suggesting that this may be an important moral truth (Cunningham 1998). The Golden Rule underlies acts of kindness, caring, and altruism that go above and beyond "business as usual" or "usual care" (Huang, 2005). As such, this heuristic or 'rule of thumb' has universal appeal and helps guide our behaviors toward the welfare of others. So why question the Golden Rule? Unless used mindfully, any heuristic can be overly-simplistic and lead to unintended, negative consequences.A heuristic is a rule of thumb that people use to simplify potentially overwhelming or complex events. These rules of thumb are largely unconscious, and occur irrespective of training and educational level (Gilovich, Griffin & Kahneman 2002). Rules of thumb, such as the Golden Rule, allow a person to reduce a complex situation to something manageable-e.g., 'when in doubt, do what I would want done'. Because it is a simplifying tool, however, the Golden Rule may lead to inappropriate actions because important factors may be overlooked.In this article we describe "The Golden Rule" as used by administrators, supervisors, charge nurses, and CNAs in case studies of four nursing homes. By describing use of this rule-of-thumb, we aim to challenge nurses in nursing homes to: 1) be mindful of their use of "The Golden Rule" and its impact on staff and residents; and 2) help staff members think through how and why "The Golden Rule" may impact their relationships with staff and residents.
Conditioning of high voltage radio frequency cavities by using fuzzy logic in connection with rule based programming

NASA Astrophysics Data System (ADS)

Perreard, S.; Wildner, E.

1994-12-01

Many processes are controlled by experts using some kind of mental model to decide on actions and make conclusions. This model, based on heuristic knowledge, can often be represented by rules and does not have to be particularly accurate. Such is the case for the problem of conditioning high voltage RF cavities; the expert has to decide, by observing some criteria, whether to increase or to decrease the voltage and by how much. A program has been implemented which can be applied to a class of similar problems. The kernel of the program is a small rule base, which is independent of the kind of cavity. To model a specific cavity, we use fuzzy logic which is implemented as a separate routine called by the rule base, to translate from numeric to symbolic information.

Vervet monkey (Chlorocebus pygerythrus) behavior in a multi-destination route: Evidence for planning ahead when heuristics fail.

PubMed

Teichroeb, Julie Annette; Smeltzer, Eve Ann

2018-01-01

Animal paths are analogous to intractable mathematical problems like the Traveling Salesman Problem (TSP) and the shortest path problem (SPP). Both the TSP and SPP require an individual to find the shortest path through multiple targets but the TSP demands a return to the start, while the SPP does not. Vervet monkeys are very efficient in solving TSPs but this species is a multiple central place forager that does not always return to the same sleeping site and thus theoretically should be selected to find solutions to SPPs rather than TSPs. We examined path choice by wild vervets in an SPP experimental array where the shortest paths usually differed from those consistent with common heuristic strategies, the nearest-neighbor rule (NNR-go to the closest resource that has not been visited), and the convex hull (put a mental loop around sites, adding inner targets in order of distance from the edge)-an efficient strategy for TSPs but not SPPs. In addition, humans solving SPPs use an initial segment strategy (ISS-choose the straightest path at the beginning, only turning when necessary) and we looked at vervet paths consistent with this strategy. In 615 trials by single foragers, paths usually conformed to the NNR and rarely the slightly more efficient convex hull, supporting that vervets may be selected to solve SPPs. Further, like humans solving SPPs, vervets showed a tendency to use the ISS. Paths consistent with heuristics dropped off sharply, and use of the shortest path increased, when heuristics led to longer paths showing trade-offs in efficiency versus cognitive load. Two individuals out of 17, found the shortest path most often, showing inter-individual variation in path planning. Given support for the NNR and the ISS, we propose a new rule-of-thumb termed the "region heuristic" that vervets may apply in multi-destination routes.
A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

NASA Astrophysics Data System (ADS)

Estiningsih, Y.; Farikhin; Tjahjana, R. H.

2018-03-01

Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.
The quasi-optimality criterion in the linear functional strategy

NASA Astrophysics Data System (ADS)

Kindermann, Stefan; Pereverzyev, Sergiy, Jr.; Pilipenko, Andrey

2018-07-01

The linear functional strategy for the regularization of inverse problems is considered. For selecting the regularization parameter therein, we propose the heuristic quasi-optimality principle and some modifications including the smoothness of the linear functionals. We prove convergence rates for the linear functional strategy with these heuristic rules taking into account the smoothness of the solution and the functionals and imposing a structural condition on the noise. Furthermore, we study these noise conditions in both a deterministic and stochastic setup and verify that for mildly-ill-posed problems and Gaussian noise, these conditions are satisfied almost surely, where on the contrary, in the severely-ill-posed case and in a similar setup, the corresponding noise condition fails to hold. Moreover, we propose an aggregation method for adaptively optimizing the parameter choice rule by making use of improved rates for linear functionals. Numerical results indicate that this method yields better results than the standard heuristic rule.
Moral heuristics.

PubMed

Sunstein, Cass R

2005-08-01

With respect to questions of fact, people use heuristics--mental short-cuts, or rules of thumb, that generally work well, but that also lead to systematic errors. People use moral heuristics too--moral short-cuts, or rules of thumb, that lead to mistaken and even absurd moral judgments. These judgments are highly relevant not only to morality, but to law and politics as well. examples are given from a number of domains, including risk regulation, punishment, reproduction and sexuality, and the act/omission distinction. in all of these contexts, rapid, intuitive judgments make a great deal of sense, but sometimes produce moral mistakes that are replicated in law and policy. One implication is that moral assessments ought not to be made by appealing to intuitions about exotic cases and problems; those intuitions are particularly unlikely to be reliable. Another implication is that some deeply held moral judgments are unsound if they are products of moral heuristics. The idea of error-prone heuristics is especially controversial in the moral domain, where agreement on the correct answer may be hard to elicit; but in many contexts, heuristics are at work and they do real damage. Moral framing effects, including those in the context of obligations to future generations, are also discussed.
Adaptive decision rules for the acquisition of nature reserves.

PubMed

Turner, Will R; Wilcove, David S

2006-04-01

Although reserve-design algorithms have shown promise for increasing the efficiency of conservation planning, recent work casts doubt on the usefulness of some of these approaches in practice. Using three data sets that vary widely in size and complexity, we compared various decision rules for acquiring reserve networks over multiyear periods. We explored three factors that are often important in real-world conservation efforts: uncertain availability of sites for acquisition, degradation of sites, and overall budget constraints. We evaluated the relative strengths and weaknesses of existing optimal and heuristic decision rules and developed a new set of adaptive decision rules that combine the strengths of existing optimal and heuristic approaches. All three of the new adaptive rules performed better than the existing rules we tested under virtually all scenarios of site availability, site degradation, and budget constraints. Moreover, the adaptive rules required no additional data beyond what was readily available and were relatively easy to compute.
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.
Parental investment: how an equity motive can produce inequality.

PubMed

Hertwig, Ralph; Davis, Jennifer Nerissa; Sulloway, Frank J

2002-09-01

The equity heuristic is a decision rule specifying that parents should attempt to subdivide resources more or less equally among their children. This investment rule coincides with the prescription from optimality models in economics and biology in cases in which expected future return for each offspring is equal. In this article, the authors present a counterintuitive implication of the equity heuristic: Whereas an equity motive produces a fair distribution at any given point in time, it yields a cumulative distribution of investments that is unequal. The authors test this analytical observation against evidence reported in studies exploring parental investment and show how the equity heuristic can provide an explanation of why the literature reports a diversity of birth order effects with respect to parental resource allocation.
A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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
Proposal of Heuristic Algorithm for Scheduling of Print Process in Auto Parts Supplier

NASA Astrophysics Data System (ADS)

Matsumoto, Shimpei; Okuhara, Koji; Ueno, Nobuyuki; Ishii, Hiroaki

We are interested in the print process on the manufacturing processes of auto parts supplier as an actual problem. The purpose of this research is to apply our scheduling technique developed in university to the actual print process in mass customization environment. Rationalization of the print process is depending on the lot sizing. The manufacturing lead time of the print process is long, and in the present method, production is done depending on worker’s experience and intuition. The construction of an efficient production system is urgent problem. Therefore, in this paper, in order to shorten the entire manufacturing lead time and to reduce the stock, we reexamine the usual method of the lot sizing rule based on heuristic technique, and we propose the improvement method which can plan a more efficient schedule.
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
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 ...
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.
Common-Sense Chemistry: The Use of Assumptions and Heuristics in Problem Solving

ERIC Educational Resources Information Center

Maeyer, Jenine Rachel

2013-01-01

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…
Beyond Decision Making: Cultural Ideology as Heuristic Paradigmatic Models.

ERIC Educational Resources Information Center

Whitley, L. Darrell

A paradigmatic model of cultural ideology provides a context for understanding the relationship between decision-making and personal and cultural rationality. Cultural rules or heuristics exist which indicate that many decisions can be made on the basis of established strategy rather than continual analytical calculations. When an optimal solution…
Extensional versus Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment.

ERIC Educational Resources Information Center

Tversky, Amos; Kahneman, Daniel

1983-01-01

Judgments under uncertainty are often mediated by intuitive heuristics that are not bound by the conjunction rule of probability. Representativeness and availability heuristics can make a conjunction appear more probable than one of its constituents. Alternative interpretations of this conjunction fallacy are discussed and attempts to combat it…
“The Golden Rule”: Only a starting point for quality care

PubMed Central

Corazzini, Kirsten N.; Lekan-Rutledge, Deborah; Utley-Smith, Queen; Piven, Mary L.; Colón-Emeric, Cathleen S.; Bailey, Donald; Ammarell, Natalie; Anderson, Ruth A.

2006-01-01

The Golden Rule guides people to choose for others what they would choose for themselves. The Golden Rule is often described as ‘putting yourself in someone else's shoes’, or ‘Do unto others as you would have them do unto you’(Baumrin 2004). The viewpoint held in the Golden Rule is noted in all the major world religions and cultures, suggesting that this may be an important moral truth (Cunningham 1998). The Golden Rule underlies acts of kindness, caring, and altruism that go above and beyond “business as usual” or “usual care” (Huang, 2005). As such, this heuristic or ‘rule of thumb’ has universal appeal and helps guide our behaviors toward the welfare of others. So why question the Golden Rule? Unless used mindfully, any heuristic can be overly-simplistic and lead to unintended, negative consequences. A heuristic is a rule of thumb that people use to simplify potentially overwhelming or complex events. These rules of thumb are largely unconscious, and occur irrespective of training and educational level (Gilovich, Griffin & Kahneman 2002). Rules of thumb, such as the Golden Rule, allow a person to reduce a complex situation to something manageable—e.g., ‘when in doubt, do what I would want done’. Because it is a simplifying tool, however, the Golden Rule may lead to inappropriate actions because important factors may be overlooked. In this article we describe “The Golden Rule” as used by administrators, supervisors, charge nurses, and CNAs in case studies of four nursing homes. By describing use of this rule-of-thumb, we aim to challenge nurses in nursing homes to: 1) be mindful of their use of “The Golden Rule” and its impact on staff and residents; and 2) help staff members think through how and why “The Golden Rule” may impact their relationships with staff and residents. PMID:17334452
Vervet monkey (Chlorocebus pygerythrus) behavior in a multi-destination route: Evidence for planning ahead when heuristics fail

PubMed Central

Smeltzer, Eve Ann

2018-01-01

Animal paths are analogous to intractable mathematical problems like the Traveling Salesman Problem (TSP) and the shortest path problem (SPP). Both the TSP and SPP require an individual to find the shortest path through multiple targets but the TSP demands a return to the start, while the SPP does not. Vervet monkeys are very efficient in solving TSPs but this species is a multiple central place forager that does not always return to the same sleeping site and thus theoretically should be selected to find solutions to SPPs rather than TSPs. We examined path choice by wild vervets in an SPP experimental array where the shortest paths usually differed from those consistent with common heuristic strategies, the nearest-neighbor rule (NNR–go to the closest resource that has not been visited), and the convex hull (put a mental loop around sites, adding inner targets in order of distance from the edge)–an efficient strategy for TSPs but not SPPs. In addition, humans solving SPPs use an initial segment strategy (ISS–choose the straightest path at the beginning, only turning when necessary) and we looked at vervet paths consistent with this strategy. In 615 trials by single foragers, paths usually conformed to the NNR and rarely the slightly more efficient convex hull, supporting that vervets may be selected to solve SPPs. Further, like humans solving SPPs, vervets showed a tendency to use the ISS. Paths consistent with heuristics dropped off sharply, and use of the shortest path increased, when heuristics led to longer paths showing trade-offs in efficiency versus cognitive load. Two individuals out of 17, found the shortest path most often, showing inter-individual variation in path planning. Given support for the NNR and the ISS, we propose a new rule-of-thumb termed the “region heuristic” that vervets may apply in multi-destination routes. PMID:29813105
Simply criminal: predicting burglars' occupancy decisions with a simple heuristic.

PubMed

Snook, Brent; Dhami, Mandeep K; Kavanagh, Jennifer M

2011-08-01

Rational choice theories of criminal decision making assume that offenders weight and integrate multiple cues when making decisions (i.e., are compensatory). We tested this assumption by comparing how well a compensatory strategy called Franklin's Rule captured burglars' decision policies regarding residence occupancy compared to a non-compensatory strategy (i.e., Matching Heuristic). Forty burglars each decided on the occupancy of 20 randomly selected photographs of residences (for which actual occupancy was known when the photo was taken). Participants also provided open-ended reports on the cues that influenced their decisions in each case, and then rated the importance of eight cues (e.g., deadbolt visible) over all decisions. Burglars predicted occupancy beyond chance levels. The Matching Heuristic was a significantly better predictor of burglars' decisions than Franklin's Rule, and cue use in the Matching Heuristic better corresponded to the cue ecological validities in the environment than cue use in Franklin's Rule. The most important cue in burglars' models was also the most ecologically valid or predictive of actual occupancy (i.e., vehicle present). The majority of burglars correctly identified the most important cue in their models, and the open-ended technique showed greater correspondence between self-reported and captured cue use than the rating over decision technique. Our findings support a limited rationality perspective to understanding criminal decision making, and have implications for crime prevention.
Relating Local to Global Spatial Knowledge: Heuristic Influence of Local Features on Direction Estimates

ERIC Educational Resources Information Center

Phillips, Daniel W.; Montello, Daniel R.

2015-01-01

Previous research has examined heuristics--simplified decision-making rules-of-thumb--for geospatial reasoning. This study examined at two locations the influence of beliefs about local coastline orientation on estimated directions to local and distant places; estimates were made immediately or after fifteen seconds. This study goes beyond…

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.
An innovative artificial bee colony algorithm and its application to a practical intercell scheduling problem

NASA Astrophysics Data System (ADS)

Li, Dongni; Guo, Rongtao; Zhan, Rongxin; Yin, Yong

2018-06-01

In this article, an innovative artificial bee colony (IABC) algorithm is proposed, which incorporates two mechanisms. On the one hand, to provide the evolutionary process with a higher starting level, genetic programming (GP) is used to generate heuristic rules by exploiting the elements that constitute the problem. On the other hand, to achieve a better balance between exploration and exploitation, a leading mechanism is proposed to attract individuals towards a promising region. To evaluate the performance of IABC in solving practical and complex problems, it is applied to the intercell scheduling problem with limited transportation capacity. It is observed that the GP-generated rules incorporate the elements of the most competing human-designed rules, and they are more effective than the human-designed ones. Regarding the leading mechanism, the strategies of the ageing leader and multiple challengers make the algorithm less likely to be trapped in local optima.
Sophisticated Approval Voting, Ignorance Priors, and Plurality Heuristics: A Behavioral Social Choice Analysis in a Thurstonian Framework

ERIC Educational Resources Information Center

Regenwetter, Michel; Ho, Moon-Ho R.; Tsetlin, Ilia

2007-01-01

This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two…
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.
After the Liverpool Care Pathway—development of heuristics to guide end of life care for people with dementia: protocol of the ALCP study

PubMed Central

Davies, N; Manthorpe, J; Sampson, E L; Iliffe, S

2015-01-01

Introduction End of life care guidance for people with dementia is lacking and this has been made more problematic in England with the removal of one of the main end of life care guidelines which offered some structure, the Liverpool Care Pathway. This guidance gap may be eased with the development of heuristics (rules of thumb) which offer a fast and frugal form of decision-making. Objective To develop a toolkit of heuristics (rules of thumb) for practitioners to use when caring for people with dementia at the end of life. Method and analysis A mixed-method study using a co-design approach to develop heuristics in three phases. In phase 1, we will conduct at least six focus groups with family carers, health and social care practitioners from both hospital and community care services, using the ‘think-aloud’ method to understand decision-making processes and to develop a set of heuristics. The focus group topic guide will be developed from the findings of a previous study of 46 interviews of family carers about quality end-of-life care for people with dementia and a review of the literature. A multidisciplinary development team of health and social care practitioners will synthesise the findings from the focus groups to devise and refine a toolkit of heuristics. Phase 2 will test the use of heuristics in practice in five sites: one general practice, one community nursing team, one hospital ward and two palliative care teams working in the community. Phase 3 will evaluate and further refine the toolkit of heuristics through group interviews, online questionnaires and semistructured interviews. Ethics and dissemination This study has received ethical approval from a local NHS research ethics committee (Rec ref: 15/LO/0156). The findings of this study will be presented in peer-reviewed publications and national and international conferences. PMID:26338688
An Exploration of Administrative Heuristics in the United States and the United Kingdom

ERIC Educational Resources Information Center

English, Fenwick W.; Bolton, Cheryl L.

2008-01-01

This article is a report on a study of the use of heuristics, shortcuts, and rules of thumb by middle-line managers in institutions of higher education in the United States and the United Kingdom. Using a nonprobability convenience sample, the coinvestigators interviewed 13 middle-line managers over 5 months from eight institutions. The results…
Pareto 80/20 Law: Derivation via Random Partitioning

ERIC Educational Resources Information Center

Lipovetsky, Stan

2009-01-01

The Pareto 80/20 Rule, also known as the Pareto principle or law, states that a small number of causes (20%) is responsible for a large percentage (80%) of the effect. Although widely recognized as a heuristic rule, this proportion has not been theoretically based. The article considers derivation of this 80/20 rule and some other standard…
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.
A co-design process developing heuristics for practitioners providing end of life care for people with dementia.

PubMed

Davies, Nathan; Mathew, Rammya; Wilcock, Jane; Manthorpe, Jill; Sampson, Elizabeth L; Lamahewa, Kethakie; Iliffe, Steve

2016-08-02

The end of life for someone with dementia can present many challenges for practitioners; such as, providing care if there are swallowing difficulties. This study aimed to develop a toolkit of heuristics (rules-of-thumb) to aid practitioners making end-of-life care decisions for people with dementia. An iterative co-design approach was adopted using a literature review and qualitative methods, including; 1) qualitative interviews and focus groups with family carers and 2) focus groups with health and care professionals. Family carers were recruited from a national charity, purposively sampling those with experience of end-of-life care for a person with dementia. Health and care professionals were purposively sampled to include a broad range of expertise including; general practitioners, palliative care specialists, and geriatricians. A co-design group was established consisting of health and social care experts and family carers, to synthesise the findings from the qualitative work and produce a toolkit of heuristics to be tested in practice. Four broad areas were identified as requiring complex decisions at the end of life; 1) eating/swallowing difficulties, 2) agitation/restlessness, 3) ending life-sustaining treatment, and 4) providing "routine care" at the end of life. Each topic became a heuristic consisting of rules arranged into flowcharts. Eating/swallowing difficulties have three rules; ensuring eating/swallowing difficulties do not come as a surprise, considering if the situation is an emergency, and considering 'comfort feeding' only versus time-trialled artificial feeding. Agitation/restlessness encourages a holistic approach, considering the environment, physical causes, and the carer's wellbeing. Ending life-sustaining treatment supports practitioners through a process of considering the benefits of treatment versus quality-of-life and comfort. Finally, a heuristic on providing routine care such as bathing, prompts practitioners to consider adapting the delivery of care, in order to promote comfort and dignity at the end of life. The heuristics are easy to use and remember, offering a novel approach to decision making for dementia end-of-life care. They have the potential to be used alongside existing end-of-life care recommendations, adding more readily available practical assistance. This is the first study to synthesise experience and existing evidence into easy-to-use heuristics for dementia end-of-life care.
Age Effects and Heuristics in Decision Making*

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects. PMID:22544977
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.
Age Effects and Heuristics in Decision Making.

PubMed

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2012-05-01

Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects.
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 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.
Intuitive and deliberate judgments are based on common principles.

PubMed

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, and rational processes (assumed to characterize deliberate judgments). In contrast, we provide convergent arguments and evidence for a unified theoretical approach to both intuitive and deliberative judgments. Both are rule-based, and in fact, the very same rules can underlie both intuitive and deliberate judgments. The important open question is that of rule selection, and we propose a 2-step process in which the task itself and the individual's memory constrain the set of applicable rules, whereas the individual's processing potential and the (perceived) ecological rationality of the rule for the task guide the final selection from that set. Deliberate judgments are not generally more accurate than intuitive judgments; in both cases, accuracy depends on the match between rule and environment: the rules' ecological rationality. Heuristics that are less effortful and in which parts of the information are ignored can be more accurate than cognitive strategies that have more information and computation. The proposed framework adumbrates a unified approach that specifies the critical dimensions on which judgmental situations may vary and the environmental conditions under which rules can be expected to be successful.
Bargmann's theorem and position-dependent effective mass

NASA Astrophysics Data System (ADS)

Kawamura, Kiyoshi; Brown, Ronald A.

1988-03-01

The physical significance of Galilean transformations applied to effective-mass (EM) equations for Bloch electrons in Wannier representation is discussed and contrasted with that of Galilean coordinate transformations applied to the free-particle Schrödinger equation. Mass constraints imposed on the latter by Bargmann's (1954) superselection rule do not extend to the EM, and criticisms of the position-dependent EM concept which have invoked Bargmann's theorem are shown to be without foundation. Other criticisms concerning the nonuniqueness and non-Hermiticity of effective Hamiltonians which employ this concept to describe crystals of graded composition are discussed, and it is argued that the problems are associated with the heuristic nature of the virtual-crystal model which is adopted rather than with the position-dependent EM.
Plausible inference: A multi-valued logic for problem solving

NASA Technical Reports Server (NTRS)

Friedman, L.

1979-01-01

A new logic is developed which permits continuously variable strength of belief in the truth of assertions. Four inference rules result, with formal logic as a limiting case. Quantification of belief is defined. Propagation of belief to linked assertions results from dependency-based techniques of truth maintenance so that local consistency is achieved or contradiction discovered in problem solving. Rules for combining, confirming, or disconfirming beliefs are given, and several heuristics are suggested that apply to revising already formed beliefs in the light of new evidence. The strength of belief that results in such revisions based on conflicting evidence are a highly subjective phenomenon. Certain quantification rules appear to reflect an orderliness in the subjectivity. Several examples of reasoning by plausible inference are given, including a legal example and one from robot learning. Propagation of belief takes place in directions forbidden in formal logic and this results in conclusions becoming possible for a given set of assertions that are not reachable by formal logic.
HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

PubMed

Kim, J; Kasabov, N

1999-11-01

This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.
SYSTEMATIZATION OF MASS LEVELS OF PARTICLES AND RESONANCES ON HEURISTIC BASIS

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

Takabayasi, T.

1963-12-16

Once more a scheme of simple mass rules and formulas for particles and resonant levels is investigated and organized, based on some general hypotheses. The essential ingredients in the scheme are, on one hand, the equalinterval rule governing the isosinglet meson series, associated with particularly simple mass ratio between the 2/sup ++/ level f and 0/sup ++/ level ABC, and on the other a new basic mass formula that unifies some of the meson and baryon levels. The whole baryon levels are arranged in a table analogous to the periodic table, and then correspondences between different series and equivalence betweenmore » spin and hypercharge, when properly applied, just fix the whole baryon mass spectrum in good agreement with observations. Connections with the scheme of mass formulas formerly given are also shown. (auth)« less

Heuristic extraction of rules in pruned artificial neural networks models used for quantifying highly overlapping chromatographic peaks.

PubMed

Hervás, César; Silva, Manuel; Serrano, Juan Manuel; Orejuela, Eva

2004-01-01

The suitability of an approach for extracting heuristic rules from trained artificial neural networks (ANNs) pruned by a regularization method and with architectures designed by evolutionary computation for quantifying highly overlapping chromatographic peaks is demonstrated. The ANN input data are estimated by the Levenberg-Marquardt method in the form of a four-parameter Weibull curve associated with the profile of the chromatographic band. To test this approach, two N-methylcarbamate pesticides, carbofuran and propoxur, were quantified using a classic peroxyoxalate chemiluminescence reaction as a detection system for chromatographic analysis. Straightforward network topologies (one and two outputs models) allow the analytes to be quantified in concentration ratios ranging from 1:7 to 5:1 with an average standard error of prediction for the generalization test of 2.7 and 2.3% for carbofuran and propoxur, respectively. The reduced dimensions of the selected ANN architectures, especially those obtained after using heuristic rules, allowed simple quantification equations to be developed that transform the input variables into output variables. These equations can be easily interpreted from a chemical point of view to attain quantitative analytical information regarding the effect of both analytes on the characteristics of chromatographic bands, namely profile, dispersion, peak height, and residence time. Copyright 2004 American Chemical Society
Selecting Pesticides and Nonchemical Alternatives: Green Thumbs' Rules of Thumb Decision Tools.

ERIC Educational Resources Information Center

Grieshop, James I.; And Others

1992-01-01

A sample of 78 (of 320) home gardeners use rules of thumb (heuristics) to choose between chemical pesticides and nonchemical alternatives. Pesticides rank low in 24 choice attributes where alternatives rank high, and vice versa. Gender, age, and years of pesticide use correlate with pesticide selection. (SK)
Notions of "Generation" in Rhetorical Studies.

ERIC Educational Resources Information Center

Young, Richard

A study of the meanings of "generation," a popular term in current rhetorical jargon, reveals important developments in the art and theory of rhetoric. As now used, it refers without clear distinction to rule-governed, heuristic, and trial-and-error procedures. The rule-governed procedures of transformation grammar are being employed to…
Survey of Literature Pertaining to Decision Making Styles and Individual Factors

DTIC Science & Technology

2005-10-01

facilitation Rules of engagement (ROE) Deductive reasoning Heuristic(s) Emotion/ Affect Consensus Time pressure Rational decision making Recognition...managers are more likely to use an intuitive decision making style, while Sensing/ Feeling types use more of a rational style. These results were also...performance of the individual, team and organization. Research has indicated that a variety of individual factors affect the way in which people make
Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm

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

Kobayashi, Yoko; Aiyoshi, Eitaro

2002-10-15

A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies suchmore » as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained.« less
Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations.

PubMed

Branke, Jürgen; Hildebrandt, Torsten; Scholz-Reiter, Bernd

2015-01-01

Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by experts in a time consuming trial-and-error process. Recently, evolutionary algorithms have been proposed to automate the design process. There are several possibilities to represent rules for this hyper-heuristic search. Because the representation determines the search neighborhood and the complexity of the rules that can be evolved, a suitable choice of representation is key for a successful evolutionary algorithm. In this paper we empirically compare three different representations, both numeric and symbolic, for automated rule design: A linear combination of attributes, a representation based on artificial neural networks, and a tree representation. Using appropriate evolutionary algorithms (CMA-ES for the neural network and linear representations, genetic programming for the tree representation), we empirically investigate the suitability of each representation in a dynamic stochastic job shop scenario. We also examine the robustness of the evolved dispatching rules against variations in the underlying job shop scenario, and visualize what the rules do, in order to get an intuitive understanding of their inner workings. Results indicate that the tree representation using an improved version of genetic programming gives the best results if many candidate rules can be evaluated, closely followed by the neural network representation that already leads to good results for small to moderate computational budgets. The linear representation is found to be competitive only for extremely small computational budgets.
After the Liverpool Care Pathway--development of heuristics to guide end of life care for people with dementia: protocol of the ALCP study.

PubMed

Davies, N; Manthorpe, J; Sampson, E L; Iliffe, S

2015-09-02

End of life care guidance for people with dementia is lacking and this has been made more problematic in England with the removal of one of the main end of life care guidelines which offered some structure, the Liverpool Care Pathway. This guidance gap may be eased with the development of heuristics (rules of thumb) which offer a fast and frugal form of decision-making. To develop a toolkit of heuristics (rules of thumb) for practitioners to use when caring for people with dementia at the end of life. A mixed-method study using a co-design approach to develop heuristics in three phases. In phase 1, we will conduct at least six focus groups with family carers, health and social care practitioners from both hospital and community care services, using the 'think-aloud' method to understand decision-making processes and to develop a set of heuristics. The focus group topic guide will be developed from the findings of a previous study of 46 interviews of family carers about quality end-of-life care for people with dementia and a review of the literature. A multidisciplinary development team of health and social care practitioners will synthesise the findings from the focus groups to devise and refine a toolkit of heuristics. Phase 2 will test the use of heuristics in practice in five sites: one general practice, one community nursing team, one hospital ward and two palliative care teams working in the community. Phase 3 will evaluate and further refine the toolkit of heuristics through group interviews, online questionnaires and semistructured interviews. This study has received ethical approval from a local NHS research ethics committee (Rec ref: 15/LO/0156). The findings of this study will be presented in peer-reviewed publications and national and international conferences. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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.
Brain Mechanisms for Making, Breaking, and Changing Rules

NASA Astrophysics Data System (ADS)

Levine, Daniel S.

Individuals differ widely, and the same person varies over time, in their tendency to seek maximum information versus their tendency to follow the simplest heuristics. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge maximization and heuristic simplification. The amygdala is more activated in individuals who use primitive heuristics, whereas two areas of the frontal lobes are more activated in individuals with a strong knowledge drive: one area involved in detecting risk or conflict, and another involved in choosing task-appropriate responses. Both of these motivations have engineering uses. There is benefit to understanding a situation at a high enough level to respond in a flexible manner when the context is complex and time allows detailed consideration. Yet simplifying heuristics can yield benefits when the context is routine or when time is limited.
Planning 3-D collision-free paths using spheres

NASA Technical Reports Server (NTRS)

Bonner, Susan; Kelley, Robert B.

1989-01-01

A scheme for the representation of objects, the Successive Spherical Approximation (SSA), facilitates the rapid planning of collision-free paths in a 3-D, dynamic environment. The hierarchical nature of the SSA allows collision-free paths to be determined efficiently while still providing for the exact representation of dynamic objects. The concept of a freespace cell is introduced to allow human 3-D conceptual knowledge to be used in facilitating satisfying choices for paths. Collisions can be detected at a rate better than 1 second per environment object per path. This speed enables the path planning process to apply a hierarchy of rules to create a heuristically satisfying collision-free path.
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.
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
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.
Search asymmetries: parallel processing of uncertain sensory information.

PubMed

Vincent, Benjamin T

2011-08-01

What is the mechanism underlying search phenomena such as search asymmetry? Two-stage models such as Feature Integration Theory and Guided Search propose parallel pre-attentive processing followed by serial post-attentive processing. They claim search asymmetry effects are indicative of finding pairs of features, one processed in parallel, the other in serial. An alternative proposal is that a 1-stage parallel process is responsible, and search asymmetries occur when one stimulus has greater internal uncertainty associated with it than another. While the latter account is simpler, only a few studies have set out to empirically test its quantitative predictions, and many researchers still subscribe to the 2-stage account. This paper examines three separate parallel models (Bayesian optimal observer, max rule, and a heuristic decision rule). All three parallel models can account for search asymmetry effects and I conclude that either people can optimally utilise the uncertain sensory data available to them, or are able to select heuristic decision rules which approximate optimal performance. Copyright © 2011 Elsevier Ltd. All rights reserved.
An investigation of the use of temporal decomposition in space mission scheduling

NASA Technical Reports Server (NTRS)

Bullington, Stanley E.; Narayanan, Venkat

1994-01-01

This research involves an examination of techniques for solving scheduling problems in long-duration space missions. The mission timeline is broken up into several time segments, which are then scheduled incrementally. Three methods are presented for identifying the activities that are to be attempted within these segments. The first method is a mathematical model, which is presented primarily to illustrate the structure of the temporal decomposition problem. Since the mathematical model is bound to be computationally prohibitive for realistic problems, two heuristic assignment procedures are also presented. The first heuristic method is based on dispatching rules for activity selection, and the second heuristic assigns performances of a model evenly over timeline segments. These heuristics are tested using a sample Space Station mission and a Spacelab mission. The results are compared with those obtained by scheduling the missions without any problem decomposition. The applicability of this approach to large-scale mission scheduling problems is also discussed.
Anytime synthetic projection: Maximizing the probability of goal satisfaction

NASA Technical Reports Server (NTRS)

Drummond, Mark; Bresina, John L.

1990-01-01

A projection algorithm is presented for incremental control rule synthesis. The algorithm synthesizes an initial set of goal achieving control rules using a combination of situation probability and estimated remaining work as a search heuristic. This set of control rules has a certain probability of satisfying the given goal. The probability is incrementally increased by synthesizing additional control rules to handle 'error' situations the execution system is likely to encounter when following the initial control rules. By using situation probabilities, the algorithm achieves a computationally effective balance between the limited robustness of triangle tables and the absolute robustness of universal plans.
Heuristics in primary care for recognition of unreported vision loss in older people: a technology development study.

PubMed

Wijeyekoon, Skanda; Kharicha, Kalpa; Iliffe, Steve

2015-09-01

To evaluate heuristics (rules of thumb) for recognition of undetected vision loss in older patients in primary care. Vision loss is associated with ageing, and its prevalence is increasing. Visual impairment has a broad impact on health, functioning and well-being. Unrecognised vision loss remains common, and screening interventions have yet to reduce its prevalence. An alternative approach is to enhance practitioners' skills in recognising undetected vision loss, by having a more detailed picture of those who are likely not to act on vision changes, report symptoms or have eye tests. This paper describes a qualitative technology development study to evaluate heuristics for recognition of undetected vision loss in older patients in primary care. Using a previous modelling study, two heuristics in the form of mnemonics were developed to aid pattern recognition and allow general practitioners to identify potential cases of unreported vision loss. These heuristics were then analysed with experts. Findings It was concluded that their implementation in modern general practice was unsuitable and an alternative solution should be sort.
Are children conservative, liberal, or metacognitive? Preliminary evidence for the involvement of the distinctiveness heuristic in decision making.

PubMed

Geurten, Marie; Willems, Sylvie; Meulemans, Thierry

2015-04-01

The experiment tested whether young children are able to reduce their false recognition rate after distinctive encoding by implementing a strategic metacognitive rule. The participants, 72 children aged 4, 6, and 9 years, studied two lists of unrelated items. One of these lists was visually displayed (picture condition), whereas the other was presented auditorily (word condition). After each study phase, participants completed recognition tests. Finally, they answered questions about their explicit knowledge of the distinctive encoding effect. The results revealed that even the youngest children in our sample showed a smaller proportion of intrusions in the picture condition than in the word condition. Furthermore, the results of the signal detection analyses were consistent with the hypothesis that the lower rate of false recognitions after picture encoding results from the implementation of a conservative response criterion based on metacognitive expectations (distinctiveness heuristic). Moreover, the absence of correlation between children's explicit knowledge of the distinctiveness rule and their effective use of this metacognitive heuristic seems to indicate that its involvement in memory decisions could be mediated by implicit mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.
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.
Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

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.
Understanding Singular Vectors

ERIC Educational Resources Information Center

James, David; Botteron, Cynthia

2013-01-01

matrix yields a surprisingly simple, heuristical approximation to its singular vectors. There are correspondingly good approximations to the singular values. Such rules of thumb provide an intuitive interpretation of the singular vectors that helps explain why the SVD is so…
The Attitude Heuristic and Selective Fact Identification.

ERIC Educational Resources Information Center

Pratkanis, Anthony R.

The effects of attitudes on social memory have not been determined. Some studies have shown attitudes to serve as a heuristic for estimating an answer about past behavior. When an attitude heuristic is applied to recall of an event, "memory" will appear to be "superior," to the extent that the subject's inferences and constructions coincide with…
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.
Better Decomposition Heuristics for the Maximum-Weight Connected Graph Problem Using Betweenness Centrality

NASA Astrophysics Data System (ADS)

Yamamoto, Takanori; Bannai, Hideo; Nagasaki, Masao; Miyano, Satoru

We present new decomposition heuristics for finding the optimal solution for the maximum-weight connected graph problem, which is known to be NP-hard. Previous optimal algorithms for solving the problem decompose the input graph into subgraphs using heuristics based on node degree. We propose new heuristics based on betweenness centrality measures, and show through computational experiments that our new heuristics tend to reduce the number of subgraphs in the decomposition, and therefore could lead to the reduction in computational time for finding the optimal solution. The method is further applied to analysis of biological pathway data.
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.
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
Solving the Container Stowage Problem (CSP) using Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Matsaini; Santosa, Budi

2018-04-01

Container Stowage Problem (CSP) is a problem of containers arrangement into ships by considering rules such as: total weight, weight of one stack, destination, equilibrium, and placement of containers on vessel. Container stowage problem is combinatorial problem and hard to solve with enumeration technique. It is an NP-Hard Problem. Therefore, to find a solution, metaheuristics is preferred. The objective of solving the problem is to minimize the amount of shifting such that the unloading time is minimized. Particle Swarm Optimization (PSO) is proposed to solve the problem. The implementation of PSO is combined with some steps which are stack position change rules, stack changes based on destination, and stack changes based on the weight type of the stacks (light, medium, and heavy). The proposed method was applied on five different cases. The results were compared to Bee Swarm Optimization (BSO) and heuristics method. PSO provided mean of 0.87% gap and time gap of 60 second. While BSO provided mean of 2,98% gap and 459,6 second to the heuristcs.
Adaptive time-variant models for fuzzy-time-series forecasting.

PubMed

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.
Negative Example Selection for Protein Function Prediction: The NoGO Database

PubMed Central

Youngs, Noah; Penfold-Brown, Duncan; Bonneau, Richard; Shasha, Dennis

2014-01-01

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html). PMID:24922051
Parental Explicit Heuristics in Decision-making for Children With Life-threatening Illnesses

PubMed Central

Renjilian, Chris B.; Womer, James W.; Carroll, Karen W.; Kang, Tammy I.

2013-01-01

OBJECTIVE: To identify and illustrate common explicit heuristics (decision-making aids or shortcuts expressed verbally as terse rules of thumb, aphorisms, maxims, or mantras and intended to convey a compelling truth or guiding principle) used by parents of children with life-threatening illnesses when confronting and making medical decisions. METHODS: Prospective cross-sectional observational study of 69 parents of 46 children who participated in the Decision-making in Pediatric Palliative Care Study between 2006 and 2008 at the Children’s Hospital of Philadelphia. Parents were guided individually through a semistructured in-depth interview about their experiences and thoughts regarding making medical decisions on behalf of their ill children, and the transcribed interviews were qualitatively analyzed. RESULTS: All parents in our study employed explicit heuristics in interviews about decision-making for their children, with the number of identified explicit heuristics used by an individual parent ranging from tens to hundreds. The heuristics served 5 general functions: (1) to depict or facilitate understanding of a complex situation; (2) to clarify, organize, and focus pertinent information and values; (3) to serve as a decision-making compass; (4) to communicate with others about a complex topic; and (5) to justify a choice. CONCLUSIONS: Explicit heuristics played an important role in decision-making and communication about decision-making in our population of parents. Recognizing explicit heuristics in parent interactions and understanding their content and functions can aid clinicians in their efforts to partner with parents in the decision-making process. PMID:23319524
Parental explicit heuristics in decision-making for children with life-threatening illnesses.

PubMed

Renjilian, Chris B; Womer, James W; Carroll, Karen W; Kang, Tammy I; Feudtner, Chris

2013-02-01

To identify and illustrate common explicit heuristics (decision-making aids or shortcuts expressed verbally as terse rules of thumb, aphorisms, maxims, or mantras and intended to convey a compelling truth or guiding principle) used by parents of children with life-threatening illnesses when confronting and making medical decisions. Prospective cross-sectional observational study of 69 parents of 46 children who participated in the Decision-making in Pediatric Palliative Care Study between 2006 and 2008 at the Children's Hospital of Philadelphia. Parents were guided individually through a semistructured in-depth interview about their experiences and thoughts regarding making medical decisions on behalf of their ill children, and the transcribed interviews were qualitatively analyzed. All parents in our study employed explicit heuristics in interviews about decision-making for their children, with the number of identified explicit heuristics used by an individual parent ranging from tens to hundreds. The heuristics served 5 general functions: (1) to depict or facilitate understanding of a complex situation; (2) to clarify, organize, and focus pertinent information and values; (3) to serve as a decision-making compass; (4) to communicate with others about a complex topic; and (5) to justify a choice. Explicit heuristics played an important role in decision-making and communication about decision-making in our population of parents. Recognizing explicit heuristics in parent interactions and understanding their content and functions can aid clinicians in their efforts to partner with parents in the decision-making process.
A new chaotic multi-verse optimization algorithm for solving engineering optimization problems

NASA Astrophysics Data System (ADS)

Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella

2018-03-01

Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.
Navigating a Mobile Robot Across Terrain Using Fuzzy Logic

NASA Technical Reports Server (NTRS)

Seraji, Homayoun; Howard, Ayanna; Bon, Bruce

2003-01-01

A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.
Heuristics Applied in the Development of Advanced Space Mission Concepts

NASA Technical Reports Server (NTRS)

Nilsen, Erik N.

1998-01-01

Advanced mission studies are the first step in determining the feasibility of a given space exploration concept. A space scientist develops a science goal in the exploration of space. This may be a new observation method, a new instrument or a mission concept to explore a solar system body. In order to determine the feasibility of a deep space mission, a concept study is convened to determine the technology needs and estimated cost of performing that mission. Heuristics are one method of defining viable mission and systems architectures that can be assessed for technology readiness and cost. Developing a viable architecture depends to a large extent upon extending the existing body of knowledge, and applying it in new and novel ways. These heuristics have evolved over time to include methods for estimating technical complexity, technology development, cost modeling and mission risk in the unique context of deep space missions. This paper examines the processes involved in performing these advanced concepts studies, and analyzes the application of heuristics in the development of an advanced in-situ planetary mission. The Venus Surface Sample Return mission study provides a context for the examination of the heuristics applied in the development of the mission and systems architecture. This study is illustrative of the effort involved in the initial assessment of an advance mission concept, and the knowledge and tools that are applied.
The numerical modelling and process simulation for the fault diagnosis of rotary kiln incinerator.

PubMed

Roh, S D; Kim, S W; Cho, W S

2001-10-01

The numerical modelling and process simulation for the fault diagnosis of rotary kiln incinerator were accomplished. In the numerical modelling, two models applied to the modelling within the kiln are the combustion chamber model including the mass and energy balance equations for two combustion chambers and 3D thermal model. The combustion chamber model predicts temperature within the kiln, flue gas composition, flux and heat of combustion. Using the combustion chamber model and 3D thermal model, the production-rules for the process simulation can be obtained through interrelation analysis between control and operation variables. The process simulation of the kiln is operated with the production-rules for automatic operation. The process simulation aims to provide fundamental solutions to the problems in incineration process by introducing an online expert control system to provide an integrity in process control and management. Knowledge-based expert control systems use symbolic logic and heuristic rules to find solutions for various types of problems. It was implemented to be a hybrid intelligent expert control system by mutually connecting with the process control systems which has the capability of process diagnosis, analysis and control.
Generalizing a model beyond the inherence heuristic and applying it to beliefs about objective value.

PubMed

Wood, Graham

2014-10-01

The inherence heuristic is characterized as part of an instantiation of a more general model that describes the interaction between undeveloped intuitions, produced by System 1 heuristics, and developed beliefs, constructed by System 2 reasoning. The general model is described and illustrated by examining another instantiation of the process that constructs belief in objective moral value.
Automatic extraction of road features in urban environments using dense ALS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Truong-Hong, Linh; Riveiro, Belén; Laefer, Debra

2018-02-01

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.

Extension of the firefly algorithm and preference rules for solving MINLP problems

NASA Astrophysics Data System (ADS)

Costa, M. Fernanda P.; Francisco, Rogério B.; Rocha, Ana Maria A. C.; Fernandes, Edite M. G. P.

2017-07-01

An extension of the firefly algorithm (FA) for solving mixed-integer nonlinear programming (MINLP) problems is presented. Although penalty functions are nowadays frequently used to handle integrality conditions and inequality and equality constraints, this paper proposes the implementation within the FA of a simple rounded-based heuristic and four preference rules to find and converge to MINLP feasible solutions. Preliminary numerical experiments are carried out to validate the proposed methodology.
Cognitive biases and decision making in gambling.

PubMed

Chóliz, Mariano

2010-08-01

Heuristics and cognitive biases can occur in reasoning and decision making. Some of them are very common in gamblers (illusion of control, representativeness, availability, etc.). Structural characteristics and functioning of games of chance favor the appearance of these biases. Two experiments were conducted with nonpathological gamblers. The first experiment was a game of dice with wagers. In the second experiment, the participants played two bingo games. Specific rules of the games favored the appearance of cognitive bias (illusion of control) and heuristics (representativeness and availability) and influence on the bets. Results and implications for gambling are discussed.
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.
Answer First: Applying the Heuristic-Analytic Theory of Reasoning to Examine Student Intuitive Thinking in the Context of Physics

ERIC Educational Resources Information Center

Kryjevskaia, Mila; Stetzer, MacKenzie R.; Grosz, Nathaniel

2014-01-01

We have applied the heuristic-analytic theory of reasoning to interpret inconsistencies in student reasoning approaches to physics problems. This study was motivated by an emerging body of evidence that suggests that student conceptual and reasoning competence demonstrated on one task often fails to be exhibited on another. Indeed, even after…
INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS.

PubMed

Villar, Sofía S

2016-01-01

Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects' state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics.
INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS

PubMed Central

Villar, Sofía S.

2016-01-01

Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects’ state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics. PMID:27212781
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).
An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller

ERIC Educational Resources Information Center

Mamdani, E. H.; Assilian, S.

1975-01-01

This paper describes an experiment on the "linguistic" synthesis of a controller for a model industrial plant (a steam engine). Fuzzy logic is used to convert heuristic control rules stated by a human operator into an automatic control strategy. (Author)
Administrative Decision Making and Quasi Decision Making: An Empirical Study Using the Protocol Method.

ERIC Educational Resources Information Center

Fraser, Hugh W.; Anderson, Mary E.

1982-01-01

This exploratory study attempted to identify variables in need of further investigation. Those to emerge included heuristics or rules of thumb used by administrators in decision making, personality variables, and methods for evaluating alternatives. (Author/JM)
A lack of appetite for information and computation. Simple heuristics in food choice.

PubMed

Schulte-Mecklenbeck, Michael; Sohn, Matthias; de Bellis, Emanuel; Martin, Nathalie; Hertwig, Ralph

2013-12-01

The predominant, but largely untested, assumption in research on food choice is that people obey the classic commandments of rational behavior: they carefully look up every piece of relevant information, weight each piece according to subjective importance, and then combine them into a judgment or choice. In real world situations, however, the available time, motivation, and computational resources may simply not suffice to keep these commandments. Indeed, there is a large body of research suggesting that human choice is often better accommodated by heuristics-simple rules that enable decision making on the basis of a few, but important, pieces of information. We investigated the prevalence of such heuristics in a computerized experiment that engaged participants in a series of choices between two lunch dishes. Employing MouselabWeb, a process-tracing technique, we found that simple heuristics described an overwhelmingly large proportion of choices, whereas strategies traditionally deemed rational were barely apparent in our data. Replicating previous findings, we also observed that visual stimulus segments received a much larger proportion of attention than any nutritional values did. Our results suggest that, consistent with human behavior in other domains, people make their food choices on the basis of simple and informationally frugal heuristics. Copyright © 2013 Elsevier Ltd. All rights reserved.
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
A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811
Heuristic rule for binary superlattice coassembly: mixed plastic mesophases of hard polyhedral nanoparticles.

PubMed

Khadilkar, Mihir R; Escobedo, Fernando A

2014-10-17

Sought-after ordered structures of mixtures of hard anisotropic nanoparticles can often be thermodynamically unfavorable due to the components' geometric incompatibility to densely pack into regular lattices. A simple compatibilization rule is identified wherein the particle sizes are chosen such that the order-disorder transition pressures of the pure components match (and the entropies of the ordered phases are similar). Using this rule with representative polyhedra from the truncated-cube family that form pure-component plastic crystals, Monte Carlo simulations show the formation of plastic-solid solutions for all compositions and for a wide range of volume fractions.
C-Language Integrated Production System, Version 5.1

NASA Technical Reports Server (NTRS)

Riley, Gary; Donnell, Brian; Ly, Huyen-Anh VU; Culbert, Chris; Savely, Robert T.; Mccoy, Daniel J.; Giarratano, Joseph

1992-01-01

CLIPS 5.1 provides cohesive software tool for handling wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented, and procedural. Rule-based programming provides representation of knowledge by use of heuristics. Object-oriented programming enables modeling of complex systems as modular components. Procedural programming enables CLIPS to represent knowledge in ways similar to those allowed in such languages as C, Pascal, Ada, and LISP. Working with CLIPS 5.1, one can develop expert-system software by use of rule-based programming only, object-oriented programming only, procedural programming only, or combinations of the three.
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,…
Memory Efficient Ranking.

ERIC Educational Resources Information Center

Moffat, Alistair; And Others

1994-01-01

Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…
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.
Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.
Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

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.
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
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.
A Plea for Process in Personality Prevarication

PubMed Central

Kuncel, Nathan R.; Goldberg, Lewis R.; Kiger, Tom

2011-01-01

We make a series recommendations for focusing research on personality test faking. Overall we suggest that a focus on the response process test takers go through will accelerate our understanding of faking behavior. We argue that the decision making process for faking must be simple and dependent on a modest set of decision rules or heuristics. The set of heuristics used by any given test taker will, in turn, be the result of test taker goals and situational press. By focusing in on what the test taker is doing we will avoid adopting the wrong frame of reference and, hopefully, make ever more rapid progress. PMID:21966260
Strategies for diagnosing leg oedema in primary care: a qualitative study of GPs' approaches.

PubMed

Diederich, Judith; Hartel, Simone; Baum, Erika; Bösner, Stefan

2014-12-01

The symptom leg oedema represents a broad range of possible underlying aetiologies. The background of leg oedema is multifactorial and usually the GP is the first contact point for patients presenting with this symptom. GPs rely on patient history and physical examination as their main diagnostic tools. To identify GPs' diagnostic approaches and heuristics in patients presenting with leg oedema. Interviews with 15 GPs (20-30 min) using a semi-structured interview-guideline were conducted. GPs described their individual diagnostic strategies concerning all patients presenting with leg oedema they had prospectively identified during the previous four weeks. Interviews were taped and transcribed verbatim. Qualitative analysis was conducted by two independent raters. GPs applied a variety of diagnostic approaches, which can be grouped in active and passive strategies. Active strategies comprised the use of decision rules and guidelines, Bayesian arguing, problem dichotomisation and discrepancy heuristics. Passive approaches included test of time, therapy as diagnosis, and taking patient assumptions into account. When dealing with leg oedema, GPs use prior information of individual patients in a specific way. There is a broad variety of diagnostic approaches that can be grouped in 'active' and 'passive' behaviour. Approaches mostly match with established diagnostic strategies in primary care.
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.
HYPO: A Precedent-Based Legal Reasoner

DTIC Science & Technology

1987-11-01

identify legal issues in the analysis of law school exam- ination fact patterns involving the contracts law of offer and acceptance. The program...primarily used i’-then rules and an ATN to represent its legal knowledge of contract law . It used heuristics for distinguishing "hard" and "easy" legal...similar to Gardner’s. Also, the use of rules in Meldmdn (to define the elements of a claim) and Gardner (to define ingredients of contract law ) are similar
Bandit strategies evaluated in the context of clinical trials in rare life-threatening diseases.

PubMed

Villar, Sofía S

2018-04-01

In a rare life-threatening disease setting the number of patients in the trial is a high proportion of all patients with the condition (if not all of them). Further, this number is usually not enough to guarantee the required statistical power to detect a treatment effect of a meaningful size. In such a context, the idea of prioritizing patient benefit over hypothesis testing as the goal of the trial can lead to a trial design that produces useful information to guide treatment, even if it does not do so with the standard levels of statistical confidence. The idealised model to consider such an optimal design of a clinical trial is known as a classic multi-armed bandit problem with a finite patient horizon and a patient benefit objective function. Such a design maximises patient benefit by balancing the learning and earning goals as data accumulates and given the patient horizon. On the other hand, optimally solving such a model has a very high computational cost (many times prohibitive) and more importantly, a cumbersome implementation, even for populations as small as a hundred patients. Several computationally feasible heuristic rules to address this problem have been proposed over the last 40 years in the literature. In this article we study a novel heuristic approach to solve it based on the reformulation of the problem as a Restless bandit problem and the derivation of its corresponding Whittle index rule. Such rule was recently proposed in the context of a clinical trial in Villar et al (2015). We perform extensive computational studies to compare through both exact value calculations and simulated values the performance of this rule, other index rules and simpler heuristics previously proposed in the literature. Our results suggest that for the two and three-armed case and a patient horizon less or equal than a hundred patients, all index rules are a priori practically identical in terms of the expected proportion of success attained when all arms start with a uniform prior. However, we find that a posteriori, for specific values of the parameters of interest, the index policies outperform the simpler rules in every instance and specially so in the case of many arms and a larger, though still relatively small, total number of patients with the diseases. The very good performance of bandit rules in terms of patient benefit (i.e. expected number of successes and mean number of patients allocated to the best arm, if it exists) makes them very appealing in context of the challenge posed by drug development for rare life threatening diseases.
Applying usability heuristics to radiotherapy systems.

PubMed

Chan, Alvita J; Islam, Mohammad K; Rosewall, Tara; Jaffray, David A; Easty, Anthony C; Cafazzo, Joseph A

2012-01-01

Heuristic evaluations have been used to evaluate safety of medical devices by identifying and assessing usability issues. Since radiotherapy treatment delivery systems often consist of multiple complex user-interfaces, a heuristic evaluation was conducted to assess the potential safety issues of such a system. A heuristic evaluation was conducted to evaluate the treatment delivery system at Princess Margaret Hospital (Toronto, Canada). Two independent evaluators identified usability issues with the user-interfaces and rated the severity of each issue. The evaluators identified 75 usability issues in total. Eighteen of them were rated as high severity, indicating the potential to have a major impact on patient safety. A majority of issues were found on the record and verify system, and many were associated with the patient setup process. While the hospital has processes in place to ensure patient safety, recommendations were developed to further mitigate the risks of potential consequences. Heuristic evaluation is an efficient and inexpensive method that can be successfully applied to radiotherapy delivery systems to identify usability issues and improve patient safety. Although this study was conducted only at one site, the findings may have broad implications for the design of these systems. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
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.
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.
Family stories and the use of heuristics: women from suspected hereditary breast and ovarian cancer (HBOC) families.

PubMed

Kenen, Regina; Ardern-Jones, Audrey; Eeles, Rosalind

2003-11-01

The practice of medicine will increasingly be medicine of the family rather than the traditional physician/patient dyad, especially where a genetic condition is involved. This study explores how clients from suspected hereditary breast and ovarian cancer (HBOC) families seeking cancer genetics risk counselling are influenced by family stories and the use of heuristics (inferential shortcuts used to make sense of complicated information) in interpreting and applying genetic information they receive, and suggests ways in which genetic counsellors can integrate family context into their traditional counselling practices. We conducted an exploratory, qualitative study at a major clinical and research cancer centre in the United Kingdom from January to June 2000 which was reviewed by the hospital clinical research and ethics committees. Twenty-one semi-structured, in-depth interviews were conducted using a purposive sample of women coming to the cancer genetics clinic for the first time, supplemented by five months of clinical observation at weekly clinics. In addition to many family stories based on the number and outcomes of the cancers in their families, we noted: (1) fragments of stories, (2) secret stories, (3) emerging explanations and (4) misconceptions, We did not find widespread intergenerational family myths, The women used three main heuristics in interpreting their breast/ ovarian cancer risk: (1) representativeness, (2) availability and (3) illusion of control, as well as what Kahneman refers to as the Peak and End rule. Recent psychological research indicates that illusions of control may have positive affects on both physical and mental health. This may pose a future ethical issue for genetic counsellors in determining how to balance the benefit of positive illusions with the delivery of statistical probabilities of risk.
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.
Adaptive Neurons For Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1990-01-01

Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.
Developing Expert Systems for the Analysis of Syntactic and Semantic Patterns.

ERIC Educational Resources Information Center

Hellwig, Harold H.

Noting that expert computer systems respond to various contexts in terms of knowledge representation, this paper explains that heuristic rules of production, procedural representation, and frame representation have been adapted to such areas as medical diagnosis, signal interpretation, design and planning of electrical circuits and computer system…
Syntax Flowcharts for Advanced French Courses.

ERIC Educational Resources Information Center

Bryant, William H.

1983-01-01

The use of syntax flow charts as a graphic illustration of syntactic rules is suggested as both an instructional and a heuristic tool. Charts for these French structures are presented: negating of verbal expressions; balancing of conditional tenses; use of imperfect versus compound; agreement of past participles; and subjunctive sequences. (MSE)
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.
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.
Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.

PubMed

Nallaperuma, Samadhi; Neumann, Frank; Sudholt, Dirk

2017-01-01

Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed-time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1+1) EA and (1+[Formula: see text]) EA algorithms for the TSP in a smoothed complexity setting, and derive the lower bounds of the expected fitness gain for a specified number of generations.

Machine learning for the structure-energy-property landscapes of molecular crystals.

PubMed

Musil, Félix; De, Sandip; Yang, Jack; Campbell, Joshua E; Day, Graeme M; Ceriotti, Michele

2018-02-07

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol -1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure-property relations in molecular crystal engineering.
Making Predictions about Chemical Reactivity: Assumptions and Heuristics

ERIC Educational Resources Information Center

Maeyer, Jenine; Talanquer, Vicente

2013-01-01

Diverse implicit cognitive elements seem to support but also constrain reasoning in different domains. Many of these cognitive constraints can be thought of as either implicit assumptions about the nature of things or reasoning heuristics for decision-making. In this study we applied this framework to investigate college students' understanding of…
Ethical Reasoning: A Heuristic Approach for Business Educators.

ERIC Educational Resources Information Center

Molberg, Diane R.

For the teaching of business report writing, ethical reasoning can be used as a heuristic for thinking that will encourage a more effective communication pattern for business students. Writing processes can be applied to thinking processes to help students approach theoretical concepts, make decisions, and write more effective business reports. A…
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).
Non linear predictive control of a LEGO mobile robot

NASA Astrophysics Data System (ADS)

Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.

2014-10-01

Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.
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.
Intuitive Judgments Govern Students' Answering Patterns in Multiple-Choice Exercises in Organic Chemistry

ERIC Educational Resources Information Center

Graulich, Nicole

2015-01-01

Research in chemistry education has revealed that students going through their undergraduate and graduate studies in organic chemistry have a fragmented conceptual knowledge of the subject. Rote memorization, rule-based reasoning, and heuristic strategies seem to strongly influence students' performances. There appears to be a gap between what we…
The Counter-Intuitive Non-Informative Prior for the Bernoulli Family

ERIC Educational Resources Information Center

Zhu, Mu; Lu, Arthur Y.

2004-01-01

In Bayesian statistics, the choice of the prior distribution is often controversial. Different rules for selecting priors have been suggested in the literature, which, sometimes, produce priors that are difficult for the students to understand intuitively. In this article, we use a simple heuristic to illustrate to the students the rather…
A heuristic statistical stopping rule for iterative reconstruction in emission tomography.

PubMed

Ben Bouallègue, F; Crouzet, J F; Mariano-Goulart, D

2013-01-01

We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for MLEM reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the GATE platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time.
Laparoscopic bile duct injury: understanding the psychology and heuristics of the error.

PubMed

Dekker, Sidney W A; Hugh, Thomas B

2008-12-01

Bile duct injury is an important unsolved problem of laparoscopic cholecystectomy, occurring with unacceptable frequency even in the hands of experienced surgeons. This suggests that a systemic predisposition to the injury is intrinsic to cholecystectomy and indicates that an analysis of the psychology and heuristics of surgical decision-making in relation to duct identification may be a guide to prevention. Review of published reports on laparoscopic bile duct injury from 1997 to 2007 was carried out. An analysis was also carried out of the circumstances of the injuries in 49 patients who had transection of an extrahepatic bile duct and who were referred for reconstruction or were assessed in a medicolegal context. Special emphasis was placed on identifying the possible psychological aspects of duct misidentification. Review of published work showed an emphasis on the technical aspects of correct identification of the cystic duct, with few papers addressing the heuristics and psychology of surgical decision-making during cholecystectomy. Duct misidentification was the cause of injury in 42 out of the 49 reviewed patients (86%). The injury was not recognized at operation in 70% and delay in recognition persisted into the postoperative period in 57%. Underestimation of risk, cue ambiguity and visual misperception ('seeing what you believe') were important factors in misidentification. Delay in recognition of the injury is a feature consistent with cognitive fixation and plan continuation, which help construct and sustain the duct misidentification during the operation and beyond. Changing the 'culture' of cholecystectomy is probably the most effective strategy for preventing laparoscopic bile duct injury, especially if combined with new technical approaches and an understanding of the heuristics and psychology of the duct misidentification error. Training of surgeons for laparoscopic cholecystectomy should emphasize the need to be alert for cues that the incorrect duct is being dissected or that a bile duct injury might have occurred. Surgeons may also be trained to accept the need for plan modification, to seek cues that refute a given hypothesis and to apply 'stopping rules' for modifying or converting the operation.
Choice of population database for forensic DNA profile analysis.

PubMed

Steele, Christopher D; Balding, David J

2014-12-01

When evaluating the weight of evidence (WoE) for an individual to be a contributor to a DNA sample, an allele frequency database is required. The allele frequencies are needed to inform about genotype probabilities for unknown contributors of DNA to the sample. Typically databases are available from several populations, and a common practice is to evaluate the WoE using each available database for each unknown contributor. Often the most conservative WoE (most favourable to the defence) is the one reported to the court. However the number of human populations that could be considered is essentially unlimited and the number of contributors to a sample can be large, making it impractical to perform every possible WoE calculation, particularly for complex crime scene profiles. We propose instead the use of only the database that best matches the ancestry of the queried contributor, together with a substantial FST adjustment. To investigate the degree of conservativeness of this approach, we performed extensive simulations of one- and two-contributor crime scene profiles, in the latter case with, and without, the profile of the second contributor available for the analysis. The genotypes were simulated using five population databases, which were also available for the analysis, and evaluations of WoE using our heuristic rule were compared with several alternative calculations using different databases. Using FST=0.03, we found that our heuristic gave WoE more favourable to the defence than alternative calculations in well over 99% of the comparisons we considered; on average the difference in WoE was just under 0.2 bans (orders of magnitude) per locus. The degree of conservativeness of the heuristic rule can be adjusted through the FST value. We propose the use of this heuristic for DNA profile WoE calculations, due to its ease of implementation, and efficient use of the evidence while allowing a flexible degree of conservativeness. Copyright © 2014. Published by Elsevier Ireland Ltd.
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.
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.
The Labeling Strategy: Moving beyond Order in Counting Problems

ERIC Educational Resources Information Center

CadwalladerOlsker, Todd

2013-01-01

Permutations and combinations are used to solve certain kinds of counting problems, but many students have trouble distinguishing which of these concepts applies to a given problem. An "order heuristic" is usually used to distinguish the two, but this heuristic can cause confusion when problems do not explicitly mention order. This…
Heuristics as a Basis for Assessing Creative Potential: Measures, Methods, and Contingencies

ERIC Educational Resources Information Center

Vessey, William B.; Mumford, Michael D.

2012-01-01

Studies of creative thinking skills have generally measured a single aspect of creativity, divergent thinking. A number of other processes involved in creative thought have been identified. Effective execution of these processes is held to depend on the strategies applied in process execution, or heuristics. In this article, we review prior…
Using Problem-Solving to Think and Write: Tagmemics for High School Students.

ERIC Educational Resources Information Center

Brostoff, Anita

Secondary school and college students can learn how to shape thought through shaping language by using tagmemic heuristics. To approach writing as a thinking process, students apply three heuristics: one for identifying and stating problems, one for exploring problems, and one for evaluating hypotheses or solutions. Guided by a series of…
Applied tagmemics: A heuristic approach to the use of graphic aids in technical writing

NASA Technical Reports Server (NTRS)

Brownlee, P. P.; Kirtz, M. K.

1981-01-01

In technical report writing, two needs which must be met if reports are to be useable by an audience are the language needs and the technical needs of that particular audience. A heuristic analysis helps to decide the most suitable format for information; that is, whether the information should be presented verbally or visually. The report writing process should be seen as an organic whole which can be divided and subdivided according to the writer's purpose, but which always functions as a totality. The tagmemic heuristic, because it itself follows a process of deconstructing and reconstructing information, lends itself to being a useful approach to the teaching of technical writing. By applying the abstract questions this heuristic asks to specific parts of the report. The language and technical needs of the audience are analyzed by examining the viability of the solution within the givens of the corporate structure, and by deciding which graphic or verbal format will best suit the writer's purpose. By following such a method, answers which are both specific and thorough in their range of application are found.
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.
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.
Making decisions at the end of life when caring for a person with dementia: a literature review to explore the potential use of heuristics in difficult decision-making.

PubMed

Mathew, R; Davies, N; Manthorpe, J; Iliffe, S

2016-07-19

Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Making decisions at the end of life when caring for a person with dementia: a literature review to explore the potential use of heuristics in difficult decision-making

PubMed Central

Mathew, R; Davies, N; Manthorpe, J; Iliffe, S

2016-01-01

Objective Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. Design A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. Data sources A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. Results The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. Conclusions The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. PMID:27436665
Two fast and accurate heuristic RBF learning rules for data classification.

PubMed

Rouhani, Modjtaba; Javan, Dawood S

2016-03-01

This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. Copyright © 2015 Elsevier Ltd. All rights reserved.
An expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1992-01-01

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).
Correlated pay-offs are key to cooperation

PubMed Central

Frommen, Joachim G.; Riehl, Christina

2016-01-01

The general belief that cooperation and altruism in social groups result primarily from kin selection has recently been challenged, not least because results from cooperatively breeding insects and vertebrates have shown that groups may be composed mainly of non-relatives. This allows testing predictions of reciprocity theory without the confounding effect of relatedness. Here, we review complementary and alternative evolutionary mechanisms to kin selection theory and provide empirical examples of cooperative behaviour among unrelated individuals in a wide range of taxa. In particular, we focus on the different forms of reciprocity and on their underlying decision rules, asking about evolutionary stability, the conditions selecting for reciprocity and the factors constraining reciprocal cooperation. We find that neither the cognitive requirements of reciprocal cooperation nor the often sequential nature of interactions are insuperable stumbling blocks for the evolution of reciprocity. We argue that simple decision rules such as ‘help anyone if helped by someone’ should get more attention in future research, because empirical studies show that animals apply such rules, and theoretical models find that they can create stable levels of cooperation under a wide range of conditions. Owing to its simplicity, behaviour based on such a heuristic may in fact be ubiquitous. Finally, we argue that the evolution of exchange and trading of service and commodities among social partners needs greater scientific focus. PMID:26729924
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.
NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)/EXPERT: Bridging the gap between artificial intelligence and FORTRAN

NASA Technical Reports Server (NTRS)

Fink, Pamela K.; Palmer, Karol K.

1988-01-01

The development of a probabilistic structural analysis methodology (PSAM) is described. In the near-term, the methodology will be applied to designing critical components of the next generation space shuttle main engine. In the long-term, PSAM will be applied very broadly, providing designers with a new technology for more effective design of structures whose character and performance are significantly affected by random variables. The software under development to implement the ideas developed in PSAM resembles, in many ways, conventional deterministic structural analysis code. However, several additional capabilities regarding the probabilistic analysis makes the input data requirements and the resulting output even more complex. As a result, an intelligent front- and back-end to the code is being developed to assist the design engineer in providing the input data in a correct and appropriate manner. The type of knowledge that this entails is, in general, heuristically-based, allowing the fairly well-understood technology of production rules to apply with little difficulty. However, the PSAM code, called NESSUS, is written in FORTRAN-77 and runs on a DEC VAX. Thus, the associated expert system, called NESSUS/EXPERT, must run on a DEC VAX as well, and integrate effectively and efficiently with the existing FORTRAN code. This paper discusses the process undergone to select a suitable tool, identify an appropriate division between the functions that should be performed in FORTRAN and those that should be performed by production rules, and how integration of the conventional and AI technologies was achieved.
Experiments in Knowledge Refinement for a Large Rule-Based System

DTIC Science & Technology

1993-08-01

empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system
The Art of Snaring Dragons. Artificial Intelligence Memo Number 338. Revised.

ERIC Educational Resources Information Center

Cohen, Harvey A.

Several models for problem solving are discussed, and the idea of a heuristic frame is developed. This concept provides a description of the evolution of problem-solving skills in terms of the growth of the number of algorithms available and increased sophistication in their use. The heuristic frame model is applied to two sets of physical…
Using Control Heuristics as a Means to Explore the Educational Potential of Robotics Kits

ERIC Educational Resources Information Center

Gaudiello, Ilaria; Zibetti, Elisabetta

2013-01-01

The educational potential of robotics kits as a form of control technology will remain undervalued until meaningful observation parameters are identified to enable a better understanding of children?s control strategies. For this reason, this paper aims primarily to identify and classify the heuristics spontaneously applied by 6-10 year old…
Towards Cognitive Load Theory as Guideline for Instructional Design in Science Education

ERIC Educational Resources Information Center

Meissner, Barbara; Bogner, Franz X.

2013-01-01

We applied cognitive load theory in an heuristic out-of-school science lesson. The lesson comprises experiments concerning major attributes of NaCl and was designed for 5th to 8th grade students. Our interest focused on whether cognitive load theory provides sufficient guidelines for instructional design in the field of heuristic science…
An algorithm for the optimal collection of wet waste.

PubMed

Laureri, Federica; Minciardi, Riccardo; Robba, Michela

2016-02-01

This work refers to the development of an approach for planning wet waste (food waste and other) collection at a metropolitan scale. Some specific modeling features distinguish this specific waste collection problem from the other ones. For instance, there may be significant differences as regards the values of the parameters (such as weight and volume) characterizing the various collection points. As it happens for classical waste collection planning, even in the case of wet waste, one has to deal with difficult combinatorial problems, where the determination of an optimal solution may require a very large computational effort, in the case of problem instances having a noticeable dimensionality. For this reason, in this work, a heuristic procedure for the optimal planning of wet waste is developed and applied to problem instances drawn from a real case study. The performances that can be obtained by applying such a procedure are evaluated by a comparison with those obtainable via a general-purpose mathematical programming software package, as well as those obtained by applying very simple decision rules commonly used in practice. The considered case study consists in an area corresponding to the historical center of the Municipality of Genoa. Copyright © 2015 Elsevier Ltd. All rights reserved.
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.
Reward-Guided Learning with and without Causal Attribution

PubMed Central

Jocham, Gerhard; Brodersen, Kay H.; Constantinescu, Alexandra O.; Kahn, Martin C.; Ianni, Angela M.; Walton, Mark E.; Rushworth, Matthew F.S.; Behrens, Timothy E.J.

2016-01-01

Summary When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task. PMID:26971947
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.
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
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
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.
Approximation algorithms for a genetic diagnostics problem.

PubMed

Kosaraju, S R; Schäffer, A A; Biesecker, L G

1998-01-01

We define and study a combinatorial problem called WEIGHTED DIAGNOSTIC COVER (WDC) that models the use of a laboratory technique called genotyping in the diagnosis of an important class of chromosomal aberrations. An optimal solution to WDC would enable us to define a genetic assay that maximizes the diagnostic power for a specified cost of laboratory work. We develop approximation algorithms for WDC by making use of the well-known problem SET COVER for which the greedy heuristic has been extensively studied. We prove worst-case performance bounds on the greedy heuristic for WDC and for another heuristic we call directional greedy. We implemented both heuristics. We also implemented a local search heuristic that takes the solutions obtained by greedy and dir-greedy and applies swaps until they are locally optimal. We report their performance on a real data set that is representative of the options that a clinical geneticist faces for the real diagnostic problem. Many open problems related to WDC remain, both of theoretical interest and practical importance.
Usability evaluation of Laboratory and Radiology Information Systems integrated into a hospital information system.

PubMed

Nabovati, Ehsan; Vakili-Arki, Hasan; Eslami, Saeid; Khajouei, Reza

2014-04-01

This study was conducted to evaluate the usability of widely used laboratory and radiology information systems. Three usability experts independently evaluated the user interfaces of Laboratory and Radiology Information Systems using heuristic evaluation method. They applied Nielsen's heuristics to identify and classify usability problems and Nielsen's severity rating to judge their severity. Overall, 116 unique heuristic violations were identified as usability problems. In terms of severity, 67 % of problems were rated as major and catastrophic. Among 10 heuristics, "consistency and standards" was violated most frequently. Moreover, mean severity of problems concerning "error prevention" and "help and documentation" heuristics was higher than of the others. Despite widespread use of specific healthcare information systems, they suffer from usability problems. Improving the usability of systems by following existing design standards and principles from the early phased of system development life cycle is recommended. Especially, it is recommended that the designers design systems that inhibit the initiation of erroneous actions and provide sufficient guidance to users.
About approximation of integer factorization problem by the combination fixed-point iteration method and Bayesian rounding for quantum cryptography

NASA Astrophysics Data System (ADS)

Ogorodnikov, Yuri; Khachay, Michael; Pljonkin, Anton

2018-04-01

We describe the possibility of employing the special case of the 3-SAT problem stemming from the well known integer factorization problem for the quantum cryptography. It is known, that for every instance of our 3-SAT setting the given 3-CNF is satisfiable by a unique truth assignment, and the goal is to find this assignment. Since the complexity status of the factorization problem is still undefined, development of approximation algorithms and heuristics adopts interest of numerous researchers. One of promising approaches to construction of approximation techniques is based on real-valued relaxation of the given 3-CNF followed by minimizing of the appropriate differentiable loss function, and subsequent rounding of the fractional minimizer obtained. Actually, algorithms developed this way differ by the rounding scheme applied on their final stage. We propose a new rounding scheme based on Bayesian learning. The article shows that the proposed method can be used to determine the security in quantum key distribution systems. In the quantum distribution the Shannon rules is applied and the factorization problem is paramount when decrypting secret keys.

A Blind Spot in Research on Foreign Language Effects in Judgment and Decision-Making.

PubMed

Polonioli, Andrea

2018-01-01

One of the most fascinating topics of current investigation in the literature on judgment and decision-making concerns the exploration of foreign language effects (henceforth, FLE). Specifically, recent research suggests that presenting information in a foreign language helps reasoners make better choices. However, this piece aims at making scholars aware of a blind spot in this stream of research. In particular, research on FLE has imported only one view of judgment and decision-making, in which the heuristics that people use are seen as conducive to biases and, in turn, to costly mistakes. But heuristics are not necessarily a liability, and this article indicates two routes to push forward research on FLE in judgment and decision-making. First, research on FLE should be expanded to explore also classes of fast and frugal heuristics, which have been shown to lead to accurate predictions in several contexts characterized by uncertainty. Second, research on FLE should be open to challenge the interpretations given to previous FLE findings, since alternative accounts are plausible and not ruled out by evidence.
Heuristics can produce surprisingly rational probability estimates: Comment on Costello and Watts (2014).

PubMed

Nilsson, Håkan; Juslin, Peter; Winman, Anders

2016-01-01

Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014). (c) 2015 APA, all rights reserved).
A Blind Spot in Research on Foreign Language Effects in Judgment and Decision-Making

PubMed Central

Polonioli, Andrea

2018-01-01

One of the most fascinating topics of current investigation in the literature on judgment and decision-making concerns the exploration of foreign language effects (henceforth, FLE). Specifically, recent research suggests that presenting information in a foreign language helps reasoners make better choices. However, this piece aims at making scholars aware of a blind spot in this stream of research. In particular, research on FLE has imported only one view of judgment and decision-making, in which the heuristics that people use are seen as conducive to biases and, in turn, to costly mistakes. But heuristics are not necessarily a liability, and this article indicates two routes to push forward research on FLE in judgment and decision-making. First, research on FLE should be expanded to explore also classes of fast and frugal heuristics, which have been shown to lead to accurate predictions in several contexts characterized by uncertainty. Second, research on FLE should be open to challenge the interpretations given to previous FLE findings, since alternative accounts are plausible and not ruled out by evidence. PMID:29662457
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…
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.
Brown-Utility Heuristic? The Presence and Contributing Factors of Latino Linked Fate

ERIC Educational Resources Information Center

Sanchez, Gabriel R.; Masuoka, Natalie

2010-01-01

In an electoral system governed by the plurality rule, those groups who wield the greatest amount of power in the United States are those who vote as a cohesive bloc. Although the size of the Latino population is growing, it is unclear whether all Latinos perceive a shared collective identity that will be exercised in the political realm. This…
Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

ERIC Educational Resources Information Center

Sayre, Scott Alan

The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…
Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.

2012-12-25

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J

2013-07-30

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

PubMed Central

Kind, Tobias; Fiehn, Oliver

2007-01-01

Background Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. Results An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. Conclusion The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website. PMID:17389044
Expert overseer for mass spectrometer system

DOEpatents

Filby, Evan E.; Rankin, Richard A.

1991-01-01

An expert overseer for the operation and real-time management of a mass spectrometer and associated laboratory equipment. The overseer is a computer-based expert diagnostic system implemented on a computer separate from the dedicated computer used to control the mass spectrometer and produce the analysis results. An interface links the overseer to components of the mass spectrometer, components of the laboratory support system, and the dedicated control computer. Periodically, the overseer polls these devices and as well as itself. These data are fed into an expert portion of the system for real-time evaluation. A knowledge base used for the evaluation includes both heuristic rules and precise operation parameters. The overseer also compares current readings to a long-term database to detect any developing trends using a combination of statistical and heuristic rules to evaluate the results. The overseer has the capability to alert lab personnel whenever questionable readings or trends are observed and provide a background review of the problem and suggest root causes and potential solutions, or appropriate additional tests that could be performed. The overseer can change the sequence or frequency of the polling to respond to an observation in the current data.
Figure Control of Lightweight Optical Structures

NASA Technical Reports Server (NTRS)

Main, John A.; Song, Haiping

2005-01-01

The goal of this paper is to demonstrate the use of fuzzy logic controllers in modifying the figure of a piezoceramic bimorph mirror. Non-contact electron actuation technology is used to actively control a bimorph mirror comprised two PZT-5H wafers by varying the electron flux and electron voltages. Due to electron blooming generated by the electron flux, it is difficult to develop an accurate control model for the bimorph mirror through theoretical analysis alone. The non-contact shape control system with electron flux blooming can be approximately described with a heuristic model based on experimental data. Two fuzzy logic feedback controllers are developed to control the shape of the bimorph mirror according to heuristic fuzzy inference rules generated from previous experimental results. Validation of the proposed fuzzy logic controllers is also discussed.
Open shop scheduling problem to minimize total weighted completion time

NASA Astrophysics Data System (ADS)

Bai, Danyu; Zhang, Zhihai; Zhang, Qiang; Tang, Mengqian

2017-01-01

A given number of jobs in an open shop scheduling environment must each be processed for given amounts of time on each of a given set of machines in an arbitrary sequence. This study aims to achieve a schedule that minimizes total weighted completion time. Owing to the strong NP-hardness of the problem, the weighted shortest processing time block (WSPTB) heuristic is presented to obtain approximate solutions for large-scale problems. Performance analysis proves the asymptotic optimality of the WSPTB heuristic in the sense of probability limits. The largest weight block rule is provided to seek optimal schedules in polynomial time for a special case. A hybrid discrete differential evolution algorithm is designed to obtain high-quality solutions for moderate-scale problems. Simulation experiments demonstrate the effectiveness of the proposed algorithms.
Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

NASA Technical Reports Server (NTRS)

Heyward, Ann O.; Reilly, Charles H.; Walton, Eric K.; Mata, Fernando; Olen, Carl

1990-01-01

Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.
The min-conflicts heuristic: Experimental and theoretical results

NASA Technical Reports Server (NTRS)

Minton, Steven; Philips, Andrew B.; Johnston, Mark D.; Laird, Philip

1991-01-01

This paper describes a simple heuristic method for solving large-scale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching through the space of possible repairs. The search is guided by an ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. We demonstrate empirically that the method performs orders of magnitude better than traditional backtracking techniques on certain standard problems. For example, the one million queens problem can be solved rapidly using our approach. We also describe practical scheduling applications where the method has been successfully applied. A theoretical analysis is presented to explain why the method works so well on certain types of problems and to predict when it is likely to be most effective.
Experimental evidence for convergent evolution of maternal care heuristics in industrialized and small-scale populations.

PubMed

Kushnick, Geoff; Hanowell, Ben; Kim, Jun-Hong; Langstieh, Banrida; Magnano, Vittorio; Oláh, Katalin

2015-06-01

Maternal care decision rules should evolve responsiveness to factors impinging on the fitness pay-offs of care. Because the caretaking environments common in industrialized and small-scale societies vary in predictable ways, we hypothesize that heuristics guiding maternal behaviour will also differ between these two types of populations. We used a factorial vignette experiment to elicit third-party judgements about likely caretaking decisions of a hypothetical mother and her child when various fitness-relevant factors (maternal age and access to resources, and offspring age, sex and quality) were varied systematically in seven populations-three industrialized and four small-scale. Despite considerable variation in responses, we found that three of five main effects, and the two severity effects, exhibited statistically significant industrialized/ small-scale population differences. All differences could be explained as adaptive solutions to industrialized versus small-scale caretaking environments. Further, we found gradients in the relationship between the population-specific estimates and national-level socio-economic indicators, further implicating important aspects of the variation in industrialized and small-scale caretaking environments in shaping heuristics. Although there is mounting evidence for a genetic component to human maternal behaviour, there is no current evidence for interpopulation variation in candidate genes. We nonetheless suggest that heuristics guiding maternal behaviour in diverse societies emerge via convergent evolution in response to similar selective pressures.
HERB: A production system for programming with hierarchical expert rule bases: User's manual, HERB Version 1. 0

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

Hummel, K.E.

1987-12-01

Expert systems are artificial intelligence programs that solve problems requiring large amounts of heuristic knowledge, based on years of experience and tradition. Production systems are domain-independent tools that support the development of rule-based expert systems. This document describes a general purpose production system known as HERB. This system was developed to support the programming of expert systems using hierarchically structured rule bases. HERB encourages the partitioning of rules into multiple rule bases and supports the use of multiple conflict resolution strategies. Multiple rule bases can also be placed on a system stack and simultaneously searched during each interpreter cycle. Bothmore » backward and forward chaining rules are supported by HERB. The condition portion of each rule can contain both patterns, which are matched with facts in a data base, and LISP expressions, which are explicitly evaluated in the LISP environment. Properties of objects can also be stored in the HERB data base and referenced within the scope of each rule. This document serves both as an introduction to the principles of LISP-based production systems and as a user's manual for the HERB system. 6 refs., 17 figs.« less
PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.
PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619
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.
Complexity, Heuristic, and Search Analysis for the Games of Crossings and Epaminondas

DTIC Science & Technology

2014-03-27

research in Artifical Intelligence (Section 2.1) and why games are studied (Section 2.2). Section 2.3 discusses how games are played and solved. An...5 2.1 Games in Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Game Study...Artificial Intelligence UCT Upper Confidence Bounds applied to Trees HUCT Heuristic Guided UCT LOA Lines of Action UCB Upper Confidence Bound RAVE Rapid
Machine learning for the structure–energy–property landscapes of molecular crystals† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04665k

PubMed Central

Yang, Jack; Campbell, Joshua E.; Day, Graeme M.; Ceriotti, Michele

2017-01-01

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol–1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure–property relations in molecular crystal engineering. PMID:29675175
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
College Students' Conceptions of Chemical Stability: The Widespread Adoption of a Heuristic Rule out of Context and beyond Its Range of Application

ERIC Educational Resources Information Center

Taber, Keith S.

2009-01-01

This paper reports evidence that learners commonly develop a notion of chemical stability that, whilst drawing upon ideas taught in the curriculum, is nevertheless inconsistent with basic scientific principles. A series of related small-scale studies show that many college-level students consider a chemical species with an octet structure, or a…
Maximizing the Predictive Value of Production Rules

DTIC Science & Technology

1988-08-31

Clancev, 1985] Clancey, W. "Heuristic Classification." Artifcial Intelligence . 27 (1985) 289-350. [Crawford, 19881 Crawford, S. "Extensions to the CART...Optimality 16 6.1.2. Comparative Analysis for Normally Distributed Data 17 6.2. Comparison with Alternative Machine Learning Methods 18 6.2.1. Alternative...are reported on data sets previously analyzed in the Al literature using alternative classification techniques. 1. Introduction MIanv decision-making
The Effect of Using the TI-92 on Basic College Algebra Students' Ability To Solve Word Problems.

ERIC Educational Resources Information Center

Runde, Dennis C.

As part of an effort to improve community college algebra students' ability to solve word problems, a study was undertaken at Florida's Manatee Community College to determine the effects of using heuristic instruction (i.e., providing general rules for solving different types of math problems) in combination with the TI-92 calculator. The TI-92…
Systematic assignment of thermodynamic constraints in metabolic network models

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

Background The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models. For this, several computational tools have been developed that particularly assist in identifying and compiling the organism-specific lists of metabolic reactions. In contrast, the last step of the model reconstruction process, which is the definition of the thermodynamic constraints in terms of reaction directionalities, still needs to be done manually. No computational method exists that allows for an automated and systematic assignment of reaction directions in genome-scale models. Results We present an algorithm that – based on thermodynamics, network topology and heuristic rules – automatically assigns reaction directions in metabolic models such that the reaction network is thermodynamically feasible with respect to the production of energy equivalents. It first exploits all available experimentally derived Gibbs energies of formation to identify irreversible reactions. As these thermodynamic data are not available for all metabolites, in a next step, further reaction directions are assigned on the basis of network topology considerations and thermodynamics-based heuristic rules. Briefly, the algorithm identifies reaction subsets from the metabolic network that are able to convert low-energy co-substrates into their high-energy counterparts and thus net produce energy. Our algorithm aims at disabling such thermodynamically infeasible cyclic operation of reaction subnetworks by assigning reaction directions based on a set of thermodynamics-derived heuristic rules. We demonstrate our algorithm on a genome-scale metabolic model of E. coli. The introduced systematic direction assignment yielded 130 irreversible reactions (out of 920 total reactions), which corresponds to about 70% of all irreversible reactions that are required to disable thermodynamically infeasible energy production. Conclusion Although not being fully comprehensive, our algorithm for systematic reaction direction assignment could define a significant number of irreversible reactions automatically with low computational effort. We envision that the presented algorithm is a valuable part of a computational framework that assists the automated reconstruction of genome-scale metabolic models. PMID:17123434
Common sense reasoning about petroleum flow

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

Rosenberg, S.

1981-02-01

This paper describes an expert system for understanding and Reasoning in a petroleum resources domain. A basic model is implemented in FRL (Frame Representation Language). Expertise is encoded as rule frames. The model consists of a set of episodic contexts which are sequentially generated over time. Reasoning occurs in separate reasoning contexts consisting of a buffer frame and packets of rules. These function similar to small production systems. reasoning is linked to the model through an interface of Sentinels (instance driven demons) which notice anomalous conditions. Heuristics and metaknowledge are used through the creation of further reasoning contexts which overlaymore » the simpler ones.« less
Health on impulse: when low self-control promotes healthy food choices.

PubMed

Salmon, Stefanie J; Fennis, Bob M; de Ridder, Denise T D; Adriaanse, Marieke A; de Vet, Emely

2014-02-01

Food choices are often made mindlessly, when individuals are not able or willing to exert self-control. Under low self-control, individuals have difficulties to resist palatable but unhealthy food products. In contrast to previous research aiming to foster healthy choices by promoting high self-control, this study exploits situations of low self-control, by strategically using the tendency under these conditions to rely on heuristics (simple decision rules) as quick guides to action. More specifically, the authors associated healthy food products with the social proof heuristic (i.e., normative cues that convey majority endorsement for those products). One hundred seventy-seven students (119 men), with an average age of 20.47 years (SD = 2.25) participated in the experiment. This study used a 2 (low vs. high self-control) × 2 (social proof vs. no heuristic) × 2 (trade-off vs. control choice) design, with the latter as within-subjects factor. The dependent variable was the number of healthy food choices in a food-choice task. In line with previous studies, people made fewer healthy food choices under low self-control. However, this negative effect of low self-control on food choice was reversed when the healthy option was associated with the social proof heuristic. In that case, people made more healthy choices under conditions of low self-control. Low self-control may be even more beneficial for healthy food choices than high self-control in the presence of a heuristic. Exploiting situations of low self-control is a new and promising method to promote health on impulse. PsycINFO Database Record (c) 2014 APA, all rights reserved.
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.
Helping reasoners succeed in the Wason selection task: when executive learning discourages heuristic response but does not necessarily encourage logic.

PubMed

Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier

2015-01-01

Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too "strictly" transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning.
Helping Reasoners Succeed in the Wason Selection Task: When Executive Learning Discourages Heuristic Response but Does Not Necessarily Encourage Logic

PubMed Central

Rossi, Sandrine; Cassotti, Mathieu; Moutier, Sylvain; Delcroix, Nicolas; Houdé, Olivier

2015-01-01

Reasoners make systematic logical errors by giving heuristic responses that reflect deviations from the logical norm. Influential studies have suggested first that our reasoning is often biased because we minimize cognitive effort to surpass a cognitive conflict between heuristic response from system 1 and analytic response from system 2 thinking. Additionally, cognitive control processes might be necessary to inhibit system 1 responses to activate a system 2 response. Previous studies have shown a significant effect of executive learning (EL) on adults who have transferred knowledge acquired on the Wason selection task (WST) to another isomorphic task, the rule falsification task (RFT). The original paradigm consisted of teaching participants to inhibit a classical matching heuristic that sufficed the first problem and led to significant EL transfer on the second problem. Interestingly, the reasoning tasks differed in inhibiting-heuristic metacognitive cost. Success on the WST requires half-suppression of the matching elements. In contrast, the RFT necessitates a global rejection of the matching elements for a correct answer. Therefore, metacognitive learning difficulty most likely differs depending on whether one uses the first or second task during the learning phase. We aimed to investigate this difficulty and various matching-bias inhibition effects in a new (reversed) paradigm. In this case, the transfer effect from the RFT to the WST could be more difficult because the reasoner learns to reject all matching elements in the first task. We observed that the EL leads to a significant reduction in matching selections on the WST without increasing logical performances. Interestingly, the acquired metacognitive knowledge was too “strictly” transferred and discouraged matching rather than encouraging logic. This finding underlines the complexity of learning transfer and adds new evidence to the pedagogy of reasoning. PMID:25849555
Efficient heuristics for maximum common substructure search.

PubMed

Englert, Péter; Kovács, Péter

2015-05-26

Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.
Scheduling rules to achieve lead-time targets in outpatient appointment systems.

PubMed

Nguyen, Thu-Ba T; Sivakumar, Appa Iyer; Graves, Stephen C

2017-12-01

This paper considers how to schedule appointments for outpatients, for a clinic that is subject to appointment lead-time targets for both new and returning patients. We develop heuristic rules, which are the exact and relaxed appointment scheduling rules, to schedule each new patient appointment (only) in light of uncertainty about future arrivals. The scheduling rules entail two decisions. First, the rules need to determine whether or not a patient's request can be accepted; then, if the request is not rejected, the rules prescribe how to assign the patient to an available slot. The intent of the scheduling rules is to maximize the utilization of the planned resource (i.e., the physician staff), or equivalently to maximize the number of patients that are admitted, while maintaining the service targets on the median, the 95th percentile, and the maximum appointment lead-times. We test the proposed scheduling rules with numerical experiments using real data from the chosen clinic of Tan Tock Seng hospital in Singapore. The results show the efficiency and the efficacy of the scheduling rules, in terms of the service-target satisfaction and the resource utilization. From the sensitivity analysis, we find that the performance of the proposed scheduling rules is fairly robust to the specification of the established lead-time targets.
The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

PubMed

Steginga, Suzanne K; Occhipinti, Stefano

2004-01-01

The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.
Moral satisficing: rethinking moral behavior as bounded rationality.

PubMed

Gigerenzer, Gerd

2010-07-01

What is the nature of moral behavior? According to the study of bounded rationality, it results not from character traits or rational deliberation alone, but from the interplay between mind and environment. In this view, moral behavior is based on pragmatic social heuristics rather than moral rules or maximization principles. These social heuristics are not good or bad per se, but solely in relation to the environments in which they are used. This has methodological implications for the study of morality: Behavior needs to be studied in social groups as well as in isolation, in natural environments as well as in labs. It also has implications for moral policy: Only by accepting the fact that behavior is a function of both mind and environmental structures can realistic prescriptive means of achieving moral goals be developed. Copyright © 2010 Cognitive Science Society, Inc.
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.
Quixotic medicine: physical and economic laws perilously disregarded in health care and medical education.

PubMed

Haburchak, David R; Mitchell, Bradford C; Boomer, Craig J

2008-12-01

Wise medical practice requires balancing the idealistic goals of medicine with the physical and economic realities of their application. Clinicians should know and employ the rules, maxims, and heuristics that summarize these goals and constraints. There has been little formal study of rules or laws pertaining to therapeutics and prognosis, so the authors postulate four physical and four economic laws that apply to health care: the laws of (1) finitude, (2) inertia, (3) entropy, and (4) the uncertainty principle; and the laws of (5) diminishing returns, (6) unintended consequences, (7) distribution, and (8) economizing. These laws manifest themselves in the absence of health, the pathogenesis of disease, prognosis, and the behaviors of participants in the health care enterprise. Physicians and the public perilously disregard these laws, frequently producing misdiagnoses, distraction, false expectations, unanticipated and undesirable outcomes, inequitable distribution of scarce resources, distrust, and cynicism: in short, quixotic medicine. The origins and public reinforcement of quixotic medicine make it deaf to calls for pragmatism. To achieve the Accreditation Council of Graduate Medical Education competency of systems-based practice, the authors recommend that premedical education return to a broader liberal arts curriculum and that medical education and training foster didactic and experiential knowledge of these eight laws.

Optimal two-phase sampling design for comparing accuracies of two binary classification rules.

PubMed

Xu, Huiping; Hui, Siu L; Grannis, Shaun

2014-02-10

In this paper, we consider the design for comparing the performance of two binary classification rules, for example, two record linkage algorithms or two screening tests. Statistical methods are well developed for comparing these accuracy measures when the gold standard is available for every unit in the sample, or in a two-phase study when the gold standard is ascertained only in the second phase in a subsample using a fixed sampling scheme. However, these methods do not attempt to optimize the sampling scheme to minimize the variance of the estimators of interest. In comparing the performance of two classification rules, the parameters of primary interest are the difference in sensitivities, specificities, and positive predictive values. We derived the analytic variance formulas for these parameter estimates and used them to obtain the optimal sampling design. The efficiency of the optimal sampling design is evaluated through an empirical investigation that compares the optimal sampling with simple random sampling and with proportional allocation. Results of the empirical study show that the optimal sampling design is similar for estimating the difference in sensitivities and in specificities, and both achieve a substantial amount of variance reduction with an over-sample of subjects with discordant results and under-sample of subjects with concordant results. A heuristic rule is recommended when there is no prior knowledge of individual sensitivities and specificities, or the prevalence of the true positive findings in the study population. The optimal sampling is applied to a real-world example in record linkage to evaluate the difference in classification accuracy of two matching algorithms. Copyright © 2013 John Wiley & Sons, Ltd.
Automatic Overset Grid Generation with Heuristic Feedback Control

NASA Technical Reports Server (NTRS)

Robinson, Peter I.

2001-01-01

An advancing front grid generation system for structured Overset grids is presented which automatically modifies Overset structured surface grids and control lines until user-specified grid qualities are achieved. The system is demonstrated on two examples: the first refines a space shuttle fuselage control line until global truncation error is achieved; the second advances, from control lines, the space shuttle orbiter fuselage top and fuselage side surface grids until proper overlap is achieved. Surface grids are generated in minutes for complex geometries. The system is implemented as a heuristic feedback control (HFC) expert system which iteratively modifies the input specifications for Overset control line and surface grids. It is developed as an extension of modern control theory, production rules systems and subsumption architectures. The methodology provides benefits over the full knowledge lifecycle of an expert system for knowledge acquisition, knowledge representation, and knowledge execution. The vector/matrix framework of modern control theory systematically acquires and represents expert system knowledge. Missing matrix elements imply missing expert knowledge. The execution of the expert system knowledge is performed through symbolic execution of the matrix algebra equations of modern control theory. The dot product operation of matrix algebra is generalized for heuristic symbolic terms. Constant time execution is guaranteed.
Probability versus representativeness in infancy: can infants use naïve physics to adjust population base rates in probabilistic inference?

PubMed

Denison, Stephanie; Trikutam, Pallavi; Xu, Fei

2014-08-01

A rich tradition in developmental psychology explores physical reasoning in infancy. However, no research to date has investigated whether infants can reason about physical objects that behave probabilistically, rather than deterministically. Physical events are often quite variable, in that similar-looking objects can be placed in similar contexts with different outcomes. Can infants rapidly acquire probabilistic physical knowledge, such as some leaves fall and some glasses break by simply observing the statistical regularity with which objects behave and apply that knowledge in subsequent reasoning? We taught 11-month-old infants physical constraints on objects and asked them to reason about the probability of different outcomes when objects were drawn from a large distribution. Infants could have reasoned either by using the perceptual similarity between the samples and larger distributions or by applying physical rules to adjust base rates and estimate the probabilities. Infants learned the physical constraints quickly and used them to estimate probabilities, rather than relying on similarity, a version of the representativeness heuristic. These results indicate that infants can rapidly and flexibly acquire physical knowledge about objects following very brief exposure and apply it in subsequent reasoning. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Answer first: Applying the heuristic-analytic theory of reasoning to examine student intuitive thinking in the context of physics

NASA Astrophysics Data System (ADS)

Kryjevskaia, Mila; Stetzer, MacKenzie R.; Grosz, Nathaniel

2014-12-01

We have applied the heuristic-analytic theory of reasoning to interpret inconsistencies in student reasoning approaches to physics problems. This study was motivated by an emerging body of evidence that suggests that student conceptual and reasoning competence demonstrated on one task often fails to be exhibited on another. Indeed, even after instruction specifically designed to address student conceptual and reasoning difficulties identified by rigorous research, many undergraduate physics students fail to build reasoning chains from fundamental principles even though they possess the required knowledge and skills to do so. Instead, they often rely on a variety of intuitive reasoning strategies. In this study, we developed and employed a methodology that allowed for the disentanglement of student conceptual understanding and reasoning approaches through the use of sequences of related questions. We have shown that the heuristic-analytic theory of reasoning can be used to account for, in a mechanistic fashion, the observed inconsistencies in student responses. In particular, we found that students tended to apply their correct ideas in a selective manner that supported a specific and likely anticipated conclusion while neglecting to employ the same ideas to refute an erroneous intuitive conclusion. The observed reasoning patterns were consistent with the heuristic-analytic theory, according to which reasoners develop a "first-impression" mental model and then construct an argument in support of the answer suggested by this model. We discuss implications for instruction and argue that efforts to improve student metacognition, which serves to regulate the interaction between intuitive and analytical reasoning, is likely to lead to improved student reasoning.
Heuristic Programming Project: October 1979-September 1982

DTIC Science & Technology

1985-03-27

the research on ROGET focused on acquiring the initial conceptual structure needed to design the knowedge base in the first place. ROGET’s special...the user in constructing and specifying the details of the components. A component is a collection of functions and variables that support conceptual ...other framwork , called the Backchain framework, is for building programs that use backward-chaind production rules as the primary mechanism of generating
An Investigation of Mental Coding Mechanisms and Heuristics Used in Electronics Troubleshooting.

DTIC Science & Technology

1980-04-01

that is, the particular program to be used for the decision making or problem solving exercise at hand. The relationships between LTM, the processor...stimulus input according to previously learned classifications. Norman continued by writing that the encoded information is the material which is stored...the manipulation of algebraic or other mathematical symbols according to the rules embodied in mathematical logic. Once these essentially content free
Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: Preliminary ascent knowledge requirements

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

The preliminary version of expert knowledge for the Onboard Navigation (ONAV) Ground Based Expert Trainer Ascent system for the space shuttle is presented. Included is some brief background information along with the information describing the knowledge the system will contain. Information is given on rules and heuristics, telemetry status, landing sites, inertial measurement units, and a high speed trajectory determinator (HSTD) state vector.
An Evolutionary Optimization of the Refueling Simulation for a CANDU Reactor

NASA Astrophysics Data System (ADS)

Do, Q. B.; Choi, H.; Roh, G. H.

2006-10-01

This paper presents a multi-cycle and multi-objective optimization method for the refueling simulation of a 713 MWe Canada deuterium uranium (CANDU-6) reactor based on a genetic algorithm, an elitism strategy and a heuristic rule. The proposed algorithm searches for the optimal refueling patterns for a single cycle that maximizes the average discharge burnup, minimizes the maximum channel power and minimizes the change in the zone controller unit water fills while satisfying the most important safety-related neutronic parameters of the reactor core. The heuristic rule generates an initial population of individuals very close to a feasible solution and it reduces the computing time of the optimization process. The multi-cycle optimization is carried out based on a single cycle refueling simulation. The proposed approach was verified by a refueling simulation of a natural uranium CANDU-6 reactor for an operation period of 6 months at an equilibrium state and compared with the experience-based automatic refueling simulation and the generalized perturbation theory. The comparison has shown that the simulation results are consistent from each other and the proposed approach is a reasonable optimization method of the refueling simulation that controls all the safety-related parameters of the reactor core during the simulation
KAM (Knowledge Acquisition Module): A tool to simplify the knowledge acquisition process

NASA Technical Reports Server (NTRS)

Gettig, Gary A.

1988-01-01

Analysts, knowledge engineers and information specialists are faced with increasing volumes of time-sensitive data in text form, either as free text or highly structured text records. Rapid access to the relevant data in these sources is essential. However, due to the volume and organization of the contents, and limitations of human memory and association, frequently: (1) important information is not located in time; (2) reams of irrelevant data are searched; and (3) interesting or critical associations are missed due to physical or temporal gaps involved in working with large files. The Knowledge Acquisition Module (KAM) is a microcomputer-based expert system designed to assist knowledge engineers, analysts, and other specialists in extracting useful knowledge from large volumes of digitized text and text-based files. KAM formulates non-explicit, ambiguous, or vague relations, rules, and facts into a manageable and consistent formal code. A library of system rules or heuristics is maintained to control the extraction of rules, relations, assertions, and other patterns from the text. These heuristics can be added, deleted or customized by the user. The user can further control the extraction process with optional topic specifications. This allows the user to cluster extracts based on specific topics. Because KAM formalizes diverse knowledge, it can be used by a variety of expert systems and automated reasoning applications. KAM can also perform important roles in computer-assisted training and skill development. Current research efforts include the applicability of neural networks to aid in the extraction process and the conversion of these extracts into standard formats.
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.
A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark J.

1991-01-01

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.
Rule of Thumb Proposing the Size of Aperture Expected to be Sufficient to Resolve Double Stars with Given Parameters

NASA Astrophysics Data System (ADS)

Knapp, Wilfried

2018-01-01

Visual observation of double stars is an anachronistic passion especially attractive for amateurs looking for sky objects suitable for visual observation even in light polluted areas. Session planning then requires a basic idea which objects might be suitable for a given equipmentâthis question is a long term issue for visual double star observers and obviously not easy to answer, especially for unequal bright components. Based on a reasonably large database with limited aperture observations (done with variable aperture equipment iris diaphragm or aperture masks) a heuristic approach is used to derive a statistically well founded Rule of Thumb formula.
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 System for Automatically Generating Scheduling Heuristics

NASA Technical Reports Server (NTRS)

Morris, Robert

1996-01-01

The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.
Simulation of empty container logistic management at depot

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Sek, Siaw-Ying Doreen; Chiew, Kang-Leng; Tiong, Wei-King

2017-07-01

This study focuses on the empty container management problem in a deficit regional area. Deficit area is the area having more export activities than the import activities, which always have a shortage of empty container. This environment has challenged the trading companies in the decision making in distributing the empty containers. A simulation model that fit to the environment is developed. Besides, a simple heuristic algorithm with some hard and soft constraints consideration are proposed to plan the logistic of empty container supply. Then, the feasible route with the minimum cost will be determined by applying the proposed heuristic algorithm. The heuristic algorithm can be divided into three main phases which are data sorting, data assigning and time window updating.
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
A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.
The neural basis of belief updating and rational decision making

PubMed Central

Achtziger, Anja; Hügelschäfer, Sabine; Steinhauser, Marco

2014-01-01

Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes’ rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision. PMID:22956673
Assessing the empirical validity of the "take-the-best" heuristic as a model of human probabilistic inference.

PubMed

Bröder, A

2000-09-01

The boundedly rational 'Take-The-Best" heuristic (TTB) was proposed by G. Gigerenzer, U. Hoffrage, and H. Kleinbölting (1991) as a model of fast and frugal probabilistic inferences. Although the simple lexicographic rule proved to be successful in computer simulations, direct empirical demonstrations of its adequacy as a psychological model are lacking because of several methodical problems. In 4 experiments with a total of 210 participants, this question was addressed. Whereas Experiment 1 showed that TTB is not valid as a universal hypothesis about probabilistic inferences, up to 28% of participants in Experiment 2 and 53% of participants in Experiment 3 were classified as TTB users. Experiment 4 revealed that investment costs for information seem to be a relevant factor leading participants to switch to a noncompensatory TTB strategy. The observed individual differences in strategy use imply the recommendation of an idiographic approach to decision-making research.
The neural basis of belief updating and rational decision making.

PubMed

Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco

2014-01-01

Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes' rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision.

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.
Mathematical programming formulations for satellite synthesis

NASA Technical Reports Server (NTRS)

Bhasin, Puneet; Reilly, Charles H.

1987-01-01

The problem of satellite synthesis can be described as optimally allotting locations and sometimes frequencies and polarizations, to communication satellites so that interference from unwanted satellite signals does not exceed a specified threshold. In this report, mathematical programming models and optimization methods are used to solve satellite synthesis problems. A nonlinear programming formulation which is solved using Zoutendijk's method and a gradient search method is described. Nine mixed integer programming models are considered. Results of computer runs with these nine models and five geographically compatible scenarios are presented and evaluated. A heuristic solution procedure is also used to solve two of the models studied. Heuristic solutions to three large synthesis problems are presented. The results of our analysis show that the heuristic performs very well, both in terms of solution quality and solution time, on the two models to which it was applied. It is concluded that the heuristic procedure is the best of the methods considered for solving satellite synthesis problems.
Lean Transformation of the Eye Clinic at The Hospital for Sick Children: Challenging an Implicit Mental Model and Lessons Learned.

PubMed

Wong, Agnes M F; During, David; Hartman, Michael; Lappan-Gracon, Stephanie; Hicks, Melody; Bajwa, Shiraz

2016-01-01

Long patient dwell time (i.e., the time between patients arriving and leaving the clinic) has been a long-standing issue in the eye clinic at The Hospital for Sick Children. By applying the Lean principles of eliminating waste and enhancing flow, we achieved a 26% reduction in the mean patient dwell time over an eight-month period. Importantly, the average time a patient spent with healthcare providers (value-added time) increased from 21% to 31%. In this paper, we summarized our experience by illustrating how an implicit mental model (conscious or unconscious conceptual framework from which we understand the world) pervades in the healthcare system based on deeply held but unexamined assumptions that arise from heuristics (general rules of thumb) and biases; how these assumptions can be tested by objective data; and how we can build a new mental model based on objective findings to improve the healthcare system.
Gaussian mixed model in support of semiglobal matching leveraged by ground control points

NASA Astrophysics Data System (ADS)

Ma, Hao; Zheng, Shunyi; Li, Chang; Li, Yingsong; Gui, Li

2017-04-01

Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.
Conway's "Game of Life" and the Epigenetic Principle.

PubMed

Caballero, Lorena; Hodge, Bob; Hernandez, Sergio

2016-01-01

Cellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories. Conway's Game of Life has been widely used for this purpose. This game was designed to explore the evolution of ecological communities. We apply it to other biological processes, including symbiopoiesis. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life.
An efficient approach to improve the usability of e-learning resources: the role of heuristic evaluation.

PubMed

Davids, Mogamat Razeen; Chikte, Usuf M E; Halperin, Mitchell L

2013-09-01

Optimizing the usability of e-learning materials is necessary to maximize their potential educational impact, but this is often neglected when time and other resources are limited, leading to the release of materials that cannot deliver the desired learning outcomes. As clinician-teachers in a resource-constrained environment, we investigated whether heuristic evaluation of our multimedia e-learning resource by a panel of experts would be an effective and efficient alternative to testing with end users. We engaged six inspectors, whose expertise included usability, e-learning, instructional design, medical informatics, and the content area of nephrology. They applied a set of commonly used heuristics to identify usability problems, assigning severity scores to each problem. The identification of serious problems was compared with problems previously found by user testing. The panel completed their evaluations within 1 wk and identified a total of 22 distinct usability problems, 11 of which were considered serious. The problems violated the heuristics of visibility of system status, user control and freedom, match with the real world, intuitive visual layout, consistency and conformity to standards, aesthetic and minimalist design, error prevention and tolerance, and help and documentation. Compared with user testing, heuristic evaluation found most, but not all, of the serious problems. Combining heuristic evaluation and user testing, with each involving a small number of participants, may be an effective and efficient way of improving the usability of e-learning materials. Heuristic evaluation should ideally be used first to identify the most obvious problems and, once these are fixed, should be followed by testing with typical end users.
A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

PubMed

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.
Act first, think later: the presence and absence of inferential planning in problem solving.

PubMed

Ormerod, Thomas C; Macgregor, James N; Chronicle, Edward P; Dewald, Andrew D; Chu, Yun

2013-10-01

Planning is fundamental to successful problem solving, yet individuals sometimes fail to plan even one step ahead when it lies within their competence to do so. In this article, we report two experiments in which we explored variants of a ball-weighing puzzle, a problem that has only two steps, yet nonetheless yields performance consistent with a failure to plan. The results fit a computational model in which a solver's attempts are determined by two heuristics: maximization of the apparent progress made toward the problem goal and minimization of the problem space in which attempts are sought. The effectiveness of these heuristics was determined by lookahead, defined operationally as the number of steps evaluated in a planned move. Where move outcomes cannot be visualized but must be inferred, planning is constrained to the point where some individuals apply zero lookahead, which with n-ball problems yields seemingly irrational unequal weighs. Applying general-purpose heuristics with or without lookahead accounts for a range of rational and irrational phenomena found with insight and noninsight problems.
The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)

NASA Technical Reports Server (NTRS)

Shuttleworth, W. James; Sorooshian, Soroosh

1996-01-01

This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be recognized from space, but also in then applying remotely-sensed land cover data to map aggregate values of BATS parameters for heterogeneous covers and interpreting these parameters in terms of surface-atmosphere exchanges.
REDEX - The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.
Index Fund Selections with GAs and Classifications Based on Turnover

NASA Astrophysics Data System (ADS)

Orito, Yukiko; Motoyama, Takaaki; Yamazaki, Genji

It is well known that index fund selections are important for the risk hedge of investment in a stock market. The`selection’means that for`stock index futures’, n companies of all ones in the market are selected. For index fund selections, Orito et al.(6) proposed a method consisting of the following two steps : Step 1 is to select N companies in the market with a heuristic rule based on the coefficient of determination between the return rate of each company in the market and the increasing rate of the stock price index. Step 2 is to construct a group of n companies by applying genetic algorithms to the set of N companies. We note that the rule of Step 1 is not unique. The accuracy of the results using their method depends on the length of time data (price data) in the experiments. The main purpose of this paper is to introduce a more`effective rule’for Step 1. The rule is based on turnover. The method consisting of Step 1 based on turnover and Step 2 is examined with numerical experiments for the 1st Section of Tokyo Stock Exchange. The results show that with our method, it is possible to construct the more effective index fund than the results of Orito et al.(6). The accuracy of the results using our method depends little on the length of time data (turnover data). The method especially works well when the increasing rate of the stock price index over a period can be viewed as a linear time series data.
REDEX: The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.
REDEX - The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.
REDEX: The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-04-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.
Monitoring Agents for Assisting NASA Engineers with Shuttle Ground Processing

NASA Technical Reports Server (NTRS)

Semmel, Glenn S.; Davis, Steven R.; Leucht, Kurt W.; Rowe, Danil A.; Smith, Kevin E.; Boeloeni, Ladislau

2005-01-01

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has designed, developed, and deployed a rule-based agent to monitor the Space Shuttle's ground processing telemetry stream. The NASA Engineering Shuttle Telemetry Agent increases situational awareness for system and hardware engineers during ground processing of the Shuttle's subsystems. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when user defined conditions are satisfied. Efficiency and safety are improved through increased automation. Sandia National Labs' Java Expert System Shell is employed as the agent's rule engine. The shell's predicate logic lends itself well to capturing the heuristics and specifying the engineering rules within this domain. The declarative paradigm of the rule-based agent yields a highly modular and scalable design spanning multiple subsystems of the Shuttle. Several hundred monitoring rules have been written thus far with corresponding notifications sent to Shuttle engineers. This chapter discusses the rule-based telemetry agent used for Space Shuttle ground processing. We present the problem domain along with design and development considerations such as information modeling, knowledge capture, and the deployment of the product. We also present ongoing work with other condition monitoring agents.
C-Language Integrated Production System, Version 6.0

NASA Technical Reports Server (NTRS)

Riley, Gary; Donnell, Brian; Ly, Huyen-Anh Bebe; Ortiz, Chris

1995-01-01

C Language Integrated Production System (CLIPS) computer programs are specifically intended to model human expertise or other knowledge. CLIPS is designed to enable research on, and development and delivery of, artificial intelligence on conventional computers. CLIPS 6.0 provides cohesive software tool for handling wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented, and procedural. Rule-based programming: representation of knowledge as heuristics - essentially, rules of thumb that specify set of actions performed in given situation. Object-oriented programming: modeling of complex systems comprised of modular components easily reused to model other systems or create new components. Procedural-programming: representation of knowledge in ways similar to those of such languages as C, Pascal, Ada, and LISP. Version of CLIPS 6.0 for IBM PC-compatible computers requires DOS v3.3 or later and/or Windows 3.1 or later.
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.
Maximizing the nurses' preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Jafari, Hamed; Salmasi, Nasser

2015-09-01

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.
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.
Mechanical Transformation of Task Heuristics into Operational Procedures

DTIC Science & Technology

1981-04-14

Introduction A central theme of recent research in artificial intelligence is that *Intelligent task performance requires large amounts of knowledge...PLAY P1 C4] (. (LEADING (QSO)) (OR (CAN-LEAO- HEARrS (gSO)J (mEg (SUIT-OF C3) H])] C-) (FOLLOWING (QSO)) (OR [VOID (OSO) (SUIT-LED)3 [IN-SUIT C3 (SUIT...Production rules as a representation for a knowledge based consultation system. Artificial Intelligence 8:15-45, Spring, 1977. [Davis 77b] R. Davis
Optimal harvesting for a predator-prey agent-based model using difference equations.

PubMed

Oremland, Matthew; Laubenbacher, Reinhard

2015-03-01

In this paper, a method known as Pareto optimization is applied in the solution of a multi-objective optimization problem. The system in question is an agent-based model (ABM) wherein global dynamics emerge from local interactions. A system of discrete mathematical equations is formulated in order to capture the dynamics of the ABM; while the original model is built up analytically from the rules of the model, the paper shows how minor changes to the ABM rule set can have a substantial effect on model dynamics. To address this issue, we introduce parameters into the equation model that track such changes. The equation model is amenable to mathematical theory—we show how stability analysis can be performed and validated using ABM data. We then reduce the equation model to a simpler version and implement changes to allow controls from the ABM to be tested using the equations. Cohen's weighted κ is proposed as a measure of similarity between the equation model and the ABM, particularly with respect to the optimization problem. The reduced equation model is used to solve a multi-objective optimization problem via a technique known as Pareto optimization, a heuristic evolutionary algorithm. Results show that the equation model is a good fit for ABM data; Pareto optimization provides a suite of solutions to the multi-objective optimization problem that can be implemented directly in the ABM.
Building a Personalized Cancer Treatment System.

PubMed

Martinez, Alexandra; López, Gustavo; Bola Nos, Constantino; Alvarado, Daniel; Solano, Andrés; López, Mariana; Báez, Andrés; Quirós, Steve; Mora, Rodrigo

2017-02-01

This paper reports the process by which a personalized cancer treatment system was built, following a user-centered approach. We give some background on personalized cancer treatment, the particular tumor chemosensitivity assay supported by the system, as well as some quality and legal issues related to such health systems. We describe how Contextual Design was applied when building the system. Contextual design is a user-centered design technique involving seven steps. We also provide some details about the system implementation. Finally, we explain how the Think-Aloud protocol and Heuristic Evaluation methods were used to evaluate the system and report its results. A qualitative assessment from the users perspective is also provided. Results from the heuristic evaluation indicate that only one of ten heuristics was missing from the system, while five were partially covered and four were fully covered.
SURE (Science User Resource Expert): A science planning and scheduling assistant for a resource based environment

NASA Technical Reports Server (NTRS)

Thalman, Nancy E.; Sparn, Thomas P.

1990-01-01

SURE (Science User Resource Expert) is one of three components that compose the SURPASS (Science User Resource Planning and Scheduling System). This system is a planning and scheduling tool which supports distributed planning and scheduling, based on resource allocation and optimization. Currently SURE is being used within the SURPASS by the UARS (Upper Atmospheric Research Satellite) SOLSTICE instrument to build a daily science plan and activity schedule and in a prototyping effort with NASA GSFC to demonstrate distributed planning and scheduling for the SOLSTICE II instrument on the EOS platform. For the SOLSTICE application the SURE utilizes a rule-based system. Development of a rule-based program using Ada CLIPS as opposed to using conventional programming, allows for capture of the science planning and scheduling heuristics in rules and provides flexibility in inserting or removing rules as the scientific objectives and mission constraints change. The SURE system's role as a component in the SURPASS, the purpose of the SURE planning and scheduling tool, the SURE knowledge base, and the software architecture of the SURE component are described.
Modeling User Behavior in Computer Learning Tasks.

ERIC Educational Resources Information Center

Mantei, Marilyn M.

Model building techniques from Artifical Intelligence and Information-Processing Psychology are applied to human-computer interface tasks to evaluate existing interfaces and suggest new and better ones. The model is in the form of an augmented transition network (ATN) grammar which is built by applying grammar induction heuristics on a sequential…
Commentary: Narrative Ethnography as Applied Communication Research

ERIC Educational Resources Information Center

Goodall, H. L., Jr.

2004-01-01

The breadth and heuristic merits of Harold (Buddy) Goodall's scholarship exemplify the teachings and influence of Gerald Phillips. One nominator applauds Goodall's leadership and dedication to furthering the visibility and utility of applied communication. Goodall's research is also widely used in other fields such as sociology and anthropology,…
Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

NASA Technical Reports Server (NTRS)

Gilmore, John F. (Editor)

1987-01-01

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.
Automated Classification of Phonological Errors in Aphasic Language

PubMed Central

Ahuja, Sanjeev B.; Reggia, James A.; Berndt, Rita S.

1984-01-01

Using heuristically-guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically-impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work introduces and evaluates a novel approach to error simulation and classification, it provides a prototype simulation tool for neurolinguistic research, and it forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.

PubMed

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants' choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis

PubMed Central

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection. PMID:28867996
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
Approximating Optimal Behavioural Strategies Down to Rules-of-Thumb: Energy Reserve Changes in Pairs of Social Foragers

PubMed Central

Rands, Sean A.

2011-01-01

Functional explanations of behaviour often propose optimal strategies for organisms to follow. These ‘best’ strategies could be difficult to perform given biological constraints such as neural architecture and physiological constraints. Instead, simple heuristics or ‘rules-of-thumb’ that approximate these optimal strategies may instead be performed. From a modelling perspective, rules-of-thumb are also useful tools for considering how group behaviour is shaped by the behaviours of individuals. Using simple rules-of-thumb reduces the complexity of these models, but care needs to be taken to use rules that are biologically relevant. Here, we investigate the similarity between the outputs of a two-player dynamic foraging game (which generated optimal but complex solutions) and a computational simulation of the behaviours of the two members of a foraging pair, who instead followed a rule-of-thumb approximation of the game's output. The original game generated complex results, and we demonstrate here that the simulations following the much-simplified rules-of-thumb also generate complex results, suggesting that the rule-of-thumb was sufficient to make some of the model outcomes unpredictable. There was some agreement between both modelling techniques, but some differences arose – particularly when pair members were not identical in how they gained and lost energy. We argue that exploring how rules-of-thumb perform in comparison to their optimal counterparts is an important exercise for biologically validating the output of agent-based models of group behaviour. PMID:21765938
Approximating optimal behavioural strategies down to rules-of-thumb: energy reserve changes in pairs of social foragers.

PubMed

Rands, Sean A

2011-01-01

Functional explanations of behaviour often propose optimal strategies for organisms to follow. These 'best' strategies could be difficult to perform given biological constraints such as neural architecture and physiological constraints. Instead, simple heuristics or 'rules-of-thumb' that approximate these optimal strategies may instead be performed. From a modelling perspective, rules-of-thumb are also useful tools for considering how group behaviour is shaped by the behaviours of individuals. Using simple rules-of-thumb reduces the complexity of these models, but care needs to be taken to use rules that are biologically relevant. Here, we investigate the similarity between the outputs of a two-player dynamic foraging game (which generated optimal but complex solutions) and a computational simulation of the behaviours of the two members of a foraging pair, who instead followed a rule-of-thumb approximation of the game's output. The original game generated complex results, and we demonstrate here that the simulations following the much-simplified rules-of-thumb also generate complex results, suggesting that the rule-of-thumb was sufficient to make some of the model outcomes unpredictable. There was some agreement between both modelling techniques, but some differences arose - particularly when pair members were not identical in how they gained and lost energy. We argue that exploring how rules-of-thumb perform in comparison to their optimal counterparts is an important exercise for biologically validating the output of agent-based models of group behaviour.
Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.
Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633
Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor.

PubMed

Ansari, A H; Cherian, P J; Dereymaeker, A; Matic, V; Jansen, K; De Wispelaere, L; Dielman, C; Vervisch, J; Swarte, R M; Govaert, P; Naulaers, G; De Vos, M; Van Huffel, S

2016-09-01

After identifying the most seizure-relevant characteristics by a previously developed heuristic classifier, a data-driven post-processor using a novel set of features is applied to improve the performance. The main characteristics of the outputs of the heuristic algorithm are extracted by five sets of features including synchronization, evolution, retention, segment, and signal features. Then, a support vector machine and a decision making layer remove the falsely detected segments. Four datasets including 71 neonates (1023h, 3493 seizures) recorded in two different university hospitals, are used to train and test the algorithm without removing the dubious seizures. The heuristic method resulted in a false alarm rate of 3.81 per hour and good detection rate of 88% on the entire test databases. The post-processor, effectively reduces the false alarm rate by 34% while the good detection rate decreases by 2%. This post-processing technique improves the performance of the heuristic algorithm. The structure of this post-processor is generic, improves our understanding of the core visually determined EEG features of neonatal seizures and is applicable for other neonatal seizure detectors. The post-processor significantly decreases the false alarm rate at the expense of a small reduction of the good detection rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. 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.
A real-time expert system for self-repairing flight control

NASA Technical Reports Server (NTRS)

Gaither, S. A.; Agarwal, A. K.; Shah, S. C.; Duke, E. L.

1989-01-01

An integrated environment for specifying, prototyping, and implementing a self-repairing flight-control (SRFC) strategy is described. At an interactive workstation, the user can select paradigms such as rule-based expert systems, state-transition diagrams, and signal-flow graphs and hierarchically nest them, assign timing and priority attributes, establish blackboard-type communication, and specify concurrent execution on single or multiple processors. High-fidelity nonlinear simulations of aircraft and SRFC systems can be performed off-line, with the possibility of changing SRFC rules, inference strategies, and other heuristics to correct for control deficiencies. Finally, the off-line-generated SRFC can be transformed into highly optimized application-specific real-time C-language code. An application of this environment to the design of aircraft fault detection, isolation, and accommodation algorithms is presented in detail.

Unsafe sex: decision-making biases and heuristics.

PubMed

Kaplan, B J; Shayne, V T

1993-01-01

This paper suggests that continued high-risk behavior is the result of the heuristics used to make judgments under uncertainty, and that the same heuristics may be mobilized to increase the use of safer-sex practices. In order to explain why it is that individuals fail to make effective use of the information they may have concerning rates of infection, consequences of infection and their own at-risk status, theory and research in several areas will be considered. Developments in the breadth of areas to which basic research on decision-making has been applied continue to provide new approaches toward understanding and overcoming the processes by which we reason (Kahnemann, 1991). It is worth reminding ourselves that public health campaigns in other areas have led to changes in behavior. Reasoning, even with its biases, is still the route by which we make decisions, most of them effective and self-protective.
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.
Examining student heuristic usage in a hydrogen bonding assessment.

PubMed

Miller, Kathryn; Kim, Thomas

2017-09-01

This study investigates the role of representational competence in student responses to an assessment of hydrogen bonding. The assessment couples the use of a multiple-select item ("Choose all that apply") with an open-ended item to allow for an examination of students' cognitive processes as they relate to the assignment of hydrogen bonding within a structural representation. Response patterns from the multiple-select item implicate heuristic usage as a contributing factor to students' incorrect responses. The use of heuristics is further supported by the students' corresponding responses to the open-ended assessment item. Taken together, these data suggest that poor representational competence may contribute to students' previously observed inability to correctly navigate the concept of hydrogen bonding. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):411-416, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.
A detailed comparison of optimality and simplicity in perceptual decision-making

PubMed Central

Shen, Shan; Ma, Wei Ji

2017-01-01

Two prominent ideas in the study of decision-making have been that organisms behave near-optimally, and that they use simple heuristic rules. These principles might be operating in different types of tasks, but this possibility cannot be fully investigated without a direct, rigorous comparison within a single task. Such a comparison was lacking in most previous studies, because a) the optimal decision rule was simple; b) no simple suboptimal rules were considered; c) it was unclear what was optimal, or d) a simple rule could closely approximate the optimal rule. Here, we used a perceptual decision-making task in which the optimal decision rule is well-defined and complex, and makes qualitatively distinct predictions from many simple suboptimal rules. We find that all simple rules tested fail to describe human behavior, that the optimal rule accounts well for the data, and that several complex suboptimal rules are indistinguishable from the optimal one. Moreover, we found evidence that the optimal model is close to the true model: first, the better the trial-to-trial predictions of a suboptimal model agree with those of the optimal model, the better that suboptimal model fits; second, our estimate of the Kullback-Leibler divergence between the optimal model and the true model is not significantly different from zero. When observers receive no feedback, the optimal model still describes behavior best, suggesting that sensory uncertainty is implicitly represented and taken into account. Beyond the task and models studied here, our results have implications for best practices of model comparison. PMID:27177259
An Intelligent computer-aided tutoring system for diagnosing anomalies of spacecraft in operation

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1993-01-01

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.
Decision Rules and Group Rationality: Cognitive Gain or Standstill?

PubMed Central

Curşeu, Petru Lucian; Jansen, Rob J. G.; Chappin, Maryse M. H.

2013-01-01

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups. PMID:23451050
Decision rules and group rationality: cognitive gain or standstill?

PubMed

Curşeu, Petru Lucian; Jansen, Rob J G; Chappin, Maryse M H

2013-01-01

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members' cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.
Conway's “Game of Life” and the Epigenetic Principle

PubMed Central

Caballero, Lorena; Hodge, Bob; Hernandez, Sergio

2016-01-01

Cellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories. Conway's Game of Life has been widely used for this purpose. This game was designed to explore the evolution of ecological communities. We apply it to other biological processes, including symbiopoiesis. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life PMID:27379213
Conceptual frameworks of individual work performance: a systematic review.

PubMed

Koopmans, Linda; Bernaards, Claire M; Hildebrandt, Vincent H; Schaufeli, Wilmar B; de Vet Henrica, C W; van der Beek, Allard J

2011-08-01

Individual work performance is differently conceptualized and operationalized in different disciplines. The aim of the current review was twofold: (1) identifying conceptual frameworks of individual work performance and (2) integrating these to reach a heuristic conceptual framework. A systematic review was conducted in medical, psychological, and management databases. Studies were selected independently by two researchers and included when they presented a conceptual framework of individual work performance. A total of 17 generic frameworks (applying across occupations) and 18 job-specific frameworks (applying to specific occupations) were identified. Dimensions frequently used to describe individual work performance were task performance, contextual performance, counterproductive work behavior, and adaptive performance. On the basis of the literature, a heuristic conceptual framework of individual work performance was proposed. This framework can serve as a theoretical basis for future research and practice.
Micro-seismic waveform matching inversion based on gravitational search algorithm and parallel computation

NASA Astrophysics Data System (ADS)

Jiang, Y.; Xing, H. L.

2016-12-01

Micro-seismic events induced by water injection, mining activity or oil/gas extraction are quite informative, the interpretation of which can be applied for the reconstruction of underground stress and monitoring of hydraulic fracturing progress in oil/gas reservoirs. The source characterises and locations are crucial parameters that required for these purposes, which can be obtained through the waveform matching inversion (WMI) method. Therefore it is imperative to develop a WMI algorithm with high accuracy and convergence speed. Heuristic algorithm, as a category of nonlinear method, possesses a very high convergence speed and good capacity to overcome local minimal values, and has been well applied for many areas (e.g. image processing, artificial intelligence). However, its effectiveness for micro-seismic WMI is still poorly investigated; very few literatures exits that addressing this subject. In this research an advanced heuristic algorithm, gravitational search algorithm (GSA) , is proposed to estimate the focal mechanism (angle of strike, dip and rake) and source locations in three dimension. Unlike traditional inversion methods, the heuristic algorithm inversion does not require the approximation of green function. The method directly interacts with a CPU parallelized finite difference forward modelling engine, and updating the model parameters under GSA criterions. The effectiveness of this method is tested with synthetic data form a multi-layered elastic model; the results indicate GSA can be well applied on WMI and has its unique advantages. Keywords: Micro-seismicity, Waveform matching inversion, gravitational search algorithm, parallel computation
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.
Column generation algorithms for virtual network embedding in flexi-grid optical networks.

PubMed

Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe

2018-04-16

Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.
Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
Lexique et procedures heuristiques. Arguments pour un renouvellement de l'enseignement du vocabulaire au degre elementaire (Word-Study and Heuristic Processes. Arguments for a Renewal in the Teaching of Vocabulary at the Elementary Level). Acts of the Colloquium of the Swiss Interuniversity Commission for Applied Linguistics. CILA Bulletin, No. 28.

ERIC Educational Resources Information Center

Muller, Charles

A study is described of heuristic devices useful in learning both native and second languages. The study concerns particularly the means used by very young students (second and third graders) in vocabulary acquisition and in the establishment of semantic relationships. It was of concern to verify if (1) the children would use their knowledge of…
Heuristic Optimization Approach to Selecting a Transport Connection in City Public Transport

NASA Astrophysics Data System (ADS)

Kul'ka, Jozef; Mantič, Martin; Kopas, Melichar; Faltinová, Eva; Kachman, Daniel

2017-02-01

The article presents a heuristic optimization approach to select a suitable transport connection in the framework of a city public transport. This methodology was applied on a part of the public transport in Košice, because it is the second largest city in the Slovak Republic and its network of the public transport creates a complex transport system, which consists of three different transport modes, namely from the bus transport, tram transport and trolley-bus transport. This solution focused on examining the individual transport services and their interconnection in relevant interchange points.
Heuristic algorithm for optical character recognition of Arabic script

NASA Astrophysics Data System (ADS)

Yarman-Vural, Fatos T.; Atici, A.

1996-02-01

In this paper, a heuristic method is developed for segmentation, feature extraction and recognition of the Arabic script. The study is part of a large project for the transcription of the documents in Ottoman Archives. A geometrical and topological feature analysis method is developed for segmentation and feature extraction stages. Chain code transformation is applied to main strokes of the characters which are then classified by the hidden Markov model (HMM) in the recognition stage. Experimental results indicate that the performance of the proposed method is impressive, provided that the thinning process does not yield spurious branches.
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
Of mental models, assumptions and heuristics: The case of acids and acid strength

NASA Astrophysics Data System (ADS)

McClary, Lakeisha Michelle

This study explored what cognitive resources (i.e., units of knowledge necessary to learn) first-semester organic chemistry students used to make decisions about acid strength and how those resources guided the prediction, explanation and justification of trends in acid strength. We were specifically interested in the identifying and characterizing the mental models, assumptions and heuristics that students relied upon to make their decisions, in most cases under time constraints. The views about acids and acid strength were investigated for twenty undergraduate students. Data sources for this study included written responses and individual interviews. The data was analyzed using a qualitative methodology to answer five research questions. Data analysis regarding these research questions was based on existing theoretical frameworks: problem representation (Chi, Feltovich & Glaser, 1981), mental models (Johnson-Laird, 1983); intuitive assumptions (Talanquer, 2006), and heuristics (Evans, 2008). These frameworks were combined to develop the framework from which our data were analyzed. Results indicated that first-semester organic chemistry students' use of cognitive resources was complex and dependent on their understanding of the behavior of acids. Expressed mental models were generated using prior knowledge and assumptions about acids and acid strength; these models were then employed to make decisions. Explicit and implicit features of the compounds in each task mediated participants' attention, which triggered the use of a very limited number of heuristics, or shortcut reasoning strategies. Many students, however, were able to apply more effortful analytic reasoning, though correct trends were predicted infrequently. Most students continued to use their mental models, assumptions and heuristics to explain a given trend in acid strength and to justify their predicted trends, but the tasks influenced a few students to shift from one model to another model. An emergent finding from this project was that the problem representation greatly influenced students' ability to make correct predictions in acid strength. Many students, however, were able to apply more effortful analytic reasoning, though correct trends were predicted infrequently. Most students continued to use their mental models, assumptions and heuristics to explain a given trend in acid strength and to justify their predicted trends, but the tasks influenced a few students to shift from one model to another model. An emergent finding from this project was that the problem representation greatly influenced students' ability to make correct predictions in acid strength.
A continuous usability evaluation of an electronic medication administration record application.

PubMed

Vicente Oliveros, Noelia; Gramage Caro, Teresa; Pérez Menéndez-Conde, Covadonga; Álvarez-Diaz, Ana María; Martín-Aragón Álvarez, Sagrario; Bermejo Vicedo, Teresa; Delgado Silveira, Eva

2017-12-01

The complexity of an electronic medication administration record (eMAR) has been underestimated by most designers in the past. Usability issues, such as poorly designed user application flow in eMAR, are therefore of vital importance, since they can have a negative impact on nursing activities and result in poor outcomes. The purpose of this study was to evaluate the usability of an eMAR application during its development. A usability evaluation was conducted during the development of the eMAR application. Two usability methods were used: a heuristic evaluation complemented by usability testing. Each eMAR application version provided by the vendor was evaluated by 2 hospital pharmacists, who applied the heuristic method. They reviewed the eMAR tasks, detected usability problems and their heuristic violations, and rated the severity of the usability problems. Usability testing was used to assess the final application version by observing how 3 nurses interacted with the application. Thirty-four versions were assessed before the eMAR application was considered usable. During the heuristic evaluation, the usability problems decreased from 46 unique usability problems in version 1 (V1) to 9 in version 34 (V34). In V1, usability problems were categorized into 154 heuristic violations, which decreased to 27 in V34. The average severity rating also decreased from major usability problem (2.96) to no problem (0.23). During usability testing, the 3 nurses did not encounter new usability problems. A thorough heuristic evaluation is a good method for obtaining a usable eMAR application. This evaluation points key areas for improvement and decreases usability problems and their severity. © 2017 John Wiley & Sons, Ltd.

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.
Geographical variation in body size and sexual size dimorphism in an Australian lizard, Boulenger's Skink (Morethia boulengeri).

PubMed

Michael, Damian R; Banks, Sam C; Piggott, Maxine P; Cunningham, Ross B; Crane, Mason; MacGregor, Christopher; McBurney, Lachlan; Lindenmayer, David B

2014-01-01

Ecogeographical rules help explain spatial and temporal patterns in intraspecific body size. However, many of these rules, when applied to ectothermic organisms such as reptiles, are controversial and require further investigation. To explore factors that influence body size in reptiles, we performed a heuristic study to examine body size variation in an Australian lizard, Boulenger's Skink Morethia boulengeri from agricultural landscapes in southern New South Wales, south-eastern Australia. We collected tissue and morphological data on 337 adult lizards across a broad elevation and climate gradient. We used a model-selection procedure to determine if environmental or ecological variables best explained body size variation. We explored the relationship between morphology and phylogenetic structure before modeling candidate variables from four broad domains: (1) geography (latitude, longitude and elevation), (2) climate (temperature and rainfall), (3) habitat (vegetation type, number of logs and ground cover attributes), and (4) management (land use and grazing history). Broad phylogenetic structure was evident, but on a scale larger than our study area. Lizards were sexually dimorphic, whereby females had longer snout-vent length than males, providing support for the fecundity selection hypothesis. Body size variation in M. boulengeri was correlated with temperature and rainfall, a pattern consistent with larger individuals occupying cooler and more productive parts of the landscape. Climate change forecasts, which predict warmer temperature and increased aridity, may result in reduced lizard biomass and decoupling of trophic interactions with potential implications for community organization and ecosystem function.
How to Talk about Professional Communication: Metalanguage and Heuristic Power.

ERIC Educational Resources Information Center

Killingsworth, M. Jimmie

1989-01-01

Analyzes several examples of metalanguage from current literature on professional writing, applying three principles for evaluating metalanguage in industry and academe. Considers a potentially effective metalanguage based on simple grammatical expressions. (MM)
Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving.

PubMed

Wiener, J M; Ehbauer, N N; Mallot, H A

2009-09-01

For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.
Evolving rule-based systems in two medical domains using genetic programming.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

2004-11-01

To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.
Learning Quanta: Barriers to Stimulating Transitions in Student Understanding of Orbital Ideas

ERIC Educational Resources Information Center

Taber, Keith S.

2005-01-01

This paper reports the results of applying a particular analytical perspective to data from an interview study: a typology of learning impediments informed by research into learning and students' ideas in science. This typology is a heuristic tool that may help diagnose the origins of students' learning difficulties. Here it is applied to data…
Applying Quality Indicators to Single-Case Research Designs Used in Special Education: A Systematic Review

ERIC Educational Resources Information Center

Moeller, Jeremy D.; Dattilo, John; Rusch, Frank

2015-01-01

This study examined how specific guidelines and heuristics have been used to identify methodological rigor associated with single-case research designs based on quality indicators developed by Horner et al. Specifically, this article describes how literature reviews have applied Horner et al.'s quality indicators and evidence-based criteria.…
Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.
Kotai Antibody Builder: automated high-resolution structural modeling of antibodies.

PubMed

Yamashita, Kazuo; Ikeda, Kazuyoshi; Amada, Karlou; Liang, Shide; Tsuchiya, Yuko; Nakamura, Haruki; Shirai, Hiroki; Standley, Daron M

2014-11-15

Kotai Antibody Builder is a Web service for tertiary structural modeling of antibody variable regions. It consists of three main steps: hybrid template selection by sequence alignment and canonical rules, 3D rendering of alignments and CDR-H3 loop modeling. For the last step, in addition to rule-based heuristics used to build the initial model, a refinement option is available that uses fragment assembly followed by knowledge-based scoring. Using targets from the Second Antibody Modeling Assessment, we demonstrate that Kotai Antibody Builder generates models with an overall accuracy equal to that of the best-performing semi-automated predictors using expert knowledge. Kotai Antibody Builder is available at http://kotaiab.org standley@ifrec.osaka-u.ac.jp. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Post-game analysis: An initial experiment for heuristic-based resource management in concurrent systems

NASA Technical Reports Server (NTRS)

Yan, Jerry C.

1987-01-01

In concurrent systems, a major responsibility of the resource management system is to decide how the application program is to be mapped onto the multi-processor. Instead of using abstract program and machine models, a generate-and-test framework known as 'post-game analysis' that is based on data gathered during program execution is proposed. Each iteration consists of (1) (a simulation of) an execution of the program; (2) analysis of the data gathered; and (3) the proposal of a new mapping that would have a smaller execution time. These heuristics are applied to predict execution time changes in response to small perturbations applied to the current mapping. An initial experiment was carried out using simple strategies on 'pipeline-like' applications. The results obtained from four simple strategies demonstrated that for this kind of application, even simple strategies can produce acceptable speed-up with a small number of iterations.
Analysis of complex network performance and heuristic node removal strategies

NASA Astrophysics Data System (ADS)

Jahanpour, Ehsan; Chen, Xin

2013-12-01

Removing important nodes from complex networks is a great challenge in fighting against criminal organizations and preventing disease outbreaks. Six network performance metrics, including four new metrics, are applied to quantify networks' diffusion speed, diffusion scale, homogeneity, and diameter. In order to efficiently identify nodes whose removal maximally destroys a network, i.e., minimizes network performance, ten structured heuristic node removal strategies are designed using different node centrality metrics including degree, betweenness, reciprocal closeness, complement-derived closeness, and eigenvector centrality. These strategies are applied to remove nodes from the September 11, 2001 hijackers' network, and their performance are compared to that of a random strategy, which removes randomly selected nodes, and the locally optimal solution (LOS), which removes nodes to minimize network performance at each step. The computational complexity of the 11 strategies and LOS is also analyzed. Results show that the node removal strategies using degree and betweenness centralities are more efficient than other strategies.
"First, know thyself": cognition and error in medicine.

PubMed

Elia, Fabrizio; Aprà, Franco; Verhovez, Andrea; Crupi, Vincenzo

2016-04-01

Although error is an integral part of the world of medicine, physicians have always been little inclined to take into account their own mistakes and the extraordinary technological progress observed in the last decades does not seem to have resulted in a significant reduction in the percentage of diagnostic errors. The failure in the reduction in diagnostic errors, notwithstanding the considerable investment in human and economic resources, has paved the way to new strategies which were made available by the development of cognitive psychology, the branch of psychology that aims at understanding the mechanisms of human reasoning. This new approach led us to realize that we are not fully rational agents able to take decisions on the basis of logical and probabilistically appropriate evaluations. In us, two different and mostly independent modes of reasoning coexist: a fast or non-analytical reasoning, which tends to be largely automatic and fast-reactive, and a slow or analytical reasoning, which permits to give rationally founded answers. One of the features of the fast mode of reasoning is the employment of standardized rules, termed "heuristics." Heuristics lead physicians to correct choices in a large percentage of cases. Unfortunately, cases exist wherein the heuristic triggered fails to fit the target problem, so that the fast mode of reasoning can lead us to unreflectively perform actions exposing us and others to variable degrees of risk. Cognitive errors arise as a result of these cases. Our review illustrates how cognitive errors can cause diagnostic problems in clinical practice.
Improvements on the minimax algorithm for the Laplace transformation of orbital energy denominators

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

Helmich-Paris, Benjamin, E-mail: b.helmichparis@vu.nl; Visscher, Lucas, E-mail: l.visscher@vu.nl

2016-09-15

We present a robust and non-heuristic algorithm that finds all extremum points of the error distribution function of numerically Laplace-transformed orbital energy denominators. The extremum point search is one of the two key steps for finding the minimax approximation. If pre-tabulation of initial guesses is supposed to be avoided, strategies for a sufficiently robust algorithm have not been discussed so far. We compare our non-heuristic approach with a bracketing and bisection algorithm and demonstrate that 3 times less function evaluations are required altogether when applying it to typical non-relativistic and relativistic quantum chemical systems.
[The role of gut instinct is an important subject].

PubMed

Snoek, Jos W

2010-01-01

The role of gut instinct in general practice is an important topic. The reliance on gut instinct by experienced doctors is thought to be a form of intuitive decision-making which fits in with System 1 processes in the dual process model in higher cognition. Special mention is made of the theories on intuitive decision-making by the famous Dutch psychologist De Groot, who, when investigating thought processes of chess masters more than half a century ago, developed a fundamental theory on intuitive heuristics. Further studies on the determinants and conditions under which heuristics, such as the reliance on gut instinct, are applied in clinical practice are very welcome.
Fluent, fast, and frugal? A formal model evaluation of the interplay between memory, fluency, and comparative judgments.

PubMed

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

2011-07-01

A new process model of the interplay between memory and judgment processes was recently suggested, assuming that retrieval fluency-that is, the speed with which objects are recognized-will determine inferences concerning such objects in a single-cue fashion. This aspect of the fluency heuristic, an extension of the recognition heuristic, has remained largely untested due to methodological difficulties. To overcome the latter, we propose a measurement model from the class of multinomial processing tree models that can estimate true single-cue reliance on recognition and retrieval fluency. We applied this model to aggregate and individual data from a probabilistic inference experiment and considered both goodness of fit and model complexity to evaluate different hypotheses. The results were relatively clear-cut, revealing that the fluency heuristic is an unlikely candidate for describing comparative judgments concerning recognized objects. These findings are discussed in light of a broader theoretical view on the interplay of memory and judgment processes.
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 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.
Optimal pattern distributions in Rete-based production systems

NASA Technical Reports Server (NTRS)

Scott, Stephen L.

1994-01-01

Since its introduction into the AI community in the early 1980's, the Rete algorithm has been widely used. This algorithm has formed the basis for many AI tools, including NASA's CLIPS. One drawback of Rete-based implementation, however, is that the network structures used internally by the Rete algorithm make it sensitive to the arrangement of individual patterns within rules. Thus while rules may be more or less arbitrarily placed within source files, the distribution of individual patterns within these rules can significantly affect the overall system performance. Some heuristics have been proposed to optimize pattern placement, however, these suggestions can be conflicting. This paper describes a systematic effort to measure the effect of pattern distribution on production system performance. An overview of the Rete algorithm is presented to provide context. A description of the methods used to explore the pattern ordering problem area are presented, using internal production system metrics such as the number of partial matches, and coarse-grained operating system data such as memory usage and time. The results of this study should be of interest to those developing and optimizing software for Rete-based production systems.
Distrust and the positive test heuristic: dispositional and situated social distrust improves performance on the Wason rule discovery task.

PubMed

Mayo, Ruth; Alfasi, Dana; Schwarz, Norbert

2014-06-01

Feelings of distrust alert people not to take information at face value, which may influence their reasoning strategy. Using the Wason (1960) rule identification task, we tested whether chronic and temporary distrust increase the use of negative hypothesis testing strategies suited to falsify one's own initial hunch. In Study 1, participants who were low in dispositional trust were more likely to engage in negative hypothesis testing than participants high in dispositional trust. In Study 2, trust and distrust were induced through an alleged person-memory task. Paralleling the effects of chronic distrust, participants exposed to a single distrust-eliciting face were 3 times as likely to engage in negative hypothesis testing as participants exposed to a trust-eliciting face. In both studies, distrust increased negative hypothesis testing, which was associated with better performance on the Wason task. In contrast, participants' initial rule generation was not consistently affected by distrust. These findings provide first evidence that distrust can influence which reasoning strategy people adopt. PsycINFO Database Record (c) 2014 APA, all rights reserved.
An on-line expert system for diagnosing environmentally induced spacecraft anomalies using CLIPS

NASA Technical Reports Server (NTRS)

Lauriente, Michael; Rolincik, Mark; Koons, Harry C; Gorney, David

1993-01-01

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred rules and provide links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information (varying degrees of confidence in an answer) or 'unknown' to any question. The expert system not only provides scientists with needed risk analysis and confidence estimates not available in standard numerical models or databases, but it is also an effective learning tool. In addition, the architecture of the expert system allows easy additions to the knowledge base and the database. For example, new frames concerning orbital debris and ionospheric scintillation are being considered. The system currently runs on a MicroVAX and uses the C Language Integrated Production System (CLIPS).

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…
Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.
A simple and effective figure caption detection system for old-style documents

NASA Astrophysics Data System (ADS)

Liu, Zongyi; Zhou, Hanning

2011-01-01

Identifying figure captions has wide applications in producing high quality e-books such as kindle books or ipad books. In this paper, we present a rule-based system to detect horizontal figure captions in old-style documents. Our algorithm consists of three steps: (i) segment images into regions of different types such as text and figures, (ii) search the best caption region candidate based on heuristic rules such as region alignments and distances, and (iii) expand caption regions identified in step (ii) with its neighboring text-regions in order to correct oversegmentation errors. We test our algorithm using 81 images collected from old-style books, with each image containing at least one figure area. We show that the approach is able to correctly detect figure captions from images with different layouts, and we also measure its performances in terms of both precision rate and recall rate.
A hybrid, auto-adaptive and rule-based multi-agent approach using evolutionary algorithms for improved searching

NASA Astrophysics Data System (ADS)

Izquierdo, Joaquín; Montalvo, Idel; Campbell, Enrique; Pérez-García, Rafael

2016-08-01

Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same regardless of the size, complexity and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm using techniques derived from knowledge discovery (data-mining techniques) on databases of so-far visited solutions. The aim is to improve the search mechanisms, increase computational efficiency and use rules to enrich the formulation of optimization problems, while reducing the search space and catering to realistic problems.
Resource Planning for Massive Number of Process Instances

NASA Astrophysics Data System (ADS)

Xu, Jiajie; Liu, Chengfei; Zhao, Xiaohui

Resource allocation has been recognised as an important topic for business process execution. In this paper, we focus on planning resources for a massive number of process instances to meet the process requirements and cater for rational utilisation of resources before execution. After a motivating example, we present a model for planning resources for process instances. Then we design a set of heuristic rules that take both optimised planning at build time and instance dependencies at run time into account. Based on these rules we propose two strategies, one is called holistic and the other is called batched, for resource planning. Both strategies target a lower cost, however, the holistic strategy can achieve an earlier deadline while the batched strategy aims at rational use of resources. We discuss how to find balance between them in the paper with a comprehensive experimental study on these two approaches.
Preconditioned alternating direction method of multipliers for inverse problems with constraints

NASA Astrophysics Data System (ADS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-02-01

We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method.
Universal "Imaginary Closed Circuit Method" and Formula for Determination of Direction of Induced EMF/Current

ERIC Educational Resources Information Center

Atram, Dattatraya Balaram

2011-01-01

Fleming's right-hand rule and the right-flat-hand rule are generally applied for determining the direction of flow of induced emf/current in straight conductors. The right-hand-fingers rule is applied for coils only. The right-hand-thumb rule can be applied for either straight conductors or coils. Different rules have to be applied for different…
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.
iRENEX: a clinically informed decision support system for the interpretation of ⁹⁹mTc-MAG3 scans to detect renal obstruction.

PubMed

Garcia, Ernest V; Taylor, Andrew; Folks, Russell; Manatunga, Daya; Halkar, Raghuveer; Savir-Baruch, Bital; Dubovsky, Eva

2012-09-01

Decision support systems for imaging analysis and interpretation are rapidly being developed and will have an increasing impact on the practice of medicine. RENEX is a renal expert system to assist physicians evaluate suspected obstruction in patients undergoing mercaptoacetyltriglycine (MAG3) renography. RENEX uses quantitative parameters extracted from the dynamic renal scan data using QuantEM™II and heuristic rules in the form of a knowledge base gleaned from experts to determine if a kidney is obstructed; however, RENEX does not have access to and could not consider the clinical information available to diagnosticians interpreting these studies. We designed and implemented a methodology to incorporate clinical information into RENEX, implemented motion detection and evaluated this new comprehensive system (iRENEX) in a pilot group of 51 renal patients. To reach a conclusion as to whether a kidney is obstructed, 56 new clinical rules were added to the previously reported 60 rules used to interpret quantitative MAG3 parameters. All the clinical rules were implemented after iRENEX reached a conclusion on obstruction based on the quantitative MAG3 parameters, and the evidence of obstruction was then modified by the new clinical rules. iRENEX consisted of a library to translate parameter values to certainty factors, a knowledge base with 116 heuristic interpretation rules, a forward chaining inference engine to determine obstruction and a justification engine. A clinical database was developed containing patient histories and imaging report data obtained from the hospital information system associated with the pertinent MAG3 studies. The system was fine-tuned and tested using a pilot group of 51 patients (21 men, mean age 58.2 ± 17.1 years, 100 kidneys) deemed by an expert panel to have 61 unobstructed and 39 obstructed kidneys. iRENEX, using only quantitative MAG3 data agreed with the expert panel in 87 % (34/39) of obstructed and 90 % (55/61) of unobstructed kidneys. iRENEX, using both quantitative and clinical data agreed with the expert panel in 95 % (37/39) of obstructed and 92 % (56/61) of unobstructed kidneys. The clinical information significantly (p < 0.001) increased iRENEX certainty in detecting obstruction over using the quantitative data alone. Our renal expert system for detecting renal obstruction has been substantially expanded to incorporate the clinical information available to physicians as well as advanced quality control features and was shown to interpret renal studies in a pilot group at a standardized expert level. These encouraging results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of iRENEX.
Performance Review of Harmony Search, Differential Evolution and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Mohan Pandey, Hari

2017-08-01

Metaheuristic algorithms are effective in the design of an intelligent system. These algorithms are widely applied to solve complex optimization problems, including image processing, big data analytics, language processing, pattern recognition and others. This paper presents a performance comparison of three meta-heuristic algorithms, namely Harmony Search, Differential Evolution, and Particle Swarm Optimization. These algorithms are originated altogether from different fields of meta-heuristics yet share a common objective. The standard benchmark functions are used for the simulation. Statistical tests are conducted to derive a conclusion on the performance. The key motivation to conduct this research is to categorize the computational capabilities, which might be useful to the researchers.
Combining factual and heuristic knowledge in knowledge acquisition

NASA Technical Reports Server (NTRS)

Gomez, Fernando; Hull, Richard; Karr, Clark; Hosken, Bruce; Verhagen, William

1992-01-01

A knowledge acquisition technique that combines heuristic and factual knowledge represented as two hierarchies is described. These ideas were applied to the construction of a knowledge acquisition interface to the Expert System Analyst (OPERA). The goal of OPERA is to improve the operations support of the computer network in the space shuttle launch processing system. The knowledge acquisition bottleneck lies in gathering knowledge from human experts and transferring it to OPERA. OPERA's knowledge acquisition problem is approached as a classification problem-solving task, combining this approach with the use of factual knowledge about the domain. The interface was implemented in a Symbolics workstation making heavy use of windows, pull-down menus, and other user-friendly devices.
Judgments about illegal performance-enhancing substances: reasoned, reactive, or both?

PubMed

Dodge, Tonya; Stock, Michelle; Litt, Dana

2013-07-01

This study applied aspects of the Theory of Reasoned Action and the Prototype/Willingness model to understand cognitions associated with the use of illegal performance-enhancing substances. There were two study objectives. One was to investigate whether the illegal-is-effective heuristic (i.e. belief that illegal performance-enhancing substances are more effective than legal performance-enhancing substances) affects willingness to use illegal performance-enhancing substances. The second was to examine whether attitudes, norms, and prototypes influence the willingness and intentions to use illegal performance-enhancing substances. The illegal-is-effective heuristic was a significant predictor of willingness but was not a significant predictor of intentions. Implications for future research and prevention efforts are discussed.
Intuitive Physics: Current Research and Controversies.

PubMed

Kubricht, James R; Holyoak, Keith J; Lu, Hongjing

2017-10-01

Early research in the field of intuitive physics provided extensive evidence that humans succumb to common misconceptions and biases when predicting, judging, and explaining activity in the physical world. Recent work has demonstrated that, across a diverse range of situations, some biases can be explained by the application of normative physical principles to noisy perceptual inputs. However, it remains unclear how knowledge of physical principles is learned, represented, and applied to novel situations. In this review we discuss theoretical advances from heuristic models to knowledge-based, probabilistic simulation models, as well as recent deep-learning models. We also consider how recent work may be reconciled with earlier findings that favored heuristic models. Copyright © 2017 Elsevier Ltd. All rights reserved.
Diabetic Mario: Designing and Evaluating Mobile Games for Diabetes Education.

PubMed

Baghaei, Nilufar; Nandigam, David; Casey, John; Direito, Artur; Maddison, Ralph

2016-08-01

Traditionally, diabetes education has relied on written materials, with limited resources available for children with diabetes. Mobile games can be effective and motivating tools for the promotion of children's health. In our earlier work, we proposed a novel approach for designing computer games aimed at educating children with diabetes. In this article, we apply our game design to a mobile Android game (Mario Brothers). We also introduce four heuristics that are specifically designed for evaluating the mobile game, by adapting traditional usability heuristics. Results of a pilot study (n = 12) to evaluate gameplay over 1-week showed that the children found the game engaging and improved their knowledge of healthy diet and lifestyle.
Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

PubMed

Zhang, Huaguang; Song, Ruizhuo; Wei, Qinglai; Zhang, Tieyan

2011-12-01

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.
3D near-to-surface conductivity reconstruction by inversion of VETEM data using the distorted Born iterative method

USGS Publications Warehouse

Wang, G.L.; Chew, W.C.; Cui, T.J.; Aydiner, A.A.; Wright, D.L.; Smith, D.V.

2004-01-01

Three-dimensional (3D) subsurface imaging by using inversion of data obtained from the very early time electromagnetic system (VETEM) was discussed. The study was carried out by using the distorted Born iterative method to match the internal nonlinear property of the 3D inversion problem. The forward solver was based on the total-current formulation bi-conjugate gradient-fast Fourier transform (BCCG-FFT). It was found that the selection of regularization parameter follow a heuristic rule as used in the Levenberg-Marquardt algorithm so that the iteration is stable.
Explicit analytical tuning rules for digital PID controllers via the magnitude optimum criterion.

PubMed

Papadopoulos, Konstantinos G; Yadav, Praveen K; Margaris, Nikolaos I

2017-09-01

Analytical tuning rules for digital PID type-I controllers are presented regardless of the process complexity. This explicit solution allows control engineers 1) to make an accurate examination of the effect of the controller's sampling time to the control loop's performance both in the time and frequency domain 2) to decide when the control has to be I, PI and when the derivative, D, term has to be added or omitted 3) apply this control action to a series of stable benchmark processes regardless of their complexity. The former advantages are considered critical in industry applications, since 1) most of the times the choice of the digital controller's sampling time is based on heuristics and past criteria, 2) there is little a-priori knowledge of the controlled process making the choice of the type of the controller a trial and error exercise 3) model parameters change often depending on the control loop's operating point making in this way, the problem of retuning the controller's parameter a much challenging issue. Basis of the proposed control law is the principle of the PID tuning via the Magnitude Optimum criterion. The final control law involves the controller's sampling time T s within the explicit solution of the controller's parameters. Finally, the potential of the proposed method is justified by comparing its performance with the conventional PID tuning when controlling the same process. Further investigation regarding the choice of the controller's sampling time T s is also presented and useful conclusions for control engineers are derived. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Hybridization of decomposition and local search for multiobjective optimization.

PubMed

Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

2014-10-01

Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems.
Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control

PubMed Central

Qazi, Abroon Jamal; de Silva, Clarence W.

2014-01-01

This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control. PMID:24574868
Biometric verification in dynamic writing

NASA Astrophysics Data System (ADS)

George, Susan E.

2002-03-01

Pen-tablet devices capable of capturing the dynamics of writing record temporal and pressure information as well as the spatial pattern. This paper explores biometric verification based upon the dynamics of writing where writers are distinguished not on the basis of what they write (ie the signature), but how they write. We have collected samples of dynamic writing from 38 Chinese writers. Each writer was asked to provide 10 copies of a paragraph of text and the same number of signature samples. From the data we have extracted stroke-based primitives from the sentence data utilizing pen-up/down information and heuristic rules about the shape of the character. The x, y and pressure values of each primitive were interpolated into an even temporal range based upon a 20 msec sampling rate. We applied the Daubechies 1 wavelet transform to the x signal, y signal and pressure signal using the coefficients as inputs to a multi-layer perceptron trained with back-propagation on the sentence data. We found a sensitivity of 0.977 and specificity of 0.990 recognizing writers based on test primitives extracted from sentence data and measures of 0.916 and 0.961 respectively, from test primitives extracted from signature data.

An overview of bipolar qualitative decision rules

NASA Astrophysics Data System (ADS)

Bonnefon, Jean-Francois; Dubois, Didier; Fargier, Hélène

Making a good decision is often a matter of listing and comparing positive and negative arguments, as studies in cognitive psychology have shown. In such cases, the evaluation scale should be considered bipolar, that is, negative and positive values are explicitly distinguished. Generally, positive and negative features are evaluated separately, as done in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, decisions are often made on the basis of an ordinal ranking of the pros and the cons, and focusing on the most salient features, i.e., the decision process is qualitative. In this paper, we report on a project aiming at characterizing several decision rules, based on possibilistic order of magnitude reasoning, and tailored for the joint handling of positive and negative affects, and at testing their empirical validity. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case and, like them, suffer from a lack of discrimination power. More decisive rules that refine them are also proposed. They account for both the principle of Pareto-efficiency and the notion of order of magnitude reasoning. The most decisive one uses a lexicographic ranking of the pros and cons. It comes down to a special case of Cumulative Prospect Theory, and subsumes the “Take the best” heuristic.
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.
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
36 CFR 1280.72 - What additional rules apply for a NARA approved event?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false What additional rules apply... ARCHIVES AND RECORDS ADMINISTRATION NARA FACILITIES USE OF NARA FACILITIES What Rules Apply to Use NARA Public Areas in the Washington, DC, Area? General § 1280.72 What additional rules apply for a NARA...
Invention and Gain Analysis.

ERIC Educational Resources Information Center

Weber, Robert J.; Dixon, Stacey

1989-01-01

Gain analysis is applied to the invention of the sewing needle as well as different sewing implements and modes of sewing. The analysis includes a two-subject experiment. To validate the generality of gain heuristics and underlying switching processes, the invention of the assembly line is also analyzed. (TJH)
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.
Predicting Vaccination Intention and Benefit and Risk Perceptions: The Incorporation of Affect, Trust, and Television Influence in a Dual-Mode Model.

PubMed

Chen, Nien-Tsu Nancy

2015-07-01

Major health behavior change models tend to consider health decisions as primarily resulting from a systematic appraisal of relevant beliefs, such as the perceived benefits and risks of a pharmacological intervention. Drawing on research from the disciplines of risk management, communication, and psychology, this study proposed the inclusion of a heuristic route in established theory and tested the direction of influence between heuristic and systematic process variables. Affect and social trust were included as key heuristics in the proposed dual-mode framework of health decision making. Furthermore, exposure to health-related coverage on television was considered potentially influential over both heuristic and systematic process variables. To test this framework, data were collected from a national probability sample of 584 adults in the United States in 2012 regarding their decision to vaccinate against a hypothetical avian flu. The results provided some support for the bidirectional influence between heuristic and systematic processing. Affect toward flu vaccination and trust in the Food and Drug Administration were found to be powerful predictors of vaccination intention, enhancing intention both directly and indirectly via certain systematic process variables. The direction of influence between perceived susceptibility and severity, on the one hand, and affect, on the other, is less clear, suggesting the need for further research. Contrary to the opinion of media critics, exposure to televised health coverage was negatively associated with the perceived risks of vaccination. Results from this study carry theoretical and practical implications, and applying this model to the acceptance of different health interventions constitutes an area for future inquiries. © 2015 Society for Risk Analysis.
MARS-MD: rejection based image domain material decomposition

NASA Astrophysics Data System (ADS)

Bateman, C. J.; Knight, D.; Brandwacht, B.; McMahon, J.; Healy, J.; Panta, R.; Aamir, R.; Rajendran, K.; Moghiseh, M.; Ramyar, M.; Rundle, D.; Bennett, J.; de Ruiter, N.; Smithies, D.; Bell, S. T.; Doesburg, R.; Chernoglazov, A.; Mandalika, V. B. H.; Walsh, M.; Shamshad, M.; Anjomrouz, M.; Atharifard, A.; Vanden Broeke, L.; Bheesette, S.; Kirkbride, T.; Anderson, N. G.; Gieseg, S. P.; Woodfield, T.; Renaud, P. F.; Butler, A. P. H.; Butler, P. H.

2018-05-01

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.
A Theoretically Consistent Framework for Modelling Lagrangian Particle Deposition in Plant Canopies

NASA Astrophysics Data System (ADS)

Bailey, Brian N.; Stoll, Rob; Pardyjak, Eric R.

2018-06-01

We present a theoretically consistent framework for modelling Lagrangian particle deposition in plant canopies. The primary focus is on describing the probability of particles encountering canopy elements (i.e., potential deposition), and provides a consistent means for including the effects of imperfect deposition through any appropriate sub-model for deposition efficiency. Some aspects of the framework draw upon an analogy to radiation propagation through a turbid medium with which to develop model theory. The present method is compared against one of the most commonly used heuristic Lagrangian frameworks, namely that originally developed by Legg and Powell (Agricultural Meteorology, 1979, Vol. 20, 47-67), which is shown to be theoretically inconsistent. A recommendation is made to discontinue the use of this heuristic approach in favour of the theoretically consistent framework developed herein, which is no more difficult to apply under equivalent assumptions. The proposed framework has the additional advantage that it can be applied to arbitrary canopy geometries given readily measurable parameters describing vegetation structure.
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.
Estimating the Entropy of Binary Time Series: Methodology, Some Theory and a Simulation Study

NASA Astrophysics Data System (ADS)

Gao, Yun; Kontoyiannis, Ioannis; Bienenstock, Elie

2008-06-01

Partly motivated by entropy-estimation problems in neuroscience, we present a detailed and extensive comparison between some of the most popular and effective entropy estimation methods used in practice: The plug-in method, four different estimators based on the Lempel-Ziv (LZ) family of data compression algorithms, an estimator based on the Context-Tree Weighting (CTW) method, and the renewal entropy estimator. METHODOLOGY: Three new entropy estimators are introduced; two new LZ-based estimators, and the “renewal entropy estimator,” which is tailored to data generated by a binary renewal process. For two of the four LZ-based estimators, a bootstrap procedure is described for evaluating their standard error, and a practical rule of thumb is heuristically derived for selecting the values of their parameters in practice. THEORY: We prove that, unlike their earlier versions, the two new LZ-based estimators are universally consistent, that is, they converge to the entropy rate for every finite-valued, stationary and ergodic process. An effective method is derived for the accurate approximation of the entropy rate of a finite-state hidden Markov model (HMM) with known distribution. Heuristic calculations are presented and approximate formulas are derived for evaluating the bias and the standard error of each estimator. SIMULATION: All estimators are applied to a wide range of data generated by numerous different processes with varying degrees of dependence and memory. The main conclusions drawn from these experiments include: (i) For all estimators considered, the main source of error is the bias. (ii) The CTW method is repeatedly and consistently seen to provide the most accurate results. (iii) The performance of the LZ-based estimators is often comparable to that of the plug-in method. (iv) The main drawback of the plug-in method is its computational inefficiency; with small word-lengths it fails to detect longer-range structure in the data, and with longer word-lengths the empirical distribution is severely undersampled, leading to large biases.
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.
Biased random key genetic algorithm with insertion and gender selection for capacitated vehicle routing problem with time windows

NASA Astrophysics Data System (ADS)

Rochman, Auliya Noor; Prasetyo, Hari; Nugroho, Munajat Tri

2017-06-01

Vehicle Routing Problem (VRP) often occurs when the manufacturers need to distribute their product to some customers/outlets. The distribution process is typically restricted by the capacity of the vehicle and the working hours at the distributor. This type of VRP is also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A Biased Random Key Genetic Algorithm (BRKGA) was designed and coded in MATLAB to solve the CVRPTW case of soft drink distribution. The standard BRKGA was then modified by applying chromosome insertion into the initial population and defining chromosome gender for parent undergoing crossover operation. The performance of the established algorithms was then compared to a heuristic procedure for solving a soft drink distribution. Some findings are revealed (1) the total distribution cost of BRKGA with insertion (BRKGA-I) results in a cost saving of 39% compared to the total cost of heuristic method, (2) BRKGA with the gender selection (BRKGA-GS) could further improve the performance of the heuristic method. However, the BRKGA-GS tends to yield worse results compared to that obtained from the standard BRKGA.
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.
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
Multiple kernel based feature and decision level fusion of iECO individuals for explosive hazard detection in FLIR imagery

NASA Astrophysics Data System (ADS)

Price, Stanton R.; Murray, Bryce; Hu, Lequn; Anderson, Derek T.; Havens, Timothy C.; Luke, Robert H.; Keller, James M.

2016-05-01

A serious threat to civilians and soldiers is buried and above ground explosive hazards. The automatic detection of such threats is highly desired. Many methods exist for explosive hazard detection, e.g., hand-held based sensors, downward and forward looking vehicle mounted platforms, etc. In addition, multiple sensors are used to tackle this extreme problem, such as radar and infrared (IR) imagery. In this article, we explore the utility of feature and decision level fusion of learned features for forward looking explosive hazard detection in IR imagery. Specifically, we investigate different ways to fuse learned iECO features pre and post multiple kernel (MK) support vector machine (SVM) based classification. Three MK strategies are explored; fixed rule, heuristics and optimization-based. Performance is assessed in the context of receiver operating characteristic (ROC) curves on data from a U.S. Army test site that contains multiple target and clutter types, burial depths and times of day. Specifically, the results reveal two interesting things. First, the different MK strategies appear to indicate that the different iECO individuals are all more-or-less important and there is not a dominant feature. This is reinforcing as our hypothesis was that iECO provides different ways to approach target detection. Last, we observe that while optimization-based MK is mathematically appealing, i.e., it connects the learning of the fusion to the underlying classification problem we are trying to solve, it appears to be highly susceptible to over fitting and simpler, e.g., fixed rule and heuristics approaches help us realize more generalizable iECO solutions.
Cognitive niches: an ecological model of strategy selection.

PubMed

Marewski, Julian N; Schooler, Lael J

2011-07-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.
Exploiting graph kernels for high performance biomedical relation extraction.

PubMed

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM performed better than APG kernel for the BioInfer dataset, in the Area Under Curve (AUC) measure (74% vs 69%). However, for all the other PPI datasets, namely AIMed, HPRD50, IEPA and LLL, ASM is substantially outperformed by the APG kernel in F-score and AUC measures. We demonstrate a high performance Chemical Induced Disease relation extraction, without employing external knowledge sources or task specific heuristics. Our work shows that graph kernels are effective in extracting relations that are expressed in multiple sentences. We also show that the graph kernels, namely the ASM and APG kernels, substantially outperform the tree kernels. Among the graph kernels, we showed the ASM kernel as effective for biomedical relation extraction, with comparable performance to the APG kernel for datasets such as the CID-sentence level relation extraction and BioInfer in PPI. Overall, the APG kernel is shown to be significantly more accurate than the ASM kernel, achieving better performance on most datasets.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.
Inventory control of raw material using silver meal heuristic method in PR. Trubus Alami Malang

NASA Astrophysics Data System (ADS)

Ikasari, D. M.; Lestari, E. R.; Prastya, E.

2018-03-01

The purpose of this study was to compare the total inventory cost calculated using the method applied by PR. Trubus Alami and Silver Meal Heuristic (SMH) method. The study was started by forecasting the cigarette demand from July 2016 to June 2017 (48 weeks) using additive decomposition forecasting method. The additive decomposition was used because it has the lowest value of Mean Abosolute Deviation (MAD) and Mean Squared Deviation (MSD) compared to other methods such as multiplicative decomposition, moving average, single exponential smoothing, and double exponential smoothing. The forcasting results was then converted as a raw material needs and further calculated using SMH method to obtain inventory cost. As expected, the result shows that the order frequency of using SMH methods was smaller than that of using the method applied by Trubus Alami. This affected the total inventory cost. The result suggests that using SMH method gave a 29.41% lower inventory cost, giving the cost different of IDR 21,290,622. The findings, is therefore, indicated that the PR. Trubus Alami should apply the SMH method if the company wants to reduce the total inventory cost.
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.
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
Role of medial cortical, hippocampal and striatal interactions during cognitive set-shifting.

PubMed

Graham, Steven; Phua, Elaine; Soon, Chun Siong; Oh, Tomasina; Au, Chris; Shuter, Borys; Wang, Shih-Chang; Yeh, Ing Berne

2009-05-01

To date, few studies have examined the functional connectivity of brain regions involved in complex executive function tasks, such as cognitive set-shifting. In this study, eighteen healthy volunteers performed a cognitive set-shifting task modified from the Wisconsin card sort test while undergoing functional magnetic resonance imaging. These modifications allowed better disambiguation between cognitive processes and revealed several novel findings: 1) peak activation in the caudate nuclei in the first instance of negative feedback signaling a shift in rule, 2) lowest caudate activation once the rule had been identified, 3) peak hippocampal activation once the identity of the rule had been established, and 4) decreased hippocampal activation during the generation of new rule candidates. This pattern of activation across cognitive set-shifting events suggests that the caudate nuclei play a role in response generation when the identity of the new rule is unknown. In contrast, the reciprocal pattern of hippocampal activation suggests that the hippocampi help consolidate knowledge about the correct stimulus-stimulus associations, associations that become inappropriate once the rule has changed. Functional connectivity analysis using Granger Causality Mapping revealed that caudate and hippocampal regions interacted indirectly via a circuit involving the medial orbitofrontal and posterior cingulate regions, which are known to bias attention towards stimuli based on expectations built up from task-related feedback. Taken together, the evidence suggests that these medial regions may mediate striato-hippocampal interactions and hence affect goal-directed attentional transitions from a response strategy based on stimulus-reward heuristics (caudate-dependent) to one based on stimulus-stimulus associations (hippocampus-dependent).
Dyadic fertility decisions in a life course perspective.

PubMed

Bauer, Gerrit; Kneip, Thorsten

2014-09-01

This paper focuses on how couples arrive at joint decisions with regard to fertility behaviour. We build upon previous work on decision rules that couples might apply as heuristics in order to arrive at joint action in cases in which partners' fertility preferences differ. Previous research found either stronger effects of women's desires or symmetrical effects of both spouses' desires and net benefits associated with (further) children on proceptive behaviour. The latter finding is in line with the notion of household utility maximisation, in which both partners' preferences enter into a joint utility function with equal weight. On the other hand, some evidence indicates that one partner can exercise a 'veto' if he or she anticipates individual utility losses from a further child (due to opportunity costs arising in other life domains). We now enhance previous research by applying a life-course perspective. Our analysis makes use of variation in initial conditions due to previous births: couples decide on fertility in different situations as they find themselves in different life course stages and have had certain experiences. Parity-specific differences affect not only fertility outcomes but also the decision-making process itself. Our findings show that the decision to have a first child is made jointly, and each partner may exercise a veto. On the other hand, women appear to dominate decisions on higher parity births, not per se, but because they are (still) the ones more affected by the concomitant housework. Copyright © 2013 Elsevier Ltd. All rights reserved.
The generalized 20/80 law using probabilistic fractals applied to petroleum field size

USGS Publications Warehouse

Crovelli, R.A.

1995-01-01

Fractal properties of the Pareto probability distribution are used to generalize "the 20/80 law." The 20/80 law is a heuristic law that has evolved over the years into the following rule of thumb for many populations: 20 percent of the population accounts for 80 percent of the total value. The general p100/q100 law in probabilistic form is defined with q as a function of p, where p is the population proportion and q is the proportion of total value. Using the Pareto distribution, the p100/q100 law in fractal form is derived with the parameter q being a fractal, where q unexpectedly possesses the scale invariance property. The 20/80 law is a special case of the p100/q100 law in fractal form. The p100/q100 law in fractal form is applied to petroleum fieldsize data to obtain p and q such that p100% of the oil fields greater than any specified scale or size in a geologic play account for q100% of the total oil of the fields. The theoretical percentages of total resources of oil using the fractal q are extremely close to the empirical percentages from the data using the statistic q. Also, the empirical scale invariance property of the statistic q for the petroleum fieldsize data is in excellent agreement with the theoretical scale invariance property of the fractal q. ?? 1995 Oxford University Press.
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…
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.
Problem Solving. Research Brief

ERIC Educational Resources Information Center

Muir, Mike

2004-01-01

No longer solely the domain of Mathematics, problem solving permeates every area of today's curricula. Ideally students are applying heuristics strategies in varied contexts and novel situations in every subject taught. The ability to solve problems is a basic life skill and is essential to understanding technical subjects. Problem-solving is a…
Decision making in prioritization of required operational capabilities

NASA Astrophysics Data System (ADS)

Andreeva, P.; Karev, M.; Kovacheva, Ts.

2015-10-01

The paper describes an expert heuristic approach to prioritization of required operational capabilities in the field of defense. Based on expert assessment and by application of the method of Analytical Hierarchical Process, a methodology for their prioritization has been developed. It has been applied to practical simulation decision making games.
The Heuristic Value of Cognitive Terminology

ERIC Educational Resources Information Center

Zentall, Thomas R.

2012-01-01

If judiciously applied, cognitive terminology can encourage further examination of phenomena in useful ways that may not otherwise be studied. I give examples of 3 phenomena, the study of which have benefitted from a cognitive perspective. For the first, transitive inference behavior, it appears that non-cognitive accounts cannot satisfactorily…
Toward a Psychology of Responses to Dance Performance

ERIC Educational Resources Information Center

Gervasio, Amy Herstein

2012-01-01

This paper applies contemporary principles in cognitive and social psychology to understand how Western ballet and modern dance is imbued with emotional and narrative meaning by an audience. These include nine Gestalt concepts of visual form perception as well as cognitive heuristics of representativeness and availability in concept formation and…
A Critique of Externally Oriented Behavior Management Approaches as Applied to Exceptional Black Children.

ERIC Educational Resources Information Center

Patton, James M.

The paper looks at philosophical, heuristic, and practical reasons why behavior management approaches have failed to positively impact on the lives of exceptional Black children. Critiqued are behavior modification techniques, contingency management strategies, suspensions, expulsions, and positive and negative reinforcement. Noted among the…
An Interactive Multiobjective Programming Approach to Combinatorial Data Analysis.

ERIC Educational Resources Information Center

Brusco, Michael J.; Stahl, Stephanie

2001-01-01

Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…
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).
From Cues to Nudge: A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections.

PubMed

Shaban-Nejad, Arash; Mamiya, Hiroshi; Riazanov, Alexandre; Forster, Alan J; Baker, Christopher J O; Tamblyn, Robyn; Buckeridge, David L

2016-01-01

We propose an integrated semantic web framework consisting of formal ontologies, web services, a reasoner and a rule engine that together recommend appropriate level of patient-care based on the defined semantic rules and guidelines. The classification of healthcare-associated infections within the HAIKU (Hospital Acquired Infections - Knowledge in Use) framework enables hospitals to consistently follow the standards along with their routine clinical practice and diagnosis coding to improve quality of care and patient safety. The HAI ontology (HAIO) groups over thousands of codes into a consistent hierarchy of concepts, along with relationships and axioms to capture knowledge on hospital-associated infections and complications with focus on the big four types, surgical site infections (SSIs), catheter-associated urinary tract infection (CAUTI); hospital-acquired pneumonia, and blood stream infection. By employing statistical inferencing in our study we use a set of heuristics to define the rule axioms to improve the SSI case detection. We also demonstrate how the occurrence of an SSI is identified using semantic e-triggers. The e-triggers will be used to improve our risk assessment of post-operative surgical site infections (SSIs) for patients undergoing certain type of surgeries (e.g., coronary artery bypass graft surgery (CABG)).
Unsupervised Biomedical Named Entity Recognition: Experiments with Clinical and Biological Texts

PubMed Central

Zhang, Shaodian; Elhadad, Nóemie

2013-01-01

Named entity recognition is a crucial component of biomedical natural language processing, enabling information extraction and ultimately reasoning over and knowledge discovery from text. Much progress has been made in the design of rule-based and supervised tools, but they are often genre and task dependent. As such, adapting them to different genres of text or identifying new types of entities requires major effort in re-annotation or rule development. In this paper, we propose an unsupervised approach to extracting named entities from biomedical text. We describe a stepwise solution to tackle the challenges of entity boundary detection and entity type classification without relying on any handcrafted rules, heuristics, or annotated data. A noun phrase chunker followed by a filter based on inverse document frequency extracts candidate entities from free text. Classification of candidate entities into categories of interest is carried out by leveraging principles from distributional semantics. Experiments show that our system, especially the entity classification step, yields competitive results on two popular biomedical datasets of clinical notes and biological literature, and outperforms a baseline dictionary match approach. Detailed error analysis provides a road map for future work. PMID:23954592

Design rules for quasi-linear nonlinear optical structures

NASA Astrophysics Data System (ADS)

Lytel, Richard; Mossman, Sean M.; Kuzyk, Mark G.

2015-09-01

The maximization of the intrinsic optical nonlinearities of quantum structures for ultrafast applications requires a spectrum scaling as the square of the energy eigenstate number or faster. This is a necessary condition for an intrinsic response approaching the fundamental limits. A second condition is a design generating eigenstates whose ground and lowest excited state probability densities are spatially separated to produce large differences in dipole moments while maintaining a reasonable spatial overlap to produce large off-diagonal transition moments. A structure whose design meets both conditions will necessarily have large first or second hyperpolarizabilities. These two conditions are fundamental heuristics for the design of any nonlinear optical structure.
Automated analysis of complex data

NASA Technical Reports Server (NTRS)

Saintamant, Robert; Cohen, Paul R.

1994-01-01

We have examined some of the issues involved in automating exploratory data analysis, in particular the tradeoff between control and opportunism. We have proposed an opportunistic planning solution for this tradeoff, and we have implemented a prototype, Igor, to test the approach. Our experience in developing Igor was surprisingly smooth. In contrast to earlier versions that relied on rule representation, it was straightforward to increment Igor's knowledge base without causing the search space to explode. The planning representation appears to be both general and powerful, with high level strategic knowledge provided by goals and plans, and the hooks for domain-specific knowledge are provided by monitors and focusing heuristics.
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.
7 CFR 170.1 - To which farmers markets does this rule apply?

Code of Federal Regulations, 2010 CFR

2010-01-01

... MARKETING PRACTICES UNDER THE AGRICULTURAL MARKETING ACT OF 1946 USDA FARMERS MARKET § 170.1 To which farmers markets does this rule apply? This rule applies only to the USDA Farmers Market at headquarters on...
7 CFR 170.1 - To which farmers markets does this rule apply?

Code of Federal Regulations, 2013 CFR

2013-01-01

... MARKETING PRACTICES UNDER THE AGRICULTURAL MARKETING ACT OF 1946 USDA FARMERS MARKET § 170.1 To which farmers markets does this rule apply? This rule applies only to the USDA Farmers Market at headquarters on...
7 CFR 170.1 - To which farmers markets does this rule apply?

Code of Federal Regulations, 2011 CFR

2011-01-01

... MARKETING PRACTICES UNDER THE AGRICULTURAL MARKETING ACT OF 1946 USDA FARMERS MARKET § 170.1 To which farmers markets does this rule apply? This rule applies only to the USDA Farmers Market at headquarters on...
Peak and end effects in patients' daily recall of pain and fatigue: a within-subjects analysis.

PubMed

Schneider, Stefan; Stone, Arthur A; Schwartz, Joseph E; Broderick, Joan E

2011-02-01

Clinical research often relies on retrospective recall of symptom levels, but the information contained in these ratings is not well understood. The "peak-and-end rule" suggests that the most intense (peak) and final (end) moments of an experience disproportionately influence retrospective judgments, which may bias self-reports of somatic symptoms. This study examined the extent to which peak and end symptom levels systematically affect patients' day-to-day recall of pain and fatigue. Rheumatology patients (N = 97) completed 5 to 6 momentary ratings of pain and fatigue per day as well as a daily recall rating of these symptoms for 28 consecutive days. For pain, peak and end momentary ratings predicted daily recall of average pain beyond the actual average of momentary ratings. This effect was small, yet was confirmed in both between-person and within-person (repeated measures) analyses. For fatigue, neither peak nor end momentary symptoms significantly contributed to daily recall. Of note, the evidence for peak- and end-effects in recall of pain and fatigue varied significantly between individual patients. These findings suggest that peak- and end-effects create a small bias in recall reports of pain, but not fatigue. However, there are considerable individual differences in susceptibility to peak and end heuristics. The peak-end cognitive heuristic could bias end-of-day recall of pain and fatigue. An effect was shown for pain, but not for fatigue. The effects were small and were unlikely to substantially bias end-of-day assessments. Individuals were shown to differ in the degree that the heuristic was associated with recall. Copyright © 2011 American Pain Society. Published by Elsevier Inc. All rights reserved.
A heuristic approach and heretic view on the technical issues and pitfalls in the management of penetrating abdominal injuries

PubMed Central

2010-01-01

There is a general decline in penetrating abdominal trauma throughout the western world. As a result of that, there is a significant loss of expertise in dealing with this type of injury particularly when the patient presents to theatre with physiological instability. A significant percentage of these patients will not be operated by a trauma surgeon but, by the "occasional trauma surgeon", who is usually trained as a general surgeon. Most general surgeons have a general knowledge of operating penetrating trauma, knowledge originating from their training years and possibly enhanced by reading operative surgery textbooks. Unfortunately, the details included in most of these books are not extensive enough to provide them with enough armamentaria to tackle the difficult case. In this scenario, their operative dexterity and knowledge cannot be compared to that of their trauma surgeon colleagues, something that is taken for granted in the trauma textbooks. Techniques that are considered basic and easy by the trauma surgeons can be unfamiliar and difficult to general surgeons. Knowing the danger points and pitfalls that will be encountered in penetrating trauma to the abdomen, will help the occasional trauma surgeons to avoid intraoperative errors and improve patient care. This manuscript provides a heuristic approach from surgeons working in a high volume penetrating trauma centers in South African. Some of the statements could be considered heretic by the "accepted" trauma literature. We believe that this heuristic ("rule of thumb" approach, that originating from "try and error" experience) can help surgical trainees or less experienced in penetrating trauma surgeons to improve their surgical decision making and technique, resulting in better patient outcome. PMID:20630100
Development of the IMB Model and an Evidence-Based Diabetes Self-management Mobile Application.

PubMed

Jeon, Eunjoo; Park, Hyeoun-Ae

2018-04-01

This study developed a diabetes self-management mobile application based on the information-motivation-behavioral skills (IMB) model, evidence extracted from clinical practice guidelines, and requirements identified through focus group interviews (FGIs) with diabetes patients. We developed a diabetes self-management (DSM) app in accordance with the following four stages of the system development life cycle. The functional and knowledge requirements of the users were extracted through FGIs with 19 diabetes patients. A system diagram, data models, a database, an algorithm, screens, and menus were designed. An Android app and server with an SSL protocol were developed. The DSM app algorithm and heuristics, as well as the usability of the DSM app were evaluated, and then the DSM app was modified based on heuristics and usability evaluation. A total of 11 requirement themes were identified through the FGIs. Sixteen functions and 49 knowledge rules were extracted. The system diagram consisted of a client part and server part, 78 data models, a database with 10 tables, an algorithm, and a menu structure with 6 main menus, and 40 user screens were developed. The DSM app was Android version 4.4 or higher for Bluetooth connectivity. The proficiency and efficiency scores of the algorithm were 90.96% and 92.39%, respectively. Fifteen issues were revealed through the heuristic evaluation, and the app was modified to address three of these issues. It was also modified to address five comments received by the researchers through the usability evaluation. The DSM app was developed based on behavioral change theory through IMB models. It was designed to be evidence-based, user-centered, and effective. It remains necessary to fully evaluate the effect of the DSM app on the DSM behavior changes of diabetes patients.
Development of the IMB Model and an Evidence-Based Diabetes Self-management Mobile Application

PubMed Central

Jeon, Eunjoo

2018-01-01

Objectives This study developed a diabetes self-management mobile application based on the information-motivation-behavioral skills (IMB) model, evidence extracted from clinical practice guidelines, and requirements identified through focus group interviews (FGIs) with diabetes patients. Methods We developed a diabetes self-management (DSM) app in accordance with the following four stages of the system development life cycle. The functional and knowledge requirements of the users were extracted through FGIs with 19 diabetes patients. A system diagram, data models, a database, an algorithm, screens, and menus were designed. An Android app and server with an SSL protocol were developed. The DSM app algorithm and heuristics, as well as the usability of the DSM app were evaluated, and then the DSM app was modified based on heuristics and usability evaluation. Results A total of 11 requirement themes were identified through the FGIs. Sixteen functions and 49 knowledge rules were extracted. The system diagram consisted of a client part and server part, 78 data models, a database with 10 tables, an algorithm, and a menu structure with 6 main menus, and 40 user screens were developed. The DSM app was Android version 4.4 or higher for Bluetooth connectivity. The proficiency and efficiency scores of the algorithm were 90.96% and 92.39%, respectively. Fifteen issues were revealed through the heuristic evaluation, and the app was modified to address three of these issues. It was also modified to address five comments received by the researchers through the usability evaluation. Conclusions The DSM app was developed based on behavioral change theory through IMB models. It was designed to be evidence-based, user-centered, and effective. It remains necessary to fully evaluate the effect of the DSM app on the DSM behavior changes of diabetes patients. PMID:29770246
A heuristic approach and heretic view on the technical issues and pitfalls in the management of penetrating abdominal injuries.

PubMed

Yilmaz, Tugba H; Ndofor, Brown C; Smith, Martin D; Degiannis, Elias

2010-07-14

There is a general decline in penetrating abdominal trauma throughout the western world. As a result of that, there is a significant loss of expertise in dealing with this type of injury particularly when the patient presents to theatre with physiological instability. A significant percentage of these patients will not be operated by a trauma surgeon but, by the "occasional trauma surgeon", who is usually trained as a general surgeon. Most general surgeons have a general knowledge of operating penetrating trauma, knowledge originating from their training years and possibly enhanced by reading operative surgery textbooks. Unfortunately, the details included in most of these books are not extensive enough to provide them with enough armamentaria to tackle the difficult case. In this scenario, their operative dexterity and knowledge cannot be compared to that of their trauma surgeon colleagues, something that is taken for granted in the trauma textbooks. Techniques that are considered basic and easy by the trauma surgeons can be unfamiliar and difficult to general surgeons. Knowing the danger points and pitfalls that will be encountered in penetrating trauma to the abdomen, will help the occasional trauma surgeons to avoid intraoperative errors and improve patient care. This manuscript provides a heuristic approach from surgeons working in a high volume penetrating trauma centers in South African. Some of the statements could be considered heretic by the "accepted" trauma literature. We believe that this heuristic ("rule of thumb" approach, that originating from "try and error" experience) can help surgical trainees or less experienced in penetrating trauma surgeons to improve their surgical decision making and technique, resulting in better patient outcome.
MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

USGS Publications Warehouse

Carter, J.; Finn, John T.

1999-01-01

We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.
A grand unified model for liganded gold clusters

NASA Astrophysics Data System (ADS)

Xu, Wen Wu; Zhu, Beien; Zeng, Xiao Cheng; Gao, Yi

2016-12-01

A grand unified model (GUM) is developed to achieve fundamental understanding of rich structures of all 71 liganded gold clusters reported to date. Inspired by the quark model by which composite particles (for example, protons and neutrons) are formed by combining three quarks (or flavours), here gold atoms are assigned three `flavours' (namely, bottom, middle and top) to represent three possible valence states. The `composite particles' in GUM are categorized into two groups: variants of triangular elementary block Au3(2e) and tetrahedral elementary block Au4(2e), all satisfying the duet rule (2e) of the valence shell, akin to the octet rule in general chemistry. The elementary blocks, when packed together, form the cores of liganded gold clusters. With the GUM, structures of 71 liganded gold clusters and their growth mechanism can be deciphered altogether. Although GUM is a predictive heuristic and may not be necessarily reflective of the actual electronic structure, several highly stable liganded gold clusters are predicted, thereby offering GUM-guided synthesis of liganded gold clusters by design.
Generalized quantum theory of recollapsing homogeneous cosmologies

NASA Astrophysics Data System (ADS)

Craig, David; Hartle, James B.

2004-06-01

A sum-over-histories generalized quantum theory is developed for homogeneous minisuperspace type A Bianchi cosmological models, focusing on the particular example of the classically recollapsing Bianchi type-IX universe. The decoherence functional for such universes is exhibited. We show how the probabilities of decoherent sets of alternative, coarse-grained histories of these model universes can be calculated. We consider in particular the probabilities for classical evolution defined by a suitable coarse graining. For a restricted class of initial conditions and coarse grainings we exhibit the approximate decoherence of alternative histories in which the universe behaves classically and those in which it does not. For these situations we show that the probability is near unity for the universe to recontract classically if it expands classically. We also determine the relative probabilities of quasiclassical trajectories for initial states of WKB form, recovering for such states a precise form of the familiar heuristic “JṡdΣ” rule of quantum cosmology, as well as a generalization of this rule to generic initial states.
Techniques for noise removal and registration of TIMS data

USGS Publications Warehouse

Hummer-Miller, S.

1990-01-01

Extracting subtle differences from highly correlated thermal infrared aircraft data is possible with appropriate noise filters, constructed and applied in the spatial frequency domain. This paper discusses a heuristic approach to designing noise filters for removing high- and low-spatial frequency striping and banding. Techniques for registering thermal infrared aircraft data to a topographic base using Thematic Mapper data are presented. The noise removal and registration techniques are applied to TIMS thermal infrared aircraft data. -Author
An effective PSO-based memetic algorithm for flow shop scheduling.

PubMed

Liu, Bo; Wang, Ling; Jin, Yi-Hui

2007-02-01

This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic polynomial-time (NP) hard combinatorial optimization problem. In the proposed PSO-based MA (PSOMA), both PSO-based searching operators and some special local searching operators are designed to balance the exploration and exploitation abilities. In particular, the PSOMA applies the evolutionary searching mechanism of PSO, which is characterized by individual improvement, population cooperation, and competition to effectively perform exploration. On the other hand, the PSOMA utilizes several adaptive local searches to perform exploitation. First, to make PSO suitable for solving PFSSP, a ranked-order value rule based on random key representation is presented to convert the continuous position values of particles to job permutations. Second, to generate an initial swarm with certain quality and diversity, the famous Nawaz-Enscore-Ham (NEH) heuristic is incorporated into the initialization of population. Third, to balance the exploration and exploitation abilities, after the standard PSO-based searching operation, a new local search technique named NEH_1 insertion is probabilistically applied to some good particles selected by using a roulette wheel mechanism with a specified probability. Fourth, to enrich the searching behaviors and to avoid premature convergence, a simulated annealing (SA)-based local search with multiple different neighborhoods is designed and incorporated into the PSOMA. Meanwhile, an effective adaptive meta-Lamarckian learning strategy is employed to decide which neighborhood to be used in SA-based local search. Finally, to further enhance the exploitation ability, a pairwise-based local search is applied after the SA-based search. Simulation results based on benchmarks demonstrate the effectiveness of the PSOMA. Additionally, the effects of some parameters on optimization performances are also discussed.
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…
Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis.

PubMed

Keller, Arturo A; Fournier, Eric; Fox, Jessica

2015-06-01

Development of natural landscapes to support human activities impacts the capacity of the landscape to provide ecosystem services. Typically, several ecosystem services are impacted at a single development site and various footprint scenarios are possible, thus a multi-criteria analysis is needed. Restoration potential should also be considered for the area surrounding the permanent impact site. The primary objective of this research was to develop a heuristic approach to analyze multiple criteria (e.g. impacts to various ecosystem services) in a spatial configuration with many potential development sites. The approach was to: (1) quantify the magnitude of terrestrial ecosystem service (biodiversity, carbon sequestration, nutrient and sediment retention, and pollination) impacts associated with a suite of land use change scenarios using the InVEST model; (2) normalize results across categories of ecosystem services to allow cross-service comparison; (3) apply the multi-criteria heuristic algorithm to select sites with the least impact to ecosystem services, including a spatial criterion (separation between sites). As a case study, the multi-criteria impact minimization algorithm was applied to InVEST output to select 25 potential development sites out of 204 possible locations (selected by other criteria) within a 24,000 ha property. This study advanced a generally applicable spatial multi-criteria approach for 1) considering many land use footprint scenarios, 2) balancing impact decisions across a suite of ecosystem services, and 3) determining the restoration potential of ecosystem services after impacts. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
A multiple-drawer medication layout problem in automated dispensing cabinets.

PubMed

Pazour, Jennifer A; Meller, Russell D

2012-12-01

In this paper we investigate the problem of locating medications in automated dispensing cabinets (ADCs) to minimize human selection errors. We formulate the multiple-drawer medication layout problem and show that the problem can be formulated as a quadratic assignment problem. As a way to evaluate various medication layouts, we develop a similarity rating for medication pairs. To solve industry-sized problem instances, we develop a heuristic approach. We use hospital ADC transaction data to conduct a computational experiment to test the performance of our developed heuristics, to demonstrate how our approach can aid in ADC design trade-offs, and to illustrate the potential improvements that can be made when applying an analytical process to the multiple-drawer medication layout problem. Finally, we present conclusions and future research directions.
A linguistic geometry for 3D strategic planning

NASA Technical Reports Server (NTRS)

Stilman, Boris

1995-01-01

This paper is a new step in the development and application of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing Linguistic Geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in this paper on the new pilot example of the solution of the extremely complex 3D optimization problem of strategic planning for the space combat of autonomous vehicles. This example demonstrates deep and highly selective search in comparison with conventional search algorithms.

Laser-induced electron dynamics including photoionization: A heuristic model within time-dependent configuration interaction theory.

PubMed

Klinkusch, Stefan; Saalfrank, Peter; Klamroth, Tillmann

2009-09-21

We report simulations of laser-pulse driven many-electron dynamics by means of a simple, heuristic extension of the time-dependent configuration interaction singles (TD-CIS) approach. The extension allows for the treatment of ionizing states as nonstationary states with a finite, energy-dependent lifetime to account for above-threshold ionization losses in laser-driven many-electron dynamics. The extended TD-CIS method is applied to the following specific examples: (i) state-to-state transitions in the LiCN molecule which correspond to intramolecular charge transfer, (ii) creation of electronic wave packets in LiCN including wave packet analysis by pump-probe spectroscopy, and, finally, (iii) the effect of ionization on the dynamic polarizability of H(2) when calculated nonperturbatively by TD-CIS.
Attitude sensor alignment calibration for the solar maximum mission

NASA Technical Reports Server (NTRS)

Pitone, Daniel S.; Shuster, Malcolm D.

1990-01-01

An earlier heuristic study of the fine attitude sensors for the Solar Maximum Mission (SMM) revealed a temperature dependence of the alignment about the yaw axis of the pair of fixed-head star trackers relative to the fine pointing Sun sensor. Here, new sensor alignment algorithms which better quantify the dependence of the alignments on the temperature are developed and applied to the SMM data. Comparison with the results from the previous study reveals the limitations of the heuristic approach. In addition, some of the basic assumptions made in the prelaunch analysis of the alignments of the SMM are examined. The results of this work have important consequences for future missions with stringent attitude requirements and where misalignment variations due to variations in the temperature will be significant.
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).
Applying Cognitive Work Analysis to Time Critical Targeting Functionality

DTIC Science & Technology

2004-10-01

Cognitive Task Analysis , CTA, Cognitive Task Analysis , Human Factors, GUI, Graphical User Interface, Heuristic Evaluation... Cognitive Task Analysis MITRE Briefing January 2000 Dynamic Battle Management Functional Architecture 3-1 Section 3 Human Factors...clear distinction between Cognitive Work Analysis (CWA) and Cognitive Task Analysis (CTA), therefore this document will refer to these
Applying Rhetorical Genre Studies to a Stand-Alone Online Professional Writing Course

ERIC Educational Resources Information Center

Adams, Heather Brook; Jenkins, Patricia

2015-01-01

This program profile explains and illustrates a pedagogical application of Rhetorical Genre Studies (RGS) to a one-semester, upper-division online Professional Writing course. We explain our use of a heuristic, which we liken to "night-vision goggles," that enables students to systematically analyze field data that they gather from a…
A Heuristic Model for Research on Prose Learning.

ERIC Educational Resources Information Center

Frase, Lawrence T.

Learning activities that are associated with programed materials can be applied to learning from ordinary text; in fact, there is no essential difference between programed and ordinary text. Active response so important to programed learning can be controlled in textual materials by carefully defined adjunct aids such as word lists, underlining,…
Embracing the Unknown in Community Arts Zone Visual Arts

ERIC Educational Resources Information Center

Rowsell, Jennifer; Vietgen, Peter

2017-01-01

Telling stories through photographs is certainly not a new or novel concept; however, thinking about image-making as a way of unknowing what we currently know is quite different from traditional approaches to photography. Built on an existing conceptual framework, writings on unknowing, we apply unknowing as a guiding method and heuristic to…
DOE Office of Scientific and Technical Information (OSTI.GOV)

Jason L. Wright

Finding and identifying Cryptography is a growing concern in the malware analysis community. In this paper, a heuristic method for determining the likelihood that a given function contains a cryptographic algorithm is discussed and the results of applying this method in various environments is shown. The algorithm is based on frequency analysis of opcodes that make up each function within a binary.
A Formal Construction of Term Classes. Technical Report No. TR73-18.

ERIC Educational Resources Information Center

Yu, Clement T.

The computational complexity of a formal process for the construction of term classes for information retrieval is examined. While the process is proven to be difficult computationally, heuristic methods are applied. Experimental results are obtained to illustrate the maximum possible improvement in system performance of retrieval using the formal…
Examining Student Heuristic Usage in a Hydrogen Bonding Assessment

ERIC Educational Resources Information Center

Miller, Kathryn; Kim, Thomas

2017-01-01

This study investigates the role of representational competence in student responses to an assessment of hydrogen bonding. The assessment couples the use of a multiple-select item ("Choose all that apply") with an open-ended item to allow for an examination of students' cognitive processes as they relate to the assignment of hydrogen…
Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

ERIC Educational Resources Information Center

Steinley, Douglas; Hubert, Lawrence

2008-01-01

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…
Ant system: optimization by a colony of cooperating agents.

PubMed

Dorigo, M; Maniezzo, V; Colorni, A

1996-01-01

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Firestone, Ryan; Marnay, Chris

The on-site generation of electricity can offer buildingowners and occupiers financial benefits as well as social benefits suchas reduced grid congestion, improved energy efficiency, and reducedgreenhouse gas emissions. Combined heat and power (CHP), or cogeneration,systems make use of the waste heat from the generator for site heatingneeds. Real-time optimal dispatch of CHP systems is difficult todetermine because of complicated electricity tariffs and uncertainty inCHP equipment availability, energy prices, and system loads. Typically,CHP systems use simple heuristic control strategies. This paper describesa method of determining optimal control in real-time and applies it to alight industrial site in San Diego, California, tomore » examine: 1) the addedbenefit of optimal over heuristic controls, 2) the price elasticity ofthe system, and 3) the site-attributable greenhouse gas emissions, allunder three different tariff structures. Results suggest that heuristiccontrols are adequate under the current tariff structure and relativelyhigh electricity prices, capturing 97 percent of the value of thedistributed generation system. Even more value could be captured bysimply not running the CHP system during times of unusually high naturalgas prices. Under hypothetical real-time pricing of electricity,heuristic controls would capture only 70 percent of the value ofdistributed generation.« less
Reconciling intuitive physics and Newtonian mechanics for colliding objects.

PubMed

Sanborn, Adam N; Mansinghka, Vikash K; Griffiths, Thomas L

2013-04-01

People have strong intuitions about the influence objects exert upon one another when they collide. Because people's judgments appear to deviate from Newtonian mechanics, psychologists have suggested that people depend on a variety of task-specific heuristics. This leaves open the question of how these heuristics could be chosen, and how to integrate them into a unified model that can explain human judgments across a wide range of physical reasoning tasks. We propose an alternative framework, in which people's judgments are based on optimal statistical inference over a Newtonian physical model that incorporates sensory noise and intrinsic uncertainty about the physical properties of the objects being viewed. This noisy Newton framework can be applied to a multitude of judgments, with people's answers determined by the uncertainty they have for physical variables and the constraints of Newtonian mechanics. We investigate a range of effects in mass judgments that have been taken as strong evidence for heuristic use and show that they are well explained by the interplay between Newtonian constraints and sensory uncertainty. We also consider an extended model that handles causality judgments, and obtain good quantitative agreement with human judgments across tasks that involve different judgment types with a single consistent set of parameters.
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.
Weak encoding of faces predicts socially influenced judgments of facial attractiveness.

PubMed

Schnuerch, Robert; Koppehele-Gossel, Judith; Gibbons, Henning

2015-01-01

Conforming to the majority can be seen as a heuristic type of judgment, as it allows the individual to easily choose the most accurate or most socially acceptable type of behavior. People who process the currently to-be-judged items in a superficial, heuristic way should tend to conform to group judgment more than people processing these items in a systematic and elaborate way. We investigated this hypothesis using electroencephalography (EEG), analyzing whether the strength of neural encoding of faces was related to the tendency to adopt a group's evaluative judgments regarding these faces. As expected, we found that the amplitude of the N170, a specific neural correlate of face encoding, was inversely related to conformity across participants: The weaker the faces were encoded, the more the majority response regarding the faces' attractiveness was adopted instead of relying on the actual qualities of the faces. Applying neurophysiological methodology, we thus provide support for previous claims, based on behavioral data and theorizing, that social conformity is a heuristic type of judgment. We propose that weak encoding of judgment-relevant information is a typical, possibly even necessary, precursor of socially adjusted judgments, irrespective of one's current motivational goal (i.e., to be accurate or accepted).
Low-rank structure learning via nonconvex heuristic recovery.

PubMed

Deng, Yue; Dai, Qionghai; Liu, Risheng; Zhang, Zengke; Hu, Sanqing

2013-03-01

In this paper, we propose a nonconvex framework to learn the essential low-rank structure from corrupted data. Different from traditional approaches, which directly utilizes convex norms to measure the sparseness, our method introduces more reasonable nonconvex measurements to enhance the sparsity in both the intrinsic low-rank structure and the sparse corruptions. We will, respectively, introduce how to combine the widely used ℓp norm (0 < p < 1) and log-sum term into the framework of low-rank structure learning. Although the proposed optimization is no longer convex, it still can be effectively solved by a majorization-minimization (MM)-type algorithm, with which the nonconvex objective function is iteratively replaced by its convex surrogate and the nonconvex problem finally falls into the general framework of reweighed approaches. We prove that the MM-type algorithm can converge to a stationary point after successive iterations. The proposed model is applied to solve two typical problems: robust principal component analysis and low-rank representation. Experimental results on low-rank structure learning demonstrate that our nonconvex heuristic methods, especially the log-sum heuristic recovery algorithm, generally perform much better than the convex-norm-based method (0 < p < 1) for both data with higher rank and with denser corruptions.
75 FR 22886 - Self-Regulatory Organizations; NYSE Amex LLC; Notice of Filing and Immediate Effectiveness of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-30

... Amending Rule 903 and Adopting Rule 903A April 23, 2010. Pursuant to Section 19(b)(1) of the Securities... Proposed Rule Change The Exchange proposes to amend Rule 903 and adopt Rule 903A to apply uniform objective... adopt Rule 903A to apply uniform objective standards to the range of options series exercise (or strike...
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.
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.
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
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.
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.
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.
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.
Theory for the evolution of diffusible external goods.

PubMed

Driscoll, William W; Pepper, John W

2010-09-01

Organisms from prokaryotes to plants and animals make costly investments in diffusible beneficial external products. While the costs of producing such products are born only by the producer, the benefits may be distributed more widely. How are external goods-producing populations stabilized against invasion by nonproducing variants that receive the benefits without paying the cost? This question parallels the classic question of altruism, but because external goods production need not be altruistic per se, a broader range of conditions may lead to the maintenance of these traits. We start from the physics of diffusion to develop an expression for the conditions that favor the production of diffusible external goods. Important variables in determining the evolutionary outcome include the diffusion coefficient of the good, the distance between individuals, and the uptake rate of the external good. These variables join the coefficient of relatedness and the cost/benefit ratio in an expanded form of Hamilton's rule that includes both selfish and altruistic paths to the evolution of external goods strategies. This expanded framework can be applied to any external goods trait, and is a useful heuristic even when it is difficult to quantify the fitness consequences of producing the good. © 2010 The Author(s). Journal compilation © 2010 The Society for the Study of Evolution.
Narrowing beam-walking is a clinically feasible approach for assessing balance ability in lower-limb prosthesis users.

PubMed

Sawers, Andrew; Hafner, Brian J

2018-05-08

Challenging clinical balance tests are needed to expose balance deficits in lower-limb prost-hesis users. This study examined whether narrowing beam-walking could overcome conceptual and practical limitations identified in fixed-width beam-walking. Cross-sectional. Unilateral lower-limb prosthesis users. Participants walked 10 times along a low, narrowing beam. Performance was quantified using the normalized distance walked. Heuristic rules were applied to determine whether the narrowing beam task was "too easy," "too hard," or "appropriately challenging" for each participant. Linear regression and Bland-Altman plots were used to determine whether combinations of the first 5 trials could predict participants' stable beam-walking performance. Forty unilateral lower-limb prosthesis users participated. Narrowing beam-walking was appropriately challenging for 98% of participants. Performance stabilized for 93% of participants within 5 trials, while 62% were stable across all trials. The mean of trials 3-5 accurately predicted stable performance. A clinical narrowing beam-walking test is likely to challenge a range of lower-limb prosthesis users, have minimal administrative burden, and exhibit no floor or ceiling effects. Narrowing beam-walking is therefore a clinically viable method to evaluate lower-limb prosthesis users' balance ability, but requires psychometric testing before it is used to assess fall risk.
Identity appropriateness and the structure of the theory of planned behaviour.

PubMed

Case, Philippa; Sparks, Paul; Pavey, Louisa

2016-03-01

In contrast to the cost-benefit, utility-based approach to decision-making implicit in models such as the theory of planned behaviour (TPB), the logic of appropriateness (March, 1994. A Primer on Decision Making: How decisions happen. New York, NY: The Free Press) describes decision-making in terms of heuristic decision rules that involve matching identities to situations. This research is the first to apply the logic of appropriateness in conjunction with the theoretical structure of the TPB and assessed whether a measure of identity appropriateness might independently predict adults' intentions to engage in binge drinking. In Study 1, participants (N = 197) completed questionnaires assessing attitudes, subjective norm, perceived behavioural control, past behaviour, and identity appropriateness in relation to binge drinking. Path analysis revealed an independent predictive effect of identity appropriateness on intentions in addition to an indirect effect via attitudes. In Study 2 (N = 179), a prospective measure of behaviour was included in a similar study: Identity appropriateness again predicted intentions independently of the extended TPB predictors. It was again also found to be a strong predictor of attitudes. We suggest that the notion of identity appropriateness may assist in explaining the capacity of measures of self-identity to predict people's behavioural intentions. © 2015 The British Psychological Society.
Self-Supervised Chinese Ontology Learning from Online Encyclopedias

PubMed Central

Shao, Zhiqing; Ruan, Tong

2014-01-01

Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO. PMID:24715819
Self-supervised Chinese ontology learning from online encyclopedias.

PubMed

Hu, Fanghuai; Shao, Zhiqing; Ruan, Tong

2014-01-01

Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO.
Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.
Intelligent Data Visualization for Cross-Checking Spacecraft System Diagnosis

NASA Technical Reports Server (NTRS)

Ong, James C.; Remolina, Emilio; Breeden, David; Stroozas, Brett A.; Mohammed, John L.

2012-01-01

Any reasoning system is fallible, so crew members and flight controllers must be able to cross-check automated diagnoses of spacecraft or habitat problems by considering alternate diagnoses and analyzing related evidence. Cross-checking improves diagnostic accuracy because people can apply information processing heuristics, pattern recognition techniques, and reasoning methods that the automated diagnostic system may not possess. Over time, cross-checking also enables crew members to become comfortable with how the diagnostic reasoning system performs, so the system can earn the crew s trust. We developed intelligent data visualization software that helps users cross-check automated diagnoses of system faults more effectively. The user interface displays scrollable arrays of timelines and time-series graphs, which are tightly integrated with an interactive, color-coded system schematic to show important spatial-temporal data patterns. Signal processing and rule-based diagnostic reasoning automatically identify alternate hypotheses and data patterns that support or rebut the original and alternate diagnoses. A color-coded matrix display summarizes the supporting or rebutting evidence for each diagnosis, and a drill-down capability enables crew members to quickly view graphs and timelines of the underlying data. This system demonstrates that modest amounts of diagnostic reasoning, combined with interactive, information-dense data visualizations, can accelerate system diagnosis and cross-checking.
5 CFR 839.201 - Do these rules apply to me?

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 2 2011-01-01 2011-01-01 false Do these rules apply to me? 839.201 Section 839.201 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT (CONTINUED) CIVIL SERVICE... COVERAGE CORRECTIONS ACT Eligibility General Provisions § 839.201 Do these rules apply to me? (a) These...
5 CFR 839.201 - Do these rules apply to me?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 2 2010-01-01 2010-01-01 false Do these rules apply to me? 839.201 Section 839.201 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT (CONTINUED) CIVIL SERVICE... COVERAGE CORRECTIONS ACT Eligibility General Provisions § 839.201 Do these rules apply to me? (a) These...
5 CFR 839.201 - Do these rules apply to me?

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 2 2012-01-01 2012-01-01 false Do these rules apply to me? 839.201 Section 839.201 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT (CONTINUED) CIVIL SERVICE... COVERAGE CORRECTIONS ACT Eligibility General Provisions § 839.201 Do these rules apply to me? (a) These...
5 CFR 839.201 - Do these rules apply to me?

Code of Federal Regulations, 2013 CFR

2013-01-01

... 5 Administrative Personnel 2 2013-01-01 2013-01-01 false Do these rules apply to me? 839.201 Section 839.201 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT (CONTINUED) CIVIL SERVICE... COVERAGE CORRECTIONS ACT Eligibility General Provisions § 839.201 Do these rules apply to me? (a) These...
20 CFR 416.1141 - When the presumed value rule applies.

Code of Federal Regulations, 2011 CFR

2011-04-01

....1141 Section 416.1141 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SUPPLEMENTAL SECURITY INCOME FOR THE AGED, BLIND, AND DISABLED Income In-Kind Support and Maintenance § 416.1141 When the presumed value rule applies. The presumed value rule applies whenever we must count in-kind support and...
12 CFR 223.33 - What rules apply to derivative transactions?

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 3 2011-01-01 2011-01-01 false What rules apply to derivative transactions... Requirements Under Section 23A § 223.33 What rules apply to derivative transactions? (a) Market terms requirement. Derivative transactions between a member bank and its affiliates (other than depository...

20 CFR 416.1141 - When the presumed value rule applies.

Code of Federal Regulations, 2010 CFR

2010-04-01

....1141 Section 416.1141 Employees' Benefits SOCIAL SECURITY ADMINISTRATION SUPPLEMENTAL SECURITY INCOME FOR THE AGED, BLIND, AND DISABLED Income In-Kind Support and Maintenance § 416.1141 When the presumed value rule applies. The presumed value rule applies whenever we must count in-kind support and...
31 CFR 356.32 - What tax rules apply?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false What tax rules apply? 356.32 Section 356.32 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL...) Miscellaneous Provisions § 356.32 What tax rules apply? (a) General. Securities issued under this part are...
31 CFR 356.32 - What tax rules apply?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false What tax rules apply? 356.32 Section 356.32 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL...) Miscellaneous Provisions § 356.32 What tax rules apply? (a) General. Securities issued under this part are...
31 CFR 356.32 - What tax rules apply?

Code of Federal Regulations, 2013 CFR

2013-07-01

... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false What tax rules apply? 356.32 Section 356.32 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL...) Miscellaneous Provisions § 356.32 What tax rules apply? (a) General. Securities issued under this part are...
Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

NASA Technical Reports Server (NTRS)

Weaver, Johnathan M.

1993-01-01

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.
26 CFR 1.1014-7 - Example applying rules of §§ 1.1014-4 through 1.1014-6 to case involving multiple interests.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Example applying rules of Â§Â§ 1.1014-4 through... REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Basis Rules of General Application § 1.1014-7 Example applying rules of §§ 1.1014-4 through 1.1014-6 to case involving...
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.
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.
The Acquisition of Productive Rules in Child and Adult Language Learners

ERIC Educational Resources Information Center

Schuler, Kathryn Dolores

2017-01-01

In natural language, evidence suggests that, while some rules are productive (regular), applying broadly to new words, others are restricted to a specific set of lexical items (irregular). Further, the literature suggests that children make a categorical distinction between regular and irregular rules, applying only regular rules productively…
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
Improved finite difference schemes for transonic potential calculations

NASA Technical Reports Server (NTRS)

Hafez, M.; Osher, S.; Whitlow, W., Jr.

1984-01-01

Engquist and Osher (1980) have introduced a finite difference scheme for solving the transonic small disturbance equation, taking into account cases in which only compression shocks are admitted. Osher et al. (1983) studied a class of schemes for the full potential equation. It is proved that these schemes satisfy a new discrete 'entropy inequality' which rules out expansion shocks. However, the conducted analysis is restricted to steady two-dimensional flows. The present investigation is concerned with the adoption of a heuristic approach. The full potential equation in conservation form is solved with the aid of a modified artificial density method, based on flux biasing. It is shown that, with the current scheme, expansion shocks are not possible.
Automatic movie skimming with general tempo analysis

NASA Astrophysics Data System (ADS)

Lee, Shih-Hung; Yeh, Chia-Hung; Kuo, C. C. J.

2003-11-01

Story units are extracted by general tempo analysis including tempos analysis including tempos of audio and visual information in this research. Although many schemes have been proposed to successfully segment video data into shots using basic low-level features, how to group shots into meaningful units called story units is still a challenging problem. By focusing on a certain type of video such as sport or news, we can explore models with the specific application domain knowledge. For movie contents, many heuristic rules based on audiovisual clues have been proposed with limited success. We propose a method to extract story units using general tempo analysis. Experimental results are given to demonstrate the feasibility and efficiency of the proposed technique.
Rapid, autonomous analysis of He spectra I: Overview of the RadID program, user experience, and structure

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

Gosnell, Thomas B.; Chavez, Joseph R.; Rowland, Mark S.

2014-02-26

RadID is a new gamma-ray spectrum analysis program for rapid screening of HPGe gamma-ray data to reveal the presence of radionuclide signatures. It is an autonomous, rule-based heuristic system that can identify well over 200 radioactive sources with particular interest in uranium and plutonium characteristics. It executes in about one second. RadID does not require knowledge of the detector efficiency, the source-to-detector distance, or the geometry of the inspected radiation source—including any shielding. In this first of a three-document series we sketch the RadID program’s origin, its minimal requirements, the user experience, and the program operation.
Investigation of Simulated Trading — A multi agent based trading system for optimization purposes

NASA Astrophysics Data System (ADS)

Schneider, Johannes J.

2010-07-01

Some years ago, Bachem, Hochstättler, and Malich proposed a heuristic algorithm called Simulated Trading for the optimization of vehicle routing problems. Computational agents place buy-orders and sell-orders for customers to be handled at a virtual financial market, the prices of the orders depending on the costs of inserting the customer in the tour or for his removal. According to a proposed rule set, the financial market creates a buy-and-sell graph for the various orders in the order book, intending to optimize the overall system. Here I present a thorough investigation for the application of this algorithm to the traveling salesman problem.
A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model

NASA Astrophysics Data System (ADS)

Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban

We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.
Strengthening the resiliency of the coastal transportation system through integrated simulation of storm surge, inundation, and non-recurrent congestion in Northeast Florida.

DOT National Transportation Integrated Search

2013-05-01

In this study, the MTEVA (Developed as part of CMS #2009-010) has been advanced to apply storm surge and evacuation models to the greater Jacksonville area of Northeast Florida. Heuristic and time dynamic algorithms have been enhanced to work with th...
A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model

ERIC Educational Resources Information Center

Gerrard, Meg; Gibbons, Frederick X.; Houlihan, Amy E.; Stock, Michelle L.; Pomery, Elizabeth A.

2008-01-01

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their…
Exploring Readiness, Motivation, and Capacity for Implementing an iPad Campus Initiative: A Rural Community College Case Study

ERIC Educational Resources Information Center

Smith, Douglas A.; Coleman, Dawn

2018-01-01

This intrinsic case study explored organizational readiness to implement a campus-wide technology initiative. Specifically, this research examined a rural community college's implementation of an "iPad campus" initiative in which all students, faculty, and staff were required to adopt iPad technology. We apply a heuristic for…
Maslow--Move Aside! A Heuristical Motivation Model for Leaders in Career and Technical Education

ERIC Educational Resources Information Center

Kroth, Michael

2007-01-01

Maslow's Hierarchy of Needs is often used as an example of motivational theory in both practitioner and scholarly journals, yet considerable motivational research is being conducted that is not widely known, nor applied in practical settings. This paper summarizes several of those lines of inquiry and suggests applications for career and technical…

Design Heuristics for Authentic Simulation-Based Learning Games

ERIC Educational Resources Information Center

Ney, Muriel; Gonçalves, Celso; Balacheff, Nicolas

2014-01-01

Simulation games are games for learning based on a reference in the real world. We propose a model for authenticity in this context as a result of a compromise among learning, playing and realism. In the health game used to apply this model, students interact with characters in the game through phone messages, mail messages, SMS and video.…
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.
31 CFR 375.2 - What special definitions apply to this rule?

Code of Federal Regulations, 2013 CFR

2013-07-01

... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false What special definitions apply to this rule? 375.2 Section 375.2 Money and Finance: Treasury Regulations Relating to Money and Finance... SECURITIES REDEMPTION OPERATIONS General Information § 375.2 What special definitions apply to this rule? The...
31 CFR 375.2 - What special definitions apply to this rule?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false What special definitions apply to this rule? 375.2 Section 375.2 Money and Finance: Treasury Regulations Relating to Money and Finance... SECURITIES REDEMPTION OPERATIONS General Information § 375.2 What special definitions apply to this rule? The...
31 CFR 375.2 - What special definitions apply to this rule?

Code of Federal Regulations, 2012 CFR

2012-07-01

... 31 Money and Finance:Treasury 2 2012-07-01 2012-07-01 false What special definitions apply to this rule? 375.2 Section 375.2 Money and Finance: Treasury Regulations Relating to Money and Finance... SECURITIES REDEMPTION OPERATIONS General Information § 375.2 What special definitions apply to this rule? The...
31 CFR 375.2 - What special definitions apply to this rule?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false What special definitions apply to this rule? 375.2 Section 375.2 Money and Finance: Treasury Regulations Relating to Money and Finance... SECURITIES REDEMPTION OPERATIONS General Information § 375.2 What special definitions apply to this rule? The...
12 CFR 223.33 - What rules apply to derivative transactions?

Code of Federal Regulations, 2010 CFR

2010-01-01

... Requirements Under Section 23A § 223.33 What rules apply to derivative transactions? (a) Market terms... with affiliates comply with the market terms requirement of § 223.51. (c) Credit derivatives. A credit... 12 Banks and Banking 3 2010-01-01 2010-01-01 false What rules apply to derivative transactions...
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.
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.
Guided Iterative Substructure Search (GI-SSS) - A New Trick for an Old Dog.

PubMed

Weskamp, Nils

2016-07-01

Substructure search (SSS) is a fundamental technique supported by various chemical information systems. Many users apply it in an iterative manner: they modify their queries to shape the composition of the retrieved hit sets according to their needs. We propose and evaluate two heuristic extensions of SSS aimed at simplifying these iterative query modifications by collecting additional information during query processing and visualizing this information in an intuitive way. This gives the user a convenient feedback on how certain changes to the query would affect the retrieved hit set and reduces the number of trial-and-error cycles needed to generate an optimal search result. The proposed heuristics are simple, yet surprisingly effective and can be easily added to existing SSS implementations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

PubMed

Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

2016-12-05

High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.
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.
A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.
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)
A center for commercial development of space: Real-time satellite mapping. Remote sensing-based agricultural information expert system

NASA Technical Reports Server (NTRS)

Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.

1989-01-01

The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.
Probability theory plus noise: Replies to Crupi and Tentori (2016) and to Nilsson, Juslin, and Winman (2016).

PubMed

Costello, Fintan; Watts, Paul

2016-01-01

A standard assumption in much of current psychology is that people do not reason about probability using the rules of probability theory but instead use various heuristics or "rules of thumb," which can produce systematic reasoning biases. In Costello and Watts (2014), we showed that a number of these biases can be explained by a model where people reason according to probability theory but are subject to random noise. More importantly, that model also predicted agreement with probability theory for certain expressions that cancel the effects of random noise: Experimental results strongly confirmed this prediction, showing that probabilistic reasoning is simultaneously systematically biased and "surprisingly rational." In their commentaries on that paper, both Crupi and Tentori (2016) and Nilsson, Juslin, and Winman (2016) point to various experimental results that, they suggest, our model cannot explain. In this reply, we show that our probability theory plus noise model can in fact explain every one of the results identified by these authors. This gives a degree of additional support to the view that people's probability judgments embody the rational rules of probability theory and that biases in those judgments can be explained as simply effects of random noise. (c) 2015 APA, 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…
12 CFR 308.127 - Scope.

Code of Federal Regulations, 2010 CFR

2010-01-01

... this subpart, subpart B of the Local Rules and the Uniform Rules shall apply to proceedings to order an... subpart, subpart B of the Local Rules and the Uniform Rules shall apply to proceedings by the Board of Directors to order a municipal securities dealer to cease and desist from any violation of law or regulation...

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