Relationships between depth and number of misclassifications for decision trees

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2011-01-01

This paper describes a new tool for the study of relationships between depth and number of misclassifications for decision trees. In addition to the algorithm the paper also presents the results of experiments with three datasets from UCI Machine Learning Repository [3]. © 2011 Springer-Verlag.

Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

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Dimitris G. Stavrakoudis

2014-07-01

Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

Does Decision Quality (Always) Increase with the Size of Information Samples? Some Vicissitudes in Applying the Law of Large Numbers

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Fiedler, Klaus; Kareev, Yaakov

2006-01-01

Adaptive decision making requires that contingencies between decision options and their relative assets be assessed accurately and quickly. The present research addresses the challenging notion that contingencies may be more visible from small than from large samples of observations. An algorithmic account for such a seemingly paradoxical effect…

Greedy heuristics for minimization of number of terminal nodes in decision trees

KAUST Repository

Hussain, Shahid

2014-10-01

This paper describes, in detail, several greedy heuristics for construction of decision trees. We study the number of terminal nodes of decision trees, which is closely related with the cardinality of the set of rules corresponding to the tree. We compare these heuristics empirically for two different types of datasets (datasets acquired from UCI ML Repository and randomly generated data) as well as compare with the optimal results obtained using dynamic programming method.

Greedy heuristics for minimization of number of terminal nodes in decision trees

KAUST Repository

Hussain, Shahid

2014-01-01

This paper describes, in detail, several greedy heuristics for construction of decision trees. We study the number of terminal nodes of decision trees, which is closely related with the cardinality of the set of rules corresponding to the tree. We compare these heuristics empirically for two different types of datasets (datasets acquired from UCI ML Repository and randomly generated data) as well as compare with the optimal results obtained using dynamic programming method.

Relationships Between Average Depth and Number of Nodes for Decision Trees

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2013-01-01

This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML

The influence of number line estimation precision and numeracy on risky financial decision making.

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Park, Inkyung; Cho, Soohyun

2018-01-10

This study examined whether different aspects of mathematical proficiency influence one's ability to make adaptive financial decisions. "Numeracy" refers to the ability to process numerical and probabilistic information and is commonly reported as an important factor which contributes to financial decision-making ability. The precision of mental number representation (MNR), measured with the number line estimation (NLE) task has been reported to be another critical factor. This study aimed to examine the contribution of these mathematical proficiencies while controlling for the influence of fluid intelligence, math anxiety and personality factors. In our decision-making task, participants chose between two options offering probabilistic monetary gain or loss. Sensitivity to expected value was measured as an index for the ability to discriminate between optimal versus suboptimal options. Partial correlation and hierarchical regression analyses revealed that NLE precision better explained EV sensitivity compared to numeracy, after controlling for all covariates. These results suggest that individuals with more precise MNR are capable of making more rational financial decisions. We also propose that the measurement of "numeracy," which is commonly used interchangeably with general mathematical proficiency, should include more diverse aspects of mathematical cognition including basic understanding of number magnitude. © 2018 International Union of Psychological Science.

Number of warning information sources and decision making during tornadoes.

Science.gov (United States)

Luo, Jianjun; Cong, Zhen; Liang, Daan

2015-03-01

Taking proper protective action upon receiving tornado warnings is critical to reducing casualties. With more warning information sources becoming available, how the number of such information sources affects decision making should be quantitatively investigated. To examine how the number of warning information sources affected individuals' decisions to take protective action during tornadoes. A telephone survey using random sampling was conducted in 2012 with residents in Tuscaloosa AL and Joplin MO, resulting in a working sample of 782 respondents. Both cities were struck by violent tornadoes (Enhanced Fujita Scale [EF]4 and EF5) in 2011. The analysis was conducted in 2013. Logistic regression analysis showed that relative to having only one warning information source, having two and three or more warning information sources significantly increased the odds of taking protective action in Joplin but not in Tuscaloosa; having three or more sources had a significantly stronger effect on taking protective action in Joplin than in Tuscaloosa. Having an emergency preparation plan in both cities and being white in Tuscaloosa significantly increased the odds of taking protective action, whereas being divorced in Joplin reduced these odds. Receiving warnings from more warning information sources might be more beneficial in places with less previous exposure to tornadoes and for populations with lower awareness of a potential tornado and higher probability of receiving no warnings. Emergency management agencies and public health officials should give priority to these places and populations when formulating disaster mitigation decisions and policies. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Accurate, high-throughput typing of copy number variation using paralogue ratios from dispersed repeats.

Science.gov (United States)

Armour, John A L; Palla, Raquel; Zeeuwen, Patrick L J M; den Heijer, Martin; Schalkwijk, Joost; Hollox, Edward J

2007-01-01

Recent work has demonstrated an unexpected prevalence of copy number variation in the human genome, and has highlighted the part this variation may play in predisposition to common phenotypes. Some important genes vary in number over a high range (e.g. DEFB4, which commonly varies between two and seven copies), and have posed formidable technical challenges for accurate copy number typing, so that there are no simple, cheap, high-throughput approaches suitable for large-scale screening. We have developed a simple comparative PCR method based on dispersed repeat sequences, using a single pair of precisely designed primers to amplify products simultaneously from both test and reference loci, which are subsequently distinguished and quantified via internal sequence differences. We have validated the method for the measurement of copy number at DEFB4 by comparison of results from >800 DNA samples with copy number measurements by MAPH/REDVR, MLPA and array-CGH. The new Paralogue Ratio Test (PRT) method can require as little as 10 ng genomic DNA, appears to be comparable in accuracy to the other methods, and for the first time provides a rapid, simple and inexpensive method for copy number analysis, suitable for application to typing thousands of samples in large case-control association studies.

Relationships Between Average Depth and Number of Nodes for Decision Trees

KAUST Repository

Chikalov, Igor

2013-07-24

This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1]. © Springer-Verlag Berlin Heidelberg 2014.

A new view to uncertainty in Electre III method by introducing interval numbers

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Mohammad Kazem Sayyadi

2012-07-01

Full Text Available The Electre III is a widely accepted multi attribute decision making model, which takes into account the uncertainty and vagueness. Uncertainty concept in Electre III is introduced by indifference, preference and veto thresholds, but sometimes determining their accurate values can be very hard. In this paper we represent the values of performance matrix as interval numbers and we define the links between interval numbers and concordance matrix .Without changing the concept of concordance, in our propose concept, Electre III is usable in decision making problems with interval numbers.

Relationships between average depth and number of misclassifications for decision trees

KAUST Repository

Chikalov, Igor

2014-02-14

This paper presents a new tool for the study of relationships between the total path length or the average depth and the number of misclassifications for decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [9] and datasets representing Boolean functions with 10 variables.

Relationships between average depth and number of misclassifications for decision trees

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2014-01-01

This paper presents a new tool for the study of relationships between the total path length or the average depth and the number of misclassifications for decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [9] and datasets representing Boolean functions with 10 variables.

Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA

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Chan Alan

2006-06-01

Full Text Available Abstract Background Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. Results In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A. Conclusion Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA.

Science.gov (United States)

Gibbons, Brian; Datta, Parikkhit; Wu, Ying; Chan, Alan; Al Armour, John

2006-06-30

Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH) we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A). Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

Accurate Computation of Periodic Regions' Centers in the General M-Set with Integer Index Number

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Wang Xingyuan

2010-01-01

Full Text Available This paper presents two methods for accurately computing the periodic regions' centers. One method fits for the general M-sets with integer index number, the other fits for the general M-sets with negative integer index number. Both methods improve the precision of computation by transforming the polynomial equations which determine the periodic regions' centers. We primarily discuss the general M-sets with negative integer index, and analyze the relationship between the number of periodic regions' centers on the principal symmetric axis and in the principal symmetric interior. We can get the centers' coordinates with at least 48 significant digits after the decimal point in both real and imaginary parts by applying the Newton's method to the transformed polynomial equation which determine the periodic regions' centers. In this paper, we list some centers' coordinates of general M-sets' k-periodic regions (k=3,4,5,6 for the index numbers α=−25,−24,…,−1 , all of which have highly numerical accuracy.

Aggregation operators of neutrosophic linguistic numbers for multiple attribute group decision making.

Science.gov (United States)

Ye, Jun

2016-01-01

Based on the concept of neutrosophic linguistic numbers (NLNs) in symbolic neutrosophic theory presented by Smarandache in 2015, the paper firstly proposes basic operational laws of NLNs and the expected value of a NLN to rank NLNs. Then, we propose the NLN weighted arithmetic average (NLNWAA) and NLN weighted geometric average (NLNWGA) operators and discuss their properties. Further, we establish a multiple attribute group decision-making (MAGDM) method by using the NLNWAA and NLNWGA operators under NLN environment. Finally, an illustrative example on a decision-making problem of manufacturing alternatives in the flexible manufacturing system is given to show the application of the proposed MAGDM method.

VC-dimension of univariate decision trees.

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Yildiz, Olcay Taner

2015-02-01

In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. Via a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively, we show that our VC-dimension bounds are tight for simple trees. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using structural risk minimization in decision trees, i.e., pruning. Our simulation results show that structural risk minimization pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross validation.

The Cesarean Decision Survey

Science.gov (United States)

Puia, Denise M.

2013-01-01

A descriptive study design was used to describe the decision of women having a cesarean surgery. The Cesarean Birth Decision Survey was used to collect data from 101 postpartum women who underwent a cesarean. Most of the surgeries were to primipara women who reported doctor recommendation and increased safety for the baby as the main reasons for the cesarean. Those women who had repeat cesarean surgery all cited their previous cesarean as the main reason for the current surgery. Women’s knowledge of cesarean surgery needs to be assessed early in pregnancy so that appropriate education may be provided. Accurate and ongoing information may decrease the number of women choosing a cesarean surgery. PMID:24868134

A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

Science.gov (United States)

Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

2012-01-01

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

Collective animal decisions: preference conflict and decision accuracy.

Science.gov (United States)

Conradt, Larissa

2013-12-06

Social animals frequently share decisions that involve uncertainty and conflict. It has been suggested that conflict can enhance decision accuracy. In order to judge the practical relevance of such a suggestion, it is necessary to explore how general such findings are. Using a model, I examine whether conflicts between animals in a group with respect to preferences for avoiding false positives versus avoiding false negatives could, in principle, enhance the accuracy of collective decisions. I found that decision accuracy nearly always peaked when there was maximum conflict in groups in which individuals had different preferences. However, groups with no preferences were usually even more accurate. Furthermore, a relatively slight skew towards more animals with a preference for avoiding false negatives decreased the rate of expected false negatives versus false positives considerably (and vice versa), while resulting in only a small loss of decision accuracy. I conclude that in ecological situations in which decision accuracy is crucial for fitness and survival, animals cannot 'afford' preferences with respect to avoiding false positives versus false negatives. When decision accuracy is less crucial, animals might have such preferences. A slight skew in the number of animals with different preferences will result in the group avoiding that type of error more that the majority of group members prefers to avoid. The model also indicated that knowing the average success rate ('base rate') of a decision option can be very misleading, and that animals should ignore such base rates unless further information is available.

Accurate identification of layer number for few-layer WS2 and WSe2 via spectroscopic study.

Science.gov (United States)

Li, Yuanzheng; Li, Xinshu; Yu, Tong; Yang, Guochun; Chen, Heyu; Zhang, Cen; Feng, Qiushi; Ma, Jiangang; Liu, Weizhen; Xu, Haiyang; Liu, Yichun; Liu, Xinfeng

2018-03-23

Transition metal dichalcogenides (TMDs) with a typical layered structure are highly sensitive to their layer number in optical and electronic properties. Seeking a simple and effective method for layer number identification is very important to low-dimensional TMD samples. Herein, a rapid and accurate layer number identification of few-layer WS 2 and WSe 2 is proposed via locking their photoluminescence (PL) peak-positions. As the layer number of WS 2 /WSe 2 increases, it is found that indirect transition emission is more thickness-sensitive than direct transition emission, and the PL peak-position differences between the indirect and direct transitions can be regarded as fingerprints to identify their layer number. Theoretical calculation confirms that the notable thickness-sensitivity of indirect transition derives from the variations of electron density of states of W atom d-orbitals and chalcogen atom p-orbitals. Besides, the PL peak-position differences between the indirect and direct transitions are almost independent of different insulating substrates. This work not only proposes a new method for layer number identification via PL studies, but also provides a valuable insight into the thickness-dependent optical and electronic properties of W-based TMDs.

Accurate measurement of transgene copy number in crop plants using droplet digital PCR.

Science.gov (United States)

Collier, Ray; Dasgupta, Kasturi; Xing, Yan-Ping; Hernandez, Bryan Tarape; Shao, Min; Rohozinski, Dominica; Kovak, Emma; Lin, Jeanie; de Oliveira, Maria Luiza P; Stover, Ed; McCue, Kent F; Harmon, Frank G; Blechl, Ann; Thomson, James G; Thilmony, Roger

2017-06-01

Genetic transformation is a powerful means for the improvement of crop plants, but requires labor- and resource-intensive methods. An efficient method for identifying single-copy transgene insertion events from a population of independent transgenic lines is desirable. Currently, transgene copy number is estimated by either Southern blot hybridization analyses or quantitative polymerase chain reaction (qPCR) experiments. Southern hybridization is a convincing and reliable method, but it also is expensive, time-consuming and often requires a large amount of genomic DNA and radioactively labeled probes. Alternatively, qPCR requires less DNA and is potentially simpler to perform, but its results can lack the accuracy and precision needed to confidently distinguish between one- and two-copy events in transgenic plants with large genomes. To address this need, we developed a droplet digital PCR-based method for transgene copy number measurement in an array of crops: rice, citrus, potato, maize, tomato and wheat. The method utilizes specific primers to amplify target transgenes, and endogenous reference genes in a single duplexed reaction containing thousands of droplets. Endpoint amplicon production in the droplets is detected and quantified using sequence-specific fluorescently labeled probes. The results demonstrate that this approach can generate confident copy number measurements in independent transgenic lines in these crop species. This method and the compendium of probes and primers will be a useful resource for the plant research community, enabling the simple and accurate determination of transgene copy number in these six important crop species. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

An approach to solve group-decision-making problems with ordinal interval numbers.

Science.gov (United States)

Fan, Zhi-Ping; Liu, Yang

2010-10-01

The ordinal interval number is a form of uncertain preference information in group decision making (GDM), while it is seldom discussed in the existing research. This paper investigates how the ranking order of alternatives is determined based on preference information of ordinal interval numbers in GDM problems. When ranking a large quantity of ordinal interval numbers, the efficiency and accuracy of the ranking process are critical. A new approach is proposed to rank alternatives using ordinal interval numbers when every ranking ordinal in an ordinal interval number is thought to be uniformly and independently distributed in its interval. First, we give the definition of possibility degree on comparing two ordinal interval numbers and the related theory analysis. Then, to rank alternatives, by comparing multiple ordinal interval numbers, a collective expectation possibility degree matrix on pairwise comparisons of alternatives is built, and an optimization model based on this matrix is constructed. Furthermore, an algorithm is also presented to rank alternatives by solving the model. Finally, two examples are used to illustrate the use of the proposed approach.

Quorum decision-making in foraging fish shoals.

Directory of Open Access Journals (Sweden)

Ashley J W Ward

Full Text Available Quorum responses provide a means for group-living animals to integrate and filter disparate social information to produce accurate and coherent group decisions. A quorum response may be defined as a steep increase in the probability of group members performing a given behaviour once a threshold minimum number of their group mates already performing that behaviour is exceeded. In a previous study we reported the use of a quorum response in group decision-making of threespine sticklebacks (Gasterosteus aculeatus under a simulated predation threat. Here we examine the use of quorum responses by shoals of sticklebacks in first locating and then leaving a foraging patch. We show that a quorum rule explains movement decisions by threespine sticklebacks toward and then away from a food patch. Following both to and from a food patch occurred when a threshold number of initiators was exceeded, with the threshold being determined by the group size.

Decision aids for people facing health treatment or screening decisions.

Science.gov (United States)

Stacey, Dawn; Légaré, France; Col, Nananda F; Bennett, Carol L; Barry, Michael J; Eden, Karen B; Holmes-Rovner, Margaret; Llewellyn-Thomas, Hilary; Lyddiatt, Anne; Thomson, Richard; Trevena, Lyndal; Wu, Julie H C

2014-01-28

studies).A) Criteria involving 'choice made' attributes:Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).B) Criteria involving 'decision-making process' attributes:Decision aids compared to usual care interventions resulted in:a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); andc) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more

Decision Making Based On Management Information System and Decision Support System

Directory of Open Access Journals (Sweden)

Şükrü Ada

2015-04-01

Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

Scoring and Classifying Examinees Using Measurement Decision Theory

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Lawrence M. Rudner

2009-04-01

Full Text Available This paper describes and evaluates the use of measurement decision theory (MDT to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1 the classification accuracy of tests scored using decision theory; (2 the effectiveness of different sequential testing procedures; and (3 the number of items needed to make a classification. A large percentage of examinees can be classified accurately with very few items using decision theory. A Java Applet for self instruction and software for generating, calibrating and scoring MDT data are provided.

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

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Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

Determining the number of samples required for decisions concerning remedial actions at hazardous waste sites

International Nuclear Information System (INIS)

Skiles, J.L.; Redfearn, A.; White, R.K.

1991-01-01

The processing of collecting, analyzing, and assessing the data needed to make to make decisions concerning the cleanup of hazardous waste sites is quite complex and often very expensive. This is due to the many elements that must be considered during remedial investigations. The decision maker must have sufficient data to determine the potential risks to human health and the environment and to verify compliance with regulatory requirements, given the availability of resources allocated for a site, and time constraints specified for the completion of the decision making process. It is desirable to simplify the remedial investigation procedure as much as possible to conserve both time and resources while, simultaneously, minimizing the probability of error associated with each decision to be made. With this in mind, it is necessary to have a practical and statistically valid technique for estimating the number of on-site samples required to ''guarantee'' that the correct decisions are made with a specified precision and confidence level. Here, we will examine existing methodologies and then develop our own approach for determining a statistically defensible sample size based on specific guidelines that have been established for the risk assessment process

Approaching system equilibrium with accurate or not accurate feedback information in a two-route system

Science.gov (United States)

Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi

2015-02-01

With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.

Bayesian averaging over Decision Tree models for trauma severity scoring.

Science.gov (United States)

Schetinin, V; Jakaite, L; Krzanowski, W

2018-01-01

Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

Decision rules for decision tables with many-valued decisions

KAUST Repository

Chikalov, Igor

2011-01-01

In the paper, authors presents a greedy algorithm for construction of exact and partial decision rules for decision tables with many-valued decisions. Exact decision rules can be \\'over-fitted\\', so instead of exact decision rules with many attributes, it is more appropriate to work with partial decision rules with smaller number of attributes. Based on results for set cover problem authors study bounds on accuracy of greedy algorithm for exact and partial decision rule construction, and complexity of the problem of minimization of decision rule length. © 2011 Springer-Verlag.

An Isometric Mapping Based Co-Location Decision Tree Algorithm

Science.gov (United States)

Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

AN ISOMETRIC MAPPING BASED CO-LOCATION DECISION TREE ALGORITHM

Directory of Open Access Journals (Sweden)

G. Zhou

2018-05-01

Full Text Available Decision tree (DT induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT, which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1 The extraction method of exposed carbonate rocks is of high accuracy. (2 The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Calculation of the number of branches of multi-valued decision trees in computer aided importance rank of parameters

Directory of Open Access Journals (Sweden)

Tiszbierek Agnieszka

2017-01-01

Full Text Available An elaborated digital computer programme supporting the time-consuming process of selecting the importance rank of construction and operation parameters by means of stating optimum sets is based on the Quine – McCluskey algorithm of minimizing individual partial multi-valued logic functions. The example with real time data, calculated by means of the programme, showed that among the obtained optimum sets there were such which had a different number of real branches after being presented on the multi-valued logic decision tree. That is why an idea of elaborating another functionality of the programme – a module calculating the number of branches of real, multi-valued logic decision trees presenting optimum sets chosen by the programme was pursued. This paper presents the idea and the method for developing a module calculating the number of branches, real for each of optimum sets indicated by the programme, as well as to the calculation process.

Minimizing size of decision trees for multi-label decision tables

KAUST Repository

Azad, Mohammad

2014-09-29

We used decision tree as a model to discover the knowledge from multi-label decision tables where each row has a set of decisions attached to it and our goal is to find out one arbitrary decision from the set of decisions attached to a row. The size of the decision tree can be small as well as very large. We study here different greedy as well as dynamic programming algorithms to minimize the size of the decision trees. When we compare the optimal result from dynamic programming algorithm, we found some greedy algorithms produce results which are close to the optimal result for the minimization of number of nodes (at most 18.92% difference), number of nonterminal nodes (at most 20.76% difference), and number of terminal nodes (at most 18.71% difference).

Minimizing size of decision trees for multi-label decision tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2014-01-01

We used decision tree as a model to discover the knowledge from multi-label decision tables where each row has a set of decisions attached to it and our goal is to find out one arbitrary decision from the set of decisions attached to a row. The size of the decision tree can be small as well as very large. We study here different greedy as well as dynamic programming algorithms to minimize the size of the decision trees. When we compare the optimal result from dynamic programming algorithm, we found some greedy algorithms produce results which are close to the optimal result for the minimization of number of nodes (at most 18.92% difference), number of nonterminal nodes (at most 20.76% difference), and number of terminal nodes (at most 18.71% difference).

The effect of offering different numbers of colorectal cancer screening test options in a decision aid: a pilot randomized trial

Directory of Open Access Journals (Sweden)

Brenner Alison RT

2008-01-01

Full Text Available Abstract Background Decision aids can improve decision making processes, but the amount and type of information that they should attempt to communicate is controversial. We sought to compare, in a pilot randomized trial, two colorectal cancer (CRC screening decision aids that differed in the number of screening options presented. Methods Adults ages 48–75 not currently up to date with screening were recruited from the community and randomized to view one of two versions of our previously tested CRC screening decision aid. The first version included five screening options: fecal occult blood test (FOBT, sigmoidoscopy, a combination of FOBT and sigmoidoscopy, colonoscopy, and barium enema. The second discussed only the two most frequently selected screening options, FOBT and colonoscopy. Main outcomes were differences in screening interest and test preferences between groups after decision aid viewing. Patient test preference was elicited first without any associated out-of-pocket costs (OPC, and then with the following costs: FOBT-$10, sigmoidoscopy-$50, barium enema-$50, and colonoscopy-$200. Results 62 adults participated: 25 viewed the 5-option decision aid, and 37 viewed the 2-option version. Mean age was 54 (range 48–72, 58% were women, 71% were White, 24% African-American; 58% had completed at least a 4-year college degree. Comparing participants that viewed the 5-option version with participants who viewed the 2-option version, there were no differences in screening interest after viewing (1.8 vs. 1.9, t-test p = 0.76. Those viewing the 2-option version were somewhat more likely to choose colonoscopy than those viewing the 5-option version when no out of pocket costs were assumed (68% vs. 46%, p = 0.11, but not when such costs were imposed (41% vs. 42%, p = 1.00. Conclusion The number of screening options available does not appear to have a large effect on interest in colorectal cancer screening. The effect of offering differing

ForEx++: A New Framework for Knowledge Discovery from Decision Forests

Directory of Open Access Journals (Sweden)

Md Nasim Adnan

2017-11-01

Full Text Available Decision trees are popularly used in a wide range of real world problems for both prediction and classification (logic rules discovery. A decision forest is an ensemble of decision trees and it is often built for achieving better predictive performance compared to a single decision tree. Besides improving predictive performance, a decision forest can be seen as a pool of logic rules (rules with great potential for knowledge discovery. However, a standard-sized decision forest usually generates a large number of rules that a user may not able to manage for effective knowledge analysis. In this paper, we propose a new, data set independent framework for extracting those rules that are comparatively more accurate, generalized and concise than others. We apply the proposed framework on rules generated by two different decision forest algorithms from some publicly available medical related data sets on dementia and heart disease. We then compare the quality of rules extracted by the proposed framework with rules generated from a single J48 decision tree and rules extracted by another recent method. The results reported in this paper demonstrate the effectiveness of the proposed framework.

Time-Series Approaches for Forecasting the Number of Hospital Daily Discharged Inpatients.

Science.gov (United States)

Ting Zhu; Li Luo; Xinli Zhang; Yingkang Shi; Wenwu Shen

2017-03-01

For hospitals where decisions regarding acceptable rates of elective admissions are made in advance based on expected available bed capacity and emergency requests, accurate predictions of inpatient bed capacity are especially useful for capacity reservation purposes. As given, the remaining unoccupied beds at the end of each day, bed capacity of the next day can be obtained by examining the forecasts of the number of discharged patients during the next day. The features of fluctuations in daily discharges like trend, seasonal cycles, special-day effects, and autocorrelation complicate decision optimizing, while time-series models can capture these features well. This research compares three models: a model combining seasonal regression and ARIMA, a multiplicative seasonal ARIMA (MSARIMA) model, and a combinatorial model based on MSARIMA and weighted Markov Chain models in generating forecasts of daily discharges. The models are applied to three years of discharge data of an entire hospital. Several performance measures like the direction of the symmetry value, normalized mean squared error, and mean absolute percentage error are utilized to capture the under- and overprediction in model selection. The findings indicate that daily discharges can be forecast by using the proposed models. A number of important practical implications are discussed, such as the use of accurate forecasts in discharge planning, admission scheduling, and capacity reservation.

Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

KAUST Repository

Azad, Mohammad

2018-06-06

Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle

Toward accurate and precise estimates of lion density.

Science.gov (United States)

Elliot, Nicholas B; Gopalaswamy, Arjun M

2017-08-01

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3-month survey and adapted a Bayesian spatially explicit capture-recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture-recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km 2 , and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and

Decision Making in Action

Science.gov (United States)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication

Decision Making in the Airplane

Science.gov (United States)

Orasanu, Judith; Shafto, Michael G. (Technical Monitor)

1995-01-01

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that

An accurate method for quantifying and analyzing copy number variation in porcine KIT by an oligonucleotide ligation assay

Directory of Open Access Journals (Sweden)

Cho In-Cheol

2007-11-01

Full Text Available Abstract Background Aside from single nucleotide polymorphisms, copy number variations (CNVs are the most important factors in susceptibility to genetic disorders because they affect expression levels of genes. In previous studies, pyrosequencing, mini-sequencing, real-time PCR, invader assays and other techniques have been used to detect CNVs. However, the higher the copy number in a genome, the more difficult it is to resolve the copies, so a more accurate method for measuring CNVs and assigning genotype is needed. Results PCR followed by a quantitative oligonucleotide ligation assay (qOLA was developed for quantifying CNVs. The accuracy and precision of the assay were evaluated for porcine KIT, which was selected as a model locus. Overall, the root mean squares of bias and standard deviation of qOLA were 2.09 and 0.45, respectively. These values are less than half of those in the published pyrosequencing assay for analyzing CNV in porcine KIT. Using a combined method of qOLA and another pyrosequencing for quantitative analysis of KIT copies with spliced forms, we confirmed the segregation of KIT alleles in 145 F1 animals with pedigree information and verified the correct assignment of genotypes. In a diagnostic test on 100 randomly sampled commercial pigs, there was perfect agreement between the genotypes obtained by grouping observations on a scatter plot and by clustering using the nearest centroid sorting method implemented in PROC FASTCLUS of the SAS package. In a test on 159 Large White pigs, there were only two discrepancies between genotypes assigned by the two clustering methods (98.7% agreement, confirming that the quantitative ligation assay established here makes genotyping possible through the accurate measurement of high KIT copy numbers (>4 per diploid genome. Moreover, the assay is sensitive enough for use on DNA from hair follicles, indicating that DNA from various sources could be used. Conclusion We have established a high

'Misclassification error' greedy heuristic to construct decision trees for inconsistent decision tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2014-01-01

A greedy algorithm has been presented in this paper to construct decision trees for three different approaches (many-valued decision, most common decision, and generalized decision) in order to handle the inconsistency of multiple decisions in a decision table. In this algorithm, a greedy heuristic ‘misclassification error’ is used which performs faster, and for some cost function, results are better than ‘number of boundary subtables’ heuristic in literature. Therefore, it can be used in the case of larger data sets and does not require huge amount of memory. Experimental results of depth, average depth and number of nodes of decision trees constructed by this algorithm are compared in the framework of each of the three approaches.

Determining the number of samples required for decisions concerning remedial actions at hazardous waste sites

International Nuclear Information System (INIS)

Skiles, J.L.; Redfearn, A.; White, R.K.

1991-01-01

An important consideration for every risk analyst is how many field samples should be taken so that scientifically defensible decisions concerning the need for remediation of a hazardous waste site can be made. Since any plausible remedial action alternative must, at a minimum, satisfy the condition of protectiveness of human and environmental health, we propose a risk-based approach for determining the number of samples to take during remedial investigations rather than using more traditional approaches such as considering background levels of contamination or federal or state cleanup standards

Accurate decisions in an uncertain world: collective cognition increases true positives while decreasing false positives

NARCIS (Netherlands)

Wolf, M.; Kurvers, R.H.J.M.; Ward, A.J.W.; Krause, S.; Krause, J.

2013-01-01

In a wide range of contexts, including predator avoidance, medical decision-making and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives;

Helping decision makers frame, analyze, and implement decisions

Science.gov (United States)

Runge, Michael C.; McDonald-Madden, Eve

2018-01-01

All decisions have the same recognizable elements. Context, objectives, alternatives, consequences, and deliberation. Decision makers and analysts familiar with these elements can quickly see the underlying structure of a decision.There are only a small number of classes of decisions. These classes differ in the cognitive and scientific challenge they present to the decision maker; the ability to recognize the class of decision leads a decision maker to tools to aid in the analysis.Sometimes we need more information, sometimes we don’t. The role of science in a decision-making process is to provide the predictions that link the alternative actions to the desired outcomes. Investing in more science is only valuable if it helps to choose a better action.Implementation. The successful integration of decision analysis into environmental decisions requires careful attention to the decision, the people, and the institutions involved.

Dissociating sensory from decision processes in human perceptual decision making.

Science.gov (United States)

Mostert, Pim; Kok, Peter; de Lange, Floris P

2015-12-15

A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions.

Dissociating sensory from decision processes in human perceptual decision making

Science.gov (United States)

Mostert, Pim; Kok, Peter; de Lange, Floris P.

2015-01-01

A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions. PMID:26666393

Responsive Decision-Making

DEFF Research Database (Denmark)

Pedersen, Carsten Lund; Andersen, Torben Juul

, the aim of this study is to gain deeper insights into the complex and multifaceted decision processes that take place in large complex organizations operating in dynamic high-velocity markets. It is proposed that the ability to obtain faster, more accurate and updated insights about ongoing environmental......Strategic decision making remains a focal point in the strategy field, but despite decades of rich conceptual and empirical research we still seem distant from a level of understanding that can guide corporate practices effectively under turbulent and unpredictable environmental conditions. Hence...

34 CFR 602.18 - Ensuring consistency in decision-making.

Science.gov (United States)

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false Ensuring consistency in decision-making. 602.18 Section... relies on for making accrediting decisions is accurate; and (e) Provides the institution or program with... Criteria for Recognition Required Standards and Their Application § 602.18 Ensuring consistency in decision...

Accuracy of intuition in clinical decision-making among novice clinicians.

Science.gov (United States)

Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean

2017-05-01

To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.

Construction of α-decision trees for tables with many-valued decisions

KAUST Repository

Moshkov, Mikhail; Zielosko, Beata

2011-01-01

The paper is devoted to the study of greedy algorithm for construction of approximate decision trees (α-decision trees). This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bound on the number of algorithm steps, and bound on the algorithm accuracy relative to the depth of decision trees. © 2011 Springer-Verlag.

Decision support system of e-book provider selection for library using Simple Additive Weighting

Science.gov (United States)

Ciptayani, P. I.; Dewi, K. C.

2018-01-01

Each library has its own criteria and differences in the importance of each criterion in choosing an e-book provider for them. The large number of providers and the different importance levels of each criterion make the problem of determining the e-book provider to be complex and take a considerable time in decision making. The aim of this study was to implement Decision support system (DSS) to assist the library in selecting the best e-book provider based on their preferences. The way of DSS works is by comparing the importance of each criterion and the condition of each alternative decision. SAW is one of DSS method that is quite simple, fast and widely used. This study used 9 criteria and 18 provider to demonstrate how SAW work in this study. With the DSS, then the decision-making time can be shortened and the calculation results can be more accurate than manual calculations.

The Studies of Decision Tree in Estimation of Breast Cancer Risk by Using Polymorphism Nucleotide

Directory of Open Access Journals (Sweden)

Frida Seyedmir

2017-07-01

Full Text Available Abstract Introduction:   Decision tree is the data mining tools to collect, accurate prediction and sift information from massive amounts of data that are used widely in the field of computational biology and bioinformatics. In bioinformatics can be predict on diseases, including breast cancer. The use of genomic data including single nucleotide polymorphisms is a very important factor in predicting the risk of diseases. The number of seven important SNP among hundreds of thousands genetic markers were identified as factors associated with breast cancer. The objective of this study is to evaluate the training data on decision tree predictor error of the risk of breast cancer by using single nucleotide polymorphism genotype. Methods: The risk of breast cancer were calculated associated with the use of SNP formula:xj = fo * In human,  The decision tree can be used To predict the probability of disease using single nucleotide polymorphisms .Seven SNP with different odds ratio associated with breast cancer considered and coding and design of decision tree model, C4.5, by  Csharp2013 programming language were done. In the decision tree created with the coding, the four important associated SNP was considered. The decision tree error in two case of coding and using WEKA were assessment and percentage of decision tree accuracy in prediction of breast cancer were calculated. The number of trained samples was obtained with systematic sampling. With coding, two scenarios as well as software WEKA, three scenarios with different sets of data and the number of different learning and testing, were evaluated. Results: In both scenarios of coding, by increasing the training percentage from 66/66 to 86/42, the error reduced from 55/56 to 9/09. Also by running of WEKA on three scenarios with different sets of data, the number of different education, and different tests by increasing records number from 81 to 2187, the error rate decreased from 48/15 to 13

Accurate quantum chemical calculations

Science.gov (United States)

Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

1989-01-01

An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

Decision peptide-driven: a free software tool for accurate protein quantification using gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry.

Science.gov (United States)

Santos, Hugo M; Reboiro-Jato, Miguel; Glez-Peña, Daniel; Nunes-Miranda, J D; Fdez-Riverola, Florentino; Carvallo, R; Capelo, J L

2010-09-15

The decision peptide-driven tool implements a software application for assisting the user in a protocol for accurate protein quantification based on the following steps: (1) protein separation through gel electrophoresis; (2) in-gel protein digestion; (3) direct and inverse (18)O-labeling and (4) matrix assisted laser desorption ionization time of flight mass spectrometry, MALDI analysis. The DPD software compares the MALDI results of the direct and inverse (18)O-labeling experiments and quickly identifies those peptides with paralleled loses in different sets of a typical proteomic workflow. Those peptides are used for subsequent accurate protein quantification. The interpretation of the MALDI data from direct and inverse labeling experiments is time-consuming requiring a significant amount of time to do all comparisons manually. The DPD software shortens and simplifies the searching of the peptides that must be used for quantification from a week to just some minutes. To do so, it takes as input several MALDI spectra and aids the researcher in an automatic mode (i) to compare data from direct and inverse (18)O-labeling experiments, calculating the corresponding ratios to determine those peptides with paralleled losses throughout different sets of experiments; and (ii) allow to use those peptides as internal standards for subsequent accurate protein quantification using (18)O-labeling. In this work the DPD software is presented and explained with the quantification of protein carbonic anhydrase. Copyright (c) 2010 Elsevier B.V. All rights reserved.

An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

Science.gov (United States)

Elgin, Peter D.; Thomas, Rickey P.

2004-01-01

The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

Science.gov (United States)

Van Norman, Ethan R; Christ, Theodore J

2016-10-01

Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Finding small equivalent decision trees is hard

NARCIS (Netherlands)

Zantema, H.; Bodlaender, H.L.

2000-01-01

Two decision trees are called decision equivalent if they represent the same function, i.e., they yield the same result for every possible input. We prove that given a decision tree and a number, to decide if there is a decision equivalent decision tree of size at most that number is NPcomplete. As

Accurate determination of antenna directivity

DEFF Research Database (Denmark)

Dich, Mikael

1997-01-01

The derivation of a formula for accurate estimation of the total radiated power from a transmitting antenna for which the radiated power density is known in a finite number of points on the far-field sphere is presented. The main application of the formula is determination of directivity from power......-pattern measurements. The derivation is based on the theory of spherical wave expansion of electromagnetic fields, which also establishes a simple criterion for the required number of samples of the power density. An array antenna consisting of Hertzian dipoles is used to test the accuracy and rate of convergence...

Beyond expected utility: rethinking behavioral decision research.

Science.gov (United States)

Frisch, D; Clemen, R T

1994-07-01

Much research in psychology has evaluated the quality of people's decisions by comparisons with subjective expected utility (SEU) theory. This article suggests that typical arguments made for the status of utility theory as normative do not justify its use by psychologists as a standard by which to evaluate decision quality. It is argued that to evaluate decision quality, researchers need to identify those decision processes that tend to lead to desirable outcomes. It is contended that a good decision-making process must be concerned with how (and whether) decision makers evaluate potential consequences of decisions, the extent to which they accurately identify all relevant consequences, and the way in which they make final choices. Research that bears on these issues is reviewed.

Accurate decisions in an uncertain world: collective cognition increases true positives while decreasing false positives.

Science.gov (United States)

Wolf, Max; Kurvers, Ralf H J M; Ward, Ashley J W; Krause, Stefan; Krause, Jens

2013-04-07

In a wide range of contexts, including predator avoidance, medical decision-making and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives; conversely, decreased false positives are associated with decreased true positives. We use an integrated theoretical and experimental approach to show that a group of decision-makers can overcome this basic limitation. Using a mathematical model, we show that a simple quorum decision rule enables individuals in groups to simultaneously increase true positives and decrease false positives. The results from a predator-detection experiment that we performed with humans are in line with these predictions: (i) after observing the choices of the other group members, individuals both increase true positives and decrease false positives, (ii) this effect gets stronger as group size increases, (iii) individuals use a quorum threshold set between the average true- and false-positive rates of the other group members, and (iv) individuals adjust their quorum adaptively to the performance of the group. Our results have broad implications for our understanding of the ecology and evolution of group-living animals and lend themselves for applications in the human domain such as the design of improved screening methods in medical, forensic, security and business applications.

The attentional drift-diffusion model extends to simple purchasing decisions

Directory of Open Access Journals (Sweden)

Ian eKrajbich

2012-06-01

Full Text Available How do we make simple purchasing decisions (e.g., whether or not to buy a product ata given price? Previous work has shown that the Attentional-Drift-Diffusion-Model (aDDMcan provide accurate descriptions of the psychometric data for binary and trinary value-based choices, and of how the choice process is guided by visual attention. However, the computational processes used to make purchasing decisions are unknown. Here we extend the aDDM to the case of purchasing decisions, and test it using an eye-tracking experiment. We find that the model provides a quantitatively accurate description of the relationship between choice, reaction time, and visual fixations using parameters that are very similar to those that best fit the previous data. The only critical difference is that the choice biases induced by the fixations are about half as big in purchasing decisions as in binary choices.This suggests that the brain uses similar computational processes in these varied decision situations.

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction

Science.gov (United States)

2013-01-01

Background Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case–control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. Results We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual’s continental and sub-continental ancestry. To predict an individual’s continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control’s λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of

The influence of endogenous and exogenous spatial attention on decision confidence

OpenAIRE

Kurtz, Phillipp; Shapcott, Katharine A.; Kaiser , Jochen; Schmiedt, Joscha T.; Schmid, Michael C.

2017-01-01

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence wou...

Toward a Psychology of Surrogate Decision Making.

Science.gov (United States)

Tunney, Richard J; Ziegler, Fenja V

2015-11-01

In everyday life, many of the decisions that we make are made on behalf of other people. A growing body of research suggests that we often, but not always, make different decisions on behalf of other people than the other person would choose. This is problematic in the practical case of legally designated surrogate decision makers, who may not meet the substituted judgment standard. Here, we review evidence from studies of surrogate decision making and examine the extent to which surrogate decision making accurately predicts the recipient's wishes, or if it is an incomplete or distorted application of the surrogate's own decision-making processes. We find no existing domain-general model of surrogate decision making. We propose a framework by which surrogate decision making can be assessed and a novel domain-general theory as a unifying explanatory concept for surrogate decisions. © The Author(s) 2015.

Investigation of Multi-Criteria Decision Consistency: A Triplex Approach to Optimal Oilfield Portfolio Investment Decisions

Science.gov (United States)

Qaradaghi, Mohammed

Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers' preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker's knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and

PRIA 3 Fee Determination Decision Tree

Science.gov (United States)

The PRIA 3 decision tree will help applicants requesting a pesticide registration or certain tolerance action to accurately identify the category of their application and the amount of the required fee before they submit the application.

A Decision Support System Based on Genetic Algorithm (Case Study: Scheduling in Supply Chain

Directory of Open Access Journals (Sweden)

Mohammad Ali Beheheshtinia

2016-10-01

Full Text Available Nowadays, the application of effective and efficient decisions on complex issues require the use of decision support systems. This Paper provided a decision support system based on the genetic algorithm for production and transportation scheduling problem in a supply chain. It is assumed that there are number of orders that should be produced by suppliers and should be transported to the plant by a transportation fleet. The aim is to assign orders to the suppliers, specify the order of their production, allocate processed orders to the vehicles for transport and to arrange them in a way that minimizes the total delivery time. It has been shown that the complexity of the problem was related to Np-hard and there was no possibility of using accurate methods to solve the problem in a reasonable time. So, the genetic algorithm was used in this paper to solve the problem. By using this decision support system, a new approach to supply chain management was proposed. The analysis of the approach proposed in this study compared to the conventional approaches by the decision support system indicated the preference of our proposed approach

Semiquantitative dynamic contrast-enhanced MRI for accurate classification of complex adnexal masses.

Science.gov (United States)

Kazerooni, Anahita Fathi; Malek, Mahrooz; Haghighatkhah, Hamidreza; Parviz, Sara; Nabil, Mahnaz; Torbati, Leila; Assili, Sanam; Saligheh Rad, Hamidreza; Gity, Masoumeh

2017-02-01

To identify the best dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) descriptive parameters in predicting malignancy of complex ovarian masses, and develop an optimal decision tree for accurate classification of benign and malignant complex ovarian masses. Preoperative DCE-MR images of 55 sonographically indeterminate ovarian masses (27 benign and 28 malignant) were analyzed prospectively. Four descriptive parameters of the dynamic curve, namely, time-to-peak (TTP), wash-in-rate (WIR), relative signal intensity (SI rel ), and the initial area under the curve (IAUC 60 ) were calculated on the normalized curves of specified regions-of-interest (ROIs). A two-tailed Student's t-test and two automated classifiers, linear discriminant analysis (LDA) and support vector machines (SVMs), were used to compare the performance of the mentioned parameters individually and in combination with each other. TTP (P = 6.15E-8) and WIR (P = 5.65E-5) parameters induced the highest sensitivity (89% for LDA, and 97% for SVM) and specificity (93% for LDA, and 100% for SVM), respectively. Regarding the high sensitivity of TTP and high specificity of WIR and through their combination, an accurate and simple decision-tree classifier was designed using the line equation obtained by LDA classification model. The proposed classifier achieved an accuracy of 89% and area under the ROC curve of 93%. In this study an accurate decision-tree classifier based on a combination of TTP and WIR parameters was proposed, which provides a clinically flexible framework to aid radiologists/clinicians to reach a conclusive preoperative diagnosis and patient-specific therapy plan for distinguishing malignant from benign complex ovarian masses. 2 J. Magn. Reson. Imaging 2017;45:418-427. © 2016 International Society for Magnetic Resonance in Medicine.

Cost Accounting for Decision Makers.

Science.gov (United States)

Kaneklides, Ann L.

1985-01-01

Underscores the importance of informed decision making through accurate anticipation of cost incurrence in light of changing economic and environmental conditions. Explains the concepts of cost accounting, full allocation of costs, the selection of an allocation base, the allocation of indirect costs, depreciation, and implications for community…

Decision-making: Theory and practice

OpenAIRE

SM Turpin; MA Marais

2004-01-01

This paper compares a number of theoretical models of decision-making with the way in which senior managers make decisions in practice. Six prominent decision-makers were interviewed about their own decision-making style, as well as their use of decision support technology. Significant variation was found in personal decision-making styles. However, some central themes emerged, such as the importance of sensitivity to the decision-making context, attention to the presentation of information, ...

Decision or no decision: how do patient-physician interactions end and what matters?

Science.gov (United States)

Tai-Seale, Ming; Bramson, Rachel; Bao, Xiaoming

2007-03-01

A clearly stated clinical decision can induce a cognitive closure in patients and is an important investment in the end of patient-physician communications. Little is known about how often explicit decisions are made in primary care visits. To use an innovative videotape analysis approach to assess physicians' propensity to state decisions explicitly, and to examine the factors influencing decision patterns. We coded topics discussed in 395 videotapes of primary care visits, noting the number of instances and the length of discussions on each topic, and how discussions ended. A regression analysis tested the relationship between explicit decisions and visit factors such as the nature of topics under discussion, instances of discussion, the amount of time the patient spoke, and competing demands from other topics. About 77% of topics ended with explicit decisions. Patients spoke for an average of 58 seconds total per topic. Patients spoke more during topics that ended with an explicit decision, (67 seconds), compared with 36 seconds otherwise. The number of instances of a topic was associated with higher odds of having an explicit decision (OR = 1.73, p decisions. Although discussions often ended with explicit decisions, there were variations related to the content and dynamics of interactions. We recommend strengthening patients' voice and developing clinical tools, e.g., an "exit prescription," to improving decision making.

Comparison of Greedy Algorithms for Decision Tree Optimization

KAUST Repository

Alkhalid, Abdulaziz

2013-01-01

This chapter is devoted to the study of 16 types of greedy algorithms for decision tree construction. The dynamic programming approach is used for construction of optimal decision trees. Optimization is performed relative to minimal values of average depth, depth, number of nodes, number of terminal nodes, and number of nonterminal nodes of decision trees. We compare average depth, depth, number of nodes, number of terminal nodes and number of nonterminal nodes of constructed trees with minimum values of the considered parameters obtained based on a dynamic programming approach. We report experiments performed on data sets from UCI ML Repository and randomly generated binary decision tables. As a result, for depth, average depth, and number of nodes we propose a number of good heuristics. © Springer-Verlag Berlin Heidelberg 2013.

Defense AT&L (Volume 35, Number 5, September-October 2006)

National Research Council Canada - National Science Library

2006-01-01

.... Sylvester -- Reliable, accurate data about military equipment that has received a clean audit from an independent auditor gives leaders confidence in the decisions they make for the warfighter...

Relationships for Cost and Uncertainty of Decision Trees

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2013-01-01

This chapter is devoted to the design of new tools for the study of decision trees. These tools are based on dynamic programming approach and need the consideration of subtables of the initial decision table. So this approach is applicable only to relatively small decision tables. The considered tools allow us to compute: 1. Theminimum cost of an approximate decision tree for a given uncertainty value and a cost function. 2. The minimum number of nodes in an exact decision tree whose depth is at most a given value. For the first tool we considered various cost functions such as: depth and average depth of a decision tree and number of nodes (and number of terminal and nonterminal nodes) of a decision tree. The uncertainty of a decision table is equal to the number of unordered pairs of rows with different decisions. The uncertainty of approximate decision tree is equal to the maximum uncertainty of a subtable corresponding to a terminal node of the tree. In addition to the algorithms for such tools we also present experimental results applied to various datasets acquired from UCI ML Repository [4]. © Springer-Verlag Berlin Heidelberg 2013.

Use of a Recursive-Rule eXtraction algorithm with J48graft to achieve highly accurate and concise rule extraction from a large breast cancer dataset

Directory of Open Access Journals (Sweden)

Yoichi Hayashi

Full Text Available To assist physicians in the diagnosis of breast cancer and thereby improve survival, a highly accurate computer-aided diagnostic system is necessary. Although various machine learning and data mining approaches have been devised to increase diagnostic accuracy, most current methods are inadequate. The recently developed Recursive-Rule eXtraction (Re-RX algorithm provides a hierarchical, recursive consideration of discrete variables prior to analysis of continuous data, and can generate classification rules that have been trained on the basis of both discrete and continuous attributes. The objective of this study was to extract highly accurate, concise, and interpretable classification rules for diagnosis using the Re-RX algorithm with J48graft, a class for generating a grafted C4.5 decision tree. We used the Wisconsin Breast Cancer Dataset (WBCD. Nine research groups provided 10 kinds of highly accurate concrete classification rules for the WBCD. We compared the accuracy and characteristics of the rule set for the WBCD generated using the Re-RX algorithm with J48graft with five rule sets obtained using 10-fold cross validation (CV. We trained the WBCD using the Re-RX algorithm with J48graft and the average classification accuracies of 10 runs of 10-fold CV for the training and test datasets, the number of extracted rules, and the average number of antecedents for the WBCD. Compared with other rule extraction algorithms, the Re-RX algorithm with J48graft resulted in a lower average number of rules for diagnosing breast cancer, which is a substantial advantage. It also provided the lowest average number of antecedents per rule. These features are expected to greatly aid physicians in making accurate and concise diagnoses for patients with breast cancer. Keywords: Breast cancer diagnosis, Rule extraction, Re-RX algorithm, J48graft, C4.5

INTEGRATING ABC AND EVA TO EVALUATE INVESTMENT DECISIONS

Directory of Open Access Journals (Sweden)

N. Chiadamrong

2017-12-01

Full Text Available The significance of investment is transparent in the world of competitive business. Traditional costing systems in which their emphasizes are for short term savings rather than long term benefits have shown some lacking in providing accurate and reliable cost data for the investment decisions. Activity-based Costing (ABC, which is developed to satisfy some of the weaknesses of the traditional costing systems, can provide valuable insights into the operating processes and come up with more accurate cost data. In this paper, ABC is used to provide significant information for investment decisions. Although, the ABC method provides accurate operating product costs, it does not identify which products are economic valued added creators and so contribute to companies’ wealth. This drawback can be overcome by applying Economic Value Added (EVA. The adoption of ABC and EVA can represent a considerable change in the managerial thinking and to corporate strategies and business performance.

Number of Clusters and the Quality of Hybrid Predictive Models in Analytical CRM

Directory of Open Access Journals (Sweden)

Łapczyński Mariusz

2014-08-01

Full Text Available Making more accurate marketing decisions by managers requires building effective predictive models. Typically, these models specify the probability of customer belonging to a particular category, group or segment. The analytical CRM categories refer to customers interested in starting cooperation with the company (acquisition models, customers who purchase additional products (cross- and up-sell models or customers intending to resign from the cooperation (churn models. During building predictive models researchers use analytical tools from various disciplines with an emphasis on their best performance. This article attempts to build a hybrid predictive model combining decision trees (C&RT algorithm and cluster analysis (k-means. During experiments five different cluster validity indices and eight datasets were used. The performance of models was evaluated by using popular measures such as: accuracy, precision, recall, G-mean, F-measure and lift in the first and in the second decile. The authors tried to find a connection between the number of clusters and models' quality.

The balance space approach to multicriteria decision making—involving the decision maker

OpenAIRE

Ehrgott, M.

2002-01-01

The balance space approach (introduced by Galperin in 1990) provides a new view on multicriteria optimization. Looking at deviations from global optimality of the different objectives, balance points and balance numbers are defined when either different or equal deviations for each objective are allowed. Apportioned balance numbers allow the specification of proportions among the deviations. Through this concept the decision maker can be involved in the decision process. In this paper we prov...

The attentional drift-diffusion model extends to simple purchasing decisions.

Science.gov (United States)

Krajbich, Ian; Lu, Dingchao; Camerer, Colin; Rangel, Antonio

2012-01-01

How do we make simple purchasing decisions (e.g., whether or not to buy a product at a given price)? Previous work has shown that the attentional drift-diffusion model (aDDM) can provide accurate quantitative descriptions of the psychometric data for binary and trinary value-based choices, and of how the choice process is guided by visual attention. Here we extend the aDDM to the case of purchasing decisions, and test it using an eye-tracking experiment. We find that the model also provides a reasonably accurate quantitative description of the relationship between choice, reaction time, and visual fixations using parameters that are very similar to those that best fit the previous data. The only critical difference is that the choice biases induced by the fixations are about half as big in purchasing decisions as in binary choices. This suggests that a similar computational process is used to make binary choices, trinary choices, and simple purchasing decisions.

When Is Network Lasso Accurate?

Directory of Open Access Journals (Sweden)

Alexander Jung

2018-01-01

Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

Multi-pruning of decision trees for knowledge representation and classification

KAUST Repository

Azad, Mohammad

2016-06-09

We consider two important questions related to decision trees: first how to construct a decision tree with reasonable number of nodes and reasonable number of misclassification, and second how to improve the prediction accuracy of decision trees when they are used as classifiers. We have created a dynamic programming based approach for bi-criteria optimization of decision trees relative to the number of nodes and the number of misclassification. This approach allows us to construct the set of all Pareto optimal points and to derive, for each such point, decision trees with parameters corresponding to that point. Experiments on datasets from UCI ML Repository show that, very often, we can find a suitable Pareto optimal point and derive a decision tree with small number of nodes at the expense of small increment in number of misclassification. Based on the created approach we have proposed a multi-pruning procedure which constructs decision trees that, as classifiers, often outperform decision trees constructed by CART. © 2015 IEEE.

Multi-pruning of decision trees for knowledge representation and classification

KAUST Repository

Azad, Mohammad; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2016-01-01

We consider two important questions related to decision trees: first how to construct a decision tree with reasonable number of nodes and reasonable number of misclassification, and second how to improve the prediction accuracy of decision trees when they are used as classifiers. We have created a dynamic programming based approach for bi-criteria optimization of decision trees relative to the number of nodes and the number of misclassification. This approach allows us to construct the set of all Pareto optimal points and to derive, for each such point, decision trees with parameters corresponding to that point. Experiments on datasets from UCI ML Repository show that, very often, we can find a suitable Pareto optimal point and derive a decision tree with small number of nodes at the expense of small increment in number of misclassification. Based on the created approach we have proposed a multi-pruning procedure which constructs decision trees that, as classifiers, often outperform decision trees constructed by CART. © 2015 IEEE.

Heuristic decision making in medicine

Science.gov (United States)

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

Heuristic decision making in medicine.

Science.gov (United States)

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.

Decision and Inhibitory Rule Optimization for Decision Tables with Many-valued Decisions

KAUST Repository

Alsolami, Fawaz

2016-04-25

‘If-then’ rule sets are one of the most expressive and human-readable knowledge representations. This thesis deals with optimization and analysis of decision and inhibitory rules for decision tables with many-valued decisions. The most important areas of applications are knowledge extraction and representation. The benefit of considering inhibitory rules is connected with the fact that in some situations they can describe more knowledge than the decision ones. Decision tables with many-valued decisions arise in combinatorial optimization, computational geometry, fault diagnosis, and especially under the processing of data sets. In this thesis, various examples of real-life problems are considered which help to understand the motivation of the investigation. We extend relatively simple results obtained earlier for decision rules over decision tables with many-valued decisions to the case of inhibitory rules. The behavior of Shannon functions (which characterize complexity of rule systems) is studied for finite and infinite information systems, for global and local approaches, and for decision and inhibitory rules. The extensions of dynamic programming for the study of decision rules over decision tables with single-valued decisions are generalized to the case of decision tables with many-valued decisions. These results are also extended to the case of inhibitory rules. As a result, we have algorithms (i) for multi-stage optimization of rules relative to such criteria as length or coverage, (ii) for counting the number of optimal rules, (iii) for construction of Pareto optimal points for bi-criteria optimization problems, (iv) for construction of graphs describing relationships between two cost functions, and (v) for construction of graphs describing relationships between cost and accuracy of rules. The applications of created tools include comparison (based on information about Pareto optimal points) of greedy heuristics for bi-criteria optimization of rules

Accurate thickness measurement of graphene

International Nuclear Information System (INIS)

Shearer, Cameron J; Slattery, Ashley D; Stapleton, Andrew J; Shapter, Joseph G; Gibson, Christopher T

2016-01-01

Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1–1.3 nm to 0.1–0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials. (paper)

Decision Making in Action: Applying Research to Practice

Science.gov (United States)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication

Shared decision making in endocrinology: present and future directions.

Science.gov (United States)

Rodriguez-Gutierrez, Rene; Gionfriddo, Michael R; Ospina, Naykky Singh; Maraka, Spyridoula; Tamhane, Shrikant; Montori, Victor M; Brito, Juan P

2016-08-01

In medicine and endocrinology, there are few clinical circumstances in which clinicians can accurately predict what is best for their patients. As a result, patients and clinicians frequently have to make decisions about which there is uncertainty. Uncertainty results from limitations in the research evidence, unclear patient preferences, or an inability to predict how treatments will fit into patients' daily lives. The work that patients and clinicians do together to address the patient's situation and engage in a deliberative dialogue about reasonable treatment options is often called shared decision making. Decision aids are evidence-based tools that facilitate this process. Shared decision making is a patient-centred approach in which clinicians share information about the benefits, harms, and burden of different reasonable diagnostic and treatment options, and patients explain what matters to them in view of their particular values, preferences, and personal context. Beyond the ethical argument in support of this approach, decision aids have been shown to improve patients' knowledge about the available options, accuracy of risk estimates, and decisional comfort. Decision aids also promote patient participation in the decision-making process. Despite accumulating evidence from clinical trials, policy support, and expert recommendations in endocrinology practice guidelines, shared decision making is still not routinely implemented in endocrine practice. Additional work is needed to enrich the number of available tools and to implement them in practice workflows. Also, although the evidence from randomised controlled trials favours the use of this shared decision making in other settings, populations, and illnesses, the effect of this approach has been studied in a few endocrine disorders. Future pragmatic trials are needed to explore the effect and feasibility of shared decision making implementation into routine endocrinology and primary care practice. With the

Noneconomic factors influencing scrap metal disposition decisions at DOE and NRC-licensed nuclear facilities

Energy Technology Data Exchange (ETDEWEB)

Ewen, M.D.; Robinson, L.A.

1997-02-01

The U.S. Environmental Protection Agency (EPA) is currently developing radiation protection standards for scrap metal, which will establish criteria for the unconditional clearance of scrap from nuclear facilities. In support of this effort, Industrial Economics, Incorporated is assessing the costs and benefits attributable to the rulemaking. The first step in this analysis is to develop an in-depth understanding of the factors influencing scrap disposition decisions, so that one can predict current and future practices under existing requirements and compare them to the potential effects of EPA`s rulemaking. These baseline practices are difficult to predict due to a variety of factors. First, because decommissioning activities are just beginning at many sites, current practices do not necessarily provide an accurate indicator of how these practices may evolve as site managers gain experience with related decisions. Second, a number of different regulations and policies apply to these decisions, and the interactive effects of these requirements can be difficult to predict. Third, factors other than regulatory constraints and costs may have a significant effect on related decisions, such as concerns about public perceptions. In general, research suggests that these factors tend to discourage the unconditional clearance of scrap metal.

Bayesian calibration of power plant models for accurate performance prediction

International Nuclear Information System (INIS)

Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

2014-01-01

Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

Decisions, decisions: analysis of age, cohort, and time of testing on framing of risky decision options.

Science.gov (United States)

Mayhorn, Christopher B; Fisk, Arthur D; Whittle, Justin D

2002-01-01

Decision making in uncertain environments is a daily challenge faced by adults of all ages. Framing decision options as either gains or losses is a common method of altering decision-making behavior. In the experiment reported here, benchmark decision-making data collected in the 1970s by Tversky and Kahneman (1981, 1988) were compared with data collected from current samples of young and older adults to determine whether behavior was consistent across time. Although differences did emerge between the benchmark and the present samples, the effect of framing on decision behavior was relatively stable. The present findings suggest that adults of all ages are susceptible to framing effects. Results also indicated that apparent age differences might be better explained by an analysis of cohort and time-of-testing effects. Actual or potential applications of this research include an understanding of how framing might influence the decision-making behavior of people of all ages in a number of applied contexts, such as product warning interactions and medical decision scenarios.

Alternative analysis: the prime numbers theory and an extension of the real numbers set

OpenAIRE

Sukhotin A.; Zvyagin M.

2016-01-01

Here we consider the theory of prime numbers at a new methodology. The theory of prime numbers is one of the most ancient mathematical branches. We found an estimate of the all prime numbers sum using the notions of infinite lager numbers and infinitely small numbers, farther we estimated the value of the maximal prime number. We proved that Hardy–Littlewood Hypothesis has the positive decision too. The infinite small numbers define a new methodology of the well–known function o(x) applicatio...

Cognitive Processes in Decisions Under Risk Are Not the Same As in Decisions Under Uncertainty

Directory of Open Access Journals (Sweden)

Kirsten G Volz

2012-07-01

Full Text Available We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (small world, all alternatives, consequences, and probabilities are known. In uncertain (large worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries, with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift towards studying decision processes in uncertain worlds and provide first examples.

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Three approaches to deal with inconsistent decision tables - Comparison of decision tree complexity

KAUST Repository

Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail

2013-01-01

In inconsistent decision tables, there are groups of rows with equal values of conditional attributes and different decisions (values of the decision attribute). We study three approaches to deal with such tables. Instead of a group of equal rows, we consider one row given by values of conditional attributes and we attach to this row: (i) the set of all decisions for rows from the group (many-valued decision approach); (ii) the most common decision for rows from the group (most common decision approach); and (iii) the unique code of the set of all decisions for rows from the group (generalized decision approach). We present experimental results and compare the depth, average depth and number of nodes of decision trees constructed by a greedy algorithm in the framework of each of the three approaches. © 2013 Springer-Verlag.

Relationships among various parameters for decision tree optimization

KAUST Repository

Hussain, Shahid

2014-01-14

In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

Relationships among various parameters for decision tree optimization

KAUST Repository

Hussain, Shahid

2014-01-01

In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

A Common Mechanism Underlying Food Choice and Social Decisions

Science.gov (United States)

Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

2015-01-01

People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others’ benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. PMID:26460812

A Common Mechanism Underlying Food Choice and Social Decisions.

Science.gov (United States)

Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

2015-10-01

People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making.

How to make the best decision. Philosophical aspects of clinical decision theory.

Science.gov (United States)

Wulff, H R

1981-01-01

An attempt is made to discuss some of the philosophical implications of the use of decision-analytic techniques. The probabilities of a decision analysis are subjective measures of belief, and it is concluded that clinicians base their subjective beliefs on both recorded observations and theoretical knowledge. The clinical decision maker also evaluates the consequences of his actions, and therefore clinical decision theory transcends medical science. A number of different schools of normative ethics are mentioned to illustrate the complexity of everyday decision making. The philosophical terminology is useful for the analysis of clinical problems, and it is argued that clinical decision making has both a teleological and a deontological component. The results of decision-analytic studies depend on such factors as the wealth of the country, the organization of the health service, and cultural norms.

A tool for study of optimal decision trees

KAUST Repository

Alkhalid, Abdulaziz

2010-01-01

The paper describes a tool which allows us for relatively small decision tables to make consecutive optimization of decision trees relative to various complexity measures such as number of nodes, average depth, and depth, and to find parameters and the number of optimal decision trees. © 2010 Springer-Verlag Berlin Heidelberg.

Patient and professional accuracy of recalled treatment decisions in out-patient consultations

DEFF Research Database (Denmark)

Skinner, T. C.; Barnard, K.; Cradock, S.

2007-01-01

Aims: To test the assumption that professional recall of consultation decisions is valid and more accurate than patient recall of consultation decisions. Methods: One hundred and thirty-four consultations between diabetes specialist nurses and diabetes specialist dietitians in an adult out-patien...

Decision-making: Theory and practice

Directory of Open Access Journals (Sweden)

SM Turpin

2004-12-01

Full Text Available This paper compares a number of theoretical models of decision-making with the way in which senior managers make decisions in practice. Six prominent decision-makers were interviewed about their own decision-making style, as well as their use of decision support technology. Significant variation was found in personal decision-making styles. However, some central themes emerged, such as the importance of sensitivity to the decision-making context, attention to the presentation of information, and the use of intuition. In terms of the use of decision support technology, the use of self-help tools, such as office software, was clearly favoured.

Highly accurate surface maps from profilometer measurements

Science.gov (United States)

Medicus, Kate M.; Nelson, Jessica D.; Mandina, Mike P.

2013-04-01

Many aspheres and free-form optical surfaces are measured using a single line trace profilometer which is limiting because accurate 3D corrections are not possible with the single trace. We show a method to produce an accurate fully 2.5D surface height map when measuring a surface with a profilometer using only 6 traces and without expensive hardware. The 6 traces are taken at varying angular positions of the lens, rotating the part between each trace. The output height map contains low form error only, the first 36 Zernikes. The accuracy of the height map is ±10% of the actual Zernike values and within ±3% of the actual peak to valley number. The calculated Zernike values are affected by errors in the angular positioning, by the centering of the lens, and to a small effect, choices made in the processing algorithm. We have found that the angular positioning of the part should be better than 1?, which is achievable with typical hardware. The centering of the lens is essential to achieving accurate measurements. The part must be centered to within 0.5% of the diameter to achieve accurate results. This value is achievable with care, with an indicator, but the part must be edged to a clean diameter.

Collective decisions among bacterial viruses

Science.gov (United States)

Joh, Richard; Mileyko, Yuriy; Voit, Eberhard; Weitz, Joshua

2010-03-01

For many temperate bacteriophages, the decision of whether to kill hosts or enter a latent state depends on the multiplicity of infection. In this talk, I present a quantitative model of gene regulatory dynamics to describe how phages make collective decisions within host cells. Unlike most previous studies, the copy number of viral genomes is treated as a variable. In the absence of feedback loops, viral mRNA transcription is expected to be proportional to the viral copy number. However, when there are nonlinear feedback loops in viral gene regulation, our model shows that gene expression patterns are sensitive to changes in viral copy number and there can be a domain of copy number where the system becomes bistable. Hence, the viral copy number is a key control parameter determining host cell fates. This suggests that bacterial viruses can respond adaptively to changes in population dynamics, and can make alternative decisions as a bet-hedging strategy. Finally, I present a stochastic version of viral gene regulation and discuss speed-accuracy trade-offs in the context of cell fate determination by viruses.

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

CopyNumber450kCancer: baseline correction for accurate copy number calling from the 450k methylation array.

Science.gov (United States)

Marzouka, Nour-Al-Dain; Nordlund, Jessica; Bäcklin, Christofer L; Lönnerholm, Gudmar; Syvänen, Ann-Christine; Carlsson Almlöf, Jonas

2016-04-01

The Illumina Infinium HumanMethylation450 BeadChip (450k) is widely used for the evaluation of DNA methylation levels in large-scale datasets, particularly in cancer. The 450k design allows copy number variant (CNV) calling using existing bioinformatics tools. However, in cancer samples, numerous large-scale aberrations cause shifting in the probe intensities and thereby may result in erroneous CNV calling. Therefore, a baseline correction process is needed. We suggest the maximum peak of probe segment density to correct the shift in the intensities in cancer samples. CopyNumber450kCancer is implemented as an R package. The package with examples can be downloaded at http://cran.r-project.org nour.marzouka@medsci.uu.se Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Decision support for utility environmental risk management

International Nuclear Information System (INIS)

Balson, W.E.; Wilson, D.S.

1991-01-01

This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha

2012-10-04

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

A Common Mechanism Underlying Food Choice and Social Decisions.

Directory of Open Access Journals (Sweden)

Ian Krajbich

2015-10-01

Full Text Available People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making.

Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

Science.gov (United States)

Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

2011-01-01

The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

Science.gov (United States)

Campbell, Merle Wayne

2013-01-01

Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

Regret in Decision Making

NARCIS (Netherlands)

Connolly, T.; Zeelenberg, M.

2002-01-01

Decision research has only recently started to take seriously the role of emotions in choices and decisions. Regret is the emotion that has received the most attention. In this article, we sample a number of the initial regret studies from psychology and economics, and trace some of the complexities

Optimization of decision rules based on dynamic programming approach

KAUST Repository

Zielosko, Beata

2014-01-14

This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

Neuroeconomics: cross-currents in research on decision-making.

Science.gov (United States)

Sanfey, Alan G; Loewenstein, George; McClure, Samuel M; Cohen, Jonathan D

2006-03-01

Despite substantial advances, the question of how we make decisions and judgments continues to pose important challenges for scientific research. Historically, different disciplines have approached this problem using different techniques and assumptions, with few unifying efforts made. However, the field of neuroeconomics has recently emerged as an inter-disciplinary effort to bridge this gap. Research in neuroscience and psychology has begun to investigate neural bases of decision predictability and value, central parameters in the economic theory of expected utility. Economics, in turn, is being increasingly influenced by a multiple-systems approach to decision-making, a perspective strongly rooted in psychology and neuroscience. The integration of these disparate theoretical approaches and methodologies offers exciting potential for the construction of more accurate models of decision-making.

Totally optimal decision trees for Boolean functions

KAUST Repository

Chikalov, Igor

2016-07-28

We study decision trees which are totally optimal relative to different sets of complexity parameters for Boolean functions. A totally optimal tree is an optimal tree relative to each parameter from the set simultaneously. We consider the parameters characterizing both time (in the worst- and average-case) and space complexity of decision trees, i.e., depth, total path length (average depth), and number of nodes. We have created tools based on extensions of dynamic programming to study totally optimal trees. These tools are applicable to both exact and approximate decision trees, and allow us to make multi-stage optimization of decision trees relative to different parameters and to count the number of optimal trees. Based on the experimental results we have formulated the following hypotheses (and subsequently proved): for almost all Boolean functions there exist totally optimal decision trees (i) relative to the depth and number of nodes, and (ii) relative to the depth and average depth.

Representing Boolean Functions by Decision Trees

KAUST Repository

Chikalov, Igor

2011-01-01

A Boolean or discrete function can be represented by a decision tree. A compact form of decision tree named binary decision diagram or branching program is widely known in logic design [2, 40]. This representation is equivalent to other forms, and in some cases it is more compact than values table or even the formula [44]. Representing a function in the form of decision tree allows applying graph algorithms for various transformations [10]. Decision trees and branching programs are used for effective hardware [15] and software [5] implementation of functions. For the implementation to be effective, the function representation should have minimal time and space complexity. The average depth of decision tree characterizes the expected computing time, and the number of nodes in branching program characterizes the number of functional elements required for implementation. Often these two criteria are incompatible, i.e. there is no solution that is optimal on both time and space complexity. © Springer-Verlag Berlin Heidelberg 2011.

The use of decision analytic techniques in energy policy decisions

International Nuclear Information System (INIS)

Haemaelaeinen, R.P.; Seppaelaeinen, T.O.

1986-08-01

The report reviews decision analytic techniques and their applications to energy policy decision making. Decision analysis consists in techniques for structuring the essential elements of a decision problem and mathematical methods for ranking the alternatives from a set of simple judgments. Because modeling subjective judgments is characteristic of decision analysis, the models can incorporate qualitative factors and values, which escape traditional energy modeling. Decision analysis has been applied to choices among energy supply alternatives, siting energy facilities, selecting nuclear waste repositories, selecting research and development projects, risk analysis and prioritizing alternative energy futures. Many applications are done in universities and research institutions, but during the 70's the use of decision analysis has spread both to the public and the private sector. The settings where decision analysis has been applied range from aiding a single decision maker to clarifying opposing points of view. Decision analytic methods have also been linked with energy models. The most valuable result of decision analysis is the clarification of the problem at hand. Political decisions cannot be made solely on the basis of models, but models can be used to gain insight of the decision situation. Models inevitably simplify reality, so they must be regarded only as aids to judgment. So far there has been only one decision analysis of energy policy issues in Finland with actual political decision makers as participants. The experiences of this project and numerous foreign applications do however suggest that the decision analytic approach is useful in energy policy questions. The report presents a number of Finnish energy policy decisions where decision analysis might prove useful. However, the applicability of the methods depends crucially on the actual circumstances at hand

Accurate Multisteps Traffic Flow Prediction Based on SVM

Directory of Open Access Journals (Sweden)

Zhang Mingheng

2013-01-01

Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

Method of decision tree applied in adopting the decision for promoting a company

Directory of Open Access Journals (Sweden)

Cezarina Adina TOFAN

2015-09-01

Full Text Available The decision can be defined as the way chosen from several possible to achieve an objective. An important role in the functioning of the decisional-informational system is held by the decision-making methods. Decision trees are proving to be very useful tools for taking financial decisions or regarding the numbers, where a large amount of complex information must be considered. They provide an effective structure in which alternative decisions and the implications of their choice can be assessed, and help to form a correct and balanced vision of the risks and rewards that may result from a certain choice. For these reasons, the content of this communication will review a series of decision-making criteria. Also, it will analyse the benefits of using the decision tree method in the decision-making process by providing a numerical example. On this basis, it can be concluded that the procedure may prove useful in making decisions for companies operating on markets where competition intensity is differentiated.

Arbitrarily accurate twin composite π -pulse sequences

Science.gov (United States)

Torosov, Boyan T.; Vitanov, Nikolay V.

2018-04-01

We present three classes of symmetric broadband composite pulse sequences. The composite phases are given by analytic formulas (rational fractions of π ) valid for any number of constituent pulses. The transition probability is expressed by simple analytic formulas and the order of pulse area error compensation grows linearly with the number of pulses. Therefore, any desired compensation order can be produced by an appropriate composite sequence; in this sense, they are arbitrarily accurate. These composite pulses perform equally well as or better than previously published ones. Moreover, the current sequences are more flexible as they allow total pulse areas of arbitrary integer multiples of π .

Tactical Decision Aids High Bandwidth Links Using Autonomous Vehicles

Science.gov (United States)

2004-01-01

1 Tactical Decision Aids (High Bandwidth Links Using Autonomous Vehicles ) A. J. Healey, D. P. Horner, Center for Autonomous Underwater Vehicle...SUBTITLE Tactical Decision Aids (High Bandwidth Links Using Autonomous Vehicles ) 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Evidence of different underlying processes in pattern recall and decision-making.

Science.gov (United States)

Gorman, Adam D; Abernethy, Bruce; Farrow, Damian

2015-01-01

The visual search characteristics of expert and novice basketball players were recorded during pattern recall and decision-making tasks to determine whether the two tasks shared common visual-perceptual processing strategies. The order in which participants entered the pattern elements in the recall task was also analysed to further examine the nature of the visual-perceptual strategies and the relative emphasis placed upon particular pattern features. The experts demonstrated superior performance across the recall and decision-making tasks [see also Gorman, A. D., Abernethy, B., & Farrow, D. (2012). Classical pattern recall tests and the prospective nature of expert performance. The Quarterly Journal of Experimental Psychology, 65, 1151-1160; Gorman, A. D., Abernethy, B., & Farrow, D. (2013a). Is the relationship between pattern recall and decision-making influenced by anticipatory recall? The Quarterly Journal of Experimental Psychology, 66, 2219-2236)] but a number of significant differences in the visual search data highlighted disparities in the processing strategies, suggesting that recall skill may utilize different underlying visual-perceptual processes than those required for accurate decision-making performance in the natural setting. Performance on the recall task was characterized by a proximal-to-distal order of entry of the pattern elements with participants tending to enter the players located closest to the ball carrier earlier than those located more distal to the ball carrier. The results provide further evidence of the underlying perceptual processes employed by experts when extracting visual information from complex and dynamic patterns.

A method for generating skewed random numbers using two overlapping uniform distributions

International Nuclear Information System (INIS)

Ermak, D.L.; Nasstrom, J.S.

1995-02-01

The objective of this work was to implement and evaluate a method for generating skewed random numbers using a combination of uniform random numbers. The method provides a simple and accurate way of generating skewed random numbers from the specified first three moments without an a priori specification of the probability density function. We describe the procedure for generating skewed random numbers from unifon-n random numbers, and show that it accurately produces random numbers with the desired first three moments over a range of skewness values. We also show that in the limit of zero skewness, the distribution of random numbers is an accurate approximation to the Gaussian probability density function. Future work win use this method to provide skewed random numbers for a Langevin equation model for diffusion in skewed turbulence

Quantum dot single-photon switches of resonant tunneling current for discriminating-photon-number detection.

Science.gov (United States)

Weng, Qianchun; An, Zhenghua; Zhang, Bo; Chen, Pingping; Chen, Xiaoshuang; Zhu, Ziqiang; Lu, Wei

2015-03-23

Low-noise single-photon detectors that can resolve photon numbers are used to monitor the operation of quantum gates in linear-optical quantum computation. Exactly 0, 1 or 2 photons registered in a detector should be distinguished especially in long-distance quantum communication and quantum computation. Here we demonstrate a photon-number-resolving detector based on quantum dot coupled resonant tunneling diodes (QD-cRTD). Individual quantum-dots (QDs) coupled closely with adjacent quantum well (QW) of resonant tunneling diode operate as photon-gated switches- which turn on (off) the RTD tunneling current when they trap photon-generated holes (recombine with injected electrons). Proposed electron-injecting operation fills electrons into coupled QDs which turn "photon-switches" to "OFF" state and make the detector ready for multiple-photons detection. With proper decision regions defined, 1-photon and 2-photon states are resolved in 4.2 K with excellent propabilities of accuracy of 90% and 98% respectively. Further, by identifying step-like photon responses, the photon-number-resolving capability is sustained to 77 K, making the detector a promising candidate for advanced quantum information applications where photon-number-states should be accurately distinguished.

Decisions under uncertainty using Bayesian analysis

Directory of Open Access Journals (Sweden)

Stelian STANCU

2006-01-01

Full Text Available The present paper makes a short presentation of the Bayesian decions method, where extrainformation brings a great support to decision making process, but also attract new costs. In this situation, getting new information, generally experimentaly based, contributes to diminushing the uncertainty degree that influences decision making process. As a conclusion, in a large number of decision problems, there is the possibility that the decision makers will renew some decisions already taken because of the facilities offered by obtainig extrainformation.

Accurate, high-throughput typing of copy number variation using paralogue ratios from dispersed repeats.

NARCIS (Netherlands)

Armour, J.A.; Palla, R.; Zeeuwen, P.L.J.M.; Heijer, M. den; Schalkwijk, J.; Hollox, E.J.

2007-01-01

Recent work has demonstrated an unexpected prevalence of copy number variation in the human genome, and has highlighted the part this variation may play in predisposition to common phenotypes. Some important genes vary in number over a high range (e.g. DEFB4, which commonly varies between two and

Comparison of greedy algorithms for α-decision tree construction

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2011-01-01

A comparison among different heuristics that are used by greedy algorithms which constructs approximate decision trees (α-decision trees) is presented. The comparison is conducted using decision tables based on 24 data sets from UCI Machine Learning Repository [2]. Complexity of decision trees is estimated relative to several cost functions: depth, average depth, number of nodes, number of nonterminal nodes, and number of terminal nodes. Costs of trees built by greedy algorithms are compared with minimum costs calculated by an algorithm based on dynamic programming. The results of experiments assign to each cost function a set of potentially good heuristics that minimize it. © 2011 Springer-Verlag.

The use of control charts by laypeople and hospital decision-makers for guiding decision making.

Science.gov (United States)

Schmidtke, K A; Watson, D G; Vlaev, I

2017-07-01

Graphs presenting healthcare data are increasingly available to support laypeople and hospital staff's decision making. When making these decisions, hospital staff should consider the role of chance-that is, random variation. Given random variation, decision-makers must distinguish signals (sometimes called special-cause data) from noise (common-cause data). Unfortunately, many graphs do not facilitate the statistical reasoning necessary to make such distinctions. Control charts are a less commonly used type of graph that support statistical thinking by including reference lines that separate data more likely to be signals from those more likely to be noise. The current work demonstrates for whom (laypeople and hospital staff) and when (treatment and investigative decisions) control charts strengthen data-driven decision making. We present two experiments that compare people's use of control and non-control charts to make decisions between hospitals (funnel charts vs. league tables) and to monitor changes across time (run charts with control lines vs. run charts without control lines). As expected, participants more accurately identified the outlying data using a control chart than using a non-control chart, but their ability to then apply that information to more complicated questions (e.g., where should I go for treatment?, and should I investigate?) was limited. The discussion highlights some common concerns about using control charts in hospital settings.

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

Science.gov (United States)

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.

Water supply management using an extended group fuzzy decision-making method: a case study in north-eastern Iran

Science.gov (United States)

Minatour, Yasser; Bonakdari, Hossein; Zarghami, Mahdi; Bakhshi, Maryam Ali

2015-09-01

The purpose of this study was to develop a group fuzzy multi-criteria decision-making method to be applied in rating problems associated with water resources management. Thus, here Chen's group fuzzy TOPSIS method extended by a difference technique to handle uncertainties of applying a group decision making. Then, the extended group fuzzy TOPSIS method combined with a consistency check. In the presented method, initially linguistic judgments are being surveyed via a consistency checking process, and afterward these judgments are being used in the extended Chen's fuzzy TOPSIS method. Here, each expert's opinion is turned to accurate mathematical numbers and, then, to apply uncertainties, the opinions of group are turned to fuzzy numbers using three mathematical operators. The proposed method is applied to select the optimal strategy for the rural water supply of Nohoor village in north-eastern Iran, as a case study and illustrated example. Sensitivity analyses test over results and comparing results with project reality showed that proposed method offered good results for water resources projects.

Decision support systems

DEFF Research Database (Denmark)

Jørgensen, L.N.; Noe, E.; Langvad, A.M.

2007-01-01

system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required...... by these three groups to make their decisions varies and therefore different ways of using decision support systems need to be provided. Decision support systems need to be developed in close dialogue and collaboration with user groups....

Gravimetric determination of the iodine number of carbon black

International Nuclear Information System (INIS)

Murphy, L.J. Jr.

1991-01-01

This paper discusses a gravimetric method for the determination of the iodine adsorption number of carbon black. It comprises determining the concentration of an accurately weighed iodine blank solution by adding a standardized titrant to the iodine solution until a titration endpoint is reached and determining the concentration of the iodine solution by accurately weighing the amount of the standardized titrant necessary to reach the endpoint, accurately weighing an amount of carbon black and adding an appropriate amount of an accurately weighed portion of the iodine solution, equilibrating the carbon black-iodine solution mixture, adding the standardized titrant to an accurately weighed portion of the supernatant from the carbon black-iodine mixture until a titration endpoint is reached and determining the concentration of the supernatant by accurately weighing the amount of the standardized titrant necessary to reach the endpoint, wherein the titration endpoint of the supernatant is obtained using an indicating and a reference electrode, and calculating the iodine adsorption number of the carbon black based on the gravimetrically determined concentration of the titrant, the iodine solution, and the supernatant

Real time traffic models, decision support for traffic management

NARCIS (Netherlands)

Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

2014-01-01

Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

Real Time Traffic Models, Decision Support for Traffic Management

NARCIS (Netherlands)

Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

2014-01-01

Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

Emotion and decision making: multiple modulatory neural circuits.

Science.gov (United States)

Phelps, Elizabeth A; Lempert, Karolina M; Sokol-Hessner, Peter

2014-01-01

Although the prevalent view of emotion and decision making is derived from the notion that there are dual systems of emotion and reason, a modulatory relationship more accurately reflects the current research in affective neuroscience and neuroeconomics. Studies show two potential mechanisms for affect's modulation of the computation of subjective value and decisions. Incidental affective states may carry over to the assessment of subjective value and the decision, and emotional reactions to the choice may be incorporated into the value calculation. In addition, this modulatory relationship is reciprocal: Changing emotion can change choices. This research suggests that the neural mechanisms mediating the relation between affect and choice vary depending on which affective component is engaged and which decision variables are assessed. We suggest that a detailed and nuanced understanding of emotion and decision making requires characterizing the multiple modulatory neural circuits underlying the different means by which emotion and affect can influence choices.

Real-life decision making in college students. I: Consistency across specific decisions.

Science.gov (United States)

Galotti, Kathleen M; Wiener, Hillary J D; Tandler, Jane M

2014-01-01

First-year undergraduates participated in a short-term longitudinal study of real-life decision making over their first 14 months of college. They were surveyed about 7 different decisions: choosing courses for an upcoming term (3 different terms), choosing an academic major (twice), planning for the upcoming summer, and planning for sophomore-year housing. Participants showed moderate levels of consistency in the options they considered and in the criteria they used to decide between options, with about half of the options or criteria being used at 2 different points on the decision repeatedly studied. Participants varied somewhat in structural consistency, the tendency to consider the same number of options or criteria across decisions. They also varied in the way they integrated information across decision-making tasks. We suggest that people attempt to keep the information demands of the task within workable limits, sometimes sacrificing consistency as a result.

Atomic Fisher information versus atomic number

International Nuclear Information System (INIS)

Nagy, A.; Sen, K.D.

2006-01-01

It is shown that the Thomas-Fermi Fisher information is negative. A slightly more sophisticated model proposed by Gaspar provides a qualitatively correct expression for the Fisher information: Gaspar's Fisher information is proportional to the two-third power of the atomic number. Accurate numerical calculations show an almost linear dependence on the atomic number

Hybrid multiple criteria decision-making methods

DEFF Research Database (Denmark)

Zavadskas, Edmundas Kazimieras; Govindan, K.; Antucheviciene, Jurgita

2016-01-01

Formal decision-making methods can be used to help improve the overall sustainability of industries and organisations. Recently, there has been a great proliferation of works aggregating sustainability criteria by using diverse multiple criteria decision-making (MCDM) techniques. A number of revi...

Classification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables

KAUST Repository

Azad, Mohammad

2015-10-11

Decision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized, most common and many-valued decision) to handle such inconsistency. We created different greedy algorithms using various types of impurity and uncertainty measures to construct decision trees. We compared the three approaches based on the decision tree properties of the depth, average depth and number of nodes. Based on the result of the comparison, we choose to work with the many-valued decision approach. Now to determine which greedy algorithms are efficient, we compared them based on the optimization and classification results. It was found that some greedy algorithms Mult\\\\_ws\\\\_entSort, and Mult\\\\_ws\\\\_entML are good for both optimization and classification.

Classification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2015-01-01

Decision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized, most common and many-valued decision) to handle such inconsistency. We created different greedy algorithms using various types of impurity and uncertainty measures to construct decision trees. We compared the three approaches based on the decision tree properties of the depth, average depth and number of nodes. Based on the result of the comparison, we choose to work with the many-valued decision approach. Now to determine which greedy algorithms are efficient, we compared them based on the optimization and classification results. It was found that some greedy algorithms Mult\\_ws\\_entSort, and Mult\\_ws\\_entML are good for both optimization and classification.

Innovation, Technology and Decision Making: A Perspective for Strategic Action in Firms

Science.gov (United States)

Mulenburg, Gerald M.

2002-01-01

Innovation, technology, and the making of decisions are tightly intertwined in what can generally be called, strategic decision making. Although true for all firms, it is especially true in innovative, high technology firms that operate in a turbulent, fast moving environment where strategic decisions must be made accurately and quickly to survive. This paper looks at some factors reported in the literature that affect how and why the strategic decision process is so important, especially in companies in fast-moving, competitive environments. The work of several prominent authors who looked critically at past theory and research, and the current state of knowledge and practice, provides a perspective of how firms make strategic decisions.

Family Communication about End-of-Life Decisions and the Enactment of the Decision-Maker Role

Directory of Open Access Journals (Sweden)

April R. Trees

2017-06-01

Full Text Available End-of-life (EOL decisions in families are complex and emotional sites of family interaction necessitating family members coordinate roles in the EOL decision-making process. How family members in the United States enact the decision-maker role in EOL decision situations was examined through in-depth interviews with 22 individuals who participated in EOL decision-making for a family member. A number of themes emerged from the data with regard to the enactment of the decision-maker role. Families varied in how decision makers enacted the role in relation to collective family input, with consulting, informing and collaborating as different patterns of behavior. Formal family roles along with gender- and age-based roles shaped who took on the decision-maker role. Additionally, both family members and medical professionals facilitated or undermined the decision-maker’s role enactment. Understanding the structure and enactment of the decision-maker role in family interaction provides insight into how individuals and/or family members perform the decision-making role within a cultural context that values autonomy and self-determination in combination with collective family action in EOL decision-making.

Clinical decision-making by midwives: managing case complexity.

Science.gov (United States)

Cioffi, J; Markham, R

1997-02-01

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

Competencies evaluation based on single valued neutrosophic numbers and decision analysis schema

Directory of Open Access Journals (Sweden)

Evelyn Jazmín Henríquez Antepara

2017-09-01

Full Text Available Recently, neutrosophic sets and its application to decision making have become a topic of significant importance for researchers and practitioners. The present work addresses one of the most complex aspects of the formative process based on competencies: evaluation. In this paper, a new method for competencies evaluation is developed in a multicriteria framework.

Neurosurgical decision-making with IOM: DBS surgery.

Science.gov (United States)

Arle, Jeffrey E; Shils, Jay L

2007-12-01

Intraoperative monitoring (IOM) adds new information to intraoperative surgical decision-making. When presented clearly and accurately, it can help guide decision processes during the procedure, but can be a detriment overall if the information is inaccurate or misleading. Troubleshooting abilities and vigilance of the IOM staff play a large role in bolstering the level of trust a surgeon develops in IOM. Additionally, a surgeon may impart his own interpretation and experience with this new information that can undermine or enhance its impact on the case. In this article, we explore these issues with IOM in general and as they relate to the special context of DBS for movement disorders.

Individual decision making, group decision making and deliberation

Directory of Open Access Journals (Sweden)

Radovanović Bojana

2012-01-01

Full Text Available Each of us makes a number of decisions, from the less important to those with far-reaching consequences. As members of different groups, we are also actors of group decision making. In order to make a rational decision, a choice-making procedure must satisfy a number of assumptions (conditions of rationality. In addition, when it comes to group decisions, those procedures should also be “fair.” However, it is not possible to define a procedure of choice-making that would transform individual orders of alternatives based on preferences of perfectly rational individuals into a single social order and still meet conditions of rationality and ethics. The theory of deliberative democracy appeared in response to the impossibility of Social Choice theory. The basic assumption of deliberative democracy is that individuals adjust their preferences taking into account interests of the community. They are open for discussion with other group members and are willing to change their attitudes in order to achieve common interests. Ideally, group members come to an agreement during public discussion (deliberation. Still, this concept cannot completely over­come all the difficulties posed by the theory of social choice. Specifically, there is no solution for strategic and manipulative behavior of individuals. Also, the concept of deliberative democracy faces certain problems particular to this approach, such as, to name but a few, problems with the establishment of equality of participants in the debate and their motivation, as well as problems with the organization of public hearings. [Projekat Ministarstva nauke Republike Srbije, br. 47009: Evropske integracije i društveno-ekonomske promene privrede Srbije na putu ka EU i br. 179015: Izazovi i perspektive strukturnih promena u Srbiji: Strateški pravci ekonomskog razvoja i usklađivanje sa zahtevima EU

DECISIONS, METHODS AND TECHNIQUES RELATED TO DECISION SUPPORT SYSTEMS (DSS

Directory of Open Access Journals (Sweden)

Boghean Florin

2015-07-01

Full Text Available Generalised uncertainty, a phenomenon that today’s managers are facing as part of their professional experience, makes it impossible to anticipate the way the business environment will evolve or what will be the consequences of the decisions they plan to implement. Any decision making process within the company entails the simultaneous presence of a number of economic, technical, juridical, human and managerial variables. The development and the approval of a decision is the result of decision making activities developed by the decision maker and sometimes by a decision support team or/and a decision support system (DSS. These aspects related to specific applications of decision support systems in risk management will be approached in this research paper. Decisions in general and management decisions in particular are associated with numerous risks, due to their complexity and increasing contextual orientation. In each business entity, there are concerns with the implementation of risk management in order to improve the likelihood of meeting objectives, the trust of the parties involved, increase the operational safety and security as well as the protection of the environment, minimise losses, improve organisational resilience in order to diminish the negative impact on the organisation and provide a solid foundation for decision making. Since any business entity is considered to be a wealth generator, the analysis of their performance should not be restricted to financial efficiency alone, but will also encompass their economic efficiency as well. The type of research developed in this paper entails different dimensions: conceptual, methodological, as well as empirical testing. Subsequently, the conducted research entails a methodological side, since the conducted activities have resulted in the presentation of a simulation model that is useful in decision making processes on the capital market. The research conducted in the present paper

A fourth dimension in decision making in hepatology.

Science.gov (United States)

Ilan, Yaron

2010-12-01

Today, the assessment of liver function in patients suffering from acute or chronic liver disease is based on liver biopsy and blood tests including synthetic function, liver enzymes and viral load, most of which provide only circumstantial evidence as to the degree of hepatic impairment. Most of these tests lack the degree of sensitivity to be useful for follow-up of these patients at the frequency that is needed for decision making in clinical hepatology. Accurate assessment of liver function is essential to determine both short- and long-term prognosis, and for making decisions about liver and non-liver surgery, TIPS, chemoembolization or radiofrequency ablation in patients with chronic liver disease. Liver function tests can serve as the basis for accurate decision-making regarding the need for liver transplantation in the setting of acute failure or in patients with chronic liver disease. The liver metabolic breath test relies on measuring exhaled (13) C tagged methacetin, which is metabolized only by the liver. Measuring this liver-specific substrate by means of molecular correlation spectroscopy is a rapid, non-invasive method for assessing liver function at the point-of-care. The (13) C methacetin breath test (MBT) is a powerful tool to aid clinical hepatologists in bedside decision-making. Our recent findings regarding the ability of point-of-care (13) C MBT to assess the hepatic functional reserve in patients with acute and chronic liver disease are reviewed along with suggested treatment algorithms for common liver disorders. © 2010 The Japan Society of Hepatology.

Individual differences in attention influence perceptual decision making

Directory of Open Access Journals (Sweden)

Michael Dawson Nunez

2015-02-01

Full Text Available Sequential sampling decision-making models have been successful in accounting for reactiontime (RT and accuracy data in two-alternative forced choice tasks. These models have beenused to describe the behavior of populations of participants, and explanatory structures havebeen proposed to account for between individual variability in model parameters. In this studywe show that individual differences in behavior from a novel perceptual decision making taskcan be attributed to 1 differences in evidence accumulation rates, 2 differences in variability ofevidence accumulation within trials, and 3 differences in non-decision times across individuals.Using electroencephalography (EEG, we demonstrate that these differences in cognitivevariables, in turn, can be explained by attentional differences as measured by phase-lockingof steady-state visual evoked potential (SSVEP responses to the signal and noise componentsof the visual stimulus. Parameters of a cognitive model (a diffusion model were obtained fromaccuracy and RT distributions and related to phase-locking indices (PLIs of SSVEPs with asingle step in a hierarchical Bayesian framework. Participants who were able to suppress theSSVEP response to visual noise in high frequency bands were able to accumulate correctevidence faster and had shorter non-decision times (preprocessing or motor response times,leading to more accurate responses and faster response times. We show that the combinationof cognitive modeling and neural data in a hierarchical Bayesian framework relates physiologicalprocesses to the cognitive processes of participants, and that a model with a new (out-of-sample participant’s neural data can predict that participant’s behavior more accurately thanmodels without physiological data.

Making interactive decision support for patients a reality.

NARCIS (Netherlands)

Evans, R.W.; Elwyn, G.; Edwards, A.

2004-01-01

Interactive decision support applications might help patients to make difficult decisions about their health care. They lie in the context of traditional decision aids, which are known to have effects on a number of patient outcomes, including knowledge and decisional conflict. The problem of

Shared decision making after severe stroke-How can we improve patient and family involvement in treatment decisions?

Science.gov (United States)

Visvanathan, Akila; Dennis, Martin; Mead, Gillian; Whiteley, William N; Lawton, Julia; Doubal, Fergus Neil

2017-12-01

People who are well may regard survival with disability as being worse than death. However, this is often not the case when those surviving with disability (e.g. stroke survivors) are asked the same question. Many routine treatments provided after an acute stroke (e.g. feeding via a tube) increase survival, but with disability. Therefore, clinicians need to support patients and families in making informed decisions about the use of these treatments, in a process termed shared decision making. This is challenging after acute stroke: there is prognostic uncertainty, patients are often too unwell to participate in decision making, and proxies may not know the patients' expressed wishes (i.e. values). Patients' values also change over time and in different situations. There is limited evidence on successful methods to facilitate this process. Changes targeted at components of shared decision making (e.g. decision aids to provide information and discussing patient values) increase patient satisfaction. How this influences decision making is unclear. Presumably, a "shared decision-making tool" that introduces effective changes at various stages in this process might be helpful after acute stroke. For example, by complementing professional judgement with predictions from prognostic models, clinicians could provide information that is more accurate. Decision aids that are personalized may be helpful. Further qualitative research can provide clinicians with a better understanding of patient values and factors influencing this at different time points after a stroke. The evaluation of this tool in its success to achieve outcomes consistent with patients' values may require more than one clinical trial.

An Evaluation of Factors Affecting Decision Making among 4th Grade Elementary School Students with Low Socio-Economic Status

Science.gov (United States)

Kaskaya, Alper; Calp, Sükran; Kuru, Oguzhan

2017-01-01

Decision making is one of the most important life skills. While making correct, timely, accurate and appropriate decisions lead to positive changes in one's life, making incorrect decisions may have a negative impact. It is an important issue to examine what the 4th grade students in primary school have about the decision-making ability to be…

Maintenance Decision Based on Data Fusion of Aero Engines

Directory of Open Access Journals (Sweden)

Huawei Wang

2013-01-01

Full Text Available Maintenance has gained a great importance as a support function for ensuring aero engine reliability and availability. Cost-effectiveness and risk control are two basic criteria for accurate maintenance. Given that aero engines have much condition monitoring data, this paper presents a new condition-based maintenance decision system that employs data fusion for improving accuracy of reliability evaluation. Bayesian linear model has been applied, so that the performance degradation evaluation of aero engines could be realized. A reliability evaluation model has been presented based on gamma process, which achieves the accurate evaluation by information fusion. In reliability evaluation model, the shape parameter is estimated by the performance degradation evaluation result, and the scale parameter is estimated by failure, inspection, and repair information. What is more, with such reliability evaluation as input variables and by using particle swarm optimization (PSO, a stochastic optimization of maintenance decision for aircraft engines has been presented, in which the effectiveness and the accuracy are demonstrated by a numerical example.

Stress-induced cortisol facilitates threat-related decision making among police officers.

Science.gov (United States)

Akinola, Modupe; Mendes, Wendy Berry

2012-02-01

Previous research suggests that cortisol can affect cognitive functions such as memory, decision making, and attentiveness to threat-related cues. Here, we examine whether increases in cortisol, brought on by an acute social stressor, influence threat-related decision making. Eighty-one police officers completed a standardized laboratory stressor and then immediately completed a computer simulated decision-making task designed to examine decisions to accurately shoot or not shoot armed and unarmed Black and White targets. Results indicated that police officers who had larger cortisol increases to the social-stress task subsequently made fewer errors when deciding to shoot armed Black targets relative to armed White targets, suggesting that hypothalamic pituitary adrenal (HPA) activation may exacerbate vigilance for threat cues. We conclude with a discussion of the implications of threat-initiated decision making.

More Than a Destination: Contraceptive Decision Making as a Journey.

Science.gov (United States)

Downey, Margaret Mary; Arteaga, Stephanie; Villaseñor, Elodia; Gomez, Anu Manchikanti

Contraceptive use is widely recognized as a means of reducing adverse health-related outcomes. However, dominant paradigms of contraceptive counseling may rely on a narrow definition of "evidence" (i.e., scientifically accurate but exclusive of individual women's experiences). Given increased enthusiasm for long-acting, reversible contraceptive methods, such paradigms may reinforce counseling that overprivileges effectiveness, particularly for groups considered at high risk of unintended pregnancy. This study investigates where and how women's experiences fit into the definition of evidence these counseling protocols use. Using a qualitative approach, this analysis draws on semistructured interviews with 38 young (ages 18-24) Black and Latina women. We use a qualitative content analysis approach, with coding categories derived directly from the textual data. Our analysis suggests that contraceptive decision making is an iterative, relational, reflective journey. Throughout contraceptive histories, participants described experiences evolving to create a foundation from which decision-making power was drawn. The same contraceptive-related decisions were revisited repeatedly, with knowledge accrued along the way. The cumulative experience of using, assigning meanings to, and developing values around contraception meant that young women experienced contraceptive decision making as a dynamic process. This journey creates a rich body of evidence that informs contraceptive decision making. To provide appropriate, acceptable, patient-centered family planning care, providers must engage with evidence grounded in women's expertise on their contraceptive use in addition to medically accurate data on method effectiveness, side effects, and contraindications. Copyright © 2017 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Totally optimal decision rules

KAUST Repository

Amin, Talha

2017-11-22

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Totally optimal decision rules

KAUST Repository

Amin, Talha M.; Moshkov, Mikhail

2017-01-01

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Attention and choice: a review on eye movements in decision making.

Science.gov (United States)

Orquin, Jacob L; Mueller Loose, Simone

2013-09-01

This paper reviews studies on eye movements in decision making, and compares their observations to theoretical predictions concerning the role of attention in decision making. Four decision theories are examined: rational models, bounded rationality, evidence accumulation, and parallel constraint satisfaction models. Although most theories were confirmed with regard to certain predictions, none of the theories adequately accounted for the role of attention during decision making. Several observations emerged concerning the drivers and down-stream effects of attention on choice, suggesting that attention processes plays an active role in constructing decisions. So far, decision theories have largely ignored the constructive role of attention by assuming that it is entirely determined by heuristics, or that it consists of stochastic information sampling. The empirical observations reveal that these assumptions are implausible, and that more accurate assumptions could have been made based on prior attention and eye movement research. Future decision making research would benefit from greater integration with attention research. Copyright © 2013 Elsevier B.V. All rights reserved.

Decision support for farmers in Africa: Analysis of the roles and ...

African Journals Online (AJOL)

Decision support for farmers in Africa: Analysis of the roles and ... producers to access more consumable, accurate and timely information for making informed choices. ... To capitalise on 'big data', the sub-Saharan African grain industry needs ...

INFLUENCE OF THE BRAND ON PURCHASE DECISION

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KISS MARTA

2016-12-01

Full Text Available The influence of the brand on purchase decision has been and is still extensively studied by marketers, researchers, economists, manufacturers (especially the multinational companies. In the present study we aimed to find out if the brand influences the purchase decision of consumers in general (brand products/services. A survey has been conducted in September 2016 on a number of 225 people, residents of Tîrgu Mureş city, from Romania, aged between 15 and 65+. The collected data were analyzed to comply with the obiectives and also to draw conclusions. From the study it is reveal that the purchase decision of a potencial buyer is influenced by a number of factors, in particularly by the quality and price. We chose to study the influence of brand on purchase decision, a very topical subject that can never be fully exhausted.

Heuristic decision making.

Science.gov (United States)

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.

Accurate metacognition for visual sensory memory representations.

Science.gov (United States)

Vandenbroucke, Annelinde R E; Sligte, Ilja G; Barrett, Adam B; Seth, Anil K; Fahrenfort, Johannes J; Lamme, Victor A F

2014-04-01

The capacity to attend to multiple objects in the visual field is limited. However, introspectively, people feel that they see the whole visual world at once. Some scholars suggest that this introspective feeling is based on short-lived sensory memory representations, whereas others argue that the feeling of seeing more than can be attended to is illusory. Here, we investigated this phenomenon by combining objective memory performance with subjective confidence ratings during a change-detection task. This allowed us to compute a measure of metacognition--the degree of knowledge that subjects have about the correctness of their decisions--for different stages of memory. We show that subjects store more objects in sensory memory than they can attend to but, at the same time, have similar metacognition for sensory memory and working memory representations. This suggests that these subjective impressions are not an illusion but accurate reflections of the richness of visual perception.

Number Line Estimation in Children with Developmental Dyscalculia

Science.gov (United States)

Sella, Francesco; Berteletti, Ilaria; Martina, Brazzolotto; Lucangeli, Daniela; Zorzi, Marco

2013-01-01

In the number to position task, several studies have shown that typically developing children shift from a biased (logarithmic) to an accurate (linear) mapping of symbolic digits onto a spatial position on a line. The initial pattern of overestimation of small numbers and the underestimation of larger numbers is compensated by means of age and…

Extensions of dynamic programming as a new tool for decision tree optimization

KAUST Repository

Alkhalid, Abdulaziz

2013-01-01

The chapter is devoted to the consideration of two types of decision trees for a given decision table: α-decision trees (the parameter α controls the accuracy of tree) and decision trees (which allow arbitrary level of accuracy). We study possibilities of sequential optimization of α-decision trees relative to different cost functions such as depth, average depth, and number of nodes. For decision trees, we analyze relationships between depth and number of misclassifications. We also discuss results of computer experiments with some datasets from UCI ML Repository. ©Springer-Verlag Berlin Heidelberg 2013.

The impact of the mode of thought in complex decisions: intuitive decisions are better

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Marius eUsher

2011-03-01

Full Text Available A number of recent studies have reported that decision-quality is enhanced under conditions of inattention or distraction (unconscious-thought; Dijksterhuis, 2004; Dijksterhuis et al., 2006; Dijksterhuis & Nordgren, 2006. These reports have generated considerable controversy, for both experimental (problems of replication and theoretical reasons (interpretation. Here we report the results of four experiments. The first experiment replicates the unconscious thought effect, under conditions that validate and control the subjective criterion of decision quality. The second and third experiments examine the impact of a mode of thought manipulation (without distraction on decision quality in immediate decisions. Here we find that intuitive or affective manipulations improve decision quality compared to analytic/deliberation manipulations. The fourth experiment combines the two methods (distraction and mode of thought manipulations and demonstrates enhanced decision quality, in a situation that attempts to preserve ecological validity. The results are interpreted within a framework that is based on two interacting subsystems of decision-making: an affective/intuition based system and an analytic/deliberation system.

Determination of the structure of γ-alumina from interatomic potential and first-principles calculations: The requirement of significant numbers of nonspinel positions to achieve an accurate structural model

International Nuclear Information System (INIS)

Paglia, Gianluca; Rohl, Andrew L.; Gale, Julian D.; Buckley, Craig E.

2005-01-01

We have performed an extensive computational study of γ-Al 2 O 3 , beginning with the geometric analysis of approximately 1.47 billion spinel-based structural candidates, followed by derivative method energy minimization calculations of approximately 122 000 structures. Optimization of the spinel-based structural models demonstrated that structures exhibiting nonspinel site occupancy after simulation were more energetically favorable, as suggested in other computational studies. More importantly, none of the spinel structures exhibited simulated diffraction patterns that were characteristic of γ-Al 2 O 3 . This suggests that cations of γ-Al 2 O 3 are not exclusively held in spinel positions, that the spinel model of γ-Al 2 O 3 does not accurately reflect its structure, and that a representative structure cannot be achieved from molecular modeling when the spinel representation is used as the starting structure. The latter two of these three findings are extremely important when trying to accurately model the structure. A second set of starting models were generated with a large number of cations occupying c symmetry positions, based on the findings from recent experiments. Optimization of the new c symmetry-based structural models resulted in simulated diffraction patterns that were characteristic of γ-Al 2 O 3 . The modeling, conducted using supercells, yields a more accurate and complete determination of the defect structure of γ-Al 2 O 3 than can be achieved with current experimental techniques. The results show that on average over 40% of the cations in the structure occupy nonspinel positions, and approximately two-thirds of these occupy c symmetry positions. The structures exhibit variable occupancy in the site positions that follow local symmetry exclusion rules. This variation was predominantly represented by a migration of cations away from a symmetry positions to other tetrahedral site positions during optimization which were found not to affect the

Difference Test Between Two Environments - Econometric Method of Substantiating the Decision

OpenAIRE

Albici Mihaela; Teselios Delia; ntonescu Eugenia

2012-01-01

Business decision-making environment must integrate as a whole the experience and beliefs of the techniques makers and decision support systems used. Currently, the business information environment is becoming more complex due to the increasing volume of information relevant for business area, the number of information resources and the number of technologies used for accessing and storing data. Decision support systems should serve as the main tool for decision makers in order to keep up wit...

The hidden traps in decision making.

Science.gov (United States)

Hammond, J S; Keeney, R L; Raiffa, H

1998-01-01

Bad decisions can often be traced back to the way the decisions were made--the alternatives were not clearly defined, the right information was not collected, the costs and benefits were not accurately weighted. But sometimes the fault lies not in the decision-making process but rather in the mind of the decision maker. The way the human brain works can sabotage the choices we make. John Hammond, Ralph Keeney, and Howard Raiffa examine eight psychological traps that are particularly likely to affect the way we make business decisions: The anchoring trap leads us to give disproportionate weight to the first information we receive. The statusquo trap biases us toward maintaining the current situation--even when better alternatives exist. The sunk-cost trap inclines us to perpetuate the mistakes of the past. The confirming-evidence trap leads us to seek out information supporting an existing predilection and to discount opposing information. The framing trap occurs when we misstate a problem, undermining the entire decision-making process. The overconfidence trap makes us overestimate the accuracy of our forecasts. The prudence trap leads us to be overcautious when we make estimates about uncertain events. And the recallability trap leads us to give undue weight to recent, dramatic events. The best way to avoid all the traps is awareness--forewarned is forearmed. But executives can also take other simple steps to protect themselves and their organizations from the various kinds of mental lapses. The authors show how to take action to ensure that important business decisions are sound and reliable.

Using reliability analysis to support decision making\\ud in phased mission systems

OpenAIRE

Zhang, Yang; Prescott, Darren

2017-01-01

Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary Decision Diagrams (BDDs) offer fast, accurate reliability analysis that cou...

Cognitive Reflection, Decision Biases, and Response Times

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Carlos Alos-Ferrer

2016-09-01

Full Text Available We present novel evidence on decision times and personality traits in standard questions from the decision-making literature where responses are relatively slow (medians around half a minute or above. To this end, we measured decision times in a number of incentivized, framed items (decisions from description including the Cognitive Reflection Test, two additional questions following the same logic, and a number of classic questions used to study decision biases in probability judgments (base-rate neglect, the conjunction fallacy, and the ratio bias. All questions create a conflict between an intuitive process and more deliberative thinking. For each item, we then created a non-conflict version by either making the intuitive impulse correct (resulting in an alignment question, shutting it down (creating a neutral question, or making it dominant (creating a heuristic question. For CRT questions, the differences in decision times are as predicted by dual-process theories, with alignment and heuristic variants leading to faster responses and neutral questions to slower responses than the original, conflict questions. For decision biases (where responses are slower, evidence is mixed. To explore the possible influence of personality factors on both choices and decision times, we used standard personality scales including the Rational-Experiential Inventory and the Big Five, and used the mas controls in regression analysis.

The gold analyser: a tool for valuation and a means for improved mining decisions

International Nuclear Information System (INIS)

Stewart, J.M.; Nami, M.

1986-01-01

The erratic values of gold grade in Witwatersrand placer deposits necessitates the collection of large numbers of samples for accurate valuation and ore reserve estimation. Owing to manpower requirements current sampling techniques do not allow for the collection of sufficiently large numbers of samples. A portable gold analyser, which is at an advanced stage of development, is expected to alleviate this problem. It is a lightweight instrument, intended for one-man operation, and is based on energy dispersive X-ray fluorescence principles for determining gold and other mineral concentrations. The instrument is designed for in situ face scanning operations and provides a direct readout and internal storage of the measured gold concentration. The immediate availability of an estimate of gold grade should significantly improve the quality of short-term panel-scale mining decisions. Data are presented to show the improved precision in valuation using the gold analyser instead of conventional chip sampling

FUZZY DECISION MAKING MODEL FOR BYZANTINE AGREEMENT

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S. MURUGAN

2014-04-01

Full Text Available Byzantine fault tolerance is of high importance in the distributed computing environment where malicious attacks and software errors are common. A Byzantine process sends arbitrary messages to every other process. An effective fuzzy decision making approach is proposed to eliminate the Byzantine behaviour of the services in the distributed environment. It is proposed to derive a fuzzy decision set in which the alternatives are ranked with grade of membership and based on that an appropriate decision can be arrived on the messages sent by the different services. A balanced decision is to be taken from the messages received across the services. To accomplish this, Hurwicz criterion is used to balance the optimistic and pessimistic views of the decision makers on different services. Grades of membership for the services are assessed using the non-functional Quality of Service parameters and have been estimated using fuzzy entropy measure which logically ranks the participant services. This approach for decision making is tested by varying the number of processes, varying the number of faulty services, varying the message values sent to different services and considering the variation in the views of the decision makers about the services. The experimental result shows that the decision reached is an enhanced one and in case of conflict, the proposed approach provides a concrete result, whereas decision taken using the Lamport’s algorithm is an arbitrary one.

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

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Lingjie Sun

2016-08-01

Full Text Available The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM, due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP and Dempster–Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster–Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment.

A strategic decision support system for logistics and supply chain ...

Indian Academy of Sciences (India)

T Biswas

strategic decision support model in achieving better utilization of network and resources to fulfil the ... demand is demonstrated using illustrative scenarios inspired from the real case of a logistics company. ... performance, because they determine the supply chain ..... to accurately measure the desirability of the features.

Individual differences in attention influence perceptual decision making.

Science.gov (United States)

Nunez, Michael D; Srinivasan, Ramesh; Vandekerckhove, Joachim

2015-01-01

Sequential sampling decision-making models have been successful in accounting for reaction time (RT) and accuracy data in two-alternative forced choice tasks. These models have been used to describe the behavior of populations of participants, and explanatory structures have been proposed to account for between individual variability in model parameters. In this study we show that individual differences in behavior from a novel perceptual decision making task can be attributed to (1) differences in evidence accumulation rates, (2) differences in variability of evidence accumulation within trials, and (3) differences in non-decision times across individuals. Using electroencephalography (EEG), we demonstrate that these differences in cognitive variables, in turn, can be explained by attentional differences as measured by phase-locking of steady-state visual evoked potential (SSVEP) responses to the signal and noise components of the visual stimulus. Parameters of a cognitive model (a diffusion model) were obtained from accuracy and RT distributions and related to phase-locking indices (PLIs) of SSVEPs with a single step in a hierarchical Bayesian framework. Participants who were able to suppress the SSVEP response to visual noise in high frequency bands were able to accumulate correct evidence faster and had shorter non-decision times (preprocessing or motor response times), leading to more accurate responses and faster response times. We show that the combination of cognitive modeling and neural data in a hierarchical Bayesian framework relates physiological processes to the cognitive processes of participants, and that a model with a new (out-of-sample) participant's neural data can predict that participant's behavior more accurately than models without physiological data.

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance

Science.gov (United States)

Gaoua, Nadia; de Oliveira, Rita F.; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee’s responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees’ decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies. PMID:28912742

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance

Directory of Open Access Journals (Sweden)

Nadia Gaoua

2017-08-01

Full Text Available Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee’s responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees’ decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies.

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance.

Science.gov (United States)

Gaoua, Nadia; de Oliveira, Rita F; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee's responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees' decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies.

How Accurate Appraisal of Behavioral Costs and Benefits Guides Adaptive Pain Coping

Directory of Open Access Journals (Sweden)

Wiebke Gandhi

2017-06-01

Full Text Available Coping with pain is a complex phenomenon encompassing a variety of behavioral responses and a large network of underlying neural circuits. Whether pain coping is adaptive or maladaptive depends on the type of pain (e.g., escapable or inescapable, personal factors (e.g., individual experiences with coping strategies in the past, and situational circumstances. Keeping these factors in mind, costs and benefits of different strategies have to be appraised and will guide behavioral decisions in the face of pain. In this review we present pain coping as an unconscious decision-making process during which accurately evaluated costs and benefits lead to adaptive pain coping behavior. We emphasize the importance of passive coping as an adaptive strategy when dealing with ongoing pain and thus go beyond the common view of passivity as a default state of helplessness. In combination with passive pain coping, we highlight the role of the reward system in reestablishing affective homeostasis and discuss existing evidence on a behavioral and neural level. We further present neural circuits involved in the decision-making process of pain coping when circumstances are ambiguous and, therefore, costs and benefits are difficult to anticipate. Finally, we address the wider implications of this topic by discussing its relevance for chronic pain patients.

The criteria for the decision of transrectal US-guided prostate biopsy: Can we reduce the number of unnecessary biopsies?

International Nuclear Information System (INIS)

Cho, Joon Hyung; Cho, Jae Ho; Ahn, Jay Hong; Chang, Jay Chun

2001-01-01

To establish the criteria which can safely reduce the number of unnecessary biopsies by comparing the transrectal ultrasonography (TRUS) findings, serum prostate-specific antigen (PSA), and prostate specific antigen density (PSAD) in the decision of criteria for the prostatic biopsy using TRUS. Two hundred and twenty patients underwent TRUS- guided prostate biopsy due to elevated PSA and/or focal nodule on TRUS were included. Sixty five (27.5%) patients were confirmed as prostate cancer, and remained 155 (70.5%) patients were reported as benign diseases including benign prostate hyperplasia. The sensitivity, specificity and accuracy of TRUS, PSA and PSAD were evaluated and the single criterion or the combination of the criteria which can safely reduce the unnecessary biopsies without missing prostatic cancer were investigated. The sensitivity, specificity and accuracy of TRUS, PSA (cut-off value, 4 ng/ml) and PSAD (cut-off level, 0.2 ng/ml/cm 3 ) were 78.5%/95.4%/95.4%/27.8%/51.6%/64/5%, 42.7%/64.5%/73.6%, respectively. PSAD cut-off level 0.2 ng/ml/cm 3 was the most excellent single criterion for the decision of prostatic biopsy and the number of unnecessary biopsies was 100 cases. But 3 cases of prostatic cancer which the PSAD level was below 0.2 ng/ml/cm 3 were included and in all these 3 cases, a focal nodule was detected on TRUS. Therefore, we applied these two criteria at once and the biopsies of 30 cases (13.6%) are unnecessary. With the single criterion, we could not obtain the satisfactory results but by the combinations of criteria (TRUS and PSAD), 30 (13.6%) cases are unnecessary biopsies without missing cancer. We think that the short term follow-up may be a substitute for the immediate when nodular lesion is suspicious on TRUS and serum PSAD level is below 0.2 ng/ml/cm 3 .

Dynamics of individual perceptual decisions

Science.gov (United States)

Clark, Torin K.; Lu, Yue M.; Karmali, Faisal

2015-01-01

Perceptual decision making is fundamental to a broad range of fields including neurophysiology, economics, medicine, advertising, law, etc. Although recent findings have yielded major advances in our understanding of perceptual decision making, decision making as a function of time and frequency (i.e., decision-making dynamics) is not well understood. To limit the review length, we focus most of this review on human findings. Animal findings, which are extensively reviewed elsewhere, are included when beneficial or necessary. We attempt to put these various findings and data sets, which can appear to be unrelated in the absence of a formal dynamic analysis, into context using published models. Specifically, by adding appropriate dynamic mechanisms (e.g., high-pass filters) to existing models, it appears that a number of otherwise seemingly disparate findings from the literature might be explained. One hypothesis that arises through this dynamic analysis is that decision making includes phasic (high pass) neural mechanisms, an evidence accumulator and/or some sort of midtrial decision-making mechanism (e.g., peak detector and/or decision boundary). PMID:26467513

Current status of accurate prognostic awareness in advanced/terminally ill cancer patients: Systematic review and meta-regression analysis.

Science.gov (United States)

Chen, Chen Hsiu; Kuo, Su Ching; Tang, Siew Tzuh

2017-05-01

No systematic meta-analysis is available on the prevalence of cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. To examine the prevalence of advanced/terminal cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. Systematic review and meta-analysis. MEDLINE, Embase, The Cochrane Library, CINAHL, and PsycINFO were systematically searched on accurate prognostic awareness in adult patients with advanced/terminal cancer (1990-2014). Pooled prevalences were calculated for accurate prognostic awareness by a random-effects model. Differences in weighted estimates of accurate prognostic awareness were compared by meta-regression. In total, 34 articles were retrieved for systematic review and meta-analysis. At best, only about half of advanced/terminal cancer patients accurately understood their prognosis (49.1%; 95% confidence interval: 42.7%-55.5%; range: 5.4%-85.7%). Accurate prognostic awareness was independent of service received and publication year, but highest in Australia, followed by East Asia, North America, and southern Europe and the United Kingdom (67.7%, 60.7%, 52.8%, and 36.0%, respectively; p = 0.019). Accurate prognostic awareness was higher by clinician assessment than by patient report (63.2% vs 44.5%, p cancer patients accurately understood their prognosis, with significant variations by region and assessment method. Healthcare professionals should thoroughly assess advanced/terminal cancer patients' preferences for prognostic information and engage them in prognostic discussion early in the cancer trajectory, thus facilitating their accurate prognostic awareness and the quality of end-of-life care decision-making.

Development of shared decision-making resources to help inform difficult healthcare decisions: An example focused on dysvascular partial foot and transtibial amputations.

Science.gov (United States)

Quigley, Matthew; Dillon, Michael P; Fatone, Stefania

2018-02-01

Shared decision making is a consultative process designed to encourage patient participation in decision making by providing accurate information about the treatment options and supporting deliberation with the clinicians about treatment options. The process can be supported by resources such as decision aids and discussion guides designed to inform and facilitate often difficult conversations. As this process increases in use, there is opportunity to raise awareness of shared decision making and the international standards used to guide the development of quality resources for use in areas of prosthetic/orthotic care. To describe the process used to develop shared decision-making resources, using an illustrative example focused on decisions about the level of dysvascular partial foot amputation or transtibial amputation. Development process: The International Patient Decision Aid Standards were used to guide the development of the decision aid and discussion guide focused on decisions about the level of dysvascular partial foot amputation or transtibial amputation. Examples from these shared decision-making resources help illuminate the stages of development including scoping and design, research synthesis, iterative development of a prototype, and preliminary testing with patients and clinicians not involved in the development process. Lessons learnt through the process, such as using the International Patient Decision Aid Standards checklist and development guidelines, may help inform others wanting to develop similar shared decision-making resources given the applicability of shared decision making to many areas of prosthetic-/orthotic-related practice. Clinical relevance Shared decision making is a process designed to guide conversations that help patients make an informed decision about their healthcare. Raising awareness of shared decision making and the international standards for development of high-quality decision aids and discussion guides is important

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions.

Science.gov (United States)

Nantha, Yogarabindranath Swarna

2017-11-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.

Effects of Information Visualization on Older Adults' Decision-Making Performance in a Medicare Plan Selection Task: A Comparative Usability Study.

Science.gov (United States)

Price, Margaux M; Crumley-Branyon, Jessica J; Leidheiser, William R; Pak, Richard

2016-06-01

Technology gains have improved tools for evaluating complex tasks by providing environmental supports (ES) that increase ease of use and improve performance outcomes through the use of information visualizations (info-vis). Complex info-vis emphasize the need to understand individual differences in abilities of target users, the key cognitive abilities needed to execute a decision task, and the graphical elements that can serve as the most effective ES. Older adults may be one such target user group that would benefit from increased ES to mitigate specific declines in cognitive abilities. For example, choosing a prescription drug plan is a necessary and complex task that can impact quality of life if the wrong choice is made. The decision to enroll in one plan over another can involve comparing over 15 plans across many categories. Within this context, the large amount of complex information and reduced working memory capacity puts older adults' decision making at a disadvantage. An intentionally designed ES, such as an info-vis that reduces working memory demand, may assist older adults in making the most effective decision among many options. The objective of this study is to examine whether the use of an info-vis can lower working memory demands and positively affect complex decision-making performance of older adults in the context of choosing a Medicare prescription drug plan. Participants performed a computerized decision-making task in the context of finding the best health care plan. Data included quantitative decision-making performance indicators and surveys examining previous history with purchasing insurance. Participants used a colored info-vis ES or a table (no ES) to perform the decision task. Task difficulty was manipulated by increasing the number of selection criteria used to make an accurate decision. A repeated measures analysis was performed to examine differences between the two table designs. Twenty-three older adults between the ages of 66

Bi-Criteria Optimization of Decision Trees with Applications to Data Analysis

KAUST Repository

Chikalov, Igor

2017-10-19

This paper is devoted to the study of bi-criteria optimization problems for decision trees. We consider different cost functions such as depth, average depth, and number of nodes. We design algorithms that allow us to construct the set of Pareto optimal points (POPs) for a given decision table and the corresponding bi-criteria optimization problem. These algorithms are suitable for investigation of medium-sized decision tables. We discuss three examples of applications of the created tools: the study of relationships among depth, average depth and number of nodes for decision trees for corner point detection (such trees are used in computer vision for object tracking), study of systems of decision rules derived from decision trees, and comparison of different greedy algorithms for decision tree construction as single- and bi-criteria optimization algorithms.

Zero-block mode decision algorithm for H.264/AVC.

Science.gov (United States)

Lee, Yu-Ming; Lin, Yinyi

2009-03-01

In the previous paper , we proposed a zero-block intermode decision algorithm for H.264 video coding based upon the number of zero-blocks of 4 x 4 DCT coefficients between the current macroblock and the co-located macroblock. The proposed algorithm can achieve significant improvement in computation, but the computation performance is limited for high bit-rate coding. To improve computation efficiency, in this paper, we suggest an enhanced zero-block decision algorithm, which uses an early zero-block detection method to compute the number of zero-blocks instead of direct DCT and quantization (DCT/Q) calculation and incorporates two adequate decision methods into semi-stationary and nonstationary regions of a video sequence. In addition, the zero-block decision algorithm is also applied to the intramode prediction in the P frame. The enhanced zero-block decision algorithm brings out a reduction of average 27% of total encoding time compared to the zero-block decision algorithm.

On avoiding framing effects in experienced decision makers.

Science.gov (United States)

Garcia-Retamero, Rocio; Dhami, Mandeep K

2013-01-01

The present study aimed to (a) demonstrate the effect of positive-negative framing on experienced criminal justice decision makers, (b) examine the debiasing effect of visually structured risk messages, and (c) investigate whether risk perceptions mediate the debiasing effect of visual aids on decision making. In two phases, 60 senior police officers estimated the accuracy of a counterterrorism technique in identifying whether a known terror suspect poses an imminent danger and decided whether they would recommend the technique to policy makers. Officers also rated their confidence in this recommendation. When information about the effectiveness of the counterterrorism technique was presented in a numerical format, officers' perceptions of accuracy and recommendation decisions were susceptible to the framing effect: The technique was perceived to be more accurate and was more likely to be recommended when its effectiveness was presented in a positive than in a negative frame. However, when the information was represented visually using icon arrays, there were no such framing effects. Finally, perceptions of accuracy mediated the debiasing effect of visual aids on recommendation decisions. We offer potential explanations for the debiasing effect of visual aids and implications for communicating risk to experienced, professional decision makers.

Maximizing Consensus in Portfolio Selection in Multicriteria Group Decision Making

NARCIS (Netherlands)

Michael, Emmerich T. M.; Deutz, A.H.; Li, L.; Asep, Maulana A.; Yevseyeva, I.

2016-01-01

This paper deals with a scenario of decision making where a moderator selects a (sub)set (aka portfolio) of decision alternatives from a larger set. The larger the number of decision makers who agree on a solution in the portfolio the more successful the moderator is. We assume that decision makers

MULTICRITERIA DECISION-MAKING

NARCIS (Netherlands)

HENDRIKS, MMWB; DEBOER, JH; SMILDE, AK; DOORNBOS, DA

1992-01-01

Interest is growing in multicriteria decision making (MCDM) techniques and a large number of these techniques are now available. The purpose of this tutorial is to give a theoretical description of some of the MCDM techniques. Besides this we will give an overview of the differences and similarities

Accurate shear measurement with faint sources

International Nuclear Information System (INIS)

Zhang, Jun; Foucaud, Sebastien; Luo, Wentao

2015-01-01

For cosmic shear to become an accurate cosmological probe, systematic errors in the shear measurement method must be unambiguously identified and corrected for. Previous work of this series has demonstrated that cosmic shears can be measured accurately in Fourier space in the presence of background noise and finite pixel size, without assumptions on the morphologies of galaxy and PSF. The remaining major source of error is source Poisson noise, due to the finiteness of source photon number. This problem is particularly important for faint galaxies in space-based weak lensing measurements, and for ground-based images of short exposure times. In this work, we propose a simple and rigorous way of removing the shear bias from the source Poisson noise. Our noise treatment can be generalized for images made of multiple exposures through MultiDrizzle. This is demonstrated with the SDSS and COSMOS/ACS data. With a large ensemble of mock galaxy images of unrestricted morphologies, we show that our shear measurement method can achieve sub-percent level accuracy even for images of signal-to-noise ratio less than 5 in general, making it the most promising technique for cosmic shear measurement in the ongoing and upcoming large scale galaxy surveys

Battery Management Systems: Accurate State-of-Charge Indication for Battery-Powered Applications

NARCIS (Netherlands)

Pop, V.; Bergveld, H.J.; Danilov, D.; Regtien, Paulus P.L.; Notten, P.H.L.

2008-01-01

Battery Management Systems – Universal State-of-Charge indication for portable applications describes the field of State-of-Charge (SoC) indication for rechargeable batteries. With the emergence of battery-powered devices with an increasing number of power-hungry features, accurately estimating the

Managerial Decision Making in Traffic

Directory of Open Access Journals (Sweden)

Teodor Perić

2003-11-01

Full Text Available Decision-making is defined as a selection of a certain actionamong several alternatives. It is the essence of planning, asin the managerial sense there is no plan until a decision of engagementof resources, reputation and direction of activities ismade. Decision-making is, in fact, only a step in planning, evenwhen it is performed quickly and without special consideration.It is what we all experience every day. It is one of the most fascinatingbiological activities and the subject of frightening implicationsfor the whole human race. Since various techniques improvethe system and the quality of managerial decision-making,they are classified into three assumptions: risk analysis, decision-making trees, and the theory of revealed preference. Allof these are based on the interaction of a certain number of importantvariables out of which many contain the elements ofuncertainty, but maybe also high level of probability.

Application of decision tree algorithm for identification of rock forming minerals using energy dispersive spectrometry

Science.gov (United States)

Akkaş, Efe; Çubukçu, H. Evren; Artuner, Harun

2014-05-01

Rapid and automated mineral identification is compulsory in certain applications concerning natural rocks. Among all microscopic and spectrometric methods, energy dispersive X-ray spectrometers (EDS) integrated with scanning electron microscopes produce rapid information with reliable chemical data. Although obtaining elemental data with EDS analyses is fast and easy by the help of improving technology, it is rather challenging to perform accurate and rapid identification considering the large quantity of minerals in a rock sample with varying dimensions ranging between nanometer to centimeter. Furthermore, the physical properties of the specimen (roughness, thickness, electrical conductivity, position in the instrument etc.) and the incident electron beam (accelerating voltage, beam current, spot size etc.) control the produced characteristic X-ray, which in turn affect the elemental analyses. In order to minimize the effects of these physical constraints and develop an automated mineral identification system, a rule induction paradigm has been applied to energy dispersive spectral data. Decision tree classifiers divide training data sets into subclasses using generated rules or decisions and thereby it produces classification or recognition associated with these data sets. A number of thinsections prepared from rock samples with suitable mineralogy have been investigated and a preliminary 12 distinct mineral groups (olivine, orthopyroxene, clinopyroxene, apatite, amphibole, plagioclase, K- feldspar, zircon, magnetite, titanomagnetite, biotite, quartz), comprised mostly of silicates and oxides, have been selected. Energy dispersive spectral data for each group, consisting of 240 reference and 200 test analyses, have been acquired under various, non-standard, physical and electrical conditions. The reference X-Ray data have been used to assign the spectral distribution of elements to the specified mineral groups. Consequently, the test data have been analyzed using

Decision aids for multiple-decision disease management as affected by weather input errors.

Science.gov (United States)

Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D

2011-06-01

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

A tool for study of optimal decision trees

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2010-01-01

The paper describes a tool which allows us for relatively small decision tables to make consecutive optimization of decision trees relative to various complexity measures such as number of nodes, average depth, and depth, and to find parameters

Decision trees with minimum average depth for sorting eight elements

KAUST Repository

AbouEisha, Hassan M.

2015-11-19

We prove that the minimum average depth of a decision tree for sorting 8 pairwise different elements is equal to 620160/8!. We show also that each decision tree for sorting 8 elements, which has minimum average depth (the number of such trees is approximately equal to 8.548×10^326365), has also minimum depth. Both problems were considered by Knuth (1998). To obtain these results, we use tools based on extensions of dynamic programming which allow us to make sequential optimization of decision trees relative to depth and average depth, and to count the number of decision trees with minimum average depth.

DNA barcode data accurately assign higher spider taxa

Directory of Open Access Journals (Sweden)

Jonathan A. Coddington

2016-07-01

Full Text Available The use of unique DNA sequences as a method for taxonomic identification is no longer fundamentally controversial, even though debate continues on the best markers, methods, and technology to use. Although both existing databanks such as GenBank and BOLD, as well as reference taxonomies, are imperfect, in best case scenarios “barcodes” (whether single or multiple, organelle or nuclear, loci clearly are an increasingly fast and inexpensive method of identification, especially as compared to manual identification of unknowns by increasingly rare expert taxonomists. Because most species on Earth are undescribed, a complete reference database at the species level is impractical in the near term. The question therefore arises whether unidentified species can, using DNA barcodes, be accurately assigned to more inclusive groups such as genera and families—taxonomic ranks of putatively monophyletic groups for which the global inventory is more complete and stable. We used a carefully chosen test library of CO1 sequences from 49 families, 313 genera, and 816 species of spiders to assess the accuracy of genus and family-level assignment. We used BLAST queries of each sequence against the entire library and got the top ten hits. The percent sequence identity was reported from these hits (PIdent, range 75–100%. Accurate assignment of higher taxa (PIdent above which errors totaled less than 5% occurred for genera at PIdent values >95 and families at PIdent values ≥ 91, suggesting these as heuristic thresholds for accurate generic and familial identifications in spiders. Accuracy of identification increases with numbers of species/genus and genera/family in the library; above five genera per family and fifteen species per genus all higher taxon assignments were correct. We propose that using percent sequence identity between conventional barcode sequences may be a feasible and reasonably accurate method to identify animals to family/genus. However

Decision Fusion System for Bolted Joint Monitoring

Directory of Open Access Journals (Sweden)

Dong Liang

2015-01-01

Full Text Available Bolted joint is widely used in mechanical and architectural structures, such as machine tools, industrial robots, transport machines, power plants, aviation stiffened plate, bridges, and steel towers. The bolt loosening induced by flight load and environment factor can cause joint failure leading to a disastrous accident. Hence, structural health monitoring is critical for the bolted joint detection. In order to realize a real-time and convenient monitoring and satisfy the requirement of advanced maintenance of the structure, this paper proposes an intelligent bolted joint failure monitoring approach using a developed decision fusion system integrated with Lamb wave propagation based actuator-sensor monitoring method. Firstly, the basic knowledge of decision fusion and classifier selection techniques is briefly introduced. Then, a developed decision fusion system is presented. Finally, three fusion algorithms, which consist of majority voting, Bayesian belief, and multiagent method, are adopted for comparison in a real-world monitoring experiment for the large aviation aluminum plate. Based on the results shown in the experiment, a big potential in real-time application is presented that the method can accurately and rapidly identify the bolt loosening by analyzing the acquired strain signal using proposed decision fusion system.

From quantity to number : Studies on magnitude processing

NARCIS (Netherlands)

Gebuis, T.|info:eu-repo/dai/nl/304836362

2009-01-01

The ability to work with the symbolic number system, the Arabic numbers, enables humans to perform more complex and accurate calculations than the non-symbolic numerosity system (e.g. arrays of dots). The application of this symbolic system has turned out to be so useful that we have a hard time

Distinguishing highly confident accurate and inaccurate memory: insights about relevant and irrelevant influences on memory confidence.

Science.gov (United States)

Chua, Elizabeth F; Hannula, Deborah E; Ranganath, Charan

2012-01-01

It is generally believed that accuracy and confidence in one's memory are related, but there are many instances when they diverge. Accordingly it is important to disentangle the factors that contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence.

Tactical and strategic decision-making aids for nuclear power plant emergency response

International Nuclear Information System (INIS)

Cain, D.G.

1987-01-01

This paper examines the prospective role of computer-based decision aids for nuclear power plant emergency response. The role of these systems is subordinate to human activities, but in a complementary manner these systems process decision logic more accurately and foster a more thorough understanding of emergency situations than might other wise be possible. Within this context two decision support systems being developed are discussed. Both of these systems utilize technology derived from artificial intelligence, focussing on two different facets of emergency response. An automated emergency operating procedures (EOP) tracking expert system is described as a tactical aid for control room operator response. A reactor emergency action level monitor (REALM) expert system is proposed as a strategic decision aid for site emergency response. The discrimination between tactical and strategic decision-making is an intrinsic part of this examination

Accurate Bit Error Rate Calculation for Asynchronous Chaos-Based DS-CDMA over Multipath Channel

Science.gov (United States)

Kaddoum, Georges; Roviras, Daniel; Chargé, Pascal; Fournier-Prunaret, Daniele

2009-12-01

An accurate approach to compute the bit error rate expression for multiuser chaosbased DS-CDMA system is presented in this paper. For more realistic communication system a slow fading multipath channel is considered. A simple RAKE receiver structure is considered. Based on the bit energy distribution, this approach compared to others computation methods existing in literature gives accurate results with low computation charge. Perfect estimation of the channel coefficients with the associated delays and chaos synchronization is assumed. The bit error rate is derived in terms of the bit energy distribution, the number of paths, the noise variance, and the number of users. Results are illustrated by theoretical calculations and numerical simulations which point out the accuracy of our approach.

Quadruplex MAPH: improvement of throughput in high-resolution copy number screening.

Science.gov (United States)

Tyson, Jess; Majerus, Tamsin Mo; Walker, Susan; Armour, John Al

2009-09-28

Copy number variation (CNV) in the human genome is recognised as a widespread and important source of human genetic variation. Now the challenge is to screen for these CNVs at high resolution in a reliable, accurate and cost-effective way. Multiplex Amplifiable Probe Hybridisation (MAPH) is a sensitive, high-resolution technology appropriate for screening for CNVs in a defined region, for a targeted population. We have developed MAPH to a highly multiplexed format ("QuadMAPH") that allows the user a four-fold increase in the number of loci tested simultaneously. We have used this method to analyse a genomic region of 210 kb, including the MSH2 gene and 120 kb of flanking DNA. We show that the QuadMAPH probes report copy number with equivalent accuracy to simplex MAPH, reliably demonstrating diploid copy number in control samples and accurately detecting deletions in Hereditary Non-Polyposis Colorectal Cancer (HNPCC) samples. QuadMAPH is an accurate, high-resolution method that allows targeted screening of large numbers of subjects without the expense of genome-wide approaches. Whilst we have applied this technique to a region of the human genome, it is equally applicable to the genomes of other organisms.

Real-time multiparameter pulse processing with decision tables

International Nuclear Information System (INIS)

Hull, K.; Griffin, H.

1986-01-01

Decision tables offer several advantages over other real-time multiparameter, data processing techniques. These include very high collection rates, minimum number of computer instructions, rates independent of the number of conditions applied per parameter, ease of adding or removing conditions during a session, and simplicity of implementation. Decisions table processing is important in multiparameter nuclear spectroscopy, coincidence experiments, multiparameter pulse processing (HgI 2 resolution enhancement, pulse discrimination, timing spectroscopy), and other applications can be easily implemented. (orig.)

Measurement methods and accuracy in copy number variation: failure to replicate associations of beta-defensin copy number with Crohn's disease

Science.gov (United States)

Aldhous, Marian C.; Abu Bakar, Suhaili; Prescott, Natalie J.; Palla, Raquel; Soo, Kimberley; Mansfield, John C.; Mathew, Christopher G.; Satsangi, Jack; Armour, John A.L.

2010-01-01

The copy number variation in beta-defensin genes on human chromosome 8 has been proposed to underlie susceptibility to inflammatory disorders, but presents considerable challenges for accurate typing on the scale required for adequately powered case–control studies. In this work, we have used accurate methods of copy number typing based on the paralogue ratio test (PRT) to assess beta-defensin copy number in more than 1500 UK DNA samples including more than 1000 cases of Crohn's disease. A subset of 625 samples was typed using both PRT-based methods and standard real-time PCR methods, from which direct comparisons highlight potentially serious shortcomings of a real-time PCR assay for typing this variant. Comparing our PRT-based results with two previous studies based only on real-time PCR, we find no evidence to support the reported association of Crohn's disease with either low or high beta-defensin copy number; furthermore, it is noteworthy that there are disagreements between different studies on the observed frequency distribution of copy number states among European controls. We suggest safeguards to be adopted in assessing and reporting the accuracy of copy number measurement, with particular emphasis on integer clustering of results, to avoid reporting of spurious associations in future case–control studies. PMID:20858604

Measurement methods and accuracy in copy number variation: failure to replicate associations of beta-defensin copy number with Crohn's disease.

Science.gov (United States)

Aldhous, Marian C; Abu Bakar, Suhaili; Prescott, Natalie J; Palla, Raquel; Soo, Kimberley; Mansfield, John C; Mathew, Christopher G; Satsangi, Jack; Armour, John A L

2010-12-15

The copy number variation in beta-defensin genes on human chromosome 8 has been proposed to underlie susceptibility to inflammatory disorders, but presents considerable challenges for accurate typing on the scale required for adequately powered case-control studies. In this work, we have used accurate methods of copy number typing based on the paralogue ratio test (PRT) to assess beta-defensin copy number in more than 1500 UK DNA samples including more than 1000 cases of Crohn's disease. A subset of 625 samples was typed using both PRT-based methods and standard real-time PCR methods, from which direct comparisons highlight potentially serious shortcomings of a real-time PCR assay for typing this variant. Comparing our PRT-based results with two previous studies based only on real-time PCR, we find no evidence to support the reported association of Crohn's disease with either low or high beta-defensin copy number; furthermore, it is noteworthy that there are disagreements between different studies on the observed frequency distribution of copy number states among European controls. We suggest safeguards to be adopted in assessing and reporting the accuracy of copy number measurement, with particular emphasis on integer clustering of results, to avoid reporting of spurious associations in future case-control studies.

Fast and accurate algorithm for the computation of complex linear canonical transforms.

Science.gov (United States)

Koç, Aykut; Ozaktas, Haldun M; Hesselink, Lambertus

2010-09-01

A fast and accurate algorithm is developed for the numerical computation of the family of complex linear canonical transforms (CLCTs), which represent the input-output relationship of complex quadratic-phase systems. Allowing the linear canonical transform parameters to be complex numbers makes it possible to represent paraxial optical systems that involve complex parameters. These include lossy systems such as Gaussian apertures, Gaussian ducts, or complex graded-index media, as well as lossless thin lenses and sections of free space and any arbitrary combinations of them. Complex-ordered fractional Fourier transforms (CFRTs) are a special case of CLCTs, and therefore a fast and accurate algorithm to compute CFRTs is included as a special case of the presented algorithm. The algorithm is based on decomposition of an arbitrary CLCT matrix into real and complex chirp multiplications and Fourier transforms. The samples of the output are obtained from the samples of the input in approximately N log N time, where N is the number of input samples. A space-bandwidth product tracking formalism is developed to ensure that the number of samples is information-theoretically sufficient to reconstruct the continuous transform, but not unnecessarily redundant.

Evolution of quantum-like modeling in decision making processes

Energy Technology Data Exchange (ETDEWEB)

Khrennikova, Polina [School of Management, University of Leicester, University Road Leicester LE1 7RH (United Kingdom)

2012-12-18

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schroedinger equation to describe the evolution of people's mental states. A shortcoming of Schroedinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Evolution of quantum-like modeling in decision making processes

Science.gov (United States)

Khrennikova, Polina

2012-12-01

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Evolution of quantum-like modeling in decision making processes

International Nuclear Information System (INIS)

Khrennikova, Polina

2012-01-01

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Multi-Attribute Decision-Making Method with Three-Parameter Interval Grey Number%三参数区间灰数的多属性灰靶决策方法

Institute of Scientific and Technical Information of China (English)

朱山丽; 肖美丹; 李晔

2016-01-01

The grey target decision-making model is proposed based on three-parameter interval grey number for multi-attribute decision-making problems with uncertain decision information. Firstly,a new distance measure of three-parameter interval grey number is given based on the importance of the“center of gravity”to determine the positive and negative clouts. The kernel and ranking method of three-parameter interval grey number is defined , and a new comprehensive off-target distance is proposed,which integrates the distance between different attributes to the positive and negative clouts. Attribute weights are determined by comprehensive off-target target minimum distance and grey entropy maximization. An example is presented to illustrate the usefulness and effectiveness of the proposed method.%针对决策信息不确定的多属性决策问题，提出了基于三参数区间灰数的灰靶决策方法。首先基于“重心”点的重要作用给出了一种新型的三参数区间灰数的距离测度，定义了三参数区间灰数的核和排序方法，由此确定决策方案的正负靶心，利用正负靶心距的空间投影距离求得综合靶心距，由综合靶心距最小化和灰熵最大化确定属性的权重，进而对方案进行排序。最后以一个实例说明决策模型的合理性和实用性。

Expert Decision-Making in Naturalistic Environments: A Summary of Research

Science.gov (United States)

2005-03-01

a number of descriptive decision theories arose (Plous, 1993). One of these is the rational choice model of decision - making (Janis & Mann, 1977...possible association between time pressure and increased levels of emotion . To date, the role played by emotion in decision - making has not been given... rational choice model seems to describe some decision events and Janis and Mann (1977) have highlighted emotion as a potential influence on decision

On the calculation of Lorenz numbers for complex thermoelectric materials

Science.gov (United States)

Wang, Xufeng; Askarpour, Vahid; Maassen, Jesse; Lundstrom, Mark

2018-02-01

A first-principles informed approach to the calculation of Lorenz numbers for complex thermoelectric materials is presented and discussed. Example calculations illustrate the importance of using accurate band structures and energy-dependent scattering times. Results obtained by assuming that the scattering rate follows the density-of-states show that in the non-degenerate limit, Lorenz numbers below the commonly assumed lower limit of 2 (kB /q ) 2 can occur. The physical cause of low Lorenz numbers is explained by the shape of the transport distribution. The numerical and physical issues that need to be addressed in order to produce accurate calculations of the Lorenz number are identified. The results of this study provide a general method that should contribute to the interpretation of measurements of total thermal conductivity and to the search for materials with low Lorenz numbers, which may provide improved thermoelectric figures of merit, z T .

[Participation of women in decision-making in Senegal. The numbers that speak].

Science.gov (United States)

Talla, R

1999-12-01

The most recent population survey conducted in Senegal in 1988 found that women comprise 52% of the country¿s total population and that rural women make up 75% of the active female population. The female population is very young overall since 58% of women are under 20 years old. However, women¿s numerical advantage is inversely proportional to their level of representation in decision-making situations. Senegal¿s government in power since 1998 has only 5 women among the 31 ministers, and there were only 3 female ministers in the preceding body of government leaders. This numerical underrepresentation of women is also qualitative in nature, with the female ministers holding relatively less powerful governmental positions compared to the men. Only 19 of the 140 deputies elected to the National Assembly in 1998 were women and no woman is president of a parliamentary body. Women have a greater presence at the magisterial and legislative level, but they are less present in the public sector where they comprise only 4% of the 68,000 state agents. Women overwhelmingly hold teacher and secretarial posts, while men dominate local communities. Among the 470 elected, regional councilors elected in November 1998, only 61 are women. Additional statistics and discussion are presented upon the role of women in Senegalese society, as well as upon their capacity to influence important decisions both in the public sector and at home.

Computing with Words in Decision support Systems: An overview on Models and Applications

Directory of Open Access Journals (Sweden)

Luis Martinez

2010-10-01

Full Text Available Decision making is inherent to mankind, as human beings daily face situations in which they should choose among different alternatives by means of reasoning and mental processes. Many of these decision problems are under uncertain environments with vague and imprecise information. This type of information is usually modelled by linguistic information because of the common use of language by the experts involved in the given decision situations, originating linguistic decision making. The use of linguistic information in decision making demands processes of Computing with Words to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish such processes in an accurate and interpretable way. The good performance of linguistic computing dealing with uncertainty has caused a spread use of it in different types of decision based applications. This paper overviews the more significant and extended linguistic computing models due to its key role in linguistic decision making and a wide range of the most recent applications of linguistic decision support models.

What mental process favours quality decision-making in young soccer players?

Directory of Open Access Journals (Sweden)

Grégory Hallé Petiot

2017-08-01

Full Text Available Abstract Aim The aim of this research is to identify the mechanisms that lead soccer players to make quality tactical decisions, and how these mechanisms evolve over time. Methods Ninety male youth players training in a professional club in Brazil were submitted to a soccer video test which consists in making tactical decisions when the image freezes. These participants were divided in five groups with 18 players in each of following age levels: Under-11, Under-13, Under-15, Under-17 and Under-20. The dominant statements of verbal reports were distributed in categories that reflect key mechanisms. The frequency of correct tactical answers was calculated for each statement types and Standard Residuals (e were calculated to verify the influence of the mechanisms on the quality of tactical decision for each age level. Results Results revealed that evaluation statement was related to accurate tactical decisions from Under-15 age level. Conclusion In conclusion, evaluation of perceived information makes better decision makers.

An efficient and accurate method for calculating nonlinear diffraction beam fields

Energy Technology Data Exchange (ETDEWEB)

Jeong, Hyun Jo; Cho, Sung Jong; Nam, Ki Woong; Lee, Jang Hyun [Division of Mechanical and Automotive Engineering, Wonkwang University, Iksan (Korea, Republic of)

2016-04-15

This study develops an efficient and accurate method for calculating nonlinear diffraction beam fields propagating in fluids or solids. The Westervelt equation and quasilinear theory, from which the integral solutions for the fundamental and second harmonics can be obtained, are first considered. A computationally efficient method is then developed using a multi-Gaussian beam (MGB) model that easily separates the diffraction effects from the plane wave solution. The MGB models provide accurate beam fields when compared with the integral solutions for a number of transmitter-receiver geometries. These models can also serve as fast, powerful modeling tools for many nonlinear acoustics applications, especially in making diffraction corrections for the nonlinearity parameter determination, because of their computational efficiency and accuracy.

Parallel constraint satisfaction in memory-based decisions.

Science.gov (United States)

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Dynamic programming approach to optimization of approximate decision rules

KAUST Repository

Amin, Talha

2013-02-01

This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.

Risky Group Decision-Making Method for Distribution Grid Planning

Science.gov (United States)

Li, Cunbin; Yuan, Jiahang; Qi, Zhiqiang

2015-12-01

With rapid speed on electricity using and increasing in renewable energy, more and more research pay attention on distribution grid planning. For the drawbacks of existing research, this paper proposes a new risky group decision-making method for distribution grid planning. Firstly, a mixing index system with qualitative and quantitative indices is built. On the basis of considering the fuzziness of language evaluation, choose cloud model to realize "quantitative to qualitative" transformation and construct interval numbers decision matrices according to the "3En" principle. An m-dimensional interval numbers decision vector is regarded as super cuboids in m-dimensional attributes space, using two-level orthogonal experiment to arrange points uniformly and dispersedly. The numbers of points are assured by testing numbers of two-level orthogonal arrays and these points compose of distribution points set to stand for decision-making project. In order to eliminate the influence of correlation among indices, Mahalanobis distance is used to calculate the distance from each solutions to others which means that dynamic solutions are viewed as the reference. Secondly, due to the decision-maker's attitude can affect the results, this paper defines the prospect value function based on SNR which is from Mahalanobis-Taguchi system and attains the comprehensive prospect value of each program as well as the order. At last, the validity and reliability of this method is illustrated by examples which prove the method is more valuable and superiority than the other.

GEOGRAPHIC INFORMATION SYSTEM AND REMOTE SENSING BASED DISASTER MANAGEMENT AND DECISION SUPPORT PLATFORM: AYDES

OpenAIRE

Keskin, İ.; Akbaba, N.; Tosun, M.; Tüfekçi, M. K.; Bulut, D.; Avcı, F.; Gökçe, O.

2018-01-01

The accelerated developments in information technology in recent years, increased the amount of usage of Geographic Information Systems (GIS) and Remote Sensing (RS) in disaster management considerably and the access from mobile and web-based platforms to continuous, accurate and sufficient data needed for decision-making became easier accordingly. The Disaster Management and Decision Support System (AYDES) has been developed with the purpose of managing the disaster and emergency manageme...

Quantum-Accurate Molecular Dynamics Potential for Tungsten

Energy Technology Data Exchange (ETDEWEB)

Wood, Mitchell; Thompson, Aidan P.

2017-03-01

The purpose of this short contribution is to report on the development of a Spectral Neighbor Analysis Potential (SNAP) for tungsten. We have focused on the characterization of elastic and defect properties of the pure material in order to support molecular dynamics simulations of plasma-facing materials in fusion reactors. A parallel genetic algorithm approach was used to efficiently search for fitting parameters optimized against a large number of objective functions. In addition, we have shown that this many-body tungsten potential can be used in conjunction with a simple helium pair potential1 to produce accurate defect formation energies for the W-He binary system.

Structuring and assessing large and complex decision problems using MCDA

DEFF Research Database (Denmark)

Barfod, Michael Bruhn

This paper presents an approach for the structuring and assessing of large and complex decision problems using multi-criteria decision analysis (MCDA). The MCDA problem is structured in a decision tree and assessed using the REMBRANDT technique featuring a procedure for limiting the number of pair...

Can streamlined multi-criteria decision analysis be used to implement shared decision making for colorectal cancer screening?

Science.gov (United States)

Dolan, James G.; Boohaker, Emily; Allison, Jeroan; Imperiale, Thomas F.

2013-01-01

Background Current US colorectal cancer screening guidelines that call for shared decision making regarding the choice among several recommended screening options are difficult to implement. Multi-criteria decision analysis (MCDA) is an established methodology well suited for supporting shared decision making. Our study goal was to determine if a streamlined form of MCDA using rank order based judgments can accurately assess patients’ colorectal cancer screening priorities. Methods We converted priorities for four decision criteria and three sub-criteria regarding colorectal cancer screening obtained from 484 average risk patients using the Analytic Hierarchy Process (AHP) in a prior study into rank order-based priorities using rank order centroids. We compared the two sets of priorities using Spearman rank correlation and non-parametric Bland-Altman limits of agreement analysis. We assessed the differential impact of using the rank order-based versus the AHP-based priorities on the results of a full MCDA comparing three currently recommended colorectal cancer screening strategies. Generalizability of the results was assessed using Monte Carlo simulation. Results Correlations between the two sets of priorities for the seven criteria ranged from 0.55 to 0.92. The proportions of absolute differences between rank order-based and AHP-based priorities that were more than ± 0.15 ranged from 1% to 16%. Differences in the full MCDA results were minimal and the relative rankings of the three screening options were identical more than 88% of the time. The Monte Carlo simulation results were similar. Conclusion Rank order-based MCDA could be a simple, practical way to guide individual decisions and assess population decision priorities regarding colorectal cancer screening strategies. Additional research is warranted to further explore the use of these methods for promoting shared decision making. PMID:24300851

Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

KAUST Repository

Chikalov, Igor

2013-01-01

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.

Ranking Fuzzy Numbers with a Distance Method using Circumcenter of Centroids and an Index of Modality

Directory of Open Access Journals (Sweden)

P. Phani Bushan Rao

2011-01-01

Full Text Available Ranking fuzzy numbers are an important aspect of decision making in a fuzzy environment. Since their inception in 1965, many authors have proposed different methods for ranking fuzzy numbers. However, there is no method which gives a satisfactory result to all situations. Most of the methods proposed so far are nondiscriminating and counterintuitive. This paper proposes a new method for ranking fuzzy numbers based on the Circumcenter of Centroids and uses an index of optimism to reflect the decision maker's optimistic attitude and also an index of modality that represents the neutrality of the decision maker. This method ranks various types of fuzzy numbers which include normal, generalized trapezoidal, and triangular fuzzy numbers along with crisp numbers with the particularity that crisp numbers are to be considered particular cases of fuzzy numbers.

Decision rules for decision tables with many-valued decisions

KAUST Repository

Chikalov, Igor; Zielosko, Beata

2011-01-01

In the paper, authors presents a greedy algorithm for construction of exact and partial decision rules for decision tables with many-valued decisions. Exact decision rules can be 'over-fitted', so instead of exact decision rules with many attributes

On algorithm for building of optimal α-decision trees

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2010-01-01

The paper describes an algorithm that constructs approximate decision trees (α-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic

How decisions emerge: action dynamics in intertemporal decision making.

Science.gov (United States)

Dshemuchadse, Maja; Scherbaum, Stefan; Goschke, Thomas

2013-02-01

In intertemporal decision making, individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to an extent that seems irrational from an economical perspective. This behavior has been attributed to a lack of self-control and reflection, the nonlinearity of human time perception, and several other sources. Although an increasing number of models propose different mathematical descriptions of temporal discounting, the dynamics of the decision process behind temporal discounting are much less clear. In this study, we obtained further insights into the mechanisms of intertemporal decisions by observing choice action dynamics via a novel combination of continuously recorded mouse movements and a multiple regression approach. Participants had to choose between two hypothetical options (sooner/smaller vs. later/larger) by moving the mouse cursor from the bottom of the screen either to the top left or to the top right. We observed less direct mouse movements when participants chose later/larger rewards, indicating that participants had to overcome the attraction of the sooner/smaller reward first. Additionally, our results suggest that framing time information differently changes the weighting of value. We conclude that using a continuous process-oriented approach could further advance the understanding of intertemporal choice beyond the identification of the best fitted mathematical description of the discounting function by uncovering the way intertemporal decisions are performed. 2013 APA, all rights reserved

Integrated Traffic Flow Management Decision Making

Science.gov (United States)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Phonological decisions require both the left and right supramarginal gyri

DEFF Research Database (Denmark)

Hartwigsen, Gesa; Baumgaertner, Annette; Price, Cathy J

2010-01-01

Recent functional imaging studies demonstrated that both the left and right supramarginal gyri (SMG) are activated when healthy right-handed subjects make phonological word decisions. However, lesion studies typically report difficulties with phonological processing after left rather than right...... the right or left SMG. Taken together, these findings provide converging evidence that the right SMG contributes to accurate and efficient phonological decisions in the healthy brain, with no evidence that the left and right SMG can compensate for one another during TMS. Our findings motivate detailed...... hemisphere damage. Here, we used a unique dual-site transcranial magnetic stimulation (TMS) approach to test whether the SMG in the right hemisphere contributes to modality-independent (i.e., auditory and visual) phonological decisions. To test task-specificity, we compared the effect of real or sham TMS...

Bi-Criteria Optimization of Decision Trees with Applications to Data Analysis

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2017-01-01

: the study of relationships among depth, average depth and number of nodes for decision trees for corner point detection (such trees are used in computer vision for object tracking), study of systems of decision rules derived from decision trees

Fast and accurate calculation of dilute quantum gas using Uehling–Uhlenbeck model equation

Energy Technology Data Exchange (ETDEWEB)

Yano, Ryosuke, E-mail: ryosuke.yano@tokiorisk.co.jp

2017-02-01

The Uehling–Uhlenbeck (U–U) model equation is studied for the fast and accurate calculation of a dilute quantum gas. In particular, the direct simulation Monte Carlo (DSMC) method is used to solve the U–U model equation. DSMC analysis based on the U–U model equation is expected to enable the thermalization to be accurately obtained using a small number of sample particles and the dilute quantum gas dynamics to be calculated in a practical time. Finally, the applicability of DSMC analysis based on the U–U model equation to the fast and accurate calculation of a dilute quantum gas is confirmed by calculating the viscosity coefficient of a Bose gas on the basis of the Green–Kubo expression and the shock layer of a dilute Bose gas around a cylinder.

The representation of healthcare end users' perspectives by surrogates in healthcare decisions: a literature review.

Science.gov (United States)

Shah, Syed Ghulam Sarwar; Farrow, Alexandra; Robinson, Ian

2009-12-01

The representation of end users' perspectives in healthcare decisions requires involvement of their surrogates when the end users, i.e. certain patients, elderly people, children and people with disabilities, are unable to present their views. To review critical issues, and the advantages and disadvantages of involving surrogates in representing end users' perspectives in healthcare decisions. A systematic review of literature published in peer-reviewed journals from 1990 to 2005. Findings show that surrogates are used widely in health care and that they are necessary to represent end users' perspectives in healthcare decisions when the latter are unable to do so themselves. Critical issues in using surrogates include key ethical, social, cultural, legal and medico-technological factors; ascertaining the best interest of end users; potential conflict of interest; possible biased decisions and the burden on surrogates. The key advantage of surrogate involvement in healthcare decisions is their ability to represent end users' needs, values and wishes. The main disadvantages include potential discrepancies between the decisions and conclusions of surrogates and end users; the failure of surrogates to predict end users' preferences accurately and the lack of certainty that useful information will be obtained through the surrogacy process. This systematic review has revealed that the involvement of surrogates is an additional vital way to represent end users' perspectives in healthcare decisions where for a range of reasons their opinions are unable to be effectively ascertained. However, because of the heterogeneity of surrogates and end users, the selection of appropriate surrogates and deploying surrogate decisions require particularly careful consideration of their value in individual cases; thus, subsequent decision-making must be reviewed on a case-to-case basis to seek to ensure that the best interests, needs and wishes of the end user are fully and accurately

A Decision Tree for Nonmetric Sex Assessment from the Skull.

Science.gov (United States)

Langley, Natalie R; Dudzik, Beatrix; Cloutier, Alesia

2018-01-01

This study uses five well-documented cranial nonmetric traits (glabella, mastoid process, mental eminence, supraorbital margin, and nuchal crest) and one additional trait (zygomatic extension) to develop a validated decision tree for sex assessment. The decision tree was built and cross-validated on a sample of 293 U.S. White individuals from the William M. Bass Donated Skeletal Collection. Ordinal scores from the six traits were analyzed using the partition modeling option in JMP Pro 12. A holdout sample of 50 skulls was used to test the model. The most accurate decision tree includes three variables: glabella, zygomatic extension, and mastoid process. This decision tree yielded 93.5% accuracy on the training sample, 94% on the cross-validated sample, and 96% on a holdout validation sample. Linear weighted kappa statistics indicate acceptable agreement among observers for these variables. Mental eminence should be avoided, and definitions and figures should be referenced carefully to score nonmetric traits. © 2017 American Academy of Forensic Sciences.

Does future-oriented thinking predict adolescent decision making?

Science.gov (United States)

Eskritt, Michelle; Doucette, Jesslyn; Robitaille, Lori

2014-01-01

A number of theorists, as well as plain common sense, suggest that future-oriented thinking (FOT) should be involved in decision making; therefore, the development of FOT should be related to better quality decision making. FOT and quality of the decision making were measured in adolescents as well as adults in 2 different experiments. Though the results of the first experiment revealed an increase in quality of decision making across adolescence into adulthood, there was no relationship between FOT and decision making. In the second experiment, FOT predicted performance on a more deliberative decision-making task independent of age, but not performance on the Iowa Gambling Task (IGT). Performance on the IGT was instead related to emotion regulation. The study's findings suggest that FOT can be related to reflective decision making but not necessarily decision making that is more intuitive.

Spatial Decision Support Systems

Directory of Open Access Journals (Sweden)

Silviu Ioan Bejinariu

2015-10-01

Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.

Quadruplex MAPH: improvement of throughput in high-resolution copy number screening

Directory of Open Access Journals (Sweden)

Walker Susan

2009-09-01

Full Text Available Abstract Background Copy number variation (CNV in the human genome is recognised as a widespread and important source of human genetic variation. Now the challenge is to screen for these CNVs at high resolution in a reliable, accurate and cost-effective way. Results Multiplex Amplifiable Probe Hybridisation (MAPH is a sensitive, high-resolution technology appropriate for screening for CNVs in a defined region, for a targeted population. We have developed MAPH to a highly multiplexed format ("QuadMAPH" that allows the user a four-fold increase in the number of loci tested simultaneously. We have used this method to analyse a genomic region of 210 kb, including the MSH2 gene and 120 kb of flanking DNA. We show that the QuadMAPH probes report copy number with equivalent accuracy to simplex MAPH, reliably demonstrating diploid copy number in control samples and accurately detecting deletions in Hereditary Non-Polyposis Colorectal Cancer (HNPCC samples. Conclusion QuadMAPH is an accurate, high-resolution method that allows targeted screening of large numbers of subjects without the expense of genome-wide approaches. Whilst we have applied this technique to a region of the human genome, it is equally applicable to the genomes of other organisms.

Influence of the number of players in decision making and performance in the teaching of handball

Directory of Open Access Journals (Sweden)

Javier Aguilar

2012-11-01

Full Text Available Handball is a sport in which many actions occur with speed and the pressure of time and space. It constitutes a special context in the decisions making of the players. The aim of this study was to analyze the performance and decision making using the Game Performance Assessment Instrument (GPAI, in situations of numerical equality (three against three and numerical inequality (three against two during 396 cycles of game performed by12 students of High School. Significant differences were obtained between the situations of numerical equality and inequality in three of the seven indices: in Decision Making (p=0,047, Technical Execution (p=0,032 and in Mark (p=0,050. In the first two indices the differences were in favor of numerical inequality situations and in the third, the differences were favorable in the situations of numerical equality. Finally, it could be concluded that GPAI is a valid instrument of assessing for an educational context offering an alternative to the evaluation model orientated exclusively towards the skills.Key words: GPAI, Physical Education, numerical Equality-Inequality.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-01-01

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-07-10

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

76 FR 7757 - Hull Identification Numbers for Recreational Vessels

Science.gov (United States)

2011-02-11

... DEPARTMENT OF HOMELAND SECURITY Coast Guard 33 CFR Part 181 [Docket No. USCG-2007-29236] Hull Identification Numbers for Recreational Vessels AGENCY: Coast Guard, DHS. ACTION: Follow-up to request for... expanded hull identification number (HIN). The Coast Guard's decision-making process included consideration...

Information integration in perceptual and value-based decisions

OpenAIRE

Tsetsos, K.

2012-01-01

Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been r...

The Influence of Endogenous and Exogenous Spatial Attention on Decision Confidence.

Science.gov (United States)

Kurtz, Phillipp; Shapcott, Katharine A; Kaiser, Jochen; Schmiedt, Joscha T; Schmid, Michael C

2017-07-25

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence would also increase. However, two studies investigating the effects of endogenous attention on decision confidence found contradictory results. Here we investigated the effects of two distinct forms of spatial attention on decision confidence; endogenous attention and exogenous attention. We used an orientation-matching task, comparing the two attention conditions (endogenous and exogenous) to a control condition without directed attention. Participants performed better under both attention conditions than in the control condition. Higher confidence ratings than the control condition were found under endogenous attention but not under exogenous attention. This finding suggests that while attention can increase confidence ratings, it must be voluntarily deployed for this increase to take place. We discuss possible implications of this relative overconfidence found only during endogenous attention with respect to the theoretical background of decision confidence.

Cytology-based treatment decision in primary lung cancer: is it accurate enough?

Science.gov (United States)

Sakr, Lama; Roll, Patrice; Payan, Marie-José; Liprandi, Agnès; Dutau, Hervé; Astoul, Philippe; Robaglia-Schlupp, Andrée; Loundou, Anderson; Barlesi, Fabrice

2012-03-01

Accurate distinction of lung cancer types has become increasingly important as recent trials have shown differential response to chemotherapy among non-small cell lung carcinoma (NSCLC) subtypes. Cytological procedures are frequently used but their diagnostic accuracy has been previously questioned. However, new endoscopic and cytological techniques might have improved cytological accuracy in comparison with prior findings. The aim of this study was to reassess cytological accuracy for diagnosis of lung cancer subtypes. A retrospective chart review of subjects who underwent fiberoptic bronchoscopy (FOB) for suspicion of lung cancer in 2007-2008, was undertaken. Reports of bronchoscopically derived cytological specimens were compared to those of histological material. Endoscopic findings and specific investigational techniques were taken into account. A total of 467 FOB with both cytological and histological diagnostic techniques were performed in 449 subjects. Patients consisted of 345 men and 104 women (median age, 65 yrs). Cytology proved malignancy in 157 patients. Cytologically diagnosed carcinomas were classified into squamous cell carcinoma (SqCC) in 56, adenocarcinoma (ADC) in 6, small cell lung carcinoma (SCLC) in 12, non-small cell lung carcinoma not otherwise specified (NSCLC-NOS) in 71, and unclassified carcinoma in 12. Cytology correlated fairly with biopsy specimens, as agreement was observed in 83% of SCLC, 100% of ADC, 74% of SqCC and 8% of NSCLC-NOS. Interestingly, 61% of cytologically identified NSCLC-NOS were classified as ADC by histology. Cytological accuracy improved in case of an endobronchial lesion, mainly for SqCC. These results indicate that cytological accuracy remains fair with regard to diagnosis of squamous and non-squamous lung cancer subtypes. Improvement of cytological accuracy is expected however with novel diagnostic strategies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Accurate Sample Time Reconstruction of Inertial FIFO Data

Directory of Open Access Journals (Sweden)

Sebastian Stieber

2017-12-01

Full Text Available In the context of modern cyber-physical systems, the accuracy of underlying sensor data plays an increasingly important role in sensor data fusion and feature extraction. The raw events of multiple sensors have to be aligned in time to enable high quality sensor fusion results. However, the growing number of simultaneously connected sensor devices make the energy saving data acquisition and processing more and more difficult. Hence, most of the modern sensors offer a first-in-first-out (FIFO interface to store multiple data samples and to relax timing constraints, when handling multiple sensor devices. However, using the FIFO interface increases the negative influence of individual clock drifts—introduced by fabrication inaccuracies, temperature changes and wear-out effects—onto the sampling data reconstruction. Furthermore, additional timing offset errors due to communication and software latencies increases with a growing number of sensor devices. In this article, we present an approach for an accurate sample time reconstruction independent of the actual clock drift with the help of an internal sensor timer. Such timers are already available in modern sensors, manufactured in micro-electromechanical systems (MEMS technology. The presented approach focuses on calculating accurate time stamps using the sensor FIFO interface in a forward-only processing manner as a robust and energy saving solution. The proposed algorithm is able to lower the overall standard deviation of reconstructed sampling periods below 40 μ s, while run-time savings of up to 42% are achieved, compared to single sample acquisition.

Licensing Surrogate Decision-Makers.

Science.gov (United States)

Rosoff, Philip M

2017-06-01

As medical technology continues to improve, more people will live longer lives with multiple chronic illnesses with increasing cumulative debilitation, including cognitive dysfunction. Combined with the aging of society in most developed countries, an ever-growing number of patients will require surrogate decision-makers. While advance care planning by patients still capable of expressing their preferences about medical interventions and end-of-life care can improve the quality and accuracy of surrogate decisions, this is often not the case, not infrequently leading to demands for ineffective, inappropriate and prolonged interventions. In 1980 LaFollette called for the licensing of prospective parents, basing his argument on the harm they can do to vulnerable people (children). In this paper, I apply his arguments to surrogate decision-makers for cognitively incapacitated patients, rhetorically suggesting that we require potential surrogates to qualify for this position by demonstrating their ability to make reasonable and rational decisions for others. I employ this theoretical approach to argue that the loose criteria by which we authorize surrogates' generally unchallenged power should be reconsidered.

Colorectal cancer patients' attitudes towards involvement in decision making.

Science.gov (United States)

Beaver, Kinta; Campbell, Malcolm; Craven, Olive; Jones, David; Luker, Karen A; Susnerwala, Shabbir S

2009-03-01

To design and administer an attitude rating scale, exploring colorectal cancer patients' views of involvement in decision making. To examine the impact of socio-demographic and/or treatment-related factors on decision making. To conduct principal components analysis to determine if the scale could be simplified into a number of factors for future clinical utility. An attitude rating scale was constructed based on previous qualitative work and administered to colorectal cancer patients using a cross-sectional survey approach. 375 questionnaires were returned (81.7% response). For patients it was important to be informed and involved in the decision-making process. Information was not always used to make decisions as patients placed their trust in medical expertise. Women had more positive opinions on decision making and were more likely to want to make decisions. Written information was understood to a greater degree than verbal information. The scale could be simplified to a number of factors, indicating clinical utility. Few studies have explored the attitudes of colorectal cancer patients towards involvement in decision making. This study presents new insights into how patients view the concept of participation; important when considering current policy imperatives in the UK of involving service users in all aspects of care and treatment.

Family factors in end-of-life decision-making: family conflict and proxy relationship.

Science.gov (United States)

Parks, Susan Mockus; Winter, Laraine; Santana, Abbie J; Parker, Barbara; Diamond, James J; Rose, Molly; Myers, Ronald E

2011-02-01

Few studies have examined proxy decision-making regarding end-of-life treatment decisions. Proxy accuracy is defined as whether proxy treatment choices are consistent with the expressed wishes of their index elder. The purpose of this study was to examine proxy accuracy in relation to two family factors that may influence proxy accuracy: perceived family conflict and type of elder-proxy relationship. Telephone interviews with 202 community-dwelling elders and their proxy decision makers were conducted including the Life-Support Preferences Questionnaire (LSPQ), and a measure of family conflict, and sociodemographic characteristics, including type of relationship. Elder-proxy accuracy was associated with the type of elder-proxy relationship. Adult children demonstrated the lowest elder-proxy accuracy and spousal proxies the highest elder-proxy accuracy. Elder-proxy accuracy was associated with family conflict. Proxies reporting higher family conflict had lower elder-proxy accuracy. No interaction between family conflict and relationship type was revealed. Spousal proxies were more accurate in their substituted judgment than adult children, and proxies who perceive higher degree of family conflict tended to be less accurate than those with lower family conflict. Health care providers should be aware of these family factors when discussing advance care planning.

Optimal number of circulating water pumps in a nuclear power plant

International Nuclear Information System (INIS)

Xia, Lin; Liu, Deyou; Zhou, Ling; Wang, Feng; Wang, Pei

2015-01-01

Highlights: • We present a novel method to optimize the number of variable speed pumps. • The economic effect of variable speed pumps number optimization is presented. • We present a novel method to optimize the number of constant speed pumps. • The proposed pumps number optimization method is more accurate than the widely used method. - Abstract: A circulating cooling system that uses variable speed pumps (VSPs) or constant-speed pumps (CSPs) as circulating water pumps (CWPs) is optimized to improve the cycle efficiency of nuclear power plants. This study focused on the optimal number of VSPs and CSPs. A novel method is proposed to optimize the number of VSPs with varying dry-bulb temperature and relative humidity, which could help decrease operation costs by $243,310 per year. This method is also used to optimize the number of CSPs and is compared with another widely used method that optimizes the number of CSPs according to the varying condenser inlet water temperature. A comparison shows that the proposed method is more accurate than the widely used method

Optimal number of circulating water pumps in a nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Xia, Lin [College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, Jiangsu (China); Liu, Deyou, E-mail: liudyhhuc@163.com [College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, Jiangsu (China); Zhou, Ling, E-mail: zlhhu@163.com [College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, Jiangsu (China); Wang, Feng [School of Hydraulic, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, Jiangsu (China); Wang, Pei [College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, Jiangsu (China)

2015-07-15

Highlights: • We present a novel method to optimize the number of variable speed pumps. • The economic effect of variable speed pumps number optimization is presented. • We present a novel method to optimize the number of constant speed pumps. • The proposed pumps number optimization method is more accurate than the widely used method. - Abstract: A circulating cooling system that uses variable speed pumps (VSPs) or constant-speed pumps (CSPs) as circulating water pumps (CWPs) is optimized to improve the cycle efficiency of nuclear power plants. This study focused on the optimal number of VSPs and CSPs. A novel method is proposed to optimize the number of VSPs with varying dry-bulb temperature and relative humidity, which could help decrease operation costs by $243,310 per year. This method is also used to optimize the number of CSPs and is compared with another widely used method that optimizes the number of CSPs according to the varying condenser inlet water temperature. A comparison shows that the proposed method is more accurate than the widely used method.

On algorithm for building of optimal α-decision trees

KAUST Repository

Alkhalid, Abdulaziz

2010-01-01

The paper describes an algorithm that constructs approximate decision trees (α-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic programming and extends methods described in [4] to constructing approximate decision trees. Adjustable approximation rate allows controlling algorithm complexity. The algorithm is applied to build optimal α-decision trees for two data sets from UCI Machine Learning Repository [1]. © 2010 Springer-Verlag Berlin Heidelberg.

Improving the Slum Planning Through Geospatial Decision Support System

Science.gov (United States)

Shekhar, S.

2014-11-01

In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

Design and Implementation of Multi Agent-based Information Fusion System for Supporting Decision Making (A Case Study on Military Operation

Directory of Open Access Journals (Sweden)

Arwin Datumaya Wahyudi Sumari

2008-05-01

Full Text Available Quick, accurate, and complete information is highly required for supporting strategically impact decision making in a Military Operation (MO in order to reduce the decision cycle and to minimize the loss. For that purpose, we propose, design and implement a hierarchical Multi Agent-based Information Fusion System for Decision Making Support (MAIFS-DMS. The information fusion is implemented by applying Maximum Score of the Total Sum of Joint Probabilities (MSJP fusion method and is done by a collection of Information Fusion Agents (IFA that forms a multiagent system. MAIFS uses a combination of generalization of Dasarathy and Joint Director’s Laboratory (JDL process models for information fusion mechanism. Information fusion products that are displayed in graphical forms provide comprehensive information regarding the MO area dynamics. By observing the graphics resulted from the information fusion, the commandant will have situational awareness and knowledge in order to make the most accurate strategic decision as fast as possible

Generative Agents for Player Decision Modeling in Games

DEFF Research Database (Denmark)

Holmgård, Christoffer; Liapis, Antonios; Togelius, Julian

2014-01-01

This paper presents a method for modeling player decision making through the use of agents as AI-driven personas. The paper argues that artificial agents, as generative player models, have properties that allow them to be used as psyhometrically valid, abstract simulations of a human player......’s internal decision making processes. Such agents can then be used to interpret human decision making, as personas and playtesting tools in the game design process, as baselines for adapting agents to mimic classes of human players, or as believable, human-like opponents. This argument is explored...... in a crowdsourced decision making experiment, in which the decisions of human players are recorded in a small-scale dungeon themed puzzle game. Human decisions are compared to the decisions of a number of a priori defined “archetypical” agent-personas, and the humans are characterized by their likeness...

Fast Image Texture Classification Using Decision Trees

Science.gov (United States)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Merging building maintainability and sustainability assessment: A multicriteria decision making approach

Science.gov (United States)

Asmone, A. S.; Chew, M. Y. L.

2018-02-01

Accurately predicting maintainability has been a challenge due to the complex nature of buildings, yet it is an important research area with a rising necessity. This paper explores the use of multicriteria decision making approach for merging maintainability and sustainability elements into building grading systems to attain long-term sustainability in the building industry. The paper conducts a systematic literature review on multicriteria decision analysis approach and builds on the existing knowledge of maintainability to achieve this. A conceptual framework is developed to bridge the gap between building operations and maintenance with green facilities management by forecasting green maintainability at the design stage.

Value-based reimbursement decisions for orphan drugs: a scoping review and decision framework.

Science.gov (United States)

Paulden, Mike; Stafinski, Tania; Menon, Devidas; McCabe, Christopher

2015-03-01

The rate of development of new orphan drugs continues to grow. As a result, reimbursing orphan drugs on an exceptional basis is increasingly difficult to sustain from a health system perspective. An understanding of the value that societies attach to providing orphan drugs at the expense of other health technologies is now recognised as an important input to policy debates. The aim of this work was to scope the social value arguments that have been advanced relating to the reimbursement of orphan drugs, and to locate these within a coherent decision-making framework to aid reimbursement decisions in the presence of limited healthcare resources. A scoping review of the peer reviewed and grey literature was undertaken, consisting of seven phases: (1) identifying the research question; (2) searching for relevant studies; (3) selecting studies; (4) charting, extracting and tabulating data; (5) analyzing data; (6) consulting relevant experts; and (7) presenting results. The points within decision processes where the identified value arguments would be incorporated were then located. This mapping was used to construct a framework characterising the distinct role of each value in informing decision making. The scoping review identified 19 candidate decision factors, most of which can be characterised as either value-bearing or 'opportunity cost'-determining, and also a number of value propositions and pertinent sources of preference information. We were able to synthesize these into a coherent decision-making framework. Our framework may be used to structure policy discussions and to aid transparency about the values underlying reimbursement decisions for orphan drugs. These values ought to be consistently applied to all technologies and populations affected by the decision.

Residual number processing in dyscalculia ?

OpenAIRE

Cappelletti, Marinella; Price, Cathy J.

2013-01-01

Developmental dyscalculia – a congenital learning disability in understanding numerical concepts – is typically associated with parietal lobe abnormality. However, people with dyscalculia often retain some residual numerical abilities, reported in studies that otherwise focused on abnormalities in the dyscalculic brain. Here we took a different perspective by focusing on brain regions that support residual number processing in dyscalculia. All participants accurately performed semantic and ca...

A decision support tool for sustainable supplier selection in manufacturing firms

Directory of Open Access Journals (Sweden)

Ifeyinwa Orji

2014-10-01

Full Text Available Purpose: Most original equipment manufacturers (OEMs are strategically involved in supplier base rationalization and increased consciousness of sustainable development thus, reinforcing need for accurately considering sustainability in supplier selection to improve organizational performance. In real industrial case, imprecise data, ambiguity of human judgment, uncertainty among sustainability factors and the need to capture all subjective and objective criteria are unavoidable and pose huge challenge to accurately incorporate sustainability factors into supplier selection.Methodology: This study develops a model based on integrated multi- criteria decision making (MCDM methods to solve such problems. The developed model applies Fuzzy logic, DEMATEL and TOPSIS to effectively analyze the interdependencies between sustainability criteria and to select the best sustainable supplier in fuzzy environment while capturing all subjective and objective criteria. A case study is illustrated to test the proposed model in a gear manufacturing company, an OEM to provide insights and for practical applications.Findings: Results show that social factors of sustainability ranks as the most important in supplier selection. However, the most influential sustainability sub- criteria are work safety (WS and quality.Originality/Value: The model is capable of capturing all subjective and objective criteria in fuzzy environment to accurately incorporate sustainability factors in supplier selection. It is decision support tool relevant for providing insights to managers while implementing sustainable supplier selection.

Emotional and Social Factors influence Poker Decision Making Accuracy.

Science.gov (United States)

Laakasuo, Michael; Palomäki, Jussi; Salmela, Mikko

2015-09-01

Poker is a social game, where success depends on both game strategic knowledge and emotion regulation abilities. Thus, poker provides a productive environment for studying the effects of emotional and social factors on micro-economic decision making. Previous research indicates that experiencing negative emotions, such as moral anger, reduces mathematical accuracy in poker decision making. Furthermore, various social aspects of the game—such as losing against "bad players" due to "bad luck"—seem to fuel these emotional states. We designed an Internet-based experiment, where participants' (N = 459) mathematical accuracy in five different poker decision making tasks were assessed. In addition, we manipulated the emotional and social conditions under which the tasks were presented, in a 2 × 2 experimental setup: (1) Anger versus neutral emotional state—participants were primed either with an anger-inducing, or emotionally neutral story, and (2) Social cue versus non-social cue—during the tasks, either an image of a pair of human eyes was "following" the mouse cursor, or an image of a black moving box was presented. The results showed that anger reduced mathematical accuracy of decision making only when participants were "being watched" by a pair of moving eyes. Experienced poker players made mathematically more accurate decisions than inexperienced ones. The results contribute to current understanding on how emotional and social factors influence decision making accuracy in economic games.

Decision Simulation Technique (DST) as a scanning tool for exploring and explicating sustainability issues in transport decision making

DEFF Research Database (Denmark)

Jeppesen, Sara Lise

2009-01-01

This paper places focus on explicit consideration of sustainability issues in transport decision making by presenting and using a developed “Decision Simulation Technique” (DST). This technique can be used by an analyst to ‘scan’ a transport planning problem with regard to what in DST terms...... is called a sustainability strategy. This scanning can serve the purpose of informing a group of decision makers before they actually have to deal with, for example, the choice among a number of alternatives that have all been formulated as being relevant. The main focus of the paper is to illustrate how...

Regret and adaptive decision making in young children.

Science.gov (United States)

O'Connor, Eimear; McCormack, Teresa; Beck, Sarah R; Feeney, Aidan

2015-07-01

In line with the claim that regret plays a role in decision making, O'Connor, McCormack, and Feeney (Child Development, 85 (2014) 1995-2010) found that children who reported feeling sadder on discovering they had made a non-optimal choice were more likely to make a different choice the next time around. We examined two issues of interpretation regarding this finding: whether the emotion measured was indeed regret and whether it was the experience of this emotion, rather than the ability to anticipate it, that affected decision making. To address the first issue, we varied the degree to which children aged 6 or 7 years were responsible for an outcome, assuming that responsibility is a necessary condition for regret. The second issue was addressed by examining whether children could accurately anticipate that they would feel worse on discovering they had made a non-optimal choice. Children were more likely to feel sad if they were responsible for the outcome; however, even if they were not responsible, children were more likely than chance to report feeling sadder. Moreover, across all conditions, feeling sadder was associated with making a better subsequent choice. In a separate task, we demonstrated that children of this age cannot accurately anticipate feeling sadder on discovering that they had not made the best choice. These findings suggest that although children may feel regret following a non-optimal choice, even if they were not responsible for an outcome, they may experience another negative emotion such as frustration. Experiencing either of these emotions seems to be sufficient to support better decision making. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Improving clinical decision support using data mining techniques

Science.gov (United States)

Burn-Thornton, Kath E.; Thorpe, Simon I.

1999-02-01

Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

Systematic biases in DNA copy number originate from isolation procedures

NARCIS (Netherlands)

van Heesch, S.; Mokry, M.; Boskova, V.; Junker, W.; Mehon, R.; Toonen, P.; de Bruijn, E.; Shull, J.D.; Aitman, T.J.; Cuppen, E.; Guryev, V.

2013-01-01

BACKGROUND: The ability to accurately detect DNA copy number variation in both a sensitive and quantitative manner is important in many research areas. However, genome-wide DNA copy number analyses are complicated by variations in detection signal. RESULTS: While GC content has been used to correct

Decision making in urological surgery.

Science.gov (United States)

Abboudi, Hamid; Ahmed, Kamran; Normahani, Pasha; Abboudi, May; Kirby, Roger; Challacombe, Ben; Khan, Mohammed Shamim; Dasgupta, Prokar

2012-06-01

Non-technical skills are important behavioural aspects that a urologist must be fully competent at to minimise harm to patients. The majority of surgical errors are now known to be due to errors in judgment and decision making as opposed to the technical aspects of the craft. The authors reviewed the published literature regarding decision-making theory and in practice related to urology as well as the current tools available to assess decision-making skills. Limitations include limited number of studies, and the available studies are of low quality. Decision making is the psychological process of choosing between alternative courses of action. In the surgical environment, this can often be a complex balance of benefit and risk within a variable time frame and dynamic setting. In recent years, the emphasis of new surgical curriculums has shifted towards non-technical surgical skills; however, the assessment tools in place are far from objective, reliable and valid. Surgical simulators and video-assisted questionnaires are useful methods for appraisal of trainees. Well-designed, robust and validated tools need to be implemented in training and assessment of decision-making skills in urology. Patient safety can only be ensured when safe and effective decisions are made.

Humans can consciously generate random number sequences: a possible test for artificial intelligence.

Science.gov (United States)

Persaud, Navindra

2005-01-01

Computer algorithms can only produce seemingly random or pseudorandom numbers whereas certain natural phenomena, such as the decay of radioactive particles, can be utilized to produce truly random numbers. In this study, the ability of humans to generate random numbers was tested in healthy adults. Subjects were simply asked to generate and dictate random numbers. Generated numbers were tested for uniformity, independence and information density. The results suggest that humans can generate random numbers that are uniformly distributed, independent of one another and unpredictable. If humans can generate sequences of random numbers then neural networks or forms of artificial intelligence, which are purported to function in ways essentially the same as the human brain, should also be able to generate sequences of random numbers. Elucidating the precise mechanism by which humans generate random number sequences and the underlying neural substrates may have implications in the cognitive science of decision-making. It is possible that humans use their random-generating neural machinery to make difficult decisions in which all expected outcomes are similar. It is also possible that certain people, perhaps those with neurological or psychiatric impairments, are less able or unable to generate random numbers. If the random-generating neural machinery is employed in decision making its impairment would have profound implications in matters of agency and free will.

EpHLA software: a timesaving and accurate tool for improving identification of acceptable mismatches for clinical purposes.

Science.gov (United States)

Filho, Herton Luiz Alves Sales; da Mata Sousa, Luiz Claudio Demes; von Glehn, Cristina de Queiroz Carrascosa; da Silva, Adalberto Socorro; dos Santos Neto, Pedro de Alcântara; do Nascimento, Ferraz; de Castro, Adail Fonseca; do Nascimento, Liliane Machado; Kneib, Carolina; Bianchi Cazarote, Helena; Mayumi Kitamura, Daniele; Torres, Juliane Roberta Dias; da Cruz Lopes, Laiane; Barros, Aryela Loureiro; da Silva Edlin, Evelin Nildiane; de Moura, Fernanda Sá Leal; Watanabe, Janine Midori Figueiredo; do Monte, Semiramis Jamil Hadad

2012-06-01

The HLAMatchmaker algorithm, which allows the identification of “safe” acceptable mismatches (AMMs) for recipients of solid organ and cell allografts, is rarely used in part due to the difficulty in using it in the current Excel format. The automation of this algorithm may universalize its use to benefit the allocation of allografts. Recently, we have developed a new software called EpHLA, which is the first computer program automating the use of the HLAMatchmaker algorithm. Herein, we present the experimental validation of the EpHLA program by showing the time efficiency and the quality of operation. The same results, obtained by a single antigen bead assay with sera from 10 sensitized patients waiting for kidney transplants, were analyzed either by conventional HLAMatchmaker or by automated EpHLA method. Users testing these two methods were asked to record: (i) time required for completion of the analysis (in minutes); (ii) number of eplets obtained for class I and class II HLA molecules; (iii) categorization of eplets as reactive or non-reactive based on the MFI cutoff value; and (iv) determination of AMMs based on eplets' reactivities. We showed that although both methods had similar accuracy, the automated EpHLA method was over 8 times faster in comparison to the conventional HLAMatchmaker method. In particular the EpHLA software was faster and more reliable but equally accurate as the conventional method to define AMMs for allografts. The EpHLA software is an accurate and quick method for the identification of AMMs and thus it may be a very useful tool in the decision-making process of organ allocation for highly sensitized patients as well as in many other applications.

Acceptance of shared decision making with reference to an electronic library of decision aids (arriba-lib) and its association to decision making in patients: an evaluation study.

Science.gov (United States)

Hirsch, Oliver; Keller, Heidemarie; Krones, Tanja; Donner-Banzhoff, Norbert

2011-07-07

Decision aids based on the philosophy of shared decision making are designed to help patients make informed choices among diagnostic or treatment options by delivering evidence-based information on options and outcomes. A patient decision aid can be regarded as a complex intervention because it consists of several presumably relevant components. Decision aids have rarely been field tested to assess patients' and physicians' attitudes towards them. It is also unclear what effect decision aids have on the adherence to chosen options. The electronic library of decision aids (arriba-lib) to be used within the clinical encounter has a modular structure and contains evidence-based decision aids for the following topics: cardiovascular prevention, atrial fibrillation, coronary heart disease, oral antidiabetics, conventional and intensified insulin therapy, and unipolar depression. We conducted an evaluation study in which 29 primary care physicians included 192 patients. After the consultation, patients filled in questionnaires and were interviewed via telephone two months later. We used generalised estimation equations to measure associations within patient variables and traditional crosstab analyses. Patients were highly satisfied with arriba-lib and the process of shared decision making. Two-thirds of patients reached in the telephone interview wanted to be counselled again with arriba-lib. There was a high congruence between preferred and perceived decision making. Of those patients reached in the telephone interview, 80.7% said that they implemented the decision, independent of gender and education. Elderly patients were more likely to say that they implemented the decision. Shared decision making with our multi-modular electronic library of decision aids (arriba-lib) was accepted by a high number of patients. It has positive associations to general aspects of decision making in patients. It can be used for patient groups with a wide range of individual

A Novel Method for Dynamic Multicriteria Decision Making with Hybrid Evaluation Information

OpenAIRE

Shihu Liu; Tauqir Ahmed Moughal

2014-01-01

How to select the most desirable pattern(s) is often a crucial step for decision making problem. By taking uncertainty as well as dynamic of database into consideration, in this paper, we construct a dynamic multicriteria decision making procedure, where the evaluation information of criteria is expressed by real number, intuitionistic fuzzy number, and interval-valued intuitionistic fuzzy number. During the process of algorithm construction, the evaluation information at all time episodes is...

Decision-making by an authority under influence

DEFF Research Database (Denmark)

Tranæs, Torben

1993-01-01

A characteristic set of decision problems is given when an authority has to choose between a finite number of alternatives and is being influenced by a number of parties. For instance, the location of a firm when local authorities are competing for being the host, various types of lobbyism, or when...

Decision-Tree Analysis for Predicting First-Time Pass/Fail Rates for the NCLEX-RN® in Associate Degree Nursing Students.

Science.gov (United States)

Chen, Hsiu-Chin; Bennett, Sean

2016-08-01

Little evidence shows the use of decision-tree algorithms in identifying predictors and analyzing their associations with pass rates for the NCLEX-RN(®) in associate degree nursing students. This longitudinal and retrospective cohort study investigated whether a decision-tree algorithm could be used to develop an accurate prediction model for the students' passing or failing the NCLEX-RN. This study used archived data from 453 associate degree nursing students in a selected program. The chi-squared automatic interaction detection analysis of the decision trees module was used to examine the effect of the collected predictors on passing/failing the NCLEX-RN. The actual percentage scores of Assessment Technologies Institute®'s RN Comprehensive Predictor(®) accurately identified students at risk of failing. The classification model correctly classified 92.7% of the students for passing. This study applied the decision-tree model to analyze a sequence database for developing a prediction model for early remediation in preparation for the NCLEXRN. [J Nurs Educ. 2016;55(8):454-457.]. Copyright 2016, SLACK Incorporated.

Colorectal cancer patients’ attitudes towards involvement in decision making

Science.gov (United States)

Beaver, Kinta; Campbell, Malcolm; Craven, Olive; Jones, David; Luker, Karen A.; Susnerwala, Shabbir S.

2009-01-01

Abstract Objectives  To design and administer an attitude rating scale, exploring colorectal cancer patients’ views of involvement in decision making. To examine the impact of socio‐demographic and/or treatment‐related factors on decision making. To conduct principal components analysis to determine if the scale could be simplified into a number of factors for future clinical utility. Methods  An attitude rating scale was constructed based on previous qualitative work and administered to colorectal cancer patients using a cross‐sectional survey approach. Results  375 questionnaires were returned (81.7% response). For patients it was important to be informed and involved in the decision‐making process. Information was not always used to make decisions as patients placed their trust in medical expertise. Women had more positive opinions on decision making and were more likely to want to make decisions. Written information was understood to a greater degree than verbal information. The scale could be simplified to a number of factors, indicating clinical utility. Conclusion  Few studies have explored the attitudes of colorectal cancer patients towards involvement in decision making. This study presents new insights into how patients view the concept of participation; important when considering current policy imperatives in the UK of involving service users in all aspects of care and treatment. PMID:19250150

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

Science.gov (United States)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Age Effects and Heuristics in Decision Making.

Science.gov (United States)

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.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

Directory of Open Access Journals (Sweden)

Ashlock Daniel

2009-08-01

Full Text Available Abstract Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering.

Science.gov (United States)

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-08-22

Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

Science.gov (United States)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

Decision time and confidence predict choosers' identification performance in photographic showups

Science.gov (United States)

Sagana, Anna; Sporer, Siegfried L.; Wixted, John T.

2018-01-01

In vast contrast to the multitude of lineup studies that report on the link between decision time, confidence, and identification accuracy, only a few studies looked at these associations for showups, with results varying widely across studies. We therefore set out to test the individual and combined value of decision time and post-decision confidence for diagnosing the accuracy of positive showup decisions using confidence-accuracy characteristic curves and Bayesian analyses. Three-hundred-eighty-four participants viewed a stimulus event and were subsequently presented with two showups which could be target-present or target-absent. As expected, we found a negative decision time-accuracy and a positive post-decision confidence-accuracy correlation for showup selections. Confidence-accuracy characteristic curves demonstrated the expected additive effect of combining both postdictors. Likewise, Bayesian analyses, taking into account all possible target-presence base rate values showed that fast and confident identification decisions were more diagnostic than slow or less confident decisions, with the combination of both being most diagnostic for postdicting accurate and inaccurate decisions. The postdictive value of decision time and post-decision confidence was higher when the prior probability that the suspect is the perpetrator was high compared to when the prior probability that the suspect is the perpetrator was low. The frequent use of showups in practice emphasizes the importance of these findings for court proceedings. Overall, these findings support the idea that courts should have most trust in showup identifications that were made fast and confidently, and least in showup identifications that were made slowly and with low confidence. PMID:29346394

Decision-making under risk. An overview of some alternative utility theories

International Nuclear Information System (INIS)

Pauwels, N.; Van Woensel, T.

1998-09-01

Decision-makers often have to take decisions with unknown consequences that depend on various events which on their turn can take place a certain chance. Under the given circumstances, the traditional decision criterion is based on the maximisation of the expected benefits. Experimental studies have however revealed important inconsistencies between decisions taken on the basis of this decision criterion on the one hand and the observed decisions on the other hand. The report gives an overview of a number of alternative theories extending or adapting the traditional theory in view of avoiding the observed inconsistencies

Marketing Decision Making and Decision Support: Challenges and Perspectives for Successful Marketing Management Support Systems

NARCIS (Netherlands)

G.H. van Bruggen (Gerrit); B. Wierenga (Berend)

2009-01-01

textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g.,

Value of DNA tests: a decision perspective.

Science.gov (United States)

Taroni, Franco; Bozza, Silvia; Bernard, Magali; Champod, Christophe

2007-01-01

Before a Court of Law testifying in DNA-evidence cases, scientists are often challenged with the idea that the more markers (loci) the better, i.e., why does the scientist not use 16 or more markers? This paper introduces a new perspective, decision analysis, to deal with the problem of the number of markers to type in a criminal context. The decision-making process, which plays a key role in the routine work of a forensic scientist, consists of the rational choice, given personal objectives, between two or more possible outcomes when the consequences of the choice are uncertain. Simulated results support the hypothesis that analytical added value does not increase with the number of markers.

Decision making and information flows in precision agriculture

DEFF Research Database (Denmark)

Fountas, S.; Wulfsohn, Dvora-Laiô; Blackmore, B.S.

A participative methology was developed in which farm managers decomposed their process of decision making in Precision Agriculture (PA) into brief secision statesments along with associated information requirements. The methodology was first developed on a university research farm in Denmark...... and further revised during testing on a number of research and commercial farms in Indiana, USA. Twenty-one decision analysis factors were idebfied to characterise a farm manager's decision-making process. Then a general data flow diagram (DFD) was constructed that describes the information flows "from data...... to decision". Illustrative examples of the model in the form of DFDs are presented for a strategic and an operational decision. The model was validated for a range of decisions related to operations by three university farm managers and by five commercial farmers practicing PA for cereal, corn and soybean...

A distributed clinical decision support system architecture

Directory of Open Access Journals (Sweden)

Shaker H. El-Sappagh

2014-01-01

Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

Helping Patients to Make Informed Decisions : The PARE Guide to Disseminate EULAR Recommendations Among Patients

NARCIS (Netherlands)

de Wit, M.; Bakker, M.; van Bodegom-Vos, L.; Buch, M.; Caeyers, N.; Carluccio, A.; Geenen, R.; Greiff, R.; Glüsing, B.; Gossec, L.; Kent, A.; Poldema, I.; Vliet Vlieland, T.P.M.; Wiek, D.; Schipper, K.

2015-01-01

BACKGROUND Accurate patient information is necessary to make informed health decisions. However, the traditional, scientific wording of professional recommendations is often difficult to understand for lay people. OBJECTIVES To develop a practical guide for patient organizations and health

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

Science.gov (United States)

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

Expected Utility Based Decision Making under Z-Information and Its Application.

Science.gov (United States)

Aliev, Rashad R; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H

2015-01-01

Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics.

Vegetation-Induced Roughness in Low-Reynold's Number Flows

Science.gov (United States)

Piercy, C. D.; Wynn, T. M.

2008-12-01

Wetlands are important ecosystems, providing habitat for wildlife and fish and shellfish production, water storage, erosion control, and water quality improvement and preservation. Models to estimate hydraulic resistance due to vegetation in emergent wetlands are crucial to good wetland design and analysis. The goal of this project is to improve modeling of emergent wetlands by linking properties of the vegetation to flow. Existing resistance equations such as Hoffmann (2004), Kadlec (1990), Moghadam and Kouwen (1997), Nepf (1999), and Stone and Shen (2002) were evaluated. A large outdoor vegetated flume was constructed at the Price's Fork Research Center near Blacksburg, Virginia to measure flow and water surface slope through woolgrass (Scirpus cyperinus), a common native emergent wetland plant. Measurements of clump and stem density, diameter, and volume, blockage factor, and stiffness were made after each set of flume runs. Flow rates through the flume were low (3-4 L/s) resulting in very low stem-Reynold's numbers (15-102). Since experimental flow conditions were in the laminar to transitional range, most of the models considered did not predict velocity or stage accurately except for conditions in which the stem-Reynold's number approached 100. At low stem-Reynold's numbers (drag coefficient is inversely proportional to the Reynold's number and can vary greatly with flow conditions. Most of the models considered assumed a stem-Reynold's number in the 100-105 range in which the drag coefficient is relatively constant and as a result did not predict velocity or stage accurately except for conditions in which the stem-Reynold's number approached 100. The only model that accurately predicted stem layer velocity was the Kadlec (1990) model since it does not make assumptions about flow regime; instead, the parameters are adjusted according to the site conditions. Future work includes relating the parameters used to fit the Kadlec (1990) model to measured vegetation

A Simplified Version of the Fuzzy Decision Method and its Comparison with the Paraconsistent Decision Method

Science.gov (United States)

de Carvalho, Fábio Romeu; Abe, Jair Minoro

2010-11-01

Two recent non-classical logics have been used to make decision: fuzzy logic and paraconsistent annotated evidential logic Et. In this paper we present a simplified version of the fuzzy decision method and its comparison with the paraconsistent one. Paraconsistent annotated evidential logic Et, introduced by Da Costa, Vago and Subrahmanian (1991), is capable of handling uncertain and contradictory data without becoming trivial. It has been used in many applications such as information technology, robotics, artificial intelligence, production engineering, decision making etc. Intuitively, one Et logic formula is type p(a, b), in which a and b belong to [0, 1] (real interval) and represent respectively the degree of favorable evidence (or degree of belief) and the degree of contrary evidence (or degree of disbelief) found in p. The set of all pairs (a; b), called annotations, when plotted, form the Cartesian Unitary Square (CUS). This set, containing a similar order relation of real number, comprises a network, called lattice of the annotations. Fuzzy logic was introduced by Zadeh (1965). It tries to systematize the knowledge study, searching mainly to study the fuzzy knowledge (you don't know what it means) and distinguish it from the imprecise one (you know what it means, but you don't know its exact value). This logic is similar to paraconsistent annotated one, since it attributes a numeric value (only one, not two values) to each proposition (then we can say that it is an one-valued logic). This number translates the intensity (the degree) with which the preposition is true. Let's X a set and A, a subset of X, identified by the function f(x). For each element x∈X, you have y = f(x)∈[0, 1]. The number y is called degree of pertinence of x in A. Decision making theories based on these logics have shown to be powerful in many aspects regarding more traditional methods, like the one based on Statistics. In this paper we present a first study for a simplified

Improving decision speed, accuracy and group cohesion through early information gathering in house-hunting ants.

Science.gov (United States)

Stroeymeyt, Nathalie; Giurfa, Martin; Franks, Nigel R

2010-09-29

Successful collective decision-making depends on groups of animals being able to make accurate choices while maintaining group cohesion. However, increasing accuracy and/or cohesion usually decreases decision speed and vice-versa. Such trade-offs are widespread in animal decision-making and result in various decision-making strategies that emphasize either speed or accuracy, depending on the context. Speed-accuracy trade-offs have been the object of many theoretical investigations, but these studies did not consider the possible effects of previous experience and/or knowledge of individuals on such trade-offs. In this study, we investigated how previous knowledge of their environment may affect emigration speed, nest choice and colony cohesion in emigrations of the house-hunting ant Temnothorax albipennis, a collective decision-making process subject to a classical speed-accuracy trade-off. Colonies allowed to explore a high quality nest site for one week before they were forced to emigrate found that nest and accepted it faster than emigrating naïve colonies. This resulted in increased speed in single choice emigrations and higher colony cohesion in binary choice emigrations. Additionally, colonies allowed to explore both high and low quality nest sites for one week prior to emigration remained more cohesive, made more accurate decisions and emigrated faster than emigrating naïve colonies. These results show that colonies gather and store information about available nest sites while their nest is still intact, and later retrieve and use this information when they need to emigrate. This improves colony performance. Early gathering of information for later use is therefore an effective strategy allowing T. albipennis colonies to improve simultaneously all aspects of the decision-making process--i.e. speed, accuracy and cohesion--and partly circumvent the speed-accuracy trade-off classically observed during emigrations. These findings should be taken into account

How Accurately can we Calculate Thermal Systems?

International Nuclear Information System (INIS)

Cullen, D; Blomquist, R N; Dean, C; Heinrichs, D; Kalugin, M A; Lee, M; Lee, Y; MacFarlan, R; Nagaya, Y; Trkov, A

2004-01-01

I would like to determine how accurately a variety of neutron transport code packages (code and cross section libraries) can calculate simple integral parameters, such as K eff , for systems that are sensitive to thermal neutron scattering. Since we will only consider theoretical systems, we cannot really determine absolute accuracy compared to any real system. Therefore rather than accuracy, it would be more precise to say that I would like to determine the spread in answers that we obtain from a variety of code packages. This spread should serve as an excellent indicator of how accurately we can really model and calculate such systems today. Hopefully, eventually this will lead to improvements in both our codes and the thermal scattering models that they use in the future. In order to accomplish this I propose a number of extremely simple systems that involve thermal neutron scattering that can be easily modeled and calculated by a variety of neutron transport codes. These are theoretical systems designed to emphasize the effects of thermal scattering, since that is what we are interested in studying. I have attempted to keep these systems very simple, and yet at the same time they include most, if not all, of the important thermal scattering effects encountered in a large, water-moderated, uranium fueled thermal system, i.e., our typical thermal reactors

Medical Decision-Making for Adults Who Lack Decision-Making Capacity and a Surrogate: State of the Science.

Science.gov (United States)

Kim, Hyejin; Song, Mi-Kyung

2018-01-01

Adults who lack decision-making capacity and a surrogate ("unbefriended" adults) are a vulnerable, voiceless population in health care. But little is known about this population, including how medical decisions are made for these individuals. This integrative review was to examine what is known about unbefriended adults and identify gaps in the literature. Six electronic databases were searched using 4 keywords: "unbefriended," "unrepresented patients," "adult orphans," and "incapacitated patients without surrogates." After screening, the final sample included 10 data-based articles for synthesis. Main findings include the following: (1) various terms were used to refer to adults who lack decision-making capacity and a surrogate; (2) the number of unbefriended adults was sizable and likely to grow; (3) approaches to medical decision-making for this population in health-care settings varied; and (4) professional guidelines and laws to address the issues related to this population were inconsistent. There have been no studies regarding the quality of medical decision-making and its outcomes for this population or societal impact. Extremely limited empirical data exist on unbefriended adults to develop strategies to improve how medical decisions are made for this population. There is an urgent need for research to examine the quality of medical decision-making and its outcomes for this vulnerable population.

Cognitive Reflection, Decision Biases, and Response Times.

Science.gov (United States)

Alós-Ferrer, Carlos; Garagnani, Michele; Hügelschäfer, Sabine

2016-01-01

We present novel evidence on response times and personality traits in standard questions from the decision-making literature where responses are relatively slow (medians around half a minute or above). To this end, we measured response times in a number of incentivized, framed items (decisions from description) including the Cognitive Reflection Test, two additional questions following the same logic, and a number of classic questions used to study decision biases in probability judgments (base-rate neglect, the conjunction fallacy, and the ratio bias). All questions create a conflict between an intuitive process and more deliberative thinking. For each item, we then created a non-conflict version by either making the intuitive impulse correct (resulting in an alignment question), shutting it down (creating a neutral question), or making it dominant (creating a heuristic question). For CRT questions, the differences in response times are as predicted by dual-process theories, with alignment and heuristic variants leading to faster responses and neutral questions to slower responses than the original, conflict questions. For decision biases (where responses are slower), evidence is mixed. To explore the possible influence of personality factors on both choices and response times, we used standard personality scales including the Rational-Experiential Inventory and the Big Five, and used them as controls in regression analysis.

IND - THE IND DECISION TREE PACKAGE

Science.gov (United States)

Buntine, W.

1994-01-01

A common approach to supervised classification and prediction in artificial intelligence and statistical pattern recognition is the use of decision trees. A tree is "grown" from data using a recursive partitioning algorithm to create a tree which has good prediction of classes on new data. Standard algorithms are CART (by Breiman Friedman, Olshen and Stone) and ID3 and its successor C4 (by Quinlan). As well as reimplementing parts of these algorithms and offering experimental control suites, IND also introduces Bayesian and MML methods and more sophisticated search in growing trees. These produce more accurate class probability estimates that are important in applications like diagnosis. IND is applicable to most data sets consisting of independent instances, each described by a fixed length vector of attribute values. An attribute value may be a number, one of a set of attribute specific symbols, or it may be omitted. One of the attributes is delegated the "target" and IND grows trees to predict the target. Prediction can then be done on new data or the decision tree printed out for inspection. IND provides a range of features and styles with convenience for the casual user as well as fine-tuning for the advanced user or those interested in research. IND can be operated in a CART-like mode (but without regression trees, surrogate splits or multivariate splits), and in a mode like the early version of C4. Advanced features allow more extensive search, interactive control and display of tree growing, and Bayesian and MML algorithms for tree pruning and smoothing. These often produce more accurate class probability estimates at the leaves. IND also comes with a comprehensive experimental control suite. IND consists of four basic kinds of routines: data manipulation routines, tree generation routines, tree testing routines, and tree display routines. The data manipulation routines are used to partition a single large data set into smaller training and test sets. The

Decision trees with minimum average depth for sorting eight elements

KAUST Repository

AbouEisha, Hassan M.; Chikalov, Igor; Moshkov, Mikhail

2015-01-01

We prove that the minimum average depth of a decision tree for sorting 8 pairwise different elements is equal to 620160/8!. We show also that each decision tree for sorting 8 elements, which has minimum average depth (the number of such trees

Use of Decision Tables to Simulate Management in SWAT+

Directory of Open Access Journals (Sweden)

Jeffrey G. Arnold

2018-05-01

Full Text Available Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river–reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+ model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily Nash–Sutcliffe Efficiency (NSE of 0.52 and a percent bias of −1.1%. Using decision tables to simulate management in land, river, and reservoir models was shown to have several advantages over current approaches, including: (1 mature technology with considerable literature and applications; (2 ability to accurately represent complex, real world decision-making; (3 code that is efficient, modular, and easy to maintain; and (4 tables that are easy to maintain, support, and modify.

Risk Estimation as a Decision-Making Tool for Genetic Analysis of the Breast Cancer Susceptibility Genes

Directory of Open Access Journals (Sweden)

Jenny Chang-Claude

1999-01-01

Full Text Available For genetic counselling of a woman on familial breast cancer, an accurate evaluation of the probability that she carries a germ-line mutation is needed to assist in making decisions about genetic-testing.

Towards accurate emergency response behavior

International Nuclear Information System (INIS)

Sargent, T.O.

1981-01-01

Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail

Making effective links to decision-making: Key challenges for health impact assessment

International Nuclear Information System (INIS)

Elliott, Eva; Francis, Sarah

2005-01-01

This paper draws on an exploratory research study to examine the effectiveness of health impact assessments in Wales. Through the review of five case study health impact assessments the research identified a number of benefits of the process in terms of skills and knowledge development amongst participants. The indirect contributions to decision-making were also evident including the way in which health impact assessment provided useful insights into the local community's perspective and raised awareness about the wider determinants of health. The process was also useful in establishing a dialogue between different stakeholders, which indirectly assisted decision-making and implementation. The direct links between health impact assessment and decision-making were more difficult to trace and this paper puts forward a number of suggestions for making those links more transparent. Suggestions include integrating decision-makers and clarifying the intended links to decision-making at the start of the health impact assessment process. Mainstreaming health impact assessment so that it is triggered as a routine part of all decision-making would help ensure it stands the best chance of informing decisions

Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Directory of Open Access Journals (Sweden)

Alfred J. Hildreth

2013-01-01

Full Text Available Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

The madness of crowds phenomenon in the collective decision-making by the cells, the cell's metacognition and cancer

Science.gov (United States)

Saakian, David B.

2018-02-01

Recently it has been found that the collective decision-making in the group is efficient only when the confidences (a version of metacognition) of the members are similar, and it has been assumed that the metacognition (self-reference) in general is crucial for the human cooperation. Our goal is to map the decision making by the cells to decision making by humans, looking the analog of metacognition in the cells, accurately calculate the collective sensing of chemical gradients by the cells, and apply our results to cancer. We formulated the model for the chemeosensing by the cells with different diameters, solved it accurately and found that the collective chemosensing is very similar to the collective decision making by humans. We found that the collective sensing of the ligand concentration can be worse than for the most sensitive cell. We introduced the metacognition of the cells, and verify that the metacognition is impaired for the cancer case. We assume as a hypothesis that the impaired cell metacognition in case of cancer does not allow normal multi-cellularity, and cancer can arise when the "two heads are better than one" principle fails, and there is a "madness of crowds" phenomenon instead.

Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

Science.gov (United States)

Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji

2015-07-01

The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

Regulation of experienced and anticipated regret in daily decision making.

Science.gov (United States)

Bjälkebring, Pär; Västfjäll, Daniel; Svenson, Ola; Slovic, Paul

2016-04-01

Decisions were sampled from 108 participants during 8 days using a web-based diary method. Each day participants rated experienced regret for a decision made, as well as forecasted regret for a decision to be made. Participants also indicated to what extent they used different strategies to prevent or regulate regret. Participants regretted 30% of decisions and forecasted regret in 70% of future decisions, indicating both that regret is relatively prevalent in daily decisions but also that experienced regret was less frequent than forecasted regret. In addition, a number of decision-specific regulation and prevention strategies were successfully used by the participants to minimize regret and negative emotions in daily decision making. Overall, these results suggest that regulation and prevention of regret are important strategies in many of our daily decisions. (c) 2016 APA, all rights reserved).

Deferred Personal Life Decisions of Women Physicians.

Science.gov (United States)

Bering, Jamie; Pflibsen, Lacey; Eno, Cassie; Radhakrishnan, Priya

2018-05-01

Inadequate work-life balance can have significant implications regarding individual performance, retention, and on the future of the workforce in medicine. The purpose of this study was to determine whether women physicians defer personal life decisions in pursuit of their medical career. We conducted a survey study of women physicians ages 20-80 from various medical specialties using a combination of social media platforms and women physicians' professional listservs with 801 survey responses collected from May through November 2015. The primary endpoint was whether women physicians deferred personal life decisions in pursuit of their medical career. Secondary outcomes include types of decisions deferred and correlations with age, hours worked per week, specialty, number of children, and career satisfaction. Respondents were categorized into deferred and nondeferred groups. Personal decision deferments were reported by 64% of respondents. Of these, 86% reported waiting to have children and 22% reported waiting to get married. Finally, while 85% of women in the nondeferment group would choose medicine again as a career, only 71% of women in the deferment group would do so (p job satisfaction, and insurance/administrative burden. The results of this survey have significant implications on the future of the workforce in medicine. Overall, our analysis shows that 64% of women physicians defer important life decisions in pursuit of their medical career. With an increase in the number of women physicians entering the workforce, lack of support and deferred personal decisions have a potential negative impact on individual performance and retention. Employers must consider the economic impact and potential workforce shortages that may develop if these issues are not addressed.

Phonological decisions require both the left and right supramarginal gyri.

Science.gov (United States)

Hartwigsen, Gesa; Baumgaertner, Annette; Price, Cathy J; Koehnke, Maria; Ulmer, Stephan; Siebner, Hartwig R

2010-09-21

Recent functional imaging studies demonstrated that both the left and right supramarginal gyri (SMG) are activated when healthy right-handed subjects make phonological word decisions. However, lesion studies typically report difficulties with phonological processing after left rather than right hemisphere damage. Here, we used a unique dual-site transcranial magnetic stimulation (TMS) approach to test whether the SMG in the right hemisphere contributes to modality-independent (i.e., auditory and visual) phonological decisions. To test task-specificity, we compared the effect of real or sham TMS during phonological, semantic, and perceptual decisions. To test laterality and anatomical specificity, we compared the effect of TMS over the left, right, or bilateral SMG and angular gyri. The accuracy and reaction times of phonological decisions were selectively disrupted relative to semantic and perceptual decisions when real TMS was applied over the left, right, or bilateral SMG. These effects were not observed for TMS over the angular gyri. A follow-up experiment indicated that the threshold-intensity for inducing a disruptive effect on phonological decisions was identical for unilateral TMS over the right or left SMG. Taken together, these findings provide converging evidence that the right SMG contributes to accurate and efficient phonological decisions in the healthy brain, with no evidence that the left and right SMG can compensate for one another during TMS. Our findings motivate detailed studies of phonological processing in patients with acute or long-term damage of the right SMG.

Efficient decision-making by volume-conserving physical object

International Nuclear Information System (INIS)

Kim, Song-Ju; Aono, Masashi; Nameda, Etsushi

2015-01-01

Decision-making is one of the most important intellectual abilities of not only humans but also other biological organisms, helping their survival. This ability, however, may not be limited to biological systems and may be exhibited by physical systems. Here we demonstrate that any physical object, as long as its volume is conserved when coupled with suitable operations, provides a sophisticated decision-making capability. We consider the multi-armed bandit problem (MBP), the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards. Efficient MBP solvers are useful for many practical applications, because MBP abstracts a variety of decision-making problems in real-world situations in which an efficient trial-and-error is required. These decisions are made as dictated by a physical object, which is moved in a manner similar to the fluctuations of a rigid body in a tug-of-war (TOW) game. This method, called ‘TOW dynamics’, exhibits higher efficiency than conventional reinforcement learning algorithms. We show analytical calculations that validate statistical reasons for TOW dynamics to produce the high performance despite its simplicity. These results imply that various physical systems in which some conservation law holds can be used to implement an efficient ‘decision-making object’. The proposed scheme will provide a new perspective to open up a physics-based analog computing paradigm and to understanding the biological information-processing principles that exploit their underlying physics. (paper)

Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

Science.gov (United States)

Lee, Hanbong

2017-01-01

In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

Seniority Number in Valence Bond Theory.

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Chen, Zhenhua; Zhou, Chen; Wu, Wei

2015-09-08

In this work, a hierarchy of valence bond (VB) methods based on the concept of seniority number, defined as the number of singly occupied orbitals in a determinant or an orbital configuration, is proposed and applied to the studies of the potential energy curves (PECs) of H8, N2, and C2 molecules. It is found that the seniority-based VB expansion converges more rapidly toward the full configuration interaction (FCI) or complete active space self-consistent field (CASSCF) limit and produces more accurate PECs with smaller nonparallelity errors than its molecular orbital (MO) theory-based analogue. Test results reveal that the nonorthogonal orbital-based VB theory provides a reverse but more efficient way to truncate the complete active Hilbert space by seniority numbers.

Getting DNA copy numbers without control samples.

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Ortiz-Estevez, Maria; Aramburu, Ander; Rubio, Angel

2012-08-16

The selection of the reference to scale the data in a copy number analysis has paramount importance to achieve accurate estimates. Usually this reference is generated using control samples included in the study. However, these control samples are not always available and in these cases, an artificial reference must be created. A proper generation of this signal is crucial in terms of both noise and bias.We propose NSA (Normality Search Algorithm), a scaling method that works with and without control samples. It is based on the assumption that genomic regions enriched in SNPs with identical copy numbers in both alleles are likely to be normal. These normal regions are predicted for each sample individually and used to calculate the final reference signal. NSA can be applied to any CN data regardless the microarray technology and preprocessing method. It also finds an optimal weighting of the samples minimizing possible batch effects. Five human datasets (a subset of HapMap samples, Glioblastoma Multiforme (GBM), Ovarian, Prostate and Lung Cancer experiments) have been analyzed. It is shown that using only tumoral samples, NSA is able to remove the bias in the copy number estimation, to reduce the noise and therefore, to increase the ability to detect copy number aberrations (CNAs). These improvements allow NSA to also detect recurrent aberrations more accurately than other state of the art methods. NSA provides a robust and accurate reference for scaling probe signals data to CN values without the need of control samples. It minimizes the problems of bias, noise and batch effects in the estimation of CNs. Therefore, NSA scaling approach helps to better detect recurrent CNAs than current methods. The automatic selection of references makes it useful to perform bulk analysis of many GEO or ArrayExpress experiments without the need of developing a parser to find the normal samples or possible batches within the data. The method is available in the open-source R package

Designing Effective Interactions for Concordance around End-of-Life Care Decisions: Lessons from Hospice Admission Nurses

Directory of Open Access Journals (Sweden)

Carey Candrian

2017-04-01

Full Text Available Near the end of life, hospice care reduces symptom-related distress and hospitalizations while improving caregiving outcomes. However, it takes time for a person to gain a sufficient understanding of hospice and decide to enroll. This decision is influenced by knowledge of hospice and its services, emotion and fear, cultural and religious beliefs, and an individual’s acceptance of diagnosis. Hospice admission interactions, a key influence in shaping decisions regarding hospice care, happen particularly late in the illness trajectory and are often complex, unpredictable, and highly variable. One goal of these interactions is ensuring patients and families have accurate and clear information about hospice care to facilitate informed decisions. So inconsistent are practices across hospices in consenting patients that a 2016 report from the Office of Inspector General (OIG entitled “Hospices should improve their election statements and certifications of terminal illness” called for complete and accurate election statements to ensure that hospice patients and their caregivers can make informed decisions and understand the costs and benefits of choosing hospice care. Whether complete and accurate information at initial admission visits improves interactions and outcomes is unknown. Our recent qualitative work investigating interactions between patients, caregivers, and hospice nurses has uncovered diverse and often diverging stakeholder-specific expectations and perceptions which if not addressed can create discordance and inhibit decision-making. This paper focuses on better understanding the communication dynamics and practices involved in hospice admission interactions in order to design more effective interactions and support the mandate from the OIG to provide hospice patients and their caregivers with accurate and complete information. This clarity is particularly important when discussing the non-curative nature of hospice care, and the

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

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Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Acceptability, acceptance and decision making

International Nuclear Information System (INIS)

Ackerschott, H.

2002-01-01

There is a fundamental difference between the acceptability of a civilizatory or societal risk and the acceptability of the decision-making process that leads to a civilizatory or societal risk. The analysis of individual risk decisions - regarding who, executes when which indisputably hazardous, unhealthy or dangerous behaviour under which circumstances - is not helpful in finding solutions for the political decisions at hand in Germany concerning nuclear energy in particular or energy in general. The debt for implementation of any technology, in the sense of making the technology a success in terms of broad acceptance and general utilisation, lies with the particular industry involved. Regardless of the technology, innovation research identifies the implementation phase as most critical to the success of any innovation. In this sense, nuclear technology is at best still an innovation, because the implementation has not yet been completed. Fear and opposition to innovation are ubiquitous. Even the economy - which is often described as 'rational' - is full of this resistance. Innovation has an impact on the pivotal point between stability, the presupposition for the successful execution of decisions already taken and instability, which includes insecurity, but is also necessary for the success of further development. By definition, innovations are beyond our sphere of experience; not at the level of reliability and trust yet to come. Yet they are evaluated via the simplifying heuristics for making decisions proven not only to be necessary and useful, but also accurate in the familiar. The 'settlement of the debt of implementation', the accompanying communication, the decision-making procedures concerning the regulation of averse effects of the technology, but also the tailoring of the new technology or service itself must be directed to appropriate target groups. But the group often aimed at in the nuclear debate, the group, which largely determines political

Automated Decision Tree Classification of Corneal Shape

Science.gov (United States)

Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

2011-01-01

Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification

Accurate estimation of influenza epidemics using Google search data via ARGO.

Science.gov (United States)

Yang, Shihao; Santillana, Mauricio; Kou, S C

2015-11-24

Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives. We propose an influenza tracking model, ARGO (AutoRegression with GOogle search data), that uses publicly available online search data. In addition to having a rigorous statistical foundation, ARGO outperforms all previously available Google-search-based tracking models, including the latest version of Google Flu Trends, even though it uses only low-quality search data as input from publicly available Google Trends and Google Correlate websites. ARGO not only incorporates the seasonality in influenza epidemics but also captures changes in people's online search behavior over time. ARGO is also flexible, self-correcting, robust, and scalable, making it a potentially powerful tool that can be used for real-time tracking of other social events at multiple temporal and spatial resolutions.

Checklist and Decision Support in Nutritional Care for Burned Patients

Science.gov (United States)

2016-10-01

able to construct a checklist of a clinical and physiologic model and then a computerised decision support system that will perform two functions: the...the provision of nutritional therapy, and assessment of use by nursing and physician staff KEYWORDS Nutrition, severe burn, decision support... clinical testing. Checklist and Decision Support in Nutritional Care for Burned Patients Proposal Number: 12340011 W81XWH-12-2-0074 PI: Steven E

How Decisions Can Be Organized - and Why It Matters

Directory of Open Access Journals (Sweden)

Michael Christensen

2013-12-01

Full Text Available Recent theoretical advances allow organizational designers and managers to better understand how decision processes can be improved. These advances allow managers to address a number of critical questions about the structure and process of decision making, issues that are relevant for any kind of organization be it social, political, or economic. Can we add another employee somewhere in the decision process to increase economic performance? Can we add or eliminate a channel of communication to raise the quality of decisions? What level of skill is worth paying for when we hire a decision maker? Is it a good idea to push decision makers beyond their current capacity if doing so increases their error rate by five percent? Where does the injection of inexperienced decision makers hurt the least? We describe an organizational design approach that provides answers to such questions, and we offer specific guidelines that managers can use to improve decision making in their organizations.

The potential for meta-analysis to support decision analysis in ecology.

Science.gov (United States)

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

Science.gov (United States)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Improvement of Statistical Decisions under Parametric Uncertainty

Science.gov (United States)

Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Rozevskis, Uldis

2011-10-01

A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision-making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, application examples are given.

Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

Science.gov (United States)

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2013-01-01

To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

Design and Implementation of Multi Agentbased Information Fusion System for Decision Making Support (A Case Study on Military Operation

Directory of Open Access Journals (Sweden)

Arwin Datunaya Wahyudi Sumari

2013-09-01

Full Text Available Quick, accurate, and complete information is highly required for supporting strategically impact decision making in a Military Operation (MO in order to reduce the decision cycle and to minimize the loss. For that purpose, we propose, design and implement a hierarchical Multi Agentbased Information Fusion System for Decision Making Support (MAIFSDMS. The information fusion is implemented by applying Maximum Score of the Total Sum of Joint Probabilities (MSJP fusion method and is done by a collection of Information Fusion Agents (IFA that forms a multiagent system. MAIFS uses a combination of generalization of Dasarathy and Joint Director’s Laboratory (JDL process models for information fusion mechanism. Information fusion products that are displayed in graphical forms provide comprehensive information regarding the MO’s area dynamics. By observing the graphics resulted from the information fusion, the commandant will have situational awareness and knowledge in order to make the most accurate strategic de cision as fast as possible.

Time series modelling of global mean temperature for managerial decision-making.

Science.gov (United States)

Romilly, Peter

2005-07-01

Climate change has important implications for business and economic activity. Effective management of climate change impacts will depend on the availability of accurate and cost-effective forecasts. This paper uses univariate time series techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon. Although the model is estimated on global temperature data, the methodology could also be applied to temperature data at more localised levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting evaluation shows that the chosen model performs well against rival models. The estimation results confirm the findings of a number of previous studies, namely that global mean temperatures increased significantly throughout the 20th century. The use of GARCH modelling also shows the presence of volatility clustering in the temperature data, and a positive association between volatility and global mean temperature.

Technical report on LWR design decision methodology. Phase I

International Nuclear Information System (INIS)

1980-03-01

Energy Incorporated (EI) was selected by Sandia Laboratories to develop and test on LWR design decision methodology. Contract Number 42-4229 provided funding for Phase I of this work. This technical report on LWR design decision methodology documents the activities performed under that contract. Phase I was a short-term effort to thoroughly review the curret LWR design decision process to assure complete understanding of current practices and to establish a well defined interface for development of initial quantitative design guidelines

Spectrally accurate contour dynamics

International Nuclear Information System (INIS)

Van Buskirk, R.D.; Marcus, P.S.

1994-01-01

We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use

Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management.

Science.gov (United States)

Javidi Sabbaghian, Reza; Zarghami, Mahdi; Nejadhashemi, A Pouyan; Sharifi, Mohammad Bagher; Herman, Matthew R; Daneshvar, Fariborz

2016-03-01

Effective watershed management requires the evaluation of agricultural best management practice (BMP) scenarios which carefully consider the relevant environmental, economic, and social criteria involved. In the Multiple Criteria Decision-Making (MCDM) process, scenarios are first evaluated and then ranked to determine the most desirable outcome for the particular watershed. The main challenge of this process is the accurate identification of the best solution for the watershed in question, despite the various risk attitudes presented by the associated decision-makers (DMs). This paper introduces a novel approach for implementation of the MCDM process based on a comparative neutral risk/risk-based decision analysis, which results in the selection of the most desirable scenario for use in the entire watershed. At the sub-basin level, each scenario includes multiple BMPs with scores that have been calculated using the criteria derived from two cases of neutral risk and risk-based decision-making. The simple additive weighting (SAW) operator is applied for use in neutral risk decision-making, while the ordered weighted averaging (OWA) and induced OWA (IOWA) operators are effective for risk-based decision-making. At the watershed level, the BMP scores of the sub-basins are aggregated to calculate each scenarios' combined goodness measurements; the most desirable scenario for the entire watershed is then selected based on the combined goodness measurements. Our final results illustrate the type of operator and risk attitudes needed to satisfy the relevant criteria within the number of sub-basins, and how they ultimately affect the final ranking of the given scenarios. The methodology proposed here has been successfully applied to the Honeyoey Creek-Pine Creek watershed in Michigan, USA to evaluate various BMP scenarios and determine the best solution for both the stakeholders and the overall stream health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

Science.gov (United States)

Asaad, Sameh W.; Kapur, Mohit

2016-03-15

A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

Arthroscopy Journal Prizes Are Major Decisions.

Science.gov (United States)

Lubowitz, James H; Brand, Jefferson C; Provencher, Matthew T; Rossi, Michael J

2016-01-01

According to the Harvard Business Review, the optimal number of people in a decision-making group is no more than 8. Thus, it is no surprise that 18 Arthroscopy journal associate editors had difficulty making a major decision. In the end, 18 editors did successfully select the 2015 winner of the Best Comparative Study Prize. All studies have limitations, but from a statistical standpoint, the editors believe that the conclusions of the winning study are likely correct. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Use of economic evaluation in decision making: evidence and recommendations for improvement.

Science.gov (United States)

Simoens, Steven

2010-10-22

Information about the value for money of a medicine as derived from an economic evaluation can be used for decision-making purposes by policy makers, healthcare payers, healthcare professionals and pharmaceutical companies. This article illustrates the use of economic evaluation by decision makers and formulates a number of recommendations to enhance the use of such evaluations for decision-making purposes. Over the last decades, there has been a substantial increase in the number of economic evaluations assessing the value for money of medicines. Economic evaluation is used by policy makers and healthcare payers to inform medicine pricing/reimbursement decisions in more and more countries. It is a suitable tool to evaluate medicines and to present information about their value for money to decision makers in a familiar format. In order to fully exploit the use of economic evaluation for decision-making purposes, researchers need to take care to conduct such economic evaluations according to methodologically sound principles. Additionally, researchers need to take into account the decision-making context. They need to identify the various objectives that decision makers pursue and discuss how decision makers can use study findings to attain these objectives. These issues require further attention from researchers, policy makers, healthcare payers, healthcare professionals and pharmaceutical companies with a view to optimizing the use of economic evaluation in decision making.

Decision-making impairment in obsessive-compulsive disorder as measured by the Iowa Gambling Task

Directory of Open Access Journals (Sweden)

Felipe Filardi da Rocha

2011-08-01

Full Text Available OBJECTIVE: This study aims to evaluate the process of decision-making in patients with obsessive-compulsive disorder (OCD using the Iowa Gambling Task (IGT. In addition, we intend to expand the understanding of clinical and demographic characteristics that influence decision-making. METHOD: Our sample consisted of 214 subjects (107 diagnosed with OCD and 107 healthy controls who were evaluated on their clinical, demographic and neuropsychological features. Moreover, the Iowa Gambling Task (IGT, a task that detects and measures decision-making impairments, was used. RESULTS: We found that OCD patients performed significantly worse on the IGT. Furthermore, features such as symptoms of anxiety did not influence IGT performance. CONCLUSION: Impaired decision-making seems to be a key feature of OCD. Given that OCD is a complex heterogeneous disorder, homogeneous groups are necessary for an accurate characterization of our findings.

Mapping customer journeys in multichannel decision-making

OpenAIRE

Wolny, Julia; Charoensuksai, Nipawan

2014-01-01

This study is focused on multi-channel shopping, which refers to the integration of various channels in the consumer decision-making process. The term was coined in the early 2000s to signify the integration of offline and online shopping channels. It has since evolved to encompass the proliferating number of channels and media used to formulate, evaluate and execute buying decisions. With the explosion of mobile technologies and social media, multi-channel shopping has indeed become a journe...

Web-conferencing as a viable method for group decision research

Directory of Open Access Journals (Sweden)

Michel J. J. Handgraaf

2012-09-01

Full Text Available Studying group decision-making is challenging for multiple reasons. An important logistic difficulty is studying a sufficiently large number of groups, each with multiple participants. Assembling groups online could make this process easier and also provide access to group members more representative of real-world work groups than the sample of college students that typically comprise lab Face-to-Face (FtF groups. The main goal of this paper is to compare the decisions of online groups to those of FtF groups. We did so in a study that manipulated gain/loss framing of a risky decision between groups and examined the decisions of both individual group members and groups. All of these dependent measures are compared for an online and an FtF sample. Our results suggest that web-conferencing can be a substitute for FtF interaction in group decision-making research, as we found no moderation effects of communication medium on individual or group decision outcome variables. The effects of medium that were found suggest that the use of online groups may be the preferred method for group research. To wit, discussions among the online groups were shorter, but generated a greater number of thought units, i.e., they made more efficient use of time.

Hesitant fuzzy methods for multiple criteria decision analysis

CERN Document Server

Zhang, Xiaolu

2017-01-01

The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...

Durable decision-making is central to the control of risks

International Nuclear Information System (INIS)

Zebroski, E.L.

1990-01-01

In several capacities the author has promoted the importance of risk analysis techniques as a rational path to the improved assurance of safety. The interest in decisions arose from the persistent observation of only moderate or minor impacts or benefits to practical operations from the availability of wall documented risk analysis studies for many nuclear units. The complexity and number of variables in decisions on matters of safety of large scale operations defies ordinary intuitive decision making. The structured decision process is not a panacea, but is often the practical tool of choise for managing complexity in an orderly way. Typical basic sources for decision techniques are listed in references. (orig.)

Decision Making with Imperfect Decision Makers

CERN Document Server

Guy, Tatiana Valentine; Wolpert, David H

2012-01-01

Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, lit

Ontology-based clinical decision support system applied on diabetes

OpenAIRE

Mukabunani, Alphonsine

2017-01-01

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Medical diagnosis is a multi-step process which is complex as it requires the consideration of many factors. Additionally, the accuracy of diagnosis varies depending on the skill and knowledge a physician has in the medical field. Using ICT solution, the physicians can be assisted so that they can make an accurate decision. Many applications have been developed to enhance physician performance and i...

A new method for ordering triangular fuzzy numbers

Directory of Open Access Journals (Sweden)

S.H. Nasseri

2010-09-01

Full Text Available Ranking fuzzy numbers plays a very important role in linguistic decision making and other fuzzy application systems. In spite of many ranking methods, no one can rank fuzzy numbers with human intuition consistently in all cases. Shortcoming are found in some of the convenient methods for ranking triangular fuzzy numbers such as the coefficient of variation (CV index, distance between fuzzy sets, centroid point and original point, and also weighted mean value. In this paper, we introduce a new method for ranking triangular fuzzy number to overcome the shortcomings of the previous techniques. Finally, we compare our method with some convenient methods for ranking fuzzy numbers to illustrate the advantage our method.

Application of HTA research on policy decision-making.

Science.gov (United States)

Youngkong, Sitaporn

2014-05-01

This article provides an overview of the potential uses of health technology assessment (HTA) in health technology or health intervention-related policy decision-making. It summarises the role of HTA in policy planning, health system investment, price negotiation, development of clinical practice guidelines, and communication with health professionals. While the multifaceted nature of HTA means that some aspects of the data can result in conflicting conclusions, the comprehensive approach of HTA is still recommended. To help minimise the potential conflicts within HTA data, a multicriteria decision analysis (MCDA) approach is recommended as a way to assess a number of decision criteria simultaneously. A combination of HTA with MCDA allows policy decision-making to be undertaken in an empirically rigorous and rational way. This combination can be used to support policy decision-makers in Thailand and help them prioritise topics for assessment and make informed health benefit package coverage decisions. This approach enhances the legitimacy of policy decisions by increasing the transparency, systematic nature, and inclusiveness of the process.

The impact of excess choice on deferment of decisions to volunteer

Directory of Open Access Journals (Sweden)

Lauren S. Carroll

2011-10-01

Full Text Available Excess choice has previously been shown to have detrimental effects on decisions about consumer products. As the number of options increases, people are more likely to put off making an active choice (i.e., defer and show less satisfaction with any purchase actually made. We extend this line of enquiry to choosing a charitable organisation to volunteer for. The issue is important because the number of voluntary organisations is enormous and the impact of such a decision may be greater than for consumer decisions in terms of time commitment and benefits to the volunteer and society. Study 1 asked students to examine a real volunteering website and record how many organisations they considered, decision difficulty and whether or not they would like to sign up for a chosen organisation or prefer to defer a decision. Study 2 presented either a relatively small (10 or large (30 choice set of hypothetical organisations and measured deferment likelihood and decision difficulty. In both studies the more options considered, the greater the likelihood to defer. This effect was mediated by decision difficulty. This research is the first to find that detrimental effects of excess choice extend to volunteering. Implications for volunteer recruitment are discussed.

Decision-making in administrative proceeding

Directory of Open Access Journals (Sweden)

Lončar Zoran J.

2015-01-01

Full Text Available Administrative decision-making by official who conducting the administrative procedure may have a number of advantages over the decisionmaking by the senior official which manages by the administrative authority. However, to make that such a novelty have positive effects, it is necessary, next to the amendments to the Law on Administrative Procedure, to create a number of legal and factual assumptions, on whom are based highly politicized and professionalised administrative systems today. In order to create the legal conditions for the introduction of innovations in administrative proceedings in the Republic of Serbia, it is necessary to appropriately modify, firstly certain provisions of the Law on Public Administration, as the basic systemic regulation in this area, and then the Law on Civil Servants, as the basic status regulation, so the civil servant career become less dependent on the will of officials who manage by the administrative authorities. Also, it is essential to solve a number of other issues on a proper legal way, such as way of harmonizing administrative practice within the same administrative authority, a way of solving the appeals in the case of first instance decisions made by independent administrative authority, different rules for conflict of interest with the state officers who may be authorized officials in administrative proceedings, etc.

Uncertainty about probability: a decision analysis perspective

International Nuclear Information System (INIS)

Howard, R.A.

1988-01-01

The issue of how to think about uncertainty about probability is framed and analyzed from the viewpoint of a decision analyst. The failure of nuclear power plants is used as an example. The key idea is to think of probability as describing a state of information on an uncertain event, and to pose the issue of uncertainty in this quantity as uncertainty about a number that would be definitive: it has the property that you would assign it as the probability if you knew it. Logical consistency requires that the probability to assign to a single occurrence in the absence of further information be the mean of the distribution of this definitive number, not the medium as is sometimes suggested. Any decision that must be made without the benefit of further information must also be made using the mean of the definitive number's distribution. With this formulation, they find further that the probability of r occurrences in n exchangeable trials will depend on the first n moments of the definitive number's distribution. In making decisions, the expected value of clairvoyance on the occurrence of the event must be at least as great as that on the definitive number. If one of the events in question occurs, then the increase in probability of another such event is readily computed. This means, in terms of coin tossing, that unless one is absolutely sure of the fairness of a coin, seeing a head must increase the probability of heads, in distinction to usual thought. A numerical example for nuclear power shows that the failure of one plant of a group with a low probability of failure can significantly increase the probability that must be assigned to failure of a second plant in the group

Seasonality in communication and collective decision-making in ants.

Science.gov (United States)

Stroeymeyt, N; Jordan, C; Mayer, G; Hovsepian, S; Giurfa, M; Franks, N R

2014-04-07

The ability of animals to adjust their behaviour according to seasonal changes in their ecology is crucial for their fitness. Eusocial insects display strong collective behavioural seasonality, yet the mechanisms underlying such changes are poorly understood. We show that nest preference by emigrating Temnothorax albipennis ant colonies is influenced by a season-specific modulatory pheromone that may help tune decision-making according to seasonal constraints. The modulatory pheromone triggers aversion towards low-quality nests and enhances colony cohesion in summer and autumn, but not after overwintering-in agreement with reports that field colonies split in spring and reunite in summer. Interestingly, we show that the pheromone acts by downgrading the perceived value of marked nests by informed and naive individuals. This contrasts with theories of collective intelligence, stating that accurate collective decision-making requires independent evaluation of options by individuals. The violation of independence highlighted here was accordingly shown to increase error rate during emigrations. However, this is counterbalanced by enhanced cohesion and the transmission of valuable information through the colony. Our results support recent claims that optimal decisions are not necessarily those that maximize accuracy. Other criteria-such as cohesion or reward rate-may be more relevant in animal decision-making.

Gaussian distribution of LMOV numbers

Directory of Open Access Journals (Sweden)

A. Mironov

2017-11-01

Full Text Available Recent advances in knot polynomial calculus allowed us to obtain a huge variety of LMOV integers counting degeneracy of the BPS spectrum of topological theories on the resolved conifold and appearing in the genus expansion of the plethystic logarithm of the Ooguri–Vafa partition functions. Already the very first look at this data reveals that the LMOV numbers are randomly distributed in genus (! and are very well parameterized by just three parameters depending on the representation, an integer and the knot. We present an accurate formulation and evidence in support of this new puzzling observation about the old puzzling quantities. It probably implies that the BPS states, counted by the LMOV numbers can actually be composites made from some still more elementary objects.

Introduction to Modeling of Buying Decisions

Directory of Open Access Journals (Sweden)

O. Gruenwald

2011-01-01

Full Text Available Buying decision models of customers to adjust the competitiveness of organizations have been a challenge for marketing disciplines for several generations. This topic has been explored by researchers and academics in past years, and quite an extensive theoretical base exists with a number of approaches for dealing with this challenge.This paper presents some approaches for creating a customer decision model, and provides experimental results from an electronic investigation intended to build the Kano Model; to prove an ability to understand the modeling principle; and to find out the interpretation of the examined demand in a specific market segment involving students of a technical university. The last section of the paper contains a brief introduction to Choice-Based Modeling with Choice-Based Conjoint Analysis (CBC, which was tailored for modeling purchasing decisions.

Examining Event-Related Potential (ERP) correlates of decision bias in recognition memory judgments.

Science.gov (United States)

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500-700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions.

Examining Event-Related Potential (ERP) Correlates of Decision Bias in Recognition Memory Judgments

Science.gov (United States)

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500–700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions. PMID

Examining Event-Related Potential (ERP correlates of decision bias in recognition memory judgments.

Directory of Open Access Journals (Sweden)

Holger Hill

Full Text Available Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure. Event related potentials (ERP correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias. In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320 that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500-700 ms poststimulus, bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions.

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

Science.gov (United States)

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Child Protection Decision Making: A Factorial Analysis Using Case Vignettes

Science.gov (United States)

Stokes, Jacqueline; Schmidt, Glen

2012-01-01

This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed…

Optimising Transport Decision Making using Customised Decision Models and Decision Conferences

DEFF Research Database (Denmark)

Barfod, Michael Bruhn

The subject of this Ph.D. thesis entitled “Optimising Transport Decision Making using Customised Decision Models and Decision Conferences” is multi-criteria decision analysis (MCDA) and decision support in the context of transport infrastructure assessments. Despite the fact that large amounts...... is concerned with the insufficiency of conventional cost-benefit analysis (CBA), and proposes the use of MCDA as a supplementing tool in order to also capture impacts of a more strategic character in the appraisals and hence make more use of the often large efforts put in the preliminary examinations. MCDA...... and rail to bike transport projects. Two major concerns have been to propose an examination process that can be used in situations where complex decision problems need to be addressed by experts as well as non-experts in decision making, and to identify appropriate assessment techniques to be used...

Decision theory with resource-bounded agents.

Science.gov (United States)

Halpern, Joseph Y; Pass, Rafael; Seeman, Lior

2014-04-01

There have been two major lines of research aimed at capturing resource-bounded players in game theory. The first, initiated by Rubinstein (), charges an agent for doing costly computation; the second, initiated by Neyman (), does not charge for computation, but limits the computation that agents can do, typically by modeling agents as finite automata. We review recent work on applying both approaches in the context of decision theory. For the first approach, we take the objects of choice in a decision problem to be Turing machines, and charge players for the "complexity" of the Turing machine chosen (e.g., its running time). This approach can be used to explain well-known phenomena like first-impression-matters biases (i.e., people tend to put more weight on evidence they hear early on) and belief polarization (two people with different prior beliefs, hearing the same evidence, can end up with diametrically opposed conclusions) as the outcomes of quite rational decisions. For the second approach, we model people as finite automata, and provide a simple algorithm that, on a problem that captures a number of settings of interest, provably performs optimally as the number of states in the automaton increases. Copyright © 2014 Cognitive Science Society, Inc.

DNA copy number, including telomeres and mitochondria, assayed using next-generation sequencing

Directory of Open Access Journals (Sweden)

Jackson Stuart

2010-04-01

Full Text Available Abstract Background DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number. Results We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual. Conclusion The described assay outputs absolute copy number, outputs an error estimate (p-value, and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads.

A decision support system using combined-classifier for high-speed data stream in smart grid

Science.gov (United States)

Yang, Hang; Li, Peng; He, Zhian; Guo, Xiaobin; Fong, Simon; Chen, Huajun

2016-11-01

Large volume of high-speed streaming data is generated by big power grids continuously. In order to detect and avoid power grid failure, decision support systems (DSSs) are commonly adopted in power grid enterprises. Among all the decision-making algorithms, incremental decision tree is the most widely used one. In this paper, we propose a combined classifier that is a composite of a cache-based classifier (CBC) and a main tree classifier (MTC). We integrate this classifier into a stream processing engine on top of the DSS such that high-speed steaming data can be transformed into operational intelligence efficiently. Experimental results show that our proposed classifier can return more accurate answers than other existing ones.

Safety validation of decision trees for hepatocellular carcinoma.

Science.gov (United States)

Wang, Xian-Qiang; Liu, Zhe; Lv, Wen-Ping; Luo, Ying; Yang, Guang-Yun; Li, Chong-Hui; Meng, Xiang-Fei; Liu, Yang; Xu, Ke-Sen; Dong, Jia-Hong

2015-08-21

To evaluate a different decision tree for safe liver resection and verify its efficiency. A total of 2457 patients underwent hepatic resection between January 2004 and December 2010 at the Chinese PLA General Hospital, and 634 hepatocellular carcinoma (HCC) patients were eligible for the final analyses. Post-hepatectomy liver failure (PHLF) was identified by the association of prothrombin time 50 μmol/L (the "50-50" criteria), which were assessed at day 5 postoperatively or later. The Swiss-Clavien decision tree, Tokyo University-Makuuchi decision tree, and Chinese consensus decision tree were adopted to divide patients into two groups based on those decision trees in sequence, and the PHLF rates were recorded. The overall mortality and PHLF rate were 0.16% and 3.0%. A total of 19 patients experienced PHLF. The numbers of patients to whom the Swiss-Clavien, Tokyo University-Makuuchi, and Chinese consensus decision trees were applied were 581, 573, and 622, and the PHLF rates were 2.75%, 2.62%, and 2.73%, respectively. Significantly more cases satisfied the Chinese consensus decision tree than the Swiss-Clavien decision tree and Tokyo University-Makuuchi decision tree (P decision trees. The Chinese consensus decision tree expands the indications for hepatic resection for HCC patients and does not increase the PHLF rate compared to the Swiss-Clavien and Tokyo University-Makuuchi decision trees. It would be a safe and effective algorithm for hepatectomy in patients with hepatocellular carcinoma.

How well-run boards make decisions.

Science.gov (United States)

Useem, Michael

2006-11-01

In the aftermath of seismic debacles like those that toppled Enron and WorldCom, corporate boards have been shaken up and made over. More directors are independent these days, for instance, and corporations now disclose directors' salaries and committee members' names. Research shows that most of the changes are having a positive effect on companies' performance. They are primarily structural, though, and don't go to the heart of a board's work: making the choices that shape a firm's future. Which decisions boards own and how those calls are made are largely hidden from the public. As a result, boards are often unable to learn from the best governance practices of their counterparts at other companies. This article pulls back the curtain and provides an inside look. Drawing on interviews with board members and executives at 31 companies, along with a close examination of three boardroom decisions, the author identifies several formal processes that can help companies improve their decision making: creating calendars that specify when the board and the standing committees will consider key items; drafting charters that define the decisions committees are responsible for; and developing decision protocols that divvy up responsibilities between directors and executives. The author also identifies a number of informal decision-making principles: Items that are strategically significant and touch on the firm's core values should go to the board. Large decisions should be divided into small pieces, so the board can devote sufficient attention to each one. Directors must remain vigilant to ensure that their decisions are effectively implemented. The CEO and either the nonexecutive chair or the lead director should engage in ongoing dialogue regarding which decisions to take to the full board and when. And directors should challenge assumptions before making yes-or-no decisions on management proposals.

The Impact of Forecasting on Strategic Planning and Decision Making

African Journals Online (AJOL)

Nekky Umera

strategies for the investment manager in relations to Nigeria stock market ... Forecasting generally involves using information from the past to make decision ..... that both number of share in unit and number of deal in share cannot account.

Decision-making process related to treatment and management in Korean women with breast cancer: Finding the right individualized healthcare trajectory.

Science.gov (United States)

Kim, Kkotbong; Yang, Jinhyang

2017-06-01

After being diagnosed with breast cancer, women must make a number of decisions about their treatment and management. When the decision-making process among breast cancer patients is ineffective, it results in harm to their health. Little is known about the decision-making process of breast cancer patients during the entire course of treatment and management. We investigated women with breast cancer to explore the decision-making processes related to treatment and management. Eleven women participated, all of whom were receiving treatment or management in Korea. The average participant age was 43.5years. For data collection and analysis, a grounded theory methodology was used. Through constant comparative analyses, a core category emerged that we referred to as "finding the right individualized healthcare trajectory." The decision-making process occurred in four phases: turmoil, exploration, balance, and control. The turmoil phase included weighing the credibility of information and lowering the anxiety level. The exploration phase included assessing the expertise/promptness of medical treatment and evaluating the effectiveness of follow-up management. The balance phase included performing analyses from multiple angles and rediscovering value as a human being. The control phase included constructing an individualized management system and following prescribed and other management options. It is important to provide patients with accurate information related to the treatment and management of breast cancer so that they can make effective decisions. Healthcare providers should engage with patients on issues related to their disease, understand the burden placed on patients because of issues related to their sex, and ensure that the patient has a sufficient support system. The results of this study can be used to develop phase-specific, patient-centered, and tailored interventions for breast cancer patients. Copyright © 2017 Elsevier Inc. All rights reserved.

[Decision modeling for economic evaluation of health technologies].

Science.gov (United States)

de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

2014-10-01

Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.

A Large Group Decision Making Approach Based on TOPSIS Framework with Unknown Weights Information

Directory of Open Access Journals (Sweden)

Li Yupeng

2017-01-01

Full Text Available Large group decision making considering multiple attributes is imperative in many decision areas. The weights of the decision makers (DMs is difficult to obtain for the large number of DMs. To cope with this issue, an integrated multiple-attributes large group decision making framework is proposed in this article. The fuzziness and hesitation of the linguistic decision variables are described by interval-valued intuitionistic fuzzy sets. The weights of the DMs are optimized by constructing a non-linear programming model, in which the original decision matrices are aggregated by using the interval-valued intuitionistic fuzzy weighted average operator. By solving the non-linear programming model with MATLAB®, the weights of the DMs and the fuzzy comprehensive decision matrix are determined. Then the weights of the criteria are calculated based on the information entropy theory. At last, the TOPSIS framework is employed to establish the decision process. The divergence between interval-valued intuitionistic fuzzy numbers is calculated by interval-valued intuitionistic fuzzy cross entropy. A real-world case study is constructed to elaborate the feasibility and effectiveness of the proposed methodology.

Understanding power plant investment decision processes

NARCIS (Netherlands)

Groot, J.; Richstein, J.C.; De Vries, L.J.

2013-01-01

In order to understand how companies make investment decisions under conditions of deep uncertainty, we interviewed a number of actors in the Dutch electricity sector. Most of the economic literature that is devoted to this question is prescriptive in nature, describing rational methods to the

Is decision making in hypoxia affected by pre-acclimatisation? A randomized controlled trial.

Science.gov (United States)

Niedermeier, Martin; Weisleitner, Andreas; Lamm, Claus; Ledochowski, Larissa; Frühauf, Anika; Wille, Maria; Burtscher, Martin; Kopp, Martin

2017-05-01

Decision making is impaired in hypoxic environments, which may have serious or even lethal consequences for mountaineers. An acclimatisation period prior to high altitude exposures may help to overcome adverse effects of hypoxia. Thus, we investigated possible effects of short-term pre-acclimatisation on decision making in hypoxia. In a randomized controlled study design, 52 healthy participants were allocated to a hypoxia group (HG: short-term pre-acclimatisation by the use of intermittent hypoxia 7×1h at F i O 2 =12.6%, equivalent to 4500m) or a control group (CG: sham pre-acclimatisation 7×1h at F i O 2 =20.9%, equivalent to 600m). The number of risky decisions was assessed using the Game of Dice Task at four time points during a 12-hours stay in hypoxia (F i O 2 =12.6%). 42 (HG: 27, CG: 25) participants completed the study. The number of risky decisions was significantly (p=0.048 as determined by 4×2 ANCOVA) reduced in the hypoxia group compared to the control group, partial η 2 =0.11, when the age-effect on decision making was controlled. Self-reported positive affective valence prior to decision making was negatively related to the number of risky decisions, rdecision making in hypoxia in a positive way and might be considered as a risk-reducing preparation method prior to exposures to hypoxic environments. Positive affective states seem to have a medium-sized protective effect against risky decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

An accurate nonlinear Monte Carlo collision operator

International Nuclear Information System (INIS)

Wang, W.X.; Okamoto, M.; Nakajima, N.; Murakami, S.

1995-03-01

A three dimensional nonlinear Monte Carlo collision model is developed based on Coulomb binary collisions with the emphasis both on the accuracy and implementation efficiency. The operator of simple form fulfills particle number, momentum and energy conservation laws, and is equivalent to exact Fokker-Planck operator by correctly reproducing the friction coefficient and diffusion tensor, in addition, can effectively assure small-angle collisions with a binary scattering angle distributed in a limited range near zero. Two highly vectorizable algorithms are designed for its fast implementation. Various test simulations regarding relaxation processes, electrical conductivity, etc. are carried out in velocity space. The test results, which is in good agreement with theory, and timing results on vector computers show that it is practically applicable. The operator may be used for accurately simulating collisional transport problems in magnetized and unmagnetized plasmas. (author)

Influence of acute stress on decision outcomes and heuristics.

Science.gov (United States)

Hepler, Teri J; Kovacs, Attila J

2017-03-01

The purpose of this study was to examine the take-the-first (TTF) heuristic and decision outcomes in sports under conditions of no, mental, and physical stress. Participants (N.=68) performed 8 video decision-making trials under each of 3 stress conditions: no stress (counting backwards), mental stress (mental serial subtraction), and physical stress (running on treadmill at 13 RPE). Prior to each decision-making trial, participants were exposed to 30 seconds of stress. The decision-making task required participants to watch a video depicting an offensive situation in basketball and then decide what the player with the ball should do next. No differences were found between the 3 stress conditions on TTF frequency, number of options generated, quality of first generated option, or final decision quality. However, participants performing under conditions of no stress and physical stress generated their first option and made their final decision faster than they did when making decisions under mental stress. Overall, results suggest that mental stress impairs decision speed and that TTF is an ecologically rationale heuristic in dynamic, time-pressured situations.

Disentangling participation power and decision-making in participatory design

CERN Document Server

Bratteteig, Tone

2014-01-01

Providing a critical view on user participation in design, disentangling decision making and power in design, this book uses fieldwork material from two large participatory design projects: one experimental in the field of urban planning, the other a product development project within health care. Addressing power issues in participatory design is critical to providing a realistic view of the possibilities and limitations of participation. Design is decision-making: during a design process a huge number of decisions?taken before the designers end up with a design result - an artefact or system

The thinking doctor: clinical decision making in contemporary medicine.

Science.gov (United States)

Trimble, Michael; Hamilton, Paul

2016-08-01

Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. © 2016 Royal College of Physicians.

Area 2 Photo Skid Wastewater Pit corrective action decision document Corrective Action Unit Number 332: Part 1, and Closure report: Part 2

International Nuclear Information System (INIS)

1997-01-01

The Area 2 Photo Skid Wastewater Pit, Corrective Action Site (CAS) Number 02-42-03, the only CAS in Corrective Action Unit (CAU) Number 332, has been identified as a source of unquantified, uncontrolled, and unpermitted wastewater discharge. The Photo Skid was used for photographic processing of film for projects related to weapons testing, using Kodak RA4 and GPX film processing facilities for black and white and color photographs. The CAU is located in Area 2 of the Nevada Test Site, Nye County, Nevada. The CAS consists of one unlined pit which received discharged photographic process wastewater from 1984 to 1991. The Corrective Action Decision Document (CADD) and the Closure Report (CR) have been developed to meet the requirements of the Federal Facility Agreement and Consent Order (FFACO, 1996). The CADD and the CR for this CAS have been combined because sample data collected during the site investigation do not exceed regulatory limits established during the Data Quality Objectives (DQO) process. The purpose of the CADD and the CR is to justify why no corrective action is necessary at the CAU based on process knowledge and the results of the corrective action investigation and to request closure of the CAU. This document contains Part 1 of the CADD and Part 2 of the CR

Visual Communication and Cognition in Everyday Decision-Making.

Science.gov (United States)

Jaenichen, Claudine

2017-01-01

Understanding cognition and the context of decision-making should be prioritized in the design process in order to accurately anticipate the outcome for intended audiences. A thorough understanding of cognition has been excluded from being a part of foundational design principals in visual communication. By defining leisure, direct, urgent, and emergency scenarios and providing examples of work that deeply considers the viewer's relationship to the design solution in context of these scenarios allows us to affirm the relevancy of cognition as a design variable and the importance of projects that advocate public utility.

Application of fuzzy decision-making method in nuclear emergency

International Nuclear Information System (INIS)

Xu Zhixin; Xi Shuren; Qu Jingyuan

2005-01-01

Protective actions such as evacuation, sheltering and iodine administration can be taken to mitigate the radiological consequence in the event of an accidental release. In general, decision-making of countermeasures involves both quantitative and qualitative criteria. The conventional approaches to assessing these criteria tend to be less effective when dealing with those qualitative criteria that are imprecise or vague. In this regard, fuzzy set method is an alternative tool. It can cope with vague assessment in a better way. This paper presents the application of fussy methodology to decision-making of protective actions in nuclear emergencies. In this method linguistic terms and fuzzy triangular numbers are used to represent decision-maker's subjective assessment for different decision criteria considered and decision alternatives versus the decision criteria. Following the assessment performed by specialists, corresponding evaluations can be synthesized and ranked. Finally, the optimal strategy for implementing protective actions can be recommended. (authors)

Accurate density-functional calculations on large systems: Fullerenes and magnetic clusters

International Nuclear Information System (INIS)

Dunlap, B.I.

1996-01-01

Efforts to accurately compute all-electron density-functional energies for large molecules and clusters using Gaussian basis sets will be reviewed. The foundation of this effort, variational fitting, will be described and followed by three applications of the method. The first application concerns fullerenes. When first discovered, C 60 is quite unstable relative to the higher fullerenes. In addition, to raising questions about the relative abundance of the various fullerenes, this work conflicted with the then state-of-the art density-funcitonal calculations on crystalline graphite. Now high accuracy molecular and band structure calculations are in fairly good agreement. Second, we have used these methods to design transition metal clusters having the highest magnetic moment by maximizing the symmetry-required degeneracy of the one-electron orbitals. Most recently, we have developed accurate, variational generalized-gradient approximation (GGA) forces for use in geometry optimization of clusters and in molecular-dynamics simulations of friction. The GGA optimized geometries of a number of large clusters will be given

A simple threshold rule is sufficient to explain sophisticated collective decision-making.

Directory of Open Access Journals (Sweden)

Elva J H Robinson

Full Text Available Decision-making animals can use slow-but-accurate strategies, such as making multiple comparisons, or opt for simpler, faster strategies to find a 'good enough' option. Social animals make collective decisions about many group behaviours including foraging and migration. The key to the collective choice lies with individual behaviour. We present a case study of a collective decision-making process (house-hunting ants, Temnothorax albipennis, in which a previously proposed decision strategy involved both quality-dependent hesitancy and direct comparisons of nests by scouts. An alternative possible decision strategy is that scouting ants use a very simple quality-dependent threshold rule to decide whether to recruit nest-mates to a new site or search for alternatives. We use analytical and simulation modelling to demonstrate that this simple rule is sufficient to explain empirical patterns from three studies of collective decision-making in ants, and can account parsimoniously for apparent comparison by individuals and apparent hesitancy (recruitment latency effects, when available nests differ strongly in quality. This highlights the need to carefully design experiments to detect individual comparison. We present empirical data strongly suggesting that best-of-n comparison is not used by individual ants, although individual sequential comparisons are not ruled out. However, by using a simple threshold rule, decision-making groups are able to effectively compare options, without relying on any form of direct comparison of alternatives by individuals. This parsimonious mechanism could promote collective rationality in group decision-making.

A simple threshold rule is sufficient to explain sophisticated collective decision-making.

Science.gov (United States)

Robinson, Elva J H; Franks, Nigel R; Ellis, Samuel; Okuda, Saki; Marshall, James A R

2011-01-01

Decision-making animals can use slow-but-accurate strategies, such as making multiple comparisons, or opt for simpler, faster strategies to find a 'good enough' option. Social animals make collective decisions about many group behaviours including foraging and migration. The key to the collective choice lies with individual behaviour. We present a case study of a collective decision-making process (house-hunting ants, Temnothorax albipennis), in which a previously proposed decision strategy involved both quality-dependent hesitancy and direct comparisons of nests by scouts. An alternative possible decision strategy is that scouting ants use a very simple quality-dependent threshold rule to decide whether to recruit nest-mates to a new site or search for alternatives. We use analytical and simulation modelling to demonstrate that this simple rule is sufficient to explain empirical patterns from three studies of collective decision-making in ants, and can account parsimoniously for apparent comparison by individuals and apparent hesitancy (recruitment latency) effects, when available nests differ strongly in quality. This highlights the need to carefully design experiments to detect individual comparison. We present empirical data strongly suggesting that best-of-n comparison is not used by individual ants, although individual sequential comparisons are not ruled out. However, by using a simple threshold rule, decision-making groups are able to effectively compare options, without relying on any form of direct comparison of alternatives by individuals. This parsimonious mechanism could promote collective rationality in group decision-making.

How is Shared Decision-Making Defined among African-Americans with Diabetes?

Science.gov (United States)

Peek, Monica E.; Quinn, Michael T.; Gorawara-Bhat, Rita; Odoms-Young, Angela; Wilson, Shannon C.; Chin, Marshall H.

2011-01-01

Objective This study investigates how shared decision-making (SDM) is defined by African-American patients with diabetes, and compares patients’ conceptualization of SDM with the Charles model. Methods We utilized race-concordant interviewers/moderators to conduct in-depth interviews and focus groups among a purposeful sample of African-American patients with diabetes. Each interview/focus group was audio-taped, transcribed verbatim and imported into Atlas.ti software. Coding was done using an iterative process and each transcription was independently coded by two members of the research team. Results Although the conceptual domains were similar, patient definitions of what it means to “share” in the decision-making process differed significantly from the Charles model of SDM. Patients stressed the value of being able to “tell their story and be heard” by physicians, emphasized the importance of information sharing rather than decision-making sharing, and included an acceptable role for non-adherence as a mechanism to express control and act on treatment preferences. Conclusion Current instruments may not accurately measure decision-making preferences of African-American patients with diabetes. Practice Implications Future research should develop instruments to effectively measure decision-making preferences within this population. Emphasizing information-sharing that validates patients’ experiences may be particularly meaningful to African-Americans with diabetes. PMID:18684581

Highly accurate prediction of food challenge outcome using routinely available clinical data.

Science.gov (United States)

DunnGalvin, Audrey; Daly, Deirdre; Cullinane, Claire; Stenke, Emily; Keeton, Diane; Erlewyn-Lajeunesse, Mich; Roberts, Graham C; Lucas, Jane; Hourihane, Jonathan O'B

2011-03-01

Serum specific IgE or skin prick tests are less useful at levels below accepted decision points. We sought to develop and validate a model to predict food challenge outcome by using routinely collected data in a diverse sample of children considered suitable for food challenge. The proto-algorithm was generated by using a limited data set from 1 service (phase 1). We retrospectively applied, evaluated, and modified the initial model by using an extended data set in another center (phase 2). Finally, we prospectively validated the model in a blind study in a further group of children undergoing food challenge for peanut, milk, or egg in the second center (phase 3). Allergen-specific models were developed for peanut, egg, and milk. Phase 1 (N = 429) identified 5 clinical factors associated with diagnosis of food allergy by food challenge. In phase 2 (N = 289), we examined the predictive ability of 6 clinical factors: skin prick test, serum specific IgE, total IgE minus serum specific IgE, symptoms, sex, and age. In phase 3 (N = 70), 97% of cases were accurately predicted as positive and 94% as negative. Our model showed an advantage in clinical prediction compared with serum specific IgE only, skin prick test only, and serum specific IgE and skin prick test (92% accuracy vs 57%, and 81%, respectively). Our findings have implications for the improved delivery of food allergy-related health care, enhanced food allergy-related quality of life, and economized use of health service resources by decreasing the number of food challenges performed. Copyright © 2011 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems

Directory of Open Access Journals (Sweden)

Kryszczuk Krzysztof

2007-01-01

Full Text Available We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature and multimodal (speech and face systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.

Accurate Evaluation of Quantum Integrals

Science.gov (United States)

Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)

1995-01-01

Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

Improving decision speed, accuracy and group cohesion through early information gathering in house-hunting ants.

Directory of Open Access Journals (Sweden)

Nathalie Stroeymeyt

Full Text Available BACKGROUND: Successful collective decision-making depends on groups of animals being able to make accurate choices while maintaining group cohesion. However, increasing accuracy and/or cohesion usually decreases decision speed and vice-versa. Such trade-offs are widespread in animal decision-making and result in various decision-making strategies that emphasize either speed or accuracy, depending on the context. Speed-accuracy trade-offs have been the object of many theoretical investigations, but these studies did not consider the possible effects of previous experience and/or knowledge of individuals on such trade-offs. In this study, we investigated how previous knowledge of their environment may affect emigration speed, nest choice and colony cohesion in emigrations of the house-hunting ant Temnothorax albipennis, a collective decision-making process subject to a classical speed-accuracy trade-off. METHODOLOGY/PRINCIPAL FINDINGS: Colonies allowed to explore a high quality nest site for one week before they were forced to emigrate found that nest and accepted it faster than emigrating naïve colonies. This resulted in increased speed in single choice emigrations and higher colony cohesion in binary choice emigrations. Additionally, colonies allowed to explore both high and low quality nest sites for one week prior to emigration remained more cohesive, made more accurate decisions and emigrated faster than emigrating naïve colonies. CONCLUSIONS/SIGNIFICANCE: These results show that colonies gather and store information about available nest sites while their nest is still intact, and later retrieve and use this information when they need to emigrate. This improves colony performance. Early gathering of information for later use is therefore an effective strategy allowing T. albipennis colonies to improve simultaneously all aspects of the decision-making process--i.e. speed, accuracy and cohesion--and partly circumvent the speed-accuracy trade

Shared decision-making during surgical consultation for gallstones at a safety-net hospital.

Science.gov (United States)

Mueck, Krislynn M; Leal, Isabel M; Wan, Charlie C; Goldberg, Braden F; Saunders, Tamara E; Millas, Stefanos G; Liang, Mike K; Ko, Tien C; Kao, Lillian S

2018-04-01

Understanding patient perspectives regarding shared decision-making is crucial to providing informed, patient-centered care. Little is known about perceptions of vulnerable patients regarding shared decision-making during surgical consultation. The purpose of this study was to evaluate whether a validated tool reflects perceptions of shared decision-making accurately among patients seeking surgical consultation for gallstones at a safety-net hospital. A mixed methods study was conducted in a sample of adult patients with gallstones evaluated at a safety-net surgery clinic between May to July 2016. Semi-structured interviews were conducted after their initial surgical consultation and analyzed for emerging themes. Patients were administered the Shared Decision-Making Questionnaire and Autonomy Preference Scale. Univariate analyses were performed to identify factors associated with shared decision-making and to compare the results of the surveys to those of the interviews. The majority of patients (N = 30) were female (90%), Hispanic (80%), Spanish-speaking (70%), and middle-aged (45.7 ± 16 years). The proportion of patients who perceived shared decision-making was greater in the Shared Decision-Making Questionnaire versus the interviews (83% vs 27%, P decision for operation was not associated with shared decision-making. Contributory factors to this discordance include patient unfamiliarity with shared decision-making, deference to surgeon authority, lack of discussion about different treatments, and confusion between aligned versus shared decisions. Available questionnaires may overestimate shared decision-making in vulnerable patients suggesting the need for alternative or modifications to existing methods. Furthermore, such metrics should be assessed for correlation with patient-reported outcomes, such as satisfaction with decisions and health status. Copyright © 2017 Elsevier Inc. All rights reserved.

Metric Sex Determination of the Human Coxal Bone on a Virtual Sample using Decision Trees.

Science.gov (United States)

Savall, Frédéric; Faruch-Bilfeld, Marie; Dedouit, Fabrice; Sans, Nicolas; Rousseau, Hervé; Rougé, Daniel; Telmon, Norbert

2015-11-01

Decision trees provide an alternative to multivariate discriminant analysis, which is still the most commonly used in anthropometric studies. Our study analyzed the metric characterization of a recent virtual sample of 113 coxal bones using decision trees for sex determination. From 17 osteometric type I landmarks, a dataset was built with five classic distances traditionally reported in the literature and six new distances selected using the two-step ratio method. A ten-fold cross-validation was performed, and a decision tree was established on two subsamples (training and test sets). The decision tree established on the training set included three nodes and its application to the test set correctly classified 92% of individuals. This percentage was similar to the data of the literature. The usefulness of decision trees has been demonstrated in numerous fields. They have been already used in sex determination, body mass prediction, and ancestry estimation. This study shows another use of decision trees enabling simple and accurate sex determination. © 2015 American Academy of Forensic Sciences.

Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

Science.gov (United States)

Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

2014-01-01

A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

Scientific publications: now a marketing decision?

Science.gov (United States)

Scientists have been publishing in journals related to their disciplines. Now with the advent of the internet, many more options are now available and scientific publication has become a marketing decision. Scientific journals are rated by "impact factor" which is based on the average number of cita...

Use of wind power forecasting in operational decisions.

Energy Technology Data Exchange (ETDEWEB)

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help

Strategic planning decisions in the high tech industry

CERN Document Server

Daim, Tugrul; Beyhan, Berna; Basoglu, Nuri

2013-01-01

The scale and complexity of research and practices of open innovation mandate a correspondingly sophisticated form of decision making. Strategic Planning Decisions brings together a number of tools that ease the decision process in technology companies, providing both conceptual frameworks and practical applications. Innovative approaches are presented such as an ontology-based model where all the relevant aspects of a potential technology are interrelated to provide a comprehensive and logically connected data pool for decision makers. Divided into two sections, Strategic Planning Decisions describe both strategic approaches using the decision tools, and tactical approaches. Some of these tools are expanded while some others are embedded in a model that will lay the ground for practical application. These include: ·         bibliometric analysis, ·         ontology, ·         roadmapping, ·         lead user, six sigma, and ·         multi-actor & multi-object...

Convergent validity of two decision making style measures

Directory of Open Access Journals (Sweden)

Berisha, Gentrit

2018-04-01

Full Text Available Decision making research has witnessed a growing number of studies on individual differences and decision making styles, yet the lack of comprehensive frameworks and widely accepted measures has hindered research for a long time. There is an ongoing debate on whether individuals’ styles dynamically change across time and situations according to circumstances. Furthermore, it is an open question whether these styles are mutually exclusive. Decision style measures seek to determine one’s dominant style as well as less used styles. To our knowledge this is the first study of the convergent validity of two widely used decision making style measures: The Decision Style Inventory (DSI and the General Decision Making Style (GDMS. The direction and strength of correlation between directive, analytical, conceptual and behavioral styles as measured by DSI and rational, intuitive, dependent, avoidant and spontaneous styles as measured by GDMS have been tested. Results of the current study are compared with previous studies that have used one or both of the instruments. Correlations between styles are consistent with findings from other studies using one of the decision style measures, but the strength of correlations indicates that there is no convergent validity between DSI and GDMS.

Improving life cycle assessment methodology for the application of decision support

DEFF Research Database (Denmark)

Herrmann, Ivan Tengbjerg

for the application of decision support and evaluation of uncertainty in LCA. From a decision maker’s (DM’s) point of view there are at least three main “illness” factors influencing the quality of the information that the DM uses for making decisions. The factors are not independent of each other, but it seems......) refrain from making a decision based on an LCA and thus support a decision on other parameters than the LCA environmental parameters. Conversely, it may in some decision support contexts be acceptable to base a decision on highly uncertain information. This all depends on the specific decision support...... the different steps. A deterioration of the quality in each step is likely to accumulate through the statistical value chain in terms of increased uncertainty and bias. Ultimately this can make final decision support problematic. The "Law of large numbers" (LLN) is the methodological tool/probability theory...

Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

Science.gov (United States)

2015-10-28

techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

Science.gov (United States)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

Does Delaying Judgments of Learning Really Improve the Efficacy of Study Decisions? Not So Much

Science.gov (United States)

Kimball, Daniel R.; Smith, Troy A.; Muntean, William J.

2012-01-01

A widely held assumption in metamemory is that better, more accurate metamemory monitoring leads to better, more efficacious restudy decisions, reflected in better memory performance--we refer to this causal chain as the "restudy selectivity hypothesis". In 3 sets of experiments, we tested this hypothesis by factorially manipulating…

Getting DNA copy numbers without control samples

Directory of Open Access Journals (Sweden)

Ortiz-Estevez Maria

2012-08-01

Full Text Available Abstract Background The selection of the reference to scale the data in a copy number analysis has paramount importance to achieve accurate estimates. Usually this reference is generated using control samples included in the study. However, these control samples are not always available and in these cases, an artificial reference must be created. A proper generation of this signal is crucial in terms of both noise and bias. We propose NSA (Normality Search Algorithm, a scaling method that works with and without control samples. It is based on the assumption that genomic regions enriched in SNPs with identical copy numbers in both alleles are likely to be normal. These normal regions are predicted for each sample individually and used to calculate the final reference signal. NSA can be applied to any CN data regardless the microarray technology and preprocessing method. It also finds an optimal weighting of the samples minimizing possible batch effects. Results Five human datasets (a subset of HapMap samples, Glioblastoma Multiforme (GBM, Ovarian, Prostate and Lung Cancer experiments have been analyzed. It is shown that using only tumoral samples, NSA is able to remove the bias in the copy number estimation, to reduce the noise and therefore, to increase the ability to detect copy number aberrations (CNAs. These improvements allow NSA to also detect recurrent aberrations more accurately than other state of the art methods. Conclusions NSA provides a robust and accurate reference for scaling probe signals data to CN values without the need of control samples. It minimizes the problems of bias, noise and batch effects in the estimation of CNs. Therefore, NSA scaling approach helps to better detect recurrent CNAs than current methods. The automatic selection of references makes it useful to perform bulk analysis of many GEO or ArrayExpress experiments without the need of developing a parser to find the normal samples or possible batches within the

Info-gap decision theory decisions under severe uncertainty

CERN Document Server

Ben-Haim, Yakov

2006-01-01

Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. This book is written for decision analysts. The term ""decision analyst"" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts,

Multiattribute Grey Target Decision Method Based on Soft Set Theory

Directory of Open Access Journals (Sweden)

Xia Wang

2014-01-01

Full Text Available With respect to the Multiattribute decision-making problems in which the evaluation attribute sets are different and the evaluating values of alternatives are interval grey numbers, a multiattribute grey target decision-making method in which the attribute sets are different was proposed. The concept of grey soft set was defined, and its “AND” operation was assigned by combining the intersection operation of grey number. The expression approach of new grey soft set of attribute sets considering by all decision makers were gained by applying the “AND” operation of grey soft set, and the weights of synthesis attribute were proved. The alternatives were ranked according to the size of distance of bull’s eyes of each alternative under synthetic attribute sets. The green supplier selection was illustrated to demonstrate the effectiveness of proposed model.

Women's autonomy in household decision-making: a demographic study in Nepal.

Science.gov (United States)

Acharya, Dev R; Bell, Jacqueline S; Simkhada, Padam; van Teijlingen, Edwin R; Regmi, Pramod R

2010-07-15

How socio-demographic factors influence women's autonomy in decision making on health care including purchasing goods and visiting family and relatives are very poorly studied in Nepal. This study aims to explore the links between women's household position and their autonomy in decision making. We used Nepal Demographic Health Survey (NDHS) 2006, which provided data on ever married women aged 15-49 years (n = 8257). The data consists of women's four types of household decision making; own health care, making major household purchases, making purchase for daily household needs and visits to her family or relatives. A number of socio-demographic variables were used in multivariable logistic regression to examine the relationship of these variables to all four types of decision making. Women's autonomy in decision making is positively associated with their age, employment and number of living children. Women from rural area and Terai region have less autonomy in decision making in all four types of outcome measure. There is a mixed variation in women's autonomy in the development region across all outcome measures. Western women are more likely to make decision in own health care (1.2-1.6), while they are less likely to purchase daily household needs (0.6-0.9). Women's increased education is positively associated with autonomy in own health care decision making (p make decision in own healthcare. Women from rural area and Terai region needs specific empowerment programme to enable them to be more autonomous in the household decision making. Women's autonomy by education, wealth quintile and development region needs a further social science investigation to observe the variations within each stratum. A more comprehensive strategy can enable women to access community resources, to challenge traditional norms and to access economic resources. This will lead the women to be more autonomous in decision making in the due course.

Optimization and analysis of decision trees and rules: Dynamic programming approach

KAUST Repository

Alkhalid, Abdulaziz

2013-08-01

This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.

Optimization and analysis of decision trees and rules: Dynamic programming approach

KAUST Repository

Alkhalid, Abdulaziz; Amin, Talha M.; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.

Applicability of higher-order TVD method to low mach number compressible flows

International Nuclear Information System (INIS)

Akamatsu, Mikio

1995-01-01

Steep gradients of fluid density are the influential factor of spurious oscillation in numerical solutions of low Mach number (M<<1) compressible flows. The total variation diminishing (TVD) scheme is a promising remedy to overcome this problem and obtain accurate solutions. TVD schemes for high-speed flows are, however, not compatible with commonly used methods in low Mach number flows using pressure-based formulation. In the present study a higher-order TVD scheme is constructed on a modified form of each individual scalar equation of primitive variables. It is thus clarified that the concept of TVD is applicable to low Mach number flows within the framework of the existing numerical method. Results of test problems of the moving interface of two-component gases with the density ratio ≥ 4, demonstrate the accurate and robust (wiggle-free) profile of the scheme. (author)

Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions

KAUST Repository

Azad, Mohammad

2014-09-13

The paper is devoted to the analysis of greedy algorithms for the minimization of average depth of decision trees for decision tables such that each row is labeled with a set of decisions. The goal is to find one decision from the set of decisions. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of average depth of decision trees.

Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions