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Search Results: 1 - 10 of 5026 matches for " Decision "
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Visualizing Investment Decision on Decision Balls  [PDF]
Li-Ching Ma
American Journal of Operations Research (AJOR) , 2011, DOI: 10.4236/ajor.2011.12009
Abstract: Decision makers’ choices are often influenced by visual background information. This study uses open-ended equity funds in Taiwan to investigate three well-known optimal portfolio models, including the mean-variance, maximin, and minimization of mean absolute deviation. The optimal portfolios are then visualized on Decision Balls to assist investors in making investment decisions. By observing the Decision Balls, investors can see the optimal portfolios, compare the optimal weights provided by the different models, view the cluster of funds, and even find substitute funds if preferred funds are not available.
Healthcare intelligence risk detection systems  [PDF]
Reza Safdari, Jebraeil Farzi, Marjan Ghazisaeidi, Mahboobeh Mirzaee, Azadeh Goodini
Open Journal of Preventive Medicine (OJPM) , 2013, DOI: 10.4236/ojpm.2013.38062

Background: Today, in healthcare field that is changing rapidly, decision-makers encounter with ever-increasing inquiries on clinical and administrative information to realize customers’ legal and clinical requirements. Therefore, making decisions on healthcare has changed into a vital, complex and unstructured issue. The present paper mainly focuses on describing decision-making advantages, possible risk to improve efficiency of decision-making on healthcare, and especially medical procedures. Methods: The present research is a review study, which has been carried out by searching through the authentic scientific sources, including Pubmed, Google scholar, Iranmedex, and other information sources. While defining care intelligence, here, we introduce Knowledge Discovery Database, the Clinical Support Systems, and Intelligence Risk Detection Model and provide the conceptual model. Other issues studied in this paper include the Risk Possibility Assessment Technique, Risk Possibility Detection using knowledge management techniques, and expert systems. Results & Conclusion: Modeling the Intelligence Support System is necessary for designing Real-Time Risk Detection Information Systems in clinical measures. As taking medical procedures involves complex decision-makings and possibility of high risk, operational application of the techniques derived from knowledge and data mining models under study will play a crucial role in increasing possibility of success of the measure and promoting safety of patients.

Superstitions Behavior and Decision Making in Collegiate Athletes: An Illogical Phenomenon  [PDF]
Baljinder Singh Bal, Davinder Singh, Kulroop Kaur Badwal, Gurmej Singh Dhaliwal
Advances in Physical Education (APE) , 2014, DOI: 10.4236/ape.2014.41001

This study examined the superstitious behavior and decision making among individual, dual and team sport groups. To obtain required data, the investigators had selected Ninety (N = 90) male intercollege level athletes of 19 to 25 years of age to act as subjects. They were divided into three groups; Thirty (n1 = 30) Individual Sports, Thirty (n2 = 30) Dual Sports and Thirty (n3 = 30) Team Sports athletes of various games and sport. The purposive sampling technique was used to select the subjects. All the subjects, after having been informed about the objective and protocol of the study, gave their consent and volunteered to participate in this study. To measure the level of superstitions behaviors of the subjects, the superstitions beliefs and behaviour scale constructed by Buhramann et al. (2004) was administered and to measure the level of decision making by applying decision making questionnaire prepared by French et al. (1993). One way Analysis of Variance (ANOVA) was employed to find out the intra-group differences. To test the hypothesis, the level of significance was set at .05. The results revealed significant intra-group differences among individual, dual and team sports on the variable superstitious behavior and decision making. It is concluded that the individual sport group has low superstitious belief and better decision making level as compared to their counterpart dual and team sport.

Dacian Cosmin DRAGO?
Revista Transilvan? de ?tiin?e Administrative , 2004,
Abstract: The article discusses the possibility of annulment of an administrative decision enacted with discretion power by the administrative authority, in the light of the Constitution revisited in 2003. The case study is focused on a judicial decision enacted by the Cluj County Court in 2002.
Decision Making: A Computer-Science and Information-Technology Viewpoint
Marko Bohanec
Interdisciplinary Description of Complex Systems , 2009,
Abstract: We address the phenomenon of decision making from the viewpoint of computer science and information technology. The basic question from this viewpoint is: what can the computer offer to decision makers and how it can support their work? Therefore, the main issue is to provide support to people who make complex decisions. In this article, we first present the taxonomy of disciplines that are concerned with methodological and operational aspects of decision support. At the main level, we distinguish between decision sciences, which are concerned with human decision making, and decision systems, which address computer decision making. This is followed by basic definitions related to decision processes and their components. We also describe properties that characterise different classes of decision problems. In the main part of the article, we present three prevailing approaches to decision support and give illustrative examples of their application: decision analysis, operational research, and decision support systems. Finally, we make a short overview of the area of decision systems and its achievements.
Advanced decision support for complex clinical decisions  [PDF]
Brain Keltch, Yuan Lin, Coskun Bayrak
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.35071
Abstract: A Physician’s decision-making skills are directly related to the patient’s positive outcomes. Therefore, a wealth of medical knowledge and clinical experience are key assets for a physician to have. The goal here is to use historical clinical data and relationships processed by Artificial Intelligence (AI) techniques to aid physicians in their decision making process. Presenting this information in a Clinical Decision Support System (CDSS) is an effective means to consolidate decision results. The CDSS provides a large number of medical support functions to help clinicians make the most reasonable diagnosis and choose the best treatment measures. Initial results have shown great promise in accurately predicting Fibrosis Stage in Hepatitis patients. Utilizing this tool could mitigate the need for some liver biopsies in the more than 170 million Hepatitis patients worldwide. The prototype is extendable to accommodate additional techniques (for example genetic algorithms and logistics regression) and additional medical domain solutions (for example HIV/AIDS).
Mixed Strategy Nash Equilibria in Signaling Games  [PDF]
Barry R. Cobb, Atin Basuchoudhary, Gregory Hartman
Theoretical Economics Letters (TEL) , 2013, DOI: 10.4236/tel.2013.31009

Signaling games are characterized by asymmetric information where the more informed player has a choice about what information to provide to its opponent. In this paper, decision trees are used to derive Nash equilibrium strategies for signaling games. We address the situation where neither player has any pure strategies at Nash equilibrium, i.e. a purely mixed strategy equilibrium. Additionally, we demonstrate that this approach can be used to determine whether certain strategies are part of a Nash equilibrium containing dominated strategies. Analyzing signaling games using a decision-theoretic approach allows the analyst to avoid testing individual strategies for equilibrium conditions and ensures a perfect Bayesian solution.

Decision Theory and Analysis: An Optima Value Creation Precursor for Organizations  [PDF]
Cephas A. Gbande, Paul T. Akuhwa
Open Journal of Applied Sciences (OJAppS) , 2015, DOI: 10.4236/ojapps.2015.57036
Abstract: Organizations make many informed decisions such as increasing production capacity, improving human capital, entering a new market etc. This paper shows that executives take either of the two major types of decisions: programmed (structured) and nonprogrammed (unstructured) decisions. While the programmed decisions are for perfectly stable situations, the nonprogrammed decisions are for the real world situation surrounded by uncertainties, risks and ambiguities. For an optima value creation, this paper is succinct that a robust decision theory and analysis serve as a precursor. The environment of decision-making keeps changing and it takes decision-making for organizations to change proportionately to these environmental changes if they must survive. The decision-maker uses probability values to convert uncertainties and risks into perfect knowledge poles so as to make informed decisions. Models are veritable decision making tools and are deterministic and probabilistic (or stochastic) for programmed and nonprogrammed decisions respectively. Real-world value optimization in this paper centres on decisions under pure uncertainty and risky situations generating model fits for an optima value creation. Finally, the optima value creation models under the uncertainty and risk are suggested and organizations advised to use professional decision theorists and analysts as the need arise.
HumanBoost: Utilization of Users’ Past Trust Decision for Identifying Fraudulent Websites  [PDF]
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobayashi
Journal of Intelligent Learning Systems and Applications (JILSA) , 2010, DOI: 10.4236/jilsa.2010.24022
Abstract: This paper presents HumanBoost, an approach that aims at improving the accuracy of detecting so-called phishing sites by utilizing users’ past trust decisions (PTDs). Web users are generally required to make trust decisions whenever their personal information is requested by a website. We assume that a database of user PTDs would be transformed into a binary vector, representing phishing or not-phishing, and the binary vector can be used for detecting phishing sites, similar to the existing heuristics. For our pilot study, in November 2007, we invited 10 participants and performed a subject experiment. The participants browsed 14 simulated phishing sites and six legitimate sites, and judged whether or not the site appeared to be a phishing site. We utilize participants’ trust decisions as a new heuristic and we let AdaBoost incorporate it into eight existing heuristics. The results show that the average error rate for HumanBoost was 13.4%, whereas for participants it was 19.0% and for AdaBoost 20.0%. We also conducted two follow-up studies in March 2010 and July 2010, observed that the average error rate for HumanBoost was below the others. We therefore conclude that PTDs are available as new heuristics, and HumanBoost has the potential to improve detection accuracy for Web user.
Hybrid Decision Models in Non-Proportional Reinsurance  [PDF]
Maik Wagner
Technology and Investment (TI) , 2010, DOI: 10.4236/ti.2010.11008
Abstract: Over the past years, risk measurement and therewith risk measures became more and more important in economics. While in the past risk measures were already adopted at the deposit of credit and shareholders equity, the approach now generates two hybrid decision models and applies them to the reinsurance business. The two introduced models implement a convex combination of risk measures and with it provide the possibility of modelling risk attitudes. By doing that, for the two hybrid decision models on the one hand can be shown, which risk attitude leads to the acceptance of a reinsurance contract and on the other hand, a deductible of which height an insurer is willing to undertake. Hence the possibility exists to identify the risk attitude of an insurer. In return, due to the knowledge of risk attitudes, under similar conditions the possibility arises to establish recommendations about the extent of the deductible at reinsurance contracts.
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