A fuzzy MCDA framework for safety assessment in the remediation of a uranium mill tailings site in Ukraine

The Pridneprovsky Chemical Plant was one of the largest uranium processing enterprises in the former USSR, producing a huge amount of uranium residues. The Zapadnoe tailings site contains most of these residues. We propose a theoretical framework based on multicriteria decision analysis and fuzzy logic to analyze different remediation alternatives for the Zapadnoe tailings, which simultaneously accounts for potentially conflicting economic, social and environmental objectives. We build an objective hierarchy that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, we suggest that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

An interactive method of fuzzy probability elicitation in risk analysis

Expert knowledge is used to assign probabilities to events in many risk analysis models. However, experts sometimes find it hard to provide specific values for these probabilities, preferring to express vague or imprecise terms that are mapped using a previously defined fuzzy number scale. The rigidity of these scales generates bias in the probability elicitation process and does not allow experts to adequately express their probabilistic judgments. We present an interactive method for extracting a fuzzy number from experts that represents their probabilistic judgments for a given event, along with a quality measure of the probabilistic judgments, useful in a final information filtering and analysis sensitivity process.

Fuzzy MCDA for remediation of a uranium tailing

The Pridneprovsky Chemical Plant was a largest uranium processing enterprises, producing a huge amount of uranium residues. The Zapadnoe tailings site contains the majority of these residues. We propose a theoretical framework based on Multi-Criteria Decision Analysis and fuzzy logic to analyse different remediation alternatives for the Zapadnoe tailings, in which potentially conflicting economic, radiological, social and environmental objectives are simultaneously taken into account. An objective hierarchy is built that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, it is proposed that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

A Meta-Analytic Review of Mindfulness-Based Interventions on Symptom Reduction: A Critique and Guide for Future Investigation.

Over the past decade, mindfulness practices have been used with increasing frequency as therapeutic components within cognitive behavioral treatment regimens. As is standard practice, prescriptive uses of mindfulness intervention are incorporated to improve end-state functioning by ameliorating problematic symptoms and conditions. Common change-targets include the control of cognitive and emotional content for purposes of enhancing psychological self-regulation and physical well-being. The term mindfulness applies to a heterogeneous range of practices, methods, and techniques. While there is no singular agreed upon definition for mindfulness, as a process concept, the term connotes an immediate, non-thetic access to events, wherein each occasioning event is experienced in toto within the broader contextual event-field, and distinct from intervening conceptual themes being noticed. Training in mindfulness practices may be conducted using individual, group, or small class formats. The current paper provides a meta-analytic review of 44 treatment outcome studies (extracted 1982 through 2006), which examines the clinical utility of mindfulness as the primary therapeutic approach. Results indicated that average effect sizes for mindfulness based interventions fell within the medium range for construct category variables examined (d = .56). These findings suggest that mindfulness training is a cost-effective treatment for a wide array of contemporary psychological problems and diagnoses, in addition to fostering positive psychology attributes such as quality and satisfaction with life. A critique of the research and recommendations for future research, including a need to examine the role of mindfulness as a tool for cultivating increased psychological acceptance and life satisfaction, is presented.

An analysis of ASAP impact on the judicial system. SD:ASAP analytic study no. 4 - 1976. Final report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Programs, Washington, D.C.

Oklahoma City ASAP - effectiveness and efficiency. Analytic study no. 1. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system. Fourth analytic study.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system of Fairfax, Virginia - analytic study 4, court procedures: 1976. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the impact of ASAP on the traffic safety system in Columbus, Georgia from January, 1972 - December, 1974. Analytic study 4.

National Highway Traffic Safety Administration, Washington, D.C.

San Antonio Alcohol Safety Action Project - analytic study no. 4: final analysis of the judicial system 1972 through 1974.

National Highway Traffic Safety Administration, Washington, D.C.

Post ASAP analysis of project impact on ultimate measures of performance, level III - analytic study one. 1975-1976 period. Final report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Programs, Washington, D.C.

Analytic study number four: impact on judicial disposition on DUI offenders - Utah ASAP. Final report.

Utah Department of Public Safety, Salt Lake City

Analytic study no. 1. Total project impact.

National Highway Traffic Safety Administration, Washington, D.C.

Development of an intelligent quality management system using fuzzy association rules

In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ‘‘distributed process mining” feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.