On extending generalized Bonferroni means to Atanassov orthopairs in decision making contexts

Extensions of aggregation functions to Atanassov orthopairs (often referred to as intuitionistic fuzzy sets or AIFS) usually involve replacing the standard arithmetic operations with those defined for the membership and non-membership orthopairs. One problem with such constructions is that the usual choice of operations has led to formulas which do not generalize the aggregation of ordinary fuzzy sets (where the membership and non-membership values add to 1). Previous extensions of the weighted arithmetic mean and ordered weighted averaging operator also have the absorbent element 〈1,0〉, which becomes particularly problematic in the case of the Bonferroni mean, whose generalizations are useful for modeling mandatory requirements. As well as considering the consistency and interpretability of the operations used for their construction, we hold that it is also important for aggregation functions over higher order fuzzy sets to exhibit analogous behavior to their standard definitions. After highlighting the main drawbacks of existing Bonferroni means defined for Atanassov orthopairs and interval data, we present two alternative methods for extending the generalized Bonferroni mean. Both lead to functions with properties more consistent with the original Bonferroni mean, and which coincide in the case of ordinary fuzzy values.

Mental health-related risk factors for violence : using the evidence to guide mental health triage decision making

Mental health clinicians working in emergency crisis assessment teams or mental health triage roles are required to make rapid and accurate risk assessments. The assessment of violence risk at triage is particularly pertinent to the early identification and prevention of patient violence, and to enhancing the safety of clinical staff and the general public. To date, the evidence base for mental health triage violence risk assessment has been minimal. This study aimed to address this evidence gap by identifying best available evidence for mental health-related risk factors for patientinitiated violence.We conducted a systematic review based on the National Health and Medical Research Council of Australia’s methodology for systematic reviews. A total of 6847 studies were retrieved, of which 326 studies met the study inclusion criteria. Of these studies, 277 met inclusion criteria but failed the quality appraisal process, thus a total of 49 studies were included in the final review. The risk factors that achieved the highest evidence grading were predominantly related to dynamic clinical factors immediately observable in the patient’s general appearance, behaviour and speech. These factors included hostility/anger, agitation, thought disturbance, positive symptoms of schizophrenia, suspiciousness and irritability.

Knowledge mobilization on decision making for school improvement : Canadian principals learning network.

Principals duties have expanded beyond instructional leadership. Roles now include being curriculum leader, supervisor, manager, head of finance, administration, compliance, and legal matters, and so on. These additional responsibilities impact their decision-making in relation to teaching, learning and school improvement in general. How, and on what basis, they make these decisions is crucial both to their development as instructional leaders and to educational reform processes. To contribute to knowledge on principals’ decision making skills, we have created a strategic knowledge mobilization initiative called 'Canadian Principals Learning Network (CPLN)'. Through a variety of face-to-face and online activities, it collaboratively links together an international group of practicing principals and university-based researchers with related expertise. This paper describes the initiative and outcomes.

Promotional competitions: management decision-making in the Australian consumer marketplace

This research focused on a specific form of sales promotion: promotional competitions. The work identified the processes that organizations applied when defining their marketing strategy and promotional mix, and investigated the decision influences and design considerations which shaped the profile of competitions, offering innovative decision-making models for academics and practitioners.

Application of an Adaptive Neural Network to Medical Decision Support

Medical diagnostic and prognostic problems are prime examples of decision making in the face of uncertainty. In this paper, we investigate the applicability of the Fuzzy ARTMAP neural network as an intelligent decision support system in clinical medicine. In particular, Fuzzy ARTMAP is employed as a predictive model for prognosis of complications in patients admitted to the Coronary Care Units. A number of off-line and on-line experiments have been conducted with various network parameter settings, training methods, and learning rules. The results are compared with those from other systems including the logistic regression model. In addition, the outcomes of a set of on-line learning experiments revealed the potential of employing Fuzzy ARTMAP as an autono-mously learning system that is able to learn perpetually and, at the same time, to provide useful decision support.

Innovations in knowledge processing and decision making in agent-based systems

This chapter introduces knowledge processing and decision making using agent-based technologies. The importance of creating effective and efficient computerized systems for extracting information and processing knowledge as well as for supporting decision making activities is highlighted. Then, an overview covering agent-based software tools and development methodologies, and usability and challenges of agent-based systems in industrial applications is presented. The contribution of each chapter included in this book is also described.

Negotiating local decision making to manage coastal inundation : certainty, precedence, precaution and practicality

Scientific projections for climate change induced sea level rise highlight the potential for serious consequences in low lying coastal areas, through impacts upon: built infrastructure; beneficial uses; and ecological values. An area of particular concern relates to the ways in which local decision makers work through the issues associated with new development proposals on land that may be subject to future inundation, whether permanent or temporary. In making such issues, local authorities need to consider multiple sources of evidence, and multiple perspectives on what the evidence means. In this paper we examine decision making about coastal development in south west Victoria to explore how such issues are worked through, in terms of the responsibilities of different actors, and the tensions, challenges, and implications associated with, and arising from, the way in which various actors participate in, and negotiate their way through, decision making processes. In doing so, our particular focus is on the way in which different actor types engage with and interpret particular pieces of information (e.g. estimates of sea level rise and LSIO information) which are central to the decision making process. While the focus is on local decision making in south west Victoria, the insights generated may have broader relevance.

Simulated jury decision making in online focus groups

Purpose – A significant issue in jury research has been the use of individual jurors to analyse jury decision-making. This paper aimed to examine the applicability of computer-mediated communication to a mock jury deliberation study.

Design/methodology/approach – Groups of three to five Australian residents anonymously attended a secure chat room and participated in a semi-structured discussion about a simulated child sexual assault scenario. Deliberation transcripts were analysed thematically using NVivo. A hermeneutic framework was used to analyse the deliberation transcripts.

Findings – Five interrelated themes were revealed, each reflecting the tools online juries used to communicate, create meaning, and arrive at a verdict. Electronic jury deliberation promoted an understanding of how people make sense of child sexual assault cases in Australia today.

Originality/value – This study advanced the understanding of online decision making in a child sexual assault scenario. It demonstrated that knowledge of how juries deliberate and create meaning could improve our understanding of how verdicts are achieved. Electronic mock juries are a valuable adjunct to traditional jury deliberation studies because they are cost effective, time efficient, and offer wider recruitment opportunities.

Decision-Making in Economics: Critical Lessons from Neurobiology

In this chapter, the authors consider some of the issues regarding the rational choice decision framework in neoclassical economics and how it can particularly be found wanting in the absence of due consideration for some of the underlying critical neurobiological factors which govern decision making. They develop a critical decision problem and explore the scenario where the solution predicted by formal economic theory may be in conflict with the decision that actually occurs. Such conflict is especially relevant in the context of economic decision making in emerging markets where there can be a lack of trust in the system by the agents operating within it. Based on logically consistent arguments derived from the extant literature, the authors argue that non-consideration of underlying neurobiological factors is a direct cause of this conflict.

Adaptation to climate change in regional Australia : a decision-making framework for modelling policy for rural production

A decision-making framework was developed and applied in regional Australia to identify adaptation issues arising in agricultural systems and rural production as a consequence of climate change. Australian agriculture is very susceptible to the adverse impacts of climate change, with major shifts in temperature and rainfall projected. An advantage of the framework is that it provides a suite of tools to aid in the formulation of strategies for sustainable regional development and adaptation. The decision-making framework uses a participatory approach that integrates land suitability analysis with uncertainty analysis and spatial optimisation to determine optimal agricultural land use (at a regional scale) for current and possible future climatic conditions. It thus provides a robust analytic approach to (i) recognise regions under threat of productivity declines, (ii) identify alternative cropping systems better adapted to likely future climatic conditions and (iii) investigate policy actions to improve the sub-optimal situations created by climate change. The decision-making framework and its methods were applied in a case study of the South West Region of Victoria.

Categorization of disaster decision support needs for the development of an integrated model for DMDSS

The wide variety of disasters and the large number of activities involved have resulted in the demand for separate Decision Support System (DSS) models to manage different requirements. The modular approach to model management is to provide a framework in which to focus multidisciplinary research and model integration. A broader view of our approach is to provide the flexibility to organize and adapt a tailored DSS model (or existing modular subroutines) according to the dynamic needs of a disaster. For this purpose, the existing modular subroutines of DSS models are selected and integrated to produce a dynamic integrated model focussed on a given disaster scenario. In order to facilitate the effective integration of these subroutines, it is necessary to select the appropriate modular subroutine beforehand. Therefore, subroutine selection is an important preliminary step towards model integration in developing Disaster Management Decision Support Systems (DMDSS). The ability to identify a modular subroutine for a problem is an important feature before performing model integration. Generally, decision support needs are combined, and encapsulate different requirements of decision-making in the disaster management area. Categorization of decision support needs can provide the basis for such model selection to facilitate effective and efficient decision-making in disaster management. Therefore, our focus in this paper is on developing a methodology to help identify subroutines from existing DSS models developed for disaster management on the basis of needs categorization. The problem of the formulation and execution of such modular subroutines are not addressed here. Since the focus is on the selection of the modular subroutines from the existing DMDSS models on basis of a proposed needs classification scheme.