Applying concepts of fuzzy cognitive mapping to model IT/IS investment evaluation factors

The justification process is a major concern for many organisations that are considering the adoption of Information Technology (IT) and Information Systems (IS), and is a barrier to its implementation. As a result, the competitive advantage of many companies is being put at risk because of management's inability to evaluate the holistic implication of adopting new technology, both in terms of on the benefit and cost portfolios. This paper identifies a number of well-known project appraisal techniques used in IT/IS investment justification. Furthermore, the concept of multivalent, or fuzzy logic, is used to demonstrate how inter-relationships can be modeled between key dimensions identified in the proposed conceptual evaluation model. This is highlighted using fuzzy cognitive mapping (FCM) as a technique to model each IT/IS evaluation factor (integrating strategic, tactical, operational and investment considerations). The use of an FCM is then shown to be as a complementary tool which can serve to highlight interdependencies between contributory justification factors

Observations from Canadian practitioners about the investigation and prosecution of crimes involving child and adult witnesses

Hundreds of scientific studies on the competencies and limitations of eyewitnesses have been published, but few have sought input from front-line forensic interviewers. In the current study, a research agenda was established with in-depth input from 13 forensic interviewers. Interviewers indicated which techniques they use most often, rated the usefulness of various interview techniques, and disclosed common challenges when interviewing. Although many recommended techniques were used (e.g., the Cognitive Interview and Rapport Building), some techniques shown to be effective in eliciting quality testimony in scientific studies were not always used or considered useful by front-line interviewers (e.g., permission to correct the interviewer, permission to say ‘I don’t know’). Key areas were identified to guide future research (e.g., techniques when interviewing very young children, witnesses with developmental delays)

Induction, complexity, and economic methodology

This paper focuses on induction, because the supposed weaknesses of that process are the main reason for favouring falsificationism, which plays an important part in scientific methodology generally; the paper is part of a wider study of economic methodology. The standard objections to, and paradoxes of, induction are reviewed, and this leads to the conclusion that the supposed ‘problem’ or ‘riddle’ of induction is a false one. It is an artefact of two assumptions: that the classic two-valued logic (CL) is appropriate for the contexts in which induction is relevant; and that it is the touchstone of rational thought. The status accorded to CL is the result of historical and cultural factors. The material we need to reason about falls into four distinct domains; these are explored in turn, while progressively relaxing the restrictions that are essential to the valid application of CL. The restrictions include the requirement for a pre-existing, independently-guaranteed classification, into which we can fit all new cases with certainty; and non-ambiguous relationships between antecedents and consequents. Natural kinds, determined by the existence of complex entities whose characteristics cannot be unbundled and altered in a piecemeal, arbitrary fashion, play an important part in the review; so also does fuzzy logic (FL). These are used to resolve two famous paradoxes about induction (the grue and raven paradoxes); and the case for believing that conventional logic is a subset of fuzzy logic is outlined. The latter disposes of all questions of justifying induction deductively. The concept of problem structure is used as the basis for a structured concept of rationality that is appropriate to all four of the domains mentioned above. The rehabilitation of induction supports an alternative definition of science: that it is the business of developing networks of contrastive, constitutive explanations of reproducible, inter-subjective (‘objective’) data. Social and psychological obstacles ensure the progress of science is slow and convoluted; however, the relativist arguments against such a project are rejected.induction; economics; methodology; complexity

Review of the strengths and weaknesses of risk matrices

Risk assessment and risk matrices are powered tools used in risk management and help guide in the process of decision-making in organisations. Nevertheless, risk matrices have their own weaknesses and strengths. This paper provides a critical overview of the development and use of risk matrices in different field with an example of the risk matrix used by the National Health Service (NHS) in England. Risk matrices are helpful tools for risk assessment as they use quantitative measures to ensure consistent method of determining risk but organisations should adjust the design and size of risk matrices to suit their needs

On fuzzy frontiers and fragmented foundations : some reflections on the original and new institutional economics

This article has been published in a revised form in Journal of Institutional Economics, doi: https://doi.org/10.1017/S1744137414000307 This version is free to view and download for private research and study only. Not for re-distribution, re-sale or use in derivative works. © 2014 Millennium Economics Ltd, published by Cambridge University Press.These reflections are prompted by the papers by Ménard (2014) and Ménard and Shirley (2014). Their essays centre on the path-breaking contributions to the 'new institutional economics' (NIE) by Ronald Coase, Douglass North and Oliver Williamson. In response, while recognising their substantial achievements, it is pointed out that these three thinkers had contrasting views on key points. Furthermore, Ménard's and Shirley's three 'golden triangle' NIE concepts - transaction costs, property rights and contracts - are themselves disputed. Once all this is acknowledged, differences of view appear within the NIE, raising interesting questions concerning its identity and boundaries, including its differences with the original institutionalism. There are sizeable overlaps between the two traditions. It is argued here that the NIE can learn from the original institutionalism, particularly when elaborating more dynamic analyses, and developing more nuanced, psychologically-grounded and empirically viable theories of human motivation.Peer reviewedFinal Accepted Versio

Automatic detection of welding defects using the convolutional neural network

Quality control of welded joints is an important step before commissioning of various types of metal structures. The main obstacles to the commissioning of such facilities are the areas where the welded joint deviates from acceptable defective standards. The defects of welded joints include non-welded, foreign inclusions, cracks, pores, etc. The article describes an approach to the detection of the main types of defects of welded joints using a combination of convolutional neural networks and support vector machine methods. Convolutional neural networks are used for primary classification. The support vector machine is used to accurately define defect boundaries. As a preprocessing in our work, we use the methods of morphological filtration. A series of experiments confirms the high efficiency of the proposed method in comparison with pure CNN method for detecting defects

Connectionist Inference Models

The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule-based reasoning, and whether they involve distributed or localist representations. The benefits and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used for cognitive modeling