Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision

F. Smith and Q. Shen. Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 34(5):649-663, 2004.

Most Haunted and the Convergence of Traditional Belief and Popular Television

Koven, M. (2007). Most Haunted and the Convergence of Traditional Belief and Popular Television. Folklore. 118(2), pp.183-202. RAE2008

Factors relating to motivation to change behaviour in individuals who are overweight: application of the health belief model

Background: Obesity is the most important health challenge faced at a global level and represents a rapidly growing problem to the health of populations. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. The normalisation of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation. Recognition of the problem is a key component of obesity management and it remains especially crucial to address this issue. A large amount of research has been undertaken on obesity however, limited research has been undertaken using the Health Belief Model. Aim: The aim of the research was to determine factors relating to motivation to change behaviour in individuals who perceive themselves to be overweight and investigate whether the constructs of the Health Belief Model help to explain motivation to change behaviour. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data Collection: Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Sample: A sample of 202 men and women who perceived themselves to be overweight participated in the research. Results: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p =<0.019) and environmental barriers to physical activity (p=<0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p<0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. The current study demonstrated the limited applicability of the Health Belief Model constructs to motivation to change behaviour, as not all core dimensions proved significant predictors of the dependant variable.

Genes, race, and the ethics of belief.

A Troublesome Inheritance, by Nicholas Wade, should be read by anyone interested in race and recent human evolution. Wade deserves credit for challenging the popular dog-ma that biological differences between groups either don't exist or cannot ex-plain the relative success of different groups at different tasks. Wade's work should be read alongside another re-cent book, The 10,000 Year Explosion: How Civilization Accelerated Human Evolution, by Gregory Cochran and Henry Harpending. Together, these books represent a ma-jor turning point in the public debate about the speed with which relatively isolated groups can evolve: both books suggest that small genetic differences between members of different groups can have large impacts on their abilities and propensities, which in turn affect the outcomes of the societies in which they live.

Belief and recollection of autobiographical memories.

In three experiments, undergraduates rated autobiographical memories on scales derived from existing theories of memory. In multiple regression analyses, ratings of the degree to which subjects recollected (i.e., relived) their memories were predicted by visual imagery, auditory imagery, and emotions, whereas ratings of belief in the accuracy of their memories were predicted by knowledge of the setting. Recollection was predicted equally well in between- and within-subjects analyses, but belief consistently had smaller correlations and multiple regression predictions between subjects; individual differences in the cognitive scales that we measured could not account well for individual differences in belief. In contrast, measures of mood (Beck Depression Index) and dissociation (Dissociative Experience Scale) added predictive value for belief, but not for recollection. We also found that highly relived memories almost always had strong visual images and that remember/know judgments made on autobiographical memories were more closely related to belief than to recollection.

Distributed belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

Belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-researched topic within Artificial Intelligence (AI). We argue that the new model of belief revision as discussed here is suitable for general modelling of judicial decision making, along with the extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interacting with, and influencing, other agents who are deliberating collectively. The principle of 'priority to the incoming information', as known from AI models of belief revision, is problematic when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet, we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stimuli) could attempt to handle other aspects of the deliberation which are more specific to legal narratives, to argumentation in court, and then to the debate among the jurors.

Belief, Knowledge and Expertise. The emergence of the lay expert in medical sociology

The paper has three main aims. First, to trace – through the pages of the Journal – the changing ways in which lay understandings of health and illness have been represented during the 1979-2002 period. Second, to say something about the limits of lay knowledge (and particularly lay expertise) in matters of health and medicine. Third, to call for a re-assessment of what lay people can offer to a democratised and customer sensitive system of health care and to attempt to draw a boundary around the domain of expertise. In following through on those aims, the author calls upon data derived from three current projects. These latter concern the diagnosis of Alzheimer’s disease in people with Down’s syndrome; the development of an outcome measure for people who have suffered a traumatic brain injury; and a study of why older people might reject annual influenza vaccinations. Key words: Lay health beliefs, lay expertise, Alzheimer’s, Traumatic Brain Injury, Vaccinations

Analyzing the degree of conflict among belief functions.

The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identification) of conflict among evidence has been ignored. In this paper, we formally define when two basic belief assignments are in conflict. This definition deploys quantitative measures of both the mass of the combined belief assigned to the emptyset before normalization and the distance between betting commitments of beliefs.We argue that only when both measures are high, it is safe to say the evidence is in conflict. This definition can be served as a prerequisite for selecting appropriate combination rules.