59 resultados para Swarm intelligence


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Criminal intelligence is an area of expertise highly sought-after internationally and within a variety of justice-related professions; however, producing university graduates with the requisite professional knowledge, as well as analytical, organisational and technical skills presents a pedagogical and technical challenge to university educators. The situation becomes even more challenging when students are undertaking their studies by distance education. This best practice session showcases the design of an online undergraduate unit for final year justice students which uses an evolving real-time criminal scenario as the focus of authentic learning activities in order to prepare students for graduate roles within the criminal intelligence and justice professions. Within the unit, students take on the role of criminal intelligence analysts, applying relevant theories, models and strategies to solve a complex but realistic crime and complete briefings and documentation to industry standards as their major summative assessment task. The session will demonstrate how the design of the online unit corresponds to authentic learning principles, and will specifically map the elements of the unit design to Herrington & Oliver’s instructional design framework for authentic learning (2000; Herrington & Herrington 2006). The session will show how a range of technologies was used to create a rich learning experience for students that could be easily maintained over multiple unit iterations without specialist technical support. The session will also discuss the unique pedagogical affordances and challenges implicated in the location of the unit within an online learning environment, and will reflect on some of the lessons learned from the development which may be relevant to other authentic online learning contexts.

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Criminal intelligence is an area of expertise highly sought-after internationally and within a variety of justice-related professions; however, producing university graduates with the requisite professional knowledge, as well as analytical, organisational and technical skills presents a pedagogical and technical challenge to university educators. The situation becomes even more challenging when students are undertaking their studies by distance education. This best practice session showcases the design of an online undergraduate unit for final year justice students which uses an evolving real-time criminal scenario as the focus of authentic learning activities in order to prepare students for graduate roles within the criminal intelligence and justice professions. Within the unit, students take on the role of criminal intelligence analysts, applying relevant theories, models and strategies to solve a complex but realistic crime and complete briefings and documentation to industry standards as their major summative assessment task. The session will demonstrate how the design of the online unit corresponds to authentic learning principles, and will specifically map the elements of the unit design to Herrington & Oliver’s instructional design framework for authentic learning (2000; Herrington & Herrington 2006). The session will show how a range of technologies was used to create a rich learning experience for students that could be easily maintained over multiple unit iterations without specialist technical support. The session will also discuss the unique pedagogical affordances and challenges implicated in the location of the unit within an online learning environment, and will reflect on some of the lessons learned from the development which may be relevant to other authentic online learning contexts.

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Researchers have found that transformational leadership is related to positive outcomes in educational institutions. Hence, it is important to explore constructs that may predict leadership style in order to identify potential transformational leaders in assessment and selection procedures. Several studies in non-educational settings have found that emotional intelligence is a useful predictor of transformational leadership, but these studies have generally lacked methodological rigor and contextual relevance. This project, set in Australian educational institutions, employed a more rigorous methodology to answer the question: to what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes? The project was designed to move research in the field forward by using valid and reliable instruments, controlling for other predictors, obtaining an adequately sized sample of current leaders and collecting multiple ratings of their leadership behaviours. The study (N = 144 leaders and 432 raters) results indicated that emotional intelligence was not a useful predictor of leadership style and perceived leadership outcomes. In contrast, several of the other predictors in the study were found to predict leadership style.

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Previous research into the potential ‘dark’ side of trait emotional intelligence (EI) has repeatedly demonstrated that trait EI is negatively associated with Machiavellianism. In this study, we reassess the potential dark side of trait EI, by testing whether Agreeableness mediates and/or moderates the relationship between trait EI and Machiavellianism. Hypothesized mediation and moderation effects were tested using a large sample of 884 workers who completed several self-report questionnaires. Results provide support for both hypotheses; Agreeableness was found to mediate and moderate the relationship between trait EI and Machiavellianism. Overall, results indicate that individuals high in trait EI tend to have low levels of Machiavellianism because they generally have a positive nature (i.e. are agreeable) and not because they are emotionally competent per se. Results also indicate that individuals high in ‘perceived emotional competence’ have the potential to be high in Machiavellianism, particularly when they are low in Agreeableness.

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Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.

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The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

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In this paper we focus specifically on explaining variation in core human values, and suggest that individual differences in values can be partially explained by personality traits and the perceived ability to manage emotions in the self and others (i.e. trait emotional intelligence). A sample of 209 university students was used to test hypotheses regarding several proposed direct and indirect relationships between personality traits, trait emotional intelligence and values. Consistent with the hypotheses, Harm Avoidance and Novelty Seeking were found to directly predict Hedonism, Conformity, and Stimulation. Harm Avoidance was also found to indirectly predict these values through the mediating effects of key subscales of trait emotional intelligence. Novelty Seeking was not found to be an indirect predictor of values. Results have implications for our understanding of the relationship between personality, trait emotional intelligence and values, and suggest a common basis in terms of approach and avoidance pathways.

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The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

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This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

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This thesis is an explorative study of four national level law enforcement agencies' applications of strategic intelligence against transnational organised crime. The thesis develops a hybrid conceptual model for strategic intelligence in law enforcement, which explains how strategic intelligence influences police management. Dr Coyne explored case studies of strategic intelligence in the Criminal Intelligence Service Canada, Serious and Organised Crime Agency United Kingdom, Australian Crime Commission and the Australian Federal Police. The research provides an understanding of the impact of strategic intelligence across strategic responses to transnational organised crime and the implications this has for police management and intelligence theory.

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This study explored the mediating effect of emotional intelligence (EI) and coping strategies on problem behaviours in Australian adolescents. One hundred and forty-five adolescents (60 boys and 85 girls with a mean age of 12.02 years) completed self-report instruments of EI, stress coping strategies, and problem behaviours. The relationships between Emotional Management and Control and engagement in internalising and externalising behaviours were found to be mediated by the use of non-productive coping strategies. Mediation models of the relationship between problem behaviours and the Understanding Emotions and Emotional Recognition and Expression dimensions were found to be only partially mediated by the engagement in problem-focused and non-productive coping strategies. The results are discussed in regards to how coping strategies utilised in adolescence may produce more or less adaptive patterns of coping during adulthood. The development of emotional abilities may be required to improve coping outcomes for adolescents, which in turn may produce better psychological outcomes for adolescents in the long term.

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Background and Objectives: Although depression is a commonly occurring mental illness, research concerning strategies for early detection and prophylaxis has not until now focused on the possible utility of measures of Emotional Intelligence (EI) as a potential predictive factor. The current study aimed to investigate the relationship between EI and a clinical diagnosis of depression in a cohort of adults. Methods: Sixty-two patients (59.70% female) with a DSM-IV-TR diagnosis of a major affective disorder and 39 aged matched controls (56.40% female) completed self-report instruments assessing EI and depression in a cross-sectional study. Results: Significant associations were observed between severity of depression and the EI dimensions of Emotional Management (r = -0.56) and Emotional Control (r = -0.62). The results show a reduced social involvement, an increased prior institutionalization and an increased incidence of "Schizophrenic Psychosis" and "Abnormal Personalities" in the sub-group of repeated admissions. Conclusions: Measures of EI may have predictive value in terms of early identification of those at risk for developing depression. The current study points to the potential value of conducting further studies of a prospective nature.

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Occupational stress research has consistently demonstrated negative effects for employees. Research also describes potential moderators of this relationship. While research has revealed some positive effects of emotional intelligence (EI) on employee adjustment, it has neglected investigation of their potential stress buffering effects. Based on the Job-Demand Resources model, it was predicted that higher trait emotional intelligence would act as a buffer to the potential negative effects of stressors on employee adjustment. Hierarchical multiple regression analyses with a sample of 306 nurses found no main effects of EI but revealed eight moderating effects. While some interactions support the buffering hypothesis, others revealed buffering for those with low EI. Findings are discussed in terms of theoretical and practical implications.

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The Wechsler and Stanford Binet scales are among the most commonly used tests of intelligence. In clinical practice, they often seem to be used interchangeably. This paper reports the results of two studies that compared the most recent editions of two Wechsler scales (WPPSI-III and WISC-IV) with the Stanford-Binet Fifth Edition (SB5). The participants in the first study were 36 typically developing 4-year-old children who completed the WPPSI-III and SB5 in counter-balanced order. Although correlations of composite scores ranged from r = .59 to r = .82 and were similar to those reported for earlier versions of the two instruments, more than half the sample had a score discrepancy greater than 10 points across the two instruments. In the second study, the WISC-IV and SB5 were administered to 30 children aged 12-14 years. There was a significant difference between Full Scale IQs on the two measures, with scores being higher on the WISC-IV. Differences between the two verbal scales were also significant and favoured the WISC-IV. There were moderate correlations of Full Scale IQs (r = .58) and Nonverbal IQs (r = .54) but the relationship between the two Verbal scales was not significant. For some children, notable score differences led to different categorisations of their level of intellectual ability The findings suggest that the Wechsler and Stanford Binet scales cannot be presumed to be interchangeable. The discussion focuses on how psychologists might reconcile large differences in test scores and the need for caution when interpreting and comparing test results.

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Large complex projects often fail spectacularly in terms of cost overruns and delays; witness the London Olympics and the Airbus A380. In this project, we studied the emotional intelligence (EI) of leadership teams involved in such projects. We collected our data from 370 employees in 40 project teams working on large Australian defense contracts. We asked leadership team members to complete a scale measuring their EI, and project team members to rate the success of the projects. We found it was not the mean score, but the highest EI score in the leadership team that predicted members’ project success ratings.