44 research outputs found

    A possibilistic approach to latent structure analysis for symmetric fuzzy data.

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    In many situations the available amount of data is huge and can be intractable. When the data set is single valued, latent structure models are recognized techniques, which provide a useful compression of the information. This is done by considering a regression model between observed and unobserved (latent) fuzzy variables. In this paper, an extension of latent structure analysis to deal with fuzzy data is proposed. Our extension follows the possibilistic approach, widely used both in the cluster and regression frameworks. In this case, the possibilistic approach involves the formulation of a latent structure analysis for fuzzy data by optimization. Specifically, a non-linear programming problem in which the fuzziness of the model is minimized is introduced. In order to show how our model works, the results of two applications are given.Latent structure analysis, symmetric fuzzy data set, possibilistic approach.

    Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping:a case of Mozambican banks

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    Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed

    Efficiency in South African agriculture : a two-stage fuzzy approach

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    PURPOSE : The purpose of this paper is to assess the efficiency of agricultural production in South Africa from 1970 to 2014, using an integrated two-stage fuzzy approach. DESIGN/METHODOLOGY/APPROACH : Fuzzy technique for order preference by similarity to ideal solution is used to assess the relative efficiency of agriculture in South Africa over the course of the years in the first stage. In the second stage, fuzzy regressions based on different rule-based systems are used to predict the impact of socio-economic and demographic variables on agricultural efficiency. They are compared with the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2016a). FINDINGS : The results show that the fuzzy efficiency estimates ranged from 0.40 to 0.68 implying inefficiency in South African agriculture. The results further reveal that research and development, land quality, health expenditure–population growth ratio have a significant, positive impact on efficiency levels, besides the GINI index. In terms of accuracy, fuzzy regressions outperformed the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2015). PRACTICAL IMPLICATIONS : Policies to increase social expenditure especially in terms of health and hence productivity should be prioritized. Also policies aimed at conserving the environment and hence the quality of land is needed. ORIGINALITY/VALUE : The paper is original and has not been previously published elsewhere.https://www.emerald.com/insight/publication/issn/1463-5771hj2019Economic

    Construction of Optimal Membership Functions for a Fuzzy Routing Scheme in Opportunistic Mobile Networks

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    Work, aging, mental fatigue, and eye movement dynamics

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    Visual search and VDUS

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    This wide-ranging study explored various parameters of visual search in relation to computer screen displays. Its ultimate goal was to help identify factors which could result in improvements in commercially available displays within the 'real world’. Those improvements are generally reflected in suggestions for enhancing efficiency of locatabolity of information through an acknowledgement of the visual and cognitive factors involved. The thesis commenced by introducing an ergonomics approach to the presentation of information on VDUs. Memory load and attention were discussed. In the second chapter, literature on general and theoretical aspects of visual search (with particular regard for VDUs) was reviewed. As an experimental starting point, three studies were conducted involving locating a target within arrays of varying configurations. A model concerning visual lobes was proposed. Two text-editing studies were then detailed showing superior user performances where conspicuity and the potential for peripheral vision are enhanced. Relevant eye movement data was combined with a keystroke analysis derived from an automated protocol analyser. Results of a further search task showed icons to be more quickly located within an array than textual material. Precise scan paths were then recorded and analyses suggested greater systematicity of search strategies for complex items. This led on to a relatively 'pure' search study involving materials of varying spatial frequencies. Results were discussed in terms of verbal material generally being of higher spatial frequencies and how the ease of resolution and greater cues available in peripheral vision can result in items being accessed more directly. In the final (relatively applied) study, differences in eye movement indices were found across various fonts used. One main conclusion was that eye movement monitoring was a valuable technique within the visual search/VDU research area in illuminating precise details of performance which otherwise, at best, could only be inferred

    Proceedings / 6th International Symposium of Industrial Engineering - SIE 2015, 24th-25th September, 2015, Belgrade

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    editors Vesna Spasojević-Brkić, Mirjana Misita, Dragan D. Milanovi

    Proceedings / 6th International Symposium of Industrial Engineering - SIE 2015, 24th-25th September, 2015, Belgrade

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    editors Vesna Spasojević-Brkić, Mirjana Misita, Dragan D. Milanovi

    Engineering data compendium. Human perception and performance, volume 3

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    The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design of military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by system designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is Volume 3, containing sections on Human Language Processing, Operator Motion Control, Effects of Environmental Stressors, Display Interfaces, and Control Interfaces (Real/Virtual)

    Detecting and Modelling Stress Levels in E-Learning Environment Users

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    A modern Intelligent Tutoring System (ITS) should be sentient of a learner's cognitive and affective states, as a learner’s performance could be affected by motivational and emotional factors. It is important to design a method that supports low-cost, task-independent and unobtrusive sensing of a learner’s cognitive and affective states, to improve a learner's experience in e-learning, as well as to enable personalized learning. Although tremendous related affective computing research were done in this area, there is a lack of empirical research that can automatically measure a learner's stress using objective methods. This research is set to examine how an objective stress measurement model can be developed, to compute a learner’s cognitive and emotional stress automatically using mouse and keystroke dynamics. To ensure the measurement is not affected even if the user switches between tasks, three preliminary research experiments were carried out based on three common tasks during e-learning − search, assessment and typing. A stress measurement model was then built using the datasets collected from the experiments. Three stress classifiers were tested, namely certainty factors, feedforward back-propagation neural network and adaptive neuro-fuzzy inference system. The best classifier was then integrated into the ITS stress inference engine, which is designed to decide necessary adaptation, and to provide analytical information of learners' performances, which include stress levels and learners’ behaviours when answering questions
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