The development of a computer simulation model of the interaction between the supply and usage of major components in car assembly you use in stock control

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Children's attentional skills and road behavior

Switching attention and concentration, 2 skills expected to be used by skillful pedestrians, were studied. A sample of 160 children (aged 4 years 3 months-10 years) played a computer game involving attention switching. To examine concentration, a subset of the children was distracted with a cartoon video while they attempted a difficult task that required matching familiar figures. The same subset was also observed crossing roads. Older children switched faster and were less distracted. Children who were better at switching were more likely to show awareness of traffic when about to cross a road. Children who maintained concentration when challenged by a distracting event crossed the road in a less reckless manner. Parents and educators designing safety programs should take into account the development of these skills.

Air traffic controller reactions to computer assistance

The research was instigated by the Civil Aviation Authority (CAA) to examine the implications for air traffic controllers' (ATCO) job satisfaction of the possible introduction of systems incorporating computer-assisted decision making. Additional research objectives were to assess the possible costs of reductions in ATCO job satisfaction, and to recommend appropriate task allocation between ATCOs and computer for future systems design (Chapter 1). Following a review of the literature (Chapter 2) it is argued that existing approaches to systems and job design do not allow for a sufficiently early consideration of employee needs and satisfactions in the design of complex systems. The present research develops a methodology for assessing affective reactions to an existing system as a basis for making reommendations for future systems design (Chapter 3). The method required analysis of job content using two techniques: (a) task analysis (Chapter 4.1) and (b) the Job Diagnostic Survey (JDS). ATCOs' affective reactions to the several operational positions on which they work were investigated at three levels of detail: (a) Reactions to positions, obtained by ranking techniques (Chapter 4.2); (b) Reactions to job characteristics, obtained by use of JDS (Chapter 4.3); and (c) Reactions to tasks, obtained by use of Repertory Grid technique (Chapter 4.4). The conclusion is drawn that ATCOs' motivation and satisfaction is greatly dependent on the presence of challenge, often through tasks requiring the use of decision making and other cognitive skills. Results suggest that the introduction of systems incorporating computer-assisted decision making might result in financial penalties for the CAA and significant reductions in job satisfaction for ATCOs. General recommendations are made for allocation of tasks in future systems design (Chapter 5).

Can computer-based testing achieve quality and efficiency in assessment?

This paper reports findings of a two year study concerning the development and implementation of a general-purpose computer-based assessment (CBA) system at a UK University. Data gathering took place over a period of nineteen months, involving a number of formative and summative assessments. Approximately 1,000 students, drawn from undergraduate courses, were involved in the exercise. The techniques used in gathering data included questionnaires, observation, interviews and an analysis of student scores in both conventional examinations and computer-based assessments. Comparisons with conventional assessment methods suggest that the use of CBA techniques may improve the overall performance of students. However it is clear that the technique must not be seen as a "quick fix" for problems such as rising student numbers. If one accepts that current systems test only a relatively narrow range of skills, then the hasty implementation of CBA systems will result in a distorted and inaccurate view of student performance. In turn, this may serve to reduce the overall quality of courses and - ultimately - detract from the student learning experience. On the other hand, if one adopts a considered and methodical approach to computer-based assessment, positive benefits might include increased efficiency and quality, leading to improved student learning.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.