969 resultados para Real-world


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Our eyes never remain still. Even when we stare at a fixed point, small involuntary movements take place in our eyes in an imperceptible manner. Researchers agree on the presence of three main contributions to eye movements when we fix the gaze: microsaccades, drifts and tremor. These small movements carry the image across the retina stimulating the photoreceptors and thus avoiding fading. Nowadays it is commonly accepted that these movements can improve the discrimination performance of the retina. In this paper, several retina models with and without fixational eye movements were implemented by mean of RetinaStudio tool to test the feasibility of these models to be incorporated in future neuroprostheses. For this purpose each retina model has been stimulated with natural scene images in two experiments. Results are discussed from the point of view of a neuroprosthesis development.

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Transportation Department, Joint Program Office for Intelligent Transportation Systems, Washington, D.C.

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Mode of access: Internet.

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The present study evaluated the impact of a universal prevention of depression program [the Resourceful Adolescent Program (RAP)] when implemented under real-world conditions in a school setting. Prior research has found the RAP program to be beneficial for high-school students when the program was implemented by university staff selected, trained, and supervised by a research team. The present study evaluated the RAP program when implemented by existing school personnel. Separately, we measured the impact of a training program for facilitators, the quality of subsequent program implementation, and the student's response to the RAP Program. Results showed that, in response to the training program, facilitators believed they had acquired the knowledge and confidence to implement the program and that the quality of program implementation was acceptable. The study did not demonstrate a beneficial impact of the RAP program for the students. The results raise important questions regarding the extent of training and ongoing supervision facilitators require if the beneficial outcomes for students are to be maintained when interventions are implemented under real-world conditions in school settings. (C) 2004 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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We report on teaching Information Systems Analysis (ISA) in a way that takes the classroom into the real world to enrich students' understanding of the broader role of being an IS professional. Through exposure to less controllable and more uncomfortable issues (e.g., client deadlines; unclear scope; client expectations; unhelpful colleagues, complexity about what is the problem never mind the solution) we aim to better prepare students to respond to the complex issues surrounding deployment of systems analysis methodologies in the real world. In this paper we provide enough detail on what these classes involve to allow a reader to replicate appealing elements in their own teaching. This paper is a reflection on integrating in the real world when teaching ISA – a reflection from the standpoint of students who face an unstructured and complex world and of lecturers who aim to prepare students to hit the floor running when they encounter that world.

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In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.