953 resultados para Comprehensive development


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Mode of access: Internet.

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Bibliography: p. 57-59.

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In this thesis we discuss the expansion of an existing project, called CHIMeRA, which is a comprehensive biomedical network, and the analysis of its sub-components by using graph theory. We describe how it is structured internally, what are the existing databases from which it retrieves information and what machine learning techniques are used in order to produce new knowledge. We also introduce a new technique for graph exploration that is aimed to speed-up the network cover time under the condition that the analyzed graph is stellar; if this condition is satisfied, the improvement in the performance compared to the conventional exploration technique is extremely appealing. We show that the stellar structure is highly recurrent for sub-networks in CHIMeRA generated by queries, which made this technique even more interesting. Finally, we describe the convenience in using the CHIMeRA network for research purposes and what it could become in a very near future.

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Evaluation of students undertaking fieldwork education placements is a critical process in the health professions. As training programs and practice evolve, systems for assessing students need to be reviewed and updated constantly. In 1995, staff of the occupational therapy training program at the University of Queensland, Australia decided to develop a new tool for assessing student fieldwork performance. Using an action research methodology, a team developed the Student Placement Evaluation Form, a flexible and comprehensive criterion-referenced evaluation tool. The present paper examines action research as an appropriate methodology for considering real-life organisational problems in a systematic and participatory manner. The action research cycles undertaken, including preliminary information gathering, tool development, trial stages and current use of the tool, are detailed in the report. Current and future development of the tool is also described.

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This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

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Data describing the composition of dietary supplements are not readily available to the public health community. As a result, intake from dietary supplements is generally not considered in most dietary surveys and, hence, little is known about the significance of supplement intake in relation to total diet or disease risk. To enable a more comprehensive analysis of dietary data, a database of the composition of various dietary supplements has been compiled. Active ingredients of all dietary supplements sold in Australia are included in the Australian Register of Therapeutic Goods (ARTG), maintained by the Therapeutic Goods Administration. Products included in the database were restricted to those vitamin, mineral and other supplements identified in dietary data collected from studies conducted in southeast Queensland and New South Wales (850 supplements). Conversion factors from ingredients compounds to active elements were compiled from standard sources. No account has been made for bioavailability, consistent with current practice for food composition databases. The database can be queried by ARTG identification number, brand, product title, or a variety of other fields. Expected future developments include development of standard formulations for use when supplements are incompletely specified, and expansion of products included for more widespread use.

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Purpose of review To explore recent findings bridging childhood development and common late-life mental disorders in the elderly. Recent findings We addressed aging as a part of the developmental process in central nervous system, typical and atypical neurodevelopment focusing on genetic and environmental risk factors and their interplay and links between psychopathology from childhood to the elderly, unifying theoretical perspectives and preventive intervention strategies. Summary Current findings suggest that childhood development is strictly connected to psychiatric phenotypes across the lifespan. Although we are far from a comprehensive understanding of mental health trajectories, some initial findings document both heterotypic and homotypic continuities from childhood to adulthood and from adulthood to the elderly. Our review also highlights the urgent need for investigations on preventive interventions in individuals at risk for mental disorders.