Pupil Transportation Claim Reimbursement System : user's guide for regional superintendents (ROE ADMIN).

Cover title.

Data user news /

Latest issue consulted: Vol. 16, no. 12 (Dec. 1981).

Charging for federal services.

Mode of access: Internet.

Effective affective user interface design in games

It is proposed that games, which are designed to generate positive affect, are most successful when they facilitate flow (Csikszentmihalyi 1992). Flow is a state of concentration, deep enjoyment, and total absorption in an activity. The study of games, and a resulting understanding of flow in games can inform the design of non-leisure software for positive affect. The paper considers the ways in which computer games contravene Nielsen's guidelines for heuristic evaluation ( Nielsen and Molich 1990) and how these contraventions impact on flow. The paper also explores the implications for research that stem from the differences between games played on a personal computer and games played on a dedicated console. This research takes important initial steps towards de. ning how flow in computer games can inform affective design.

Producing computer-generated tailored written information for stroke patients and their carers: System development and preliminary evaluation

Purpose: The aim of this project was to design and evaluate a system that would produce tailored information for stroke patients and their carers, customised according to their informational needs, and facilitate communication between the patient and, health professional. Method: A human factors development approach was used to develop a computer system, which dynamically compiles stroke education booklets for patients and carers. Patients and carers are able to select the topics about which they wish to receive information, the amount of information they want, and the font size of the printed booklet. The system is designed so that the health professional interacts with it, thereby providing opportunities for communication between the health professional and patient/carer at a number of points in time. Results: Preliminary evaluation of the system by health professionals, patients and carers was positive. A randomised controlled trial that examines the effect of the system on patient and carer outcomes is underway. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

The International Consortium on Mental Health Policy and Services: objectives, design and project implementation

The concept of the burden of disease, introduced and estimated for a broad range of diseases in the World Bank report of 1993 illustrated that mental and neurological disorders not only entail a higher burden than cancer, but are responsible, in developed and developing countries, for more than 15% of the total burden of all diseases. As a consequence, over the past decade, mental disorders have ranked increasingly highly on the international agenda for health. However, the fact that mental health and nervous system disorders are now high on the international health agenda is by no means a guarantee that the fate of patients suffering from these disorders in developing countries will improve. In most developing countries the treatment gap for mental and neurological disorders is still unacceptably high. To address this problem, an international network of collaborating institutions in low-income countries has been set up. The establishment and the achievements of this network-the International Consortium on Mental Health Policy and Services-are reported. Sixteen institutions in developing countries collaborate (supported by a small number of scientific resource centres in industrialized nations) in projects on applied mental health systems research. Over a two-year period, the network produced the key elements of a national mental health policy; provided tools and methods for assessing a country's current mental health status (context, needs and demands, programmes, services and care and outcomes); established a global network of expertise, i.e., institutions and experts, for use by countries wishing to reform their mental health policy, services and care; and generated guidelines and examples for upgrading mental health policy with due regard to the existing mental health delivery system and demographic, cultural and economic factors.

Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.