Practical training is an essential component of nursing students' preparation to entering the workforce and making decisions that impact patients' health and often lives. We designed a 3D game (VI-MED) to support virtual training to be used as a precursor and as a supplement to real practical training. The VI-MED system has two main components: 1. A gaming component which simulates a hospital environment with patients generated for each session and a full spectrum of interventions that the player can use on the patients, and 2. An Assessment component which monitors the players progress, updates their profile, and customizes their experience with the games accordingly. We discuss here the design of VI-MED with a special focus on the modeling of the user's (student) profile and the modeling of the patients that get generated at each game session. Both of these are driven by the learning outcomes that the nursing faculty sets for their students.

The education of students in Medical and Nursing Schools is a prime candidate to benefit from the promises of simulation-based learning tools. Well designed computer based systems have been shown to have a dramatic impact on the learning of students. At the same time, the design of these learning tools is still a pain staking task. In this paper, we share our experience at developing and testing a game-based environment for training nursing students.

Protecting computer networks from accidental and malicious harm is a critical issue. Researchers have sought a variety of solutions ranging from the purely statistical approach to approaches inspired from a variety of fields such as economics and biology. In this paper, we focus on the issue of intruder detection and propose two complementary approaches, one economics-based, the other biology-inspired. We discuss the effectiveness of these two approaches put together as compared to each one alone based on Matlab simulations.

Extending the life of a sensor network while maintaining an acceptable level of accuracy continues to be a critical challenge in long-lived applications requiring months and years of continuous operation. In this paper, we present an approach to address this challenge, namely selective querying based on the transinformation value of nodes relative to the query being executed. The approach is distributed whereby decisions are made by individual nodes and cluster heads based on information locally available. Simulation results establish the feasibility of this approach and show significant gains in the lifetime of the network.

Two kinds of fuzziness in attribute values of the fuzzy relational databases can be distinguished: One is that attribute values are possibility distributions, and the other is that there are resemblance relations in attribute domains. The fuzzy relational databases containing these two kinds of fuzziness simultaneously are called extended possibility-based fuzzy relational databases. In this paper, we focus on such fuzzy relational databases. We classify two kinds of fuzzy data redundancies and define their removal. On this basis, we define fuzzy relational operations in relational algebra, which, being similar to the conventional relational databases, are complete and sound. In particular, we investigate fuzzy querying strategies and give the form of fuzzy querying with SQL. © 2002 Wiley Periodicals, Inc.

In this article, we focus on the issues of fuzzy data dependencies. After introducing the notion of semantic equivalence degree, fuzzy functional and multivalued dependencies are defined. A set of sound and complete inference rules, similar to Armstrong's axioms for classic cases, for fuzzy functional dependencies (FFDs) and fuzzy multivalued dependencies (FMVDs) are proposed. The strategies and approaches for compressing fuzzy values by FFDs and FMVDs are investigated. By such processing, the unnecessary elements are eliminated from a fuzzy value and its range is compressed. © 2002 Wiley Periodicals, Inc.

Based on the semantic equivalence degree the formal definitions of fuzzy functional dependencies (FFDs) and fuzzy multivalued dependencies (FMVDs) are first introduced to the fuzzy relational databases, where fuzziness of data appears in attribute values in the form of possibility attributions, as well as resemblance relations in attribute domain elements, called extended possibility-based fuzzy relational databases. A set of inference rules for FFDs and FMVDs is then proposed. It is shown that FFDs and FMVDs are consistent and the inference rules are sound and complete, just as Armstrong's axioms for classic cases. © 2002 Wiley Periodicals, Inc.

Software productivity has been steadily increasing over the past 30 years, but not enough to close the gap between the demands placed on the software industry and what the state of the practice can deliver; nothing short of an order of magnitude increase in productivity will extricate the software industry from its perennial crisis. Several decades of intensive research in software engineering and artificial intelligence left few alternatives but software reuse as the (only) realistic approach to bring about the gains of productivity and quality that the software industry needs. In this paper, we discuss the implications of reuse on the production, with an emphasis on the technical challenges. Software reuse involves building software that is reusable by design and building with reusable software. Software reuse includes reusing both the products of previous software projects and the processes deployed to produce them, leading to a wide spectrum of reuse approaches, from the building blocks (reusing products) approach, on one hand, to the generative or reusable processor (reusing processes), on the other. We discuss the implication of such approaches on the organization, control, and method of software development and discuss proposed models for their economic analysis. Software reuse benefits from methodologies and tools to: (1) build more readily reusable software and (2) locate, evaluate, and tailor reusable software, the last being critical for the building blocks approach. Both sets of issues are discussed in this paper, with a focus on application generators and OO development for the first and a thorough discussion of retrieval techniques for software components, component composition (or bottom-up design), and transformational systems for the second. We conclude by highlighting areas that, in our opinion, are worthy of further investigation.>

Studies the integration of data with data analysis methods in the context of scientific databases. They author proposes a description of the analysis methods that makes them independent of the application domain (and thus reusable). This is complemented with a description that explicitly relates them to the application domain and assesses them within that context (and thus makes them easier to comprehend and use). This latter description is the focus of this work. The authors studies the nature of the information needed and proposes an outline procedure for deriving it.