487,554 research outputs found

    The Feasibility of Using Expert Systems in the Management of Human Resources

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    The purpose of this paper is to introduce a decision aid that is being used increasingly in the business world, the expert system, and to begin to examine its potential for human resource management. First, the expert system technology is reviewed, with a special emphasis on the players, those involved in developing and using the system, and the parts, the three main components of a system. This is followed by an analysis of the costs and benefits and the advantages and disadvantages that have been ascribed to expert systems. We conclude this initial research endeavor by presenting some preliminary findings which suggest that employees are willing to cooperate with expert systems, even those that require personal information, and that they see some benefits to using expert systems as decision aids

    Bridging the Gap Between Traditional Metadata and the Requirements of an Academic SDI for Interdisciplinary Research

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    Metadata has long been understood as a fundamental component of any Spatial Data Infrastructure, providing information relating to discovery, evaluation and use of datasets and describing their quality. Having good metadata about a dataset is fundamental to using it correctly and to understanding the implications of issues such as missing data or incorrect attribution on the results obtained for any analysis carried out. Traditionally, spatial data was created by expert users (e.g. national mapping agencies), who created metadata for the data. Increasingly, however, data used in spatial analysis comes from multiple sources and could be captured or used by nonexpert users – for example academic researchers ‐ many of whom are from non‐GIS disciplinary backgrounds, not familiar with metadata and perhaps working in geographically dispersed teams. This paper examines the applicability of metadata in this academic context, using a multi‐national coastal/environmental project as a case study. The work to date highlights a number of suggestions for good practice, issues and research questions relevant to Academic SDI, particularly given the increased levels of research data sharing and reuse required by UK and EU funders

    Born to be Wild: Using Communities of Practice as a Tool for Knowledge Management

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    This paper looks at what happens when Communities of Practice are used as a tool for Knowledge Management. The original concept of a Community of Practice appears to have very little in common with the knowledge sharing communities found in Knowledge Management, which are based on a revised view of 'cultivated' communities. We examine the risks and benefits of cultivating Communities of Practice rather than leaving them 'in the wild'. The paper presents the findings from two years of research in a small microelectronics firm to provide some insights into the wild vs domesticated dichotomy and discusses the implications of attempting to tame Communities of Practice in this way.Comment: Paper presented at the Ethicomp 2010: The 'Backwards, Forwards and Sideways' changes of ICT, Tarragona, Spain, April, 2010, pp. 71 - 80

    Black, Gold, and Green: Food Waste Management at Bryant University

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    The basis of this project is to examine the food waste management system at Bryant University, and to make feasible, sustainable, and cost-effective solutions for improving the system. An effective, sustainable food waste management system is an important achievement for the university in particular as Rhode Island’s landfill is quickly reaching its capacity. The study focuses on analyzing the advantages and disadvantages of the university’s current solution of sending the waste to a local pig farmer versus alternative options such as composting the waste. Research methods include surveying local food recycling and composting experts and key stakeholders, a numeric ranking system to analyze different options for Bryant, as well as benchmarking with comparable colleges and universities that have launched successful food waste management solutions

    The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques

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    The paper describes VEX-93 as a hybrid environment for developing knowledge-based and problem solver systems. It integrates methods and techniques from artificial intelligence, image and signal processing and data analysis, which can be mixed. Two hierarchical levels of reasoning contains an intelligent toolbox with one upper strategic inference engine and four lower ones containing specific reasoning models: truth-functional (rule-based), probabilistic (causal networks), fuzzy (rule-based) and case-based (frames). There are image/signal processing-analysis capabilities in the form of programming languages with more than one hundred primitive functions. User-made programs are embeddable within knowledge basis, allowing the combination of perception and reasoning. The data analyzer toolbox contains a collection of numerical classification, pattern recognition and ordination methods, with neural network tools and a data base query language at inference engines's disposal. VEX-93 is an open system able to communicate with external computer programs relevant to a particular application. Metaknowledge can be used for elaborate conclusions, and man-machine interaction includes, besides windows and graphical interfaces, acceptance of voice commands and production of speech output. The system was conceived for real-world applications in general domains, but an example of a concrete medical diagnostic support system at present under completion as a cuban-spanish project is mentioned. Present version of VEX-93 is a huge system composed by about one and half millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version

    Run-time risk management in adaptive ICT systems

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    We will present results of the SERSCIS project related to risk management and mitigation strategies in adaptive multi-stakeholder ICT systems. The SERSCIS approach involves using semantic threat models to support automated design-time threat identification and mitigation analysis. The focus of this paper is the use of these models at run-time for automated threat detection and diagnosis. This is based on a combination of semantic reasoning and Bayesian inference applied to run-time system monitoring data. The resulting dynamic risk management approach is compared to a conventional ISO 27000 type approach, and validation test results presented from an Airport Collaborative Decision Making (A-CDM) scenario involving data exchange between multiple airport service providers
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