22,922 research outputs found

    Application of Value Focused Thinking and Fuzzy Systems to Assess System Architecture

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    AbstractSince a majority of resources are obligated during the design phase of a system lifecycle, critical assessment of candidate functional and system architectures is vital to identify optimal architectures before proceeding to subsequent lifecycle phases. Common challenges associated with generation and evaluation of system functional architectures include search of the expansive design space and assessment of key performance attributes that are particularly “fuzzy” and qualitative in early architecture development. Several assessment approaches have been presented in the literature to address the assessment challenge to include Quality Function Deployment (QFD), Analytical Hierarchy Process (AHP), Value-Focused Thinking (VFT), and fuzzy logic. In this research we combine the use of value functions and fuzzy assessment to assess a functional and system architecture. There are several benefits of a methodology that combines value-focused thinking and fuzzy assessment. A distinct advantage of the methodology presented is the explicit inclusion of the customer in the assessment process through validation of the TPM value functions Involving the customer in TPM value function development and validation ensures the customer has direct input regarding the TPMs and their associated value across the range of discourse The methodology presented is flexible enough to assess architectures early in the process when things are “fuzzy” as well as later when subsystem and component performance are well defined. The methodology can also be used to analyze and assess impacts of interface changes within the system architecture. . The methodology is domain independent and can be coupled with executable models linked to scenarios. The assessment methodology is applied to the architecture for a soldier knowledge acquisition system for which the key performance attributes are affordability, performance, flexibility, updateability, and availability

    The assessment of complex learning outcomes

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    The Engineering Professors' Council (EPC) produced an output standard in 2000 containing a setof 26 generic statements of what an engineering graduate should have an ability to tackle. In addition, Higher Education (HE) is concerned with the promotion of complex or advanced understanding of subject matter. This leads to complex learning outcomes, which need to be adequately assessed. Changing demands mean changing assessment practices. While good practice is being used in many cases, there is a need to ensure assessment stimulates complex learning. The article seeks to address these issues

    Fault detection, identification and accommodation techniques for unmanned airborne vehicles

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    Unmanned Airborne Vehicles (UAV) are assuming prominent roles in both the commercial and military aerospace industries. The promise of reduced costs and reduced risk to human life is one of their major attractions, however these low-cost systems are yet to gain acceptance as a safe alternate to manned solutions. The absence of a thinking, observing, reacting and decision making pilot reduces the UAVs capability of managing adverse situations such as faults and failures. This paper presents a review of techniques that can be used to track the system health onboard a UAV. The review is based on a year long literature review aimed at identifying approaches suitable for combating the low reliability and high attrition rates of today’s UAV. This research primarily focuses on real-time, onboard implementations for generating accurate estimations of aircraft health for fault accommodation and mission management (change of mission objectives due to deterioration in aircraft health). The major task of such systems is the process of detection, identification and accommodation of faults and failures (FDIA). A number of approaches exist, of which model-based techniques show particular promise. Model-based approaches use analytical redundancy to generate residuals for the aircraft parameters that can be used to indicate the occurrence of a fault or failure. Actions such as switching between redundant components or modifying control laws can then be taken to accommodate the fault. The paper further describes recent work in evaluating neural-network approaches to sensor failure detection and identification (SFDI). The results of simulations with a variety of sensor failures, based on a Matlab non-linear aircraft model are presented and discussed. Suggestions for improvements are made based on the limitations of this neural network approach with the aim of including a broader range of failures, while still maintaining an accurate model in the presence of these failures

    The Relationship between Fuzzy Reasoning and Its Temporal Characteristics for Knowledge Management

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    The knowledge management systems based on artificial reasoning (KMAR) tries to provide computers the capabilities of performing various intelligent tasks for which their human users resort to their knowledge and collective intelligence. There is a need for incorporating aspects of time and imprecision into knowledge management systems, considering appropriate semantic foundations. The aim of this paper is to present the FRTES, a real-time fuzzy expert system, embedded in a knowledge management system. Our expert system is a special possibilistic expert system, developed in order to focus on fuzzy knowledge.Knowledge Management, Artificial Reasoning, predictability

    ERP implementation methodologies and frameworks: a literature review

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    Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

    Improving the translation environment for professional translators

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    When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project
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