327 research outputs found

    Education Quality Control Based on System Dynamics and Evolutionary Computation

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    Models and tools for value systems analysis in collaborative environments

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    Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative NetworksParticipation in collaborative networks is vital for small and medium-sized enterprises to survive in the current market, bringing them several benefits. However,participation in collaborative networks also involves risks and often consortia fail due to internal conflicts. Conflicts can be originated by different prioritization of values and different perceptions of outcomes. The perception of outcomes is, to some extent, subjective given that it depends on the preferences of the subject and how exchanges are evaluated. Therefore, the establishment of a common Value System or the effort to align the Value Systems of network members can play an important role in the collaboration sustainability. Although the topic of values and values alignment has been studied within the scope of various scientific disciplines, there is still no common understanding on these concepts and the literature does not include any suitable models to formally represent and analyze Value Systems within the scope of collaborative networks. This thesis proposes a set of models and formal mechanisms for specifying and analyzing Value Systems in collaborative networks. The development of models and methods followed a hybrid approach, where qualitative and quantitative techniques are used in order to represent and analyze the Value System. A web application was designed and a prototype developed in order to show that the models and methods proposed can be implemented by a computer program and can be integrated into a single framework in order to support Value Systems management within the scope of collaborative networks. The application of a multifaceted and systematic validation strategy, supported by the “Square Validation Framework” brought together a set of preliminary results that attest the theoretical and practical relevance of the proposed approach and allow us to conclude that: (i) it is possible to define and analyze Value Systems in collaborative networks, considering the economic and sociologic approach, in an integrated and unambiguous way, (ii) the potential impacts between Value Systems in collaborative environments can be inferred if the typical influences among core values are known and the preferences of the actors, regarding those values, are identified; (iii) the identification and assessment of Value Systems misalignments would be improved if qualitative and quantitative assessment methods integrating the notion of shared-values, potential for conflict and positive impacts were developed

    Academic Catalog: 2022-23

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    Advanced Technology for Engineering Education

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    This document contains the proceedings of the Workshop on Advanced Technology for Engineering Education, held at the Peninsula Graduate Engineering Center, Hampton, Virginia, February 24-25, 1998. The workshop was jointly sponsored by the University of Virginia's Center for Advanced Computational Technology and NASA. Workshop attendees came from NASA, other government agencies, industry and universities. The objectives of the workshop were to assess the status of advanced technologies for engineering education and to explore the possibility of forming a consortium of interested individuals/universities for curriculum reform and development using advanced technologies. The presentations covered novel delivery systems and several implementations of new technologies for engineering education. Certain materials and products are identified in this publication in order to specify adequately the materials and products that were investigated in the research effort. In no case does such identification imply recommendation or endorsement of products by NASA, nor does it imply that the materials and products are the only ones or the best ones available for this purpose. In many cases equivalent materials and products are available and would probably produce equivalent results

    Army-NASA aircrew/aircraft integration program (A3I) software detailed design document, phase 3

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    The capabilities and design approach of the MIDAS (Man-machine Integration Design and Analysis System) computer-aided engineering (CAE) workstation under development by the Army-NASA Aircrew/Aircraft Integration Program is detailed. This workstation uses graphic, symbolic, and numeric prototyping tools and human performance models as part of an integrated design/analysis environment for crewstation human engineering. Developed incrementally, the requirements and design for Phase 3 (Dec. 1987 to Jun. 1989) are described. Software tools/models developed or significantly modified during this phase included: an interactive 3-D graphic cockpit design editor; multiple-perspective graphic views to observe simulation scenarios; symbolic methods to model the mission decomposition, equipment functions, pilot tasking and loading, as well as control the simulation; a 3-D dynamic anthropometric model; an intermachine communications package; and a training assessment component. These components were successfully used during Phase 3 to demonstrate the complex interactions and human engineering findings involved with a proposed cockpit communications design change in a simulated AH-64A Apache helicopter/mission that maps to empirical data from a similar study and AH-1 Cobra flight test

    Academic Catalog: 2019-20

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    A methodology for producing reliable software, volume 1

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    An investigation into the areas having an impact on producing reliable software including automated verification tools, software modeling, testing techniques, structured programming, and management techniques is presented. This final report contains the results of this investigation, analysis of each technique, and the definition of a methodology for producing reliable software

    Process modelling to support software development under the capability maturity model

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