39,025 research outputs found

    Collaboration and Virtualization in Large Information Systems Projects

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    A project is evolving through different phases from idea and conception until the experiments, implementation and maintenance. The globalization, the Internet, the Web and the mobile computing changed many human activities, and in this respect, the realization of the Information System (IS) projects. The projects are growing, the teams are geographically distributed, and the users are heterogeneous. In this respect, the realization of the large Information Technology (IT) projects needs to use collaborative technologies. The distribution of the team, the users' heterogeneity and the project complexity determines the virtualization. This paper is an overview of these aspects for large IT projects. It shortly present a general framework developed by the authors for collaborative systems in general and adapted to collaborative project management. The general considerations are illustrated on the case of a large IT project in which the authors were involved.large IT projects, collaborative systems, virtualization, framework for collaborative virtual systems

    Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization

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    The separability assumption (Donoho & Stodden, 2003; Arora et al., 2012) turns non-negative matrix factorization (NMF) into a tractable problem. Recently, a new class of provably-correct NMF algorithms have emerged under this assumption. In this paper, we reformulate the separable NMF problem as that of finding the extreme rays of the conical hull of a finite set of vectors. From this geometric perspective, we derive new separable NMF algorithms that are highly scalable and empirically noise robust, and have several other favorable properties in relation to existing methods. A parallel implementation of our algorithm demonstrates high scalability on shared- and distributed-memory machines.Comment: 15 pages, 6 figure

    The multiple team formation problem using sociometry

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    The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes. Specifically, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP). Second, an optimization model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimization model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most efficient in almost all cases. Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research

    Making It Work: Linking Youth Reproductive Health and Livelihoods

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    Assesses the challenges and effectiveness of programs that integrate adolescent reproductive health with options that improve economic capabilities, assets, and activities. Highlights innovative approaches, and defines gaps in existing interventions
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