27,885 research outputs found

    Industrial Policy in Chile

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    This paper studies three horizontal policy instruments and two vertical ones in Chilean industrial policy, particularly regarding small and medium enterprises (SMEs). The horizontal instruments are (1) a guarantee program for borrowing by SMEs (FOGAPE), (2) a small subsidy to new exports that was applied from 1985 through 2003, and (3) the innovation subsidies provided by the Corporación de Fomento de la Producción (CORFO). The vertical policy instruments are the activities of Fundación Chile (FCh), a semi-public entrepreneur cum venture capitalist, and a CORFO program to attract foreign direct investment in information technology. Although most programs are well designed, they are numerous and insufficiently funded; Chile could benefit from a prioritization of needs and consolidation of these programs. Moreover, the instruments for making strategic bets on new sectors are particularly weak. In particular, FCh needs to refocus its activities on high-risk projects with long payoffs, something it cannot do with its small endowment.Industrial policy, Small and medium enterprises, Chile

    Integrate the GM(1,1) and Verhulst models to predict software stage effort

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    This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Software effort prediction clearly plays a crucial role in software project management. In keeping with more dynamic approaches to software development, it is not sufficient to only predict the whole-project effort at an early stage. Rather, the project manager must also dynamically predict the effort of different stages or activities during the software development process. This can assist the project manager to reestimate effort and adjust the project plan, thus avoiding effort or schedule overruns. This paper presents a method for software physical time stage-effort prediction based on grey models GM(1,1) and Verhulst. This method establishes models dynamically according to particular types of stage-effort sequences, and can adapt to particular development methodologies automatically by using a novel grey feedback mechanism. We evaluate the proposed method with a large-scale real-world software engineering dataset, and compare it with the linear regression method and the Kalman filter method, revealing that accuracy has been improved by at least 28% and 50%, respectively. The results indicate that the method can be effective and has considerable potential. We believe that stage predictions could be a useful complement to whole-project effort prediction methods.National Natural Science Foundation of China and the Hi-Tech Research and Development Program of Chin

    Mega-project engineering-management processes: pre-planning phase evaluation for construction and mining

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    Mega-projects internationally continue to experience time and cost overruns. Addressing the pre-planning phase has been assessed as a key requirement. This research-project presents two KSA mega-project resources case-studies towards an evaluation of the management-processes applied at the preplanning, design, construction and design phases to clarify procedure and recommend improvement. Findings note the impact of Stage-Gate Process, Gate-keeper approval, and scope-change processes. Recommendations for a best practice stakeholder guide are developed towards best practice

    Information mining projects management process

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    Information Mining (also known as Knowledge Discovery Process) is a growing discipline in continuous expansion. Most of the progress accomplished, are focus on the development activities (i.e. those technical activities associated with the comprehension and adaptation of data, and the implementation of data mining algorithm). According to this conceptual framework, several process models were developed, which allow organizing and defining the set of tasks related to the development of information mining projects. These approaches omit the set of tasks oriented to the management and control of the process. In this paper, we propose a transversal management process to the development process currently in use in information mining projects. The proposed process focuses on removing existing gaps, providing an improvement on the project's maturity and quality levels.Instituto de Investigación en InformáticaFacultad de Informátic

    New product development resource forecasting

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    Forecasting resource requirements for new product development (NPD) projects is essential for both strategic and tactical planning. Sophisticated, elegant planning tools to present data and inform decision-making do exist. However, in NPD, such tools run on unreliable, estimation-based resource information derived through undefined processes. This paper establishes that existing methods do not provide transparent, consistent, timely or accurate resource planning information, highlighting the need for a new approach to resource forecasting, specifically in the field of NPD. The gap between the practical issues and available methods highlights the possibility of developing a novel design of experiments approach to create resource forecasting models

    Reliability and validity in comparative studies of software prediction models

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    Empirical studies on software prediction models do not converge with respect to the question "which prediction model is best?" The reason for this lack of convergence is poorly understood. In this simulation study, we have examined a frequently used research procedure comprising three main ingredients: a single data sample, an accuracy indicator, and cross validation. Typically, these empirical studies compare a machine learning model with a regression model. In our study, we use simulation and compare a machine learning and a regression model. The results suggest that it is the research procedure itself that is unreliable. This lack of reliability may strongly contribute to the lack of convergence. Our findings thus cast some doubt on the conclusions of any study of competing software prediction models that used this research procedure as a basis of model comparison. Thus, we need to develop more reliable research procedures before we can have confidence in the conclusions of comparative studies of software prediction models

    Third Earth Resources Technology Satellite Symposium. Volume 3: Discipline summary reports

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    Presentations at the conference covered the following disciplines: (1) agriculture, forestry, and range resources; (2) land use and mapping; (3) mineral resources, geological structure, and landform surveys; (4) water resources; (5) marine resources; (6) environment surveys; and (7) interpretation techniques
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