115,882 research outputs found

    Adaptive Digital Resource Modeling as Service Provider and Consumer

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    International audienceThe increase in the production of heterogeneous and multi-source digital data over last years raises several issues regarding their management and use. Hence, users can face some difficulties in selecting the adequate digital resources and combining them to reach their objectives in a given activity. In this paper, we focus on digital resources design and management in order to enhance their retrieval, interoperability, adaptation and collaboration within an adaptive system. In practical terms, our work consists in a new method for digital resource design and management capable of enhancing their usability. It relies on RESTful web service-based methodology and platform thinking approach. We have implemented our method in an interactive and adaptive PLE to assist researchers in using and managing their digital resources, called PRISE for PeRsonal Interactive research Smart Environment. We have also undertaken some experiments with PRISE platform in our laboratory. The result showed that modeling digital resources with RESTful and platform thinking concept enhances digital resource usability in terms of retrieving, interoperability, adaptation and collaboration

    A framework for smart production-logistics systems based on CPS and industrial IoT

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    Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

    Інноваційні моделі навчання і підготовки кадрів для індустрії високих технологій в Україні

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    The problems of development of innovative learning environment of continuous education and training of skilled personnel for high-tech industry are described. Aspects of organization of ICT based learning environment of vocational and technical school on the basis of cloud computing and outsourcing are revealed. The three-stage conceptual model for perspective education and training of workers for high-tech industries is proposed. The model of cloud-based solution for design of learning environment for vocational education and training of skilled workers is introduced.У статті висвітлено проблеми розвитку інноваційного середовища навчання, неперервної освіти і підготовки кадрів для високотехнологічних галузей промисловості. Виявлено особливості організації інформаційно-освітнього середовища професійно-технічних навчальних закладів на основі технології хмарних обчислень і механізму аутсорсингу. Запропонована триступенева концептуальна модель навчання та підготовки кадрів для високотехнологічних галузей виробництва. Обґрунтовано моделі хмарних рішень для проектування середовища навчання для професійної освіти і підготовки високо кваліфікованих робітникі

    A Framework for Evaluating Model-Driven Self-adaptive Software Systems

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    In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen
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