3,815 research outputs found

    Distribution-graph based approach and extended tree growing technique in power-constrained block-test scheduling

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    A distribution-graph based scheduling algorithm is proposed together with an extended tree growing technique to deal with the problem of unequal-length block-test scheduling under power dissipation constraints. The extended tree growing technique is used in combination with the classical scheduling approach in order to improve the test concurrency having assigned power dissipation limits. Its goal is to achieve a balanced test power dissipation by employing a least mean square error function. The least mean square error function is a distribution-graph based global priority function. Test scheduling examples and experiments highlight in the end the efficiency of this approach towards a system-level test scheduling algorithm

    A combined tree growing technique for block-test scheduling under power constraints

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    A tree growing technique is used here together with classical scheduling algorithms in order to improve the test concurrency having assigned power dissipation limits. First of all, the problem of unequal-length block-test scheduling under power dissipation constraints is modeled as a tree growing problem. Then a combination of list and force-directed scheduling algorithms is adapted to tackle it. The goal of this approach is to achieve rapidly a test scheduling solution with a near-optimal test application time. This is initially achieved with the list approach. Then the power dissipation distribution of this solution is balanced by using a force-directed global priority function. The force-directed priority function is a distribution-graph based global priority function. A constant additive model is employed for power dissipation analysis and estimation. Based on test scheduling examples, the efficiency of this approach is discussed as compared to the other approaches

    Power-constrained block-test list scheduling

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    A list scheduling approach is proposed in this paper to overcome the problem of unequal-length block-test scheduling under power dissipation constraints. An extended tree growing technique is also used in combination with the list scheduling algorithm in order to improve the test concurrency, having assigned power dissipation limits. Moreover, the algorithm features a power dissipation balancing provision. Test scheduling examples are discussed, highlighting further research steps towards an efficient system-level test scheduling algorith

    A comparison of classical scheduling approaches in power-constrained block-test scheduling

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    Classical scheduling approaches are applied here to overcome the problem of unequal-length block-test scheduling under power dissipation constraints. List scheduling-like approaches are proposed first as greedy algorithms to tackle the fore mentioned problem. Then, distribution-graph based approaches are described in order to achieve balanced test concurrency and test power dissipation. An extended tree growing technique is also used in combination with these classical approaches in order to improve the test concurrency having assigned power dissipation limits. A comparison between the results of the test scheduling experiments highlights the advantages and disadvantages of applying different classical scheduling algorithms to the power-constrained test scheduling proble

    REGIONAL KNOWLEDGE MANAGEMENT FOR THE SUSTAINABLE DEVELOPMENT

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    The article intends to present the achievements of a research Romanian project Knowledge management architecture in environmental, social and economic areas,designed to support the sustainable regional development strategy . The main goal of theproject is to improve the regional knowledge management, using a virtual framework for thedesign of the regional development strategy. The innovation introduced by this approachconsists in the integration of the regional actors’ views, in order to develop a realisticregional development strategy, on a democratic and scientific base. The challenge of thisvision is to create a virtual environment for the regional knowledge management andconsensus building related to the regional strategy development. The scientific base for thedesign of the regional development strategy is represented by an improved set of socio-economic indicators and benchmarking tools.regional sustainable development set of sustainable development indicators, embeddedknowledge, e-democracy, e-Government

    REGIONAL KNOWLEDGE MANAGEMENT FOR THE SUSTAINABLE DEVELOPMENT

    Get PDF
    The article intends to present the achievements of a research Romanian project Knowledge management architecture in environmental, social and economic areas,designed to support the sustainable regional development strategy . The main goal of theproject is to improve the regional knowledge management, using a virtual framework for thedesign of the regional development strategy. The innovation introduced by this approachconsists in the integration of the regional actors’ views, in order to develop a realisticregional development strategy, on a democratic and scientific base. The challenge of thisvision is to create a virtual environment for the regional knowledge management andconsensus building related to the regional strategy development. The scientific base for thedesign of the regional development strategy is represented by an improved set of socio-economic indicators and benchmarking tools.regional sustainable development set of sustainable development indicators, embeddedknowledge, e-democracy, e-Government

    Quantization as histogram segmentation: globally optimal scalar quantizer design in network systems

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    We propose a polynomial-time algorithm for optimal scalar quantizer design on discrete-alphabet sources. Special cases of the proposed approach yield optimal design algorithms for fixed-rate and entropy-constrained scalar quantizers, multi-resolution scalar quantizers, multiple description scalar quantizers, and Wyner-Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for fixed-rate and entropy-constrained scalar quantizers and constrained optima for the other coding scenarios. We derive the algorithm by demonstrating the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph

    "With 1 follower I must be AWESOME :P". Exploring the role of irony markers in irony recognition

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    Conversations in social media often contain the use of irony or sarcasm, when the users say the opposite of what they really mean. Irony markers are the meta-communicative clues that inform the reader that an utterance is ironic. We propose a thorough analysis of theoretically grounded irony markers in two social media platforms: TwitterTwitter and RedditReddit. Classification and frequency analysis show that for TwitterTwitter, typographic markers such as emoticons and emojis are the most discriminative markers to recognize ironic utterances, while for RedditReddit the morphological markers (e.g., interjections, tag questions) are the most discriminative.Comment: ICWSM 201

    Quantization as Histogram Segmentation: Optimal Scalar Quantizer Design in Network Systems

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    An algorithm for scalar quantizer design on discrete-alphabet sources is proposed. The proposed algorithm can be used to design fixed-rate and entropy-constrained conventional scalar quantizers, multiresolution scalar quantizers, multiple description scalar quantizers, and Wyner–Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for conventional fixed-rate scalar quantizers and entropy-constrained scalar quantizers. For the other coding scenarios, the algorithm yields the best code among all codes that meet a given convexity constraint. In all cases, the algorithm run-time is polynomial in the size of the source alphabet. The algorithm derivation arises from a demonstration of the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph
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