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7th international conference on Computer and Knowledge Engineering, ICCKE 2017

ISBN: (纸本)9781538608043

the proceedings contain 77 papers. the topics discussed include: bi-objective version of team orienteering problem (BTOP);GLCM features and fuzzy nearest neighbor classifier for emotion recognition from face;using the combination of particle swarm algorithms and fuzzy approach to provide a clustering method for network nodes with coverage maintenance in wireless sensor networks;bilingualism advantage in handwritten character recognition: a deep learning investigation on Persian and Latin scripts;characterization of schizophrenia by linear kernel canonical correlation analysis of resting-state functional MRI and structural MRI;learning multi-objective binary features for image representation;a novel sine and cosine algorithm for global optimization;a comparative analysis of classification algorithms in diabetic retinopathy screening;inferring gene regulatory network using path consistency algorithm based on conditional mutual information and genetic algorithm;residential power consumption forecasting in the smart grid using ANFIS system;patchwise object tracking via structural local sparse appearance model;a cloud-based open automated demand response protocol with AMI support;additive non-Gaussian noise channel estimation by using minimum error entropy criterion;and adaptive temporal error concealment method based on the MB behavior estimation in the video.

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Risk-Based Self-Scheduling of Gencos in Smart Grids considering a New Method for Bilateral Contracts 17

Risk-Based Self-Scheduling of Gencos in Smart Grids consider...

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17th IEEE international conference on Environment and Electrical Engineering (IEEE EEEIC) / 1st IEEE Industrial and Commercial Power Systems Europe conference (IEEE I and CPS Europe)

作者： Shafie-khah, Miadreza Osorio, Gerardo J. Fitiwi, Desta Z. Catalao, Joao P. S. Siano, Pierluigi C MAST UBI Covilha Portugal INESC TEC Porto Portugal FEUP Porto Portugal INESC ID IST UL Lisbon Portugal Univ Salerno Dept Ind Engn Salerno Italy

ISBN: (纸本)9781538639177

In this work, the self-scheduling problem of a power producer in smart grids is addressed using a stochastic programming approach. Different uncertainties are considered as price uncertainties, forced-outage of the unit as well as generation reallocation. the conditional value-at-risk index is used for modeling of risk. the markets considered in this study are bilateral contracts, day-ahead and ancillary services, including spinning reserve and regulation, and spot market decisions, while an incomplete competitive market is considered. In this sense, an innovative method for bilateral contracts is proposed to increase the profit of the market without ignoring any regulatory rules. the Monte Carlo method is implemented together with a reduction scenario process to generate scenarios.

关键词： Self-scheduling Scenario generation/reduction Scenario regeneration Stochastic programming

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Proceedings of the 7th international conference Confluence 2017 on Cloud Computing, Data Science and Engineering

Proceedings of the 7th International Conference Confluence 2...

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7th international conference on Cloud Computing, Data Science and Engineering, Confluence 2017

ISBN: (纸本)9781509035182

the proceedings contain 148 papers. the topics discussed include: a practical approach of GPU bubble sort with CUDA hardware;web log analyzer tools: comparative study to analyze user behavior;a survey on driver behavior detection techniques for intelligent transportation systems;genetic programming and k-nearest neighbour classifier based intrusion detection model;an efficient hybrid approach using differential evolution and practical swarm optimization;designing optimal architecture of neural network with particle swarm optimization techniques specifically for educational dataset;cuckoo search based workflow scheduling on heterogeneous cloud resources;MSATS: multilingual sentiment analysis via text summarization;substantiation of K-means and affinity propagation algorithm;software effort estimation using machine learning techniques;root cause analysis of software bugs using machine learning techniques;efficient coordinator guided particle swarm optimization for real-parameter optimization;multi-modal travel in India: big data approach for policy analytics;analysis of various task scheduling algorithms in cloud environment: review;efficient management of distributive cloud computing system for scientific applications;workload scheduling in cloud: comprehensive survey and future research directions;deadline constrained scheduling of scientific workflows on cloud using hybrid genetic algorithm;understanding the business strategy factors that drive the business impacts of cloud computing;implementation of k-means clustering in ECB framework of cloud computing environment;and a graph semantic based approach for modeling of enterprise cloud bus system dynamics.

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Exploring one-sided communication and synchronization on a non-cache-coherent many-core architecture

Exploring one-sided communication and synchronization on a n...

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Euro-Par conference / 7th international Workshop on programming Models and Applications for Multicores and Manycores (PMAM) held in conjunction with the 21st SIGPLAN Symposium on Principles and Practice of Parallel programming (PPoPP)

作者： Christgau, Steffen Schnor, Bettina Univ Potsdam Inst Comp Sci August Bebel Str 89 D-14482 Potsdam Germany

the ongoing many-core design aims at core counts where cache coherence becomes a serious challenge. therefore, this paper discusses how one-sided communication and the required process synchronization can be realized on a non-cache-coherent many-core CPU. the Intel Single-chip Cloud Computer serves as an exemplary hardware architecture. the presented approach is based on software-managed cache coherence for MPI one-sided communication. the prototype implementation delivers a PUT performance of up to 5 times faster than the default message-based approach and reveals a reduction of the communication costs for the NAS Parallel Benchmarks 3-D fast Fourier Transform by a factor of 5. Further, the paper derives conclusions for future non-cache-coherent architectures.

关键词： MPI one-sided communication programming models and systems for many-cores synchronization software-managed cache coherence

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JParEnt: Parallel entropy decoding for JPEG decompression on heterogeneous multicore architectures 7

JParEnt: Parallel entropy decoding for JPEG decompression on...

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作者： Sodsong, Wasuwee Jung, Minyoung Park, Jinwoo Burgstaller, Bernd Yonsei Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781450341967

the JPEG format employs Huffman codes to compress the entropy data of an image. Huffman codewords are of variable length, which makes parallel entropy decoding a difficult problem. To determine the start position of a codeword in the bitstream, the previous codeword must be decoded first. We present JParEnt, a new approach to parallel entropy decoding for JPEG decompression on heterogeneous multicores. JParEnt conducts JPEG decompression in two steps: (1)an efficient sequential scan of the entropy data on the CPU to determine the start-positions (boundaries) of coefficient blocks in the bitstream, followed by (2)a parallel entropy decoding step on the graphics processing unit (GPU). the block boundary scan constitutes a reinterpretation of the Huffman-coded entropy data to determine codeword boundaries in the bitstream. We introduce a dynamic workload partitioning scheme to account for GPUs of low compute power relative to the CPU. this configuration has become common with the advent of SoCs with integrated graphics processors (IGPs). We leverage additional parallelism through pipelined execution across CPU and GPU. For systems providing a unified address space between CPU and GPU, we employ zero-copy to completely eliminate the data transfer overhead. Our experimental evaluation of JParEnt was conducted on six heterogeneous multicore systems: one server and two desktops with dedicated GPUs, one desktop with an IGP, and two embedded systems. For a selection of more than 1000JPEG images, JParEnt outperforms the SIMD-implementation of the libjpeg-turbo library by up to a factor of 4.3x, and the previously fastest JPEG decompression method for heterogeneous multicores by up to a factor of 2.2x. JParEnt's entropy data scan consumes 45% of the entropy decoding time of libjpeg-turbo on average. Given this new ratio for the sequential part of JPEG decompression, JParEnt achieves up to97% of the maximum attainable speedup (95% on average). On the IGP-based desktop platform,

关键词： JPEG decoding entropy decoding prefix codes heterogeneous multicores GPU programming

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Grounded representations through deep variational inference and dynamic programming 7

Grounded representations through deep variational inference ...

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7th joint IEEE international conference on Development Learning and Epigenetic Robotic (IEEE ICDL-EpiRob)

作者： Olier, Juan Sebastian Barakova, Emilia Rauterberg, Matthias Marcenaro, Lucio Regazzoni, Carlo Eindhoven Univ Technol Dept Ind Design Eindhoven Netherlands Univ Genoa Dept Elect Elect & Telecommun Engn & Naval Archit Genoa Italy Univ Carlos III Madrid Intelligent Syst Lab Madrid Spain

ISBN: (纸本)9781538637159

In this work, we present a method for building grounded representations by structuring the sensorimotor data of an agent. the aim is to encode sensory inputs into internal states that describe action-environment couplings, or relations that connect elements in a scene to action concepts. thus, the environment is represented regarding the sensorimotor integrations required to interact with elements in it. Such representations are acquired for a particular task in which they serve to infer important states and generate control commands accordingly. Representations are learned in an unsupervised process and are assembled into probability distributions to capture uncertainty. that is achieved through variational methods using deep learning and dynamic programming, and an architecture partially inspired by active inference. During an interaction, future representational states and sensorimotor data are actively predicted, while the incoming sensory information is incorporated through prediction error. Results in a navigation task show that situated representations emerge as sensorimotor relations that are interpretable as action concepts, and which allow interpreting important elements in the environment to generate satisfactory actions. We argue that the acquisition of such capabilities relates to the prediction processes enabled by two mechanisms;first, state-transition models explicitly dependent on the generation of control commands, and secondly, a system trained through dynamic programming, which generates further predictions that relate sensory data to expected state changes.

关键词： Electronics packaging Task analysis Dynamic programming Buildings Couplings Uncertainty Predictive models dynamic programming Electronics packaging task analysis Couplings Buildings Prediction models Task navigation representations Uncertainty Variational Inference Elements command and control

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Geothermal distribution network modeled as Heat Exchanger Network to be optimized with Mixed Integer Nonlinear programming

Geothermal distribution network modeled as Heat Exchanger Ne...

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7th international conference on Future Buildings and Districts - Energy Efficiency from Nano to Urban Scale (CISBAT)

作者： Guo, Hongshan Meggers, Forrest Princeton Univ Sch Architecture Princeton NJ 08544 USA Princeton Univ Andlinger Ctr Energy & Environm Princeton NJ 08544 USA

Geothermal energy is commonly harvested at either shallower depth (below 150ft/45.72m) for residential purposes (with ground source heat pumps), or deeper depths (beyond 8000ft/2.43 km) for Enhanced Geothermal Systems. the in-between depths are rarely visited due to high drilling costs, and the water harvested being unable to power turbines. Recent studies powered by the data released by the National Geothermal Data System (NGDS) opened a new opportunity of harvesting the geothermal potential in post-production oil/gas boreholes in Pennsylvania. We are interested therefore in whether it is feasible to connect the different heat sources with different temperature availabilities to distribute to spatially scattered end-users. Presented in this paper is a project that generates heat exchanger network configurations through mixed nonlinear programming (MINLP) problem formulation and optimization in Python. With the case intentionally simplified, the computational costs of the optimization was found to be marginal. (C) 2017 the Authors. Published by Elsevier Ltd.

关键词： Heat Exchanger Network HEN district heating geothermal heat exchanger MINLP

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7th international conference on Fundamentals of Software Engineering, FSEN 2017

7th International Conference on Fundamentals of Software Eng...

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7th international conference on Fundamentals of Software Engineering, FSEN 2017

ISBN: (纸本)9783319689715

the proceedings contain 16 papers. the special focus in this conference is on Fundamentals of Software Engineering. the topics include: Preface;implementing Open Call-by-Value;littleDarwin: A Feature-Rich and Extensible Mutation Testing Framework for Large and Complex Java Systems;tCE+: An Extension of the TCE Method for Detecting Equivalent Mutants in Java Programs;quality-Aware Reactive programming for the Internet of things;purpose-Based Policy Enforcement in Actor-Based Systems;automatic Transition System Model Identification for Network Applications from Packet Traces;gray-Box Conformance Testing for Symbolic Reactive State Machines;model Checking of Concurrent Software Systems via Heuristic-Guided SAT Solving;debugging of Concurrent Systems Using Counterexample Analysis;bisimilarity of Open Terms in Stream GSOS;composing Families of Timed Automata;a Formal Model for Multi SPLs;translating Active Objects into Colored Petri Nets for Communication Analysis;synthesizing Parameterized Self-stabilizing Rings with Constant-Space Processes;flexible Transactional Coordination in the Peer Model;using Swarm Intelligence to Generate Test Data for Covering Prime Paths.

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Model predictive control for power management in a plug-in hybrid electric vehicle with a hybrid energy storage system

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APPLIED ENERGY 2017年第Part2期185卷 1654-1662页

作者： Zhang, Shuo Xiong, Rui Sun, Fengchun Beijing Inst Technol Sch Mech Engn Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China Beijing Inst Technol Collaborat Innovat Ctr Elect Vehicles Beijing Beijing 100081 Peoples R China

the fuel economy performance of plug-in hybrid electric vehicles (PHEVs) strongly depends on the power management strategy. this study proposes an integrated power management for a PHEV with multiple energy sources, including a semi-active hybrid energy storage system (HESS) and an assistance power unit (APU). the HESS consists of battery packs and ultracapacitor packs. In the integrated control strategy, the output power between the battery packs and ultracapacitor packs is regulated by the model predictive control strategy, while the output power between the APU and HESS is allocated by the rule-based strategy. In the model predictive control process, a period of the future velocity will be predicted, and the dynamic programming algorithm will be applied to optimize the control strategy accordingly. the robustness of the proposed approach is verified by three typical driving cycles, including the Manhattan cycle, CBDC cycle and UDDSHDV cycle. the results show that the proposed control strategy can promote fuel economy compared with the original control strategy, especially in the charge sustain mode under the MANHATTAN driving cycle (21.88% improvement). (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Plug-in hybrid electric vehicle Hybrid energy storage system Assistant power unit Model predictive control Dynamic programming Power management

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A convex mathematical program for pump scheduling in a class of branched water networks

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APPLIED ENERGY 2017年第Part2期185卷 1702-1711页

作者： Bonvin, Gratien Demassey, Sophie Le Pape, Claude Maizi, Nadia Mazauric, Vincent Samperio, Alfredo PSL Res Univ Ctr Appl Math MINES ParisTech BP 207 F-06902 Sophia Antipolis France Schneider Elect Strategy & Technol 38TEC F-38050 Grenoble 9 France

We address the day-ahead pump scheduling problem for a class of branched water networks with one pumping station raising water to tanks at different places and levels. this common class is representative of rural drinking water distribution networks, though not exclusively so. Many sophisticated heuristic algorithms have been designed to tackle the challenging general problem. By focusing on a class of networks, we show that a pure model-based approach relying on a tractable mathematical program is pertinent for real-size applications. the practical advantages of this approach are that it produces optimal or near-optimal solutions with performance guarantees in near real-time, and that it is replicable without algorithmic development. We apply the approach to a real drinking water supply system and compare it to the current operational strategy based on historical data. An extensive empirical analysis assesses the financial and practical benefits: (1) it achieves significant savings in terms of operation costs and energy consumption, (2) its robustness to dynamic pricing means that demand-response can be efficiently implemented in this type of energy-intensive utility. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Pump scheduling Branched water networks Demand-response Mixed-integer non-linear programming Convex relaxation

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