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Analysis of Switch Automation Based on Active Reconfiguration Considering Reliability, Energy Storage systems. and Variable Renewables

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2019年第6期55卷 6355-6367页

作者： Santos, Sergio F. Fitiwi, Desta Z. Cruz, Marco R. M. Santos, Claudio Catalao, Joao P. S. INESC TEC P-4200465 Porto Portugal Econ & Social Res Inst Dublin 2 Ireland Trinity Coll Dublin Dublin 2 Ireland Univ Beira Interior C MAST P-6201001 Covilha Portugal Univ Porto Fac Engn P-4200465 Porto Portugal

Economic development and changing lifestyles are leading to the extensive use of energy-intensive technologies by consumers. As a result, this has led to a dramatically increased demand for electricity. In addition, the consumers' increasing demand for a more reliable and uninterrupted energy supply is posing enormous challenge for service providers. This necessitates the development of novel solutions that should be at the system operators' disposal, particularly at distribution levels. One way to partly address this concern is by automating distribution systems.and equipping them with intelligent technologies-a transformation to smart distribution systems. Such a transformation should improve system reliability and operational efficiency because such systems.will be capable of operating and immediately restoring discontinued service to consumers. To facilitate this, it is necessary to replace manual switches by remotely controlled ones, improving the system restoration capability, which is one of the key features of smart grids. This paper presents a new framework to determine the minimal set of switches that have to be replaced or optimally allocated in order to automate the system. This is supported by a sensitivity analysis. Different topologies are also assessed taking into account various reliability indices and power losses in system operation following the system's automation. Such an optimization work is done under a massive integration of renewable energy sources and energy storage systems. All this simultaneously addresses the economic and functional requirements of the automated system, ultimately improving system's reliability. The standard IEEE 119-bus standard system is used as a case study, where different types of loads are considered (residential, commercial, and industrial).

关键词： distributed smart systems distribution automation reliability self-healing service restauration smart grid

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Robust and Optimal Maximum Power Point Tracking Control of Solar PV Power System

Robust and Optimal Maximum Power Point Tracking Control of S...

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international conference on computing, Mathematics and Engineering Technologies (iCoMET)

作者： Waqas Ahmad Mirza Haris Sheh Zad Sumbul Bashir Department of Electrical Engineering Riphah International University Islamabad Pakistan Network Operations Center (NOC) Pakistan Telecommunication Company Limited Islamabad Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

This paper presents a new robust and optimal Hybrid technique for maximum power point tracking of the photovoltaic systems. The proposed hybrid scheme is composed of two well-known techniques, namely Perturb and Observe and Model Predictive Control methods, which are separately being used for detecting and tracking the maximum power point (MPP) of a solar panel system. The suggested system is efficient, robust, and stable because of its hybrid nature, as it combines the benefits of both the parent techniques. The technique is implemented with a DC-DC Buck converter, which is utilized for low power application systems. This technique targets to enhance the productivity of the PV systems.by tracking the MPP under optimized and controlled conditions. The system is verified by simulations and analyzed under different conditions for measurement of the efficiency. The results obtained after testing the system indicate that the efficiency of the new technique is better than the previous techniques, and the system is stable, controlled, optimized, and cost-effective.

关键词： Buck converters Switches Maximum power point trackers Solar panels Predictive control Topology

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Optimization of distributed resource allocation strategies in wireless systems.for maximizing QoS 3

Optimization of distributed resource allocation strategies i...

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3rd international conference on Intelligent computing in Data Sciences (ICDS)

作者： Riahi, Sara Riahi, Azzeddine Chouaib Doukkali Univ Dept Comp Sci Fac Sci El Jadida Morocco Chouaib Doukkali Univ IMC Lab Fac Sci El Jadida Morocco

ISBN: (纸本)9781728100036

In this paper, we consider that users receive data from multimedia traffic. Each traffic stream is associated with a virtual buffer or transmission buffer implemented at the base station. The packets in these buffers are waiting to be forwarded to the recipient user. Buffers are therefore powered by multimedia data streams. Therefore, a buffer may occasionally he empty so that it is not useful to allocate resources to this stream. Therefore, considering multimedia traffic, the problem is even more complex. Furthermore, we assume that each stream can have different needs in terms of quality of service. Indeed, the state of a buffer is not easily predictable since it depends on many factors: the statistical properties of the traffic to the user;the quality of the channel on the different frequencies;allocations made in previous TTIs. We take no restrictive assumption on each of these three points.

关键词： Outage probability packages quality of service LTE evaluation of performances

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distributed and automated machine learning in big data stream analytics 3

Distributed and automated machine learning in big data strea...

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3rd World conference on Smart Trends in systems. Security and Sustainability, WorldS4 2019

作者： Alsahlee, Oraib H. Al-Zu’bi, Abdallah Alamro, Ibrahim I. Alwidian, Jaber Computer science Princess Sumaya university for technology Amman Jordan INFRASOFT Middle East /Big Data department United States

ISBN: (纸本)9781728137803

Distribution and automation of machine learning, a relatively new concepts occupying the scene of data science and its applications, in an era of massive data that it is growing by the second requiring complex processing and insight generation to feed the new industry of data-driven applications, utilizing the tools of machine learning and artificial intelligence built over big data infrastructures that support parallel and real-time computing, an approach that has fulfilled the requirements to a certain degree but yet requires much more optimization and a sense of autonomy to accommodate new developments and reduce human expertise dependency to achieve the bigger picture and fulfill the potential it has of revolutionizing the tech industry and overall scene. Here in this work we briefly investigate the components required to build such complex pipelines to fulfill autonomy and distribution requirements previously mentioned and propose some abstract concepts to integrate such components to achieve somewhat parallel machine learning pipeline that requires minimal human involvement. © 2019 IEEE.

关键词： Machine learning

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Analyzing Factors that Affecting College Students' Choice of Online English Training Courses 3

Analyzing Factors that Affecting College Students' Choice of...

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3rd international conference on Intelligent systems.and Advanced computing Sciences, ISACS 2019

作者： Guo, Yanhui Li, Yan Sun, Shaomeng International College Beijing China Agricultural University Beijing China

ISBN: (纸本)9781728148137

The application of online learning has changed the traditional English learning mode, in which college students are the percipient of this change. Taking the TOEFL and IELTS online courses as examples, this paper chooses the college students as the research subject. By questionnaire survey and statistical factor analysis, four key factors affecting students' choice of off-campus online English learning are found out and defined, which are 'course demand and quality', 'communication quality', 'teaching support', 'learning cost and time' through. On this basis, this paper puts forward suggestions for the optimization of online English learning. © 2019 IEEE.

关键词： Factor analysis

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3rd international conference on Advances in computing and Data Sciences, ICACDS 2019

3rd International Conference on Advances in Computing and Da...

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3rd international conference on Advances in computing and Data Sciences, ICACDS 2019

ISBN: (纸本)9789811399411

The proceedings contain 112 papers. The special focus in this conference is on Advances in computing and Data Sciences. The topics include: Lexical Text Simplification Using WordNet;analysis and Impact of Trust and Recommendation in Social Network Based Algorithm for Delay Tolerant Network;formation of Hierarchies in the System of Organization of State Construction Supervision in Case of Reorientation of Urban Areas;customized Visualization of Email Using Sentimental and Impact Analysis in R;Role of Lexical and Syntactic Fixedness in Acquisition of Hindi MWEs;Five Input Multilayer Full Adder by QCA Designer;effect of Vaccination in the Computer Network for distributed Attacks – A Dynamic Model;ransomware Analysis Using Reverse Engineering;semantic Textual Similarity and Factorization Machine Model for Retrieval of Question-Answering;empirical Study of Test Driven Development with Scrum;krisha: An Interactive Mobile Application for Autism Children;advanced Spatial Reutilization for Finding Ideal Path in Wireless Sensor Networks;an Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion;An Upper Bound for Sorting Rn with LE;image Filtering with Iterative Wavelet Transform Based Compression;Multiresolution Satellite Fusion Method for INSAT Images;a Combinatorial Fair Economical Double Auction Resource Allocation Model;issues in Training a Convolutional Neural Network Model for Image Classification;an Approach to Find Proper Execution Parameters of n-Gram Encoding Method Based on Protein Sequence Classification;hyperglycemia Prediction Using Machine Learning: A Probabilistic Approach;microprocessor Based Edge computing for an Internet of Things (IoT) Enabled distributed Motion Control;rough-Set Based Hotspot Detection in Spatial Data.

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Decentralized Resource Auctioning for Latency-Sensitive Edge computing 3

Decentralized Resource Auctioning for Latency-Sensitive Edge...

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3rd IEEE international conference on Edge computing (IEEE EDGE)

作者： Avasalcai, Cosmin Tsigkanos, Christos Dustdar, Schahram TU Wien Distributed Syst Grp Vienna Austria

ISBN: (纸本)9781728127088

The prevalence of Internet of Things (IoT) in contemporary settings has induced systems.composed of heterogeneous devices, computing infrastructures, and cloud services. New paradigms have emerged where computational resources are managed closer to IoT end-devices, within a general theme of decoupling from the cloud. This is because meeting application demands must occur at runtime, in the face of uncertainty and in a decentralized manner. Taking advantage of available resources closer to devices calls for novel resource allocation techniques that comply with latency, privacy and decentralization demands of IoT applications. To this end, we propose a novel decentralized resource management technique and accompanying technical framework for the deployment of latency-sensitive IoT applications on edge devices. Our technique is inspired from the functionality of an auction house and has two objectives;(i) find a deployment mapping for an arbitrary application, compliant with its individual resource requirements and latency constraints, (ii) facilitate privacy, as each device participates at their own will, based on its own availability and privacy preferences. Our approach ensures seamless deployment at runtime, assuming no design-time knowledge of device resources or network topology.

关键词： Internet of Things Edge computing Resource Management Decentralization Fog computing

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Improving the Performance of Inter-node Data Exchange in Cloud-based distributed Ray Tracing by Compression 3

Improving the Performance of Inter-node Data Exchange in Clo...

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3rd international conference on Video and Image Processing (ICVIP)

作者： Liu, Yunbiao Chen, Chunyi Hu, Xiaojuan Yang, Huamin Changchun Univ Sci & Technol Sch Comp Sci & Technol Changchun Peoples R China

ISBN: (纸本)9781450376822

To improve the performance of cloud-based rendering systems. it not only requires a good load balancing algorithm, but also needs less cost for data transfer. This paper proposes an internal data compression method in the cloud, which reduces the cost of data transfer between worker nodes on the basis of Hadoop distributed framework. In this method, the coordinate system transformation and simple vector addition are used to reduce the storage space of each pixel's primary ray-object intersection point and unit normal vector. We implemented the experiment of data transfer in a Hadoop ray tracing cluster with gigabit switch. First, we compared the cost under different types of data transfer. Secondly, we measured the execution time of the compression method. Finally, we analyze the reason for the error between the decompressed data and the origin data. The results show that the cost of data transfer in our method is approximately 66% of that of the three-dimensional coordinate representation method, and the calculation error is less than 10(-6) . Thus, our proposed method can effectively improve the transfer efficiency of cloud-based rendering system.

关键词： cloud-based rendering system ray tracing Hadoop internal data transfer

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proceedings of DLS 2019: Deep Learning on Supercomputers - Held in conjunction with SC 2019: The international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of DLS 2019: Deep Learning on Supercomputers - H...

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3rd IEEE/ACM Workshop on Deep Learning on Supercomputers, DLS 2019

ISBN: (纸本)9781728160115

The proceedings contain 11 papers. The topics discussed include: scaling distributed training of flood-filling networks on HPC infrastructure for brain mapping;strategies to deploy and scale deep learning on the summit supercomputer;deep learning for gap crossing ability of ground vehicles;deep learning accelerated light source experiments;deep facial recognition using tensor?ow;scaling tensorflow, PyTorch, and MXNet using MVAPICH2 for high-performance deep learning on frontera;highly-ccalable, physics-informed GANs for learning solutions of stochastic PDEs;DeepDriveMD: deep-learning driven adaptive molecular simulations for protein folding;and deep learning accelerated light source experiments.

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Connected or Autonomous Trains? 3rd

Connected or Autonomous Trains?

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3rd international conference on Reliability, Safety, and Security of Railway systems.- Modelling, Analysis, Verification, and Certification (RSSRail)

作者： Fantechi, Alessandro Univ Florence Dept Informat Engn Florence Italy

ISBN: (纸本)9783030187446;9783030187439

In a parallel with the trends in the automotive domain, we discuss the future challenges of automation of train control, where train to infrastructure and train to train communication will support distributed control algorithms, while on board artificial intelligence will provide autonomous control decisions. Already installed systems. like ERTMS-ETCS, are actually distributed systems.that span over geographical areas and are able to safely control large physical systems. But still, crucial decisions are taken at centralized places, that concentrate communications with mobile objects. Several prospected advances, aimed at increasing capacity and automation of rail transport, go in the direction of a more dynamic network connection among mobile components, in which decisions are actually taken in a distributed way. A concept of dynamic safety envelope within which a train can safely move then emerges, built by a fusion of reliable information coming from the infrastructure and from other trains, as well as autonomously harvested by on-board "intelligent" sensors. This paper discusses some plausible scenarios in this respect and presents the basic concepts behind them.

关键词： distributed parameter control systems

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