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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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Secrecy performance analysis of single-input multiple-output generalized-K fading channels

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Frontiers of Information Technology and Electronic engineering 2016年第10期17卷 1074-1084页

作者： Lei, Hong-jiang Ansari, Imran Shafique Gao, Chao Guo, Yong-cai Pan, Gao-feng Qaraqe, Khalid A. Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China MOE Key Laboratory of Optoelectronic Technology and Systems Chongqing University Chongqing400044 China Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China

In this paper, the transmission of confidential messages through single-input multiple-output (SIMO) independent and identically generalized-K (KG) fading channels is considered, where the eavesdropper overhears the transmission from the transmitter to the receiver. Both the receiver and the eavesdropper are equipped with multiple antennas, and both active and passive eavesdroppings are considered where the channel state information of the eavesdropper’s channel is or is not available at the transmitter. The secrecy performance of SIMO KG systems is investigated. Analytical expressions for secrecy outage probability and average secrecy capacity of SIMO systems are derived via two different methods, in which KG distribution is approximated by the Gamma and mixture Gamma distributions, respectively. Numerical results are presented and verified via the Monte-Carlo simulation. © 2016, Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg.

关键词： Fading channels

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Current-based inter-turn short circuit fault modeling in permanent magnet synchronous machine using magnetic equivalent circuit model

Current-based inter-turn short circuit fault modeling in per...

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Compatibility in Power Electronics (CPE)

作者： Jawad Faiz A. H. Exiri H. Nejadi-Koti Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering University of Tehran Tehran Iran

Stator current signal analysis is used to diagnosis inter-turn short circuit fault in permanent magnet synchronous machines (PMSM). The PMSM is modeled using magnetic equivalent circuit (MEC). This method takes into account the impacts of stator teeth, rotor yoke and stator winding distribution precisely. First healthy and faulty PMSM is simulated for different fault severities. In the 2 nd step, inter-turn short circuit fault is detected and its severity is determined using the amplitude of the side band components of the stator current. Finally, the frequency components of the extended Park vector magnitude are employed as the 2 nd index for fault detection. This index is independent of the load and only depends on the fault severity.

关键词： Circuit faults Mathematical model Stator windings Integrated circuit modeling Windings Magnetic circuits

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A miniaturized Vivaldi antenna with modified feeding structure for UWB applications

A miniaturized Vivaldi antenna with modified feeding structu...

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International Symposium on Antenna Technology and Applied Electromagnetics and the Canadian Radio Science Meeting, ANTEM/URSI

作者： A. Madannezhad H. Ameri S. Sadeghi R. Faraji-Dana School of Electrical and Computer Engineering University of Tehran Center of Excellence on Applied Electromagnetic Systems University of Tehran

ISBN: (纸本)9781467384797

A miniaturized Vivaldi antenna for ultra-wideband (UWB) applications is proposed. The antenna is designed to operate in the entire UWB spectrum from 3.1 to 10.6 GHz. A new modified feeding structure is employed to miniaturize the Vivaldi antenna. The designed antenna is fabricated and tested. Experimental results show satisfactory performance of the antenna over the entire UWB frequency band.

关键词： Vivaldi antennas Antenna measurements Ultra wideband antennas Antenna feeds Impedance matching

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Hierarchical protection architecture for 380V DC data center application

Hierarchical protection architecture for 380V DC data center...

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IEEE Energy Conversion Congress and Exposition

作者： Kai Tan Xiaoqing Song Chang Peng Pengkun Liu Alex Q. Huang FREEDM Systems Center Department of Electrical and Computer Engineering North Carolina State University Raleigh NC

ISBN: (纸本)9781509007387

The DC distribution system is becoming an appealing spot due to its higher energy efficiency in recent years. Nowadays, it has been already applied in data centers, commercial buildings, electrical vehicles charger station and DC micro grid systems, etc. However, there are a lot of challenges in DC application which is not critical in traditional AC system, such as arcing, capacitive charging and discharging, etc. All of them make the protection strategy and architecture an important issue for DC application. In this paper, one 3-level hierarchy circuit protection architecture is proposed with developed solid state circuit protection hardware. It is designed with considering the power rating for DC data center load conditions. Analysis and experimental results based on 380V DC voltage have been conducted and discussed.

关键词： Fast over current tripping LVDC distribution system 380V DC data center Hot plugging hierarchy protection

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Automatically processing tweets from gang-involved youth: Towards detecting loss and aggression 26

Automatically processing tweets from gang-involved youth: To...

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26th International Conference on Computational Linguistics, COLING 2016

作者： Blevins, Terra Kwiatkowski, Robert Macbeth, Jamie McKeown, Kathleen Patton, Desmond Rambow, Owen Department of Computer Science Columbia University New YorkNY United States Department of Electrical and Computer Systems Engineering Fairfield University FairfieldCT United States School of Social Work Columbia University New YorkNY United States Center for Computational Learning Systems Columbia University New YorkNY United States

ISBN: (纸本)9784879747020

Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used, as well as a classifier for identifying tweets that express grieving and aggression. © 1963-2018 ACL.

关键词： Computational linguistics

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Sparse data 3-D X-ray reconstructions on GPU processors 14

Sparse data 3-D X-ray reconstructions on GPU processors

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Computational Imaging XIV 2016

作者： Quivira, Fernando Bedford, Simon Moore, Richard Beaty, John Castañón, David Electrical and Computer Engineering Northeastern University BostonMA United States Government Programs Astrophysics Inc City of IndustryCA United States Massachusetts General Hospital BostonMA United States Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems Northeastern University BostonMA United States Electrical and Computer Engineering Boston University BostonMA United States

The problem of obtaining 3-D tomographic images from geometries involving sparse sets of illuminators and detectors arises in applications like digital breast tomosynthesis, security inspection, non-destructive evaluation and other similar applications. In these applications, the acquired projection data is highly incomplete, so traditional reconstruction approaches such as filtered backprojection (FBP) lead to significant distortion and artifacts in the reconstruction. In this work, we describe an iterative reconstruction algorithm that exploits regularization to obtain well-posed inverse problems. However, the computations associated with these iterative algorithms are significantly greater than the FBP algorithms. We describe how we structure those computations to exploit GPU architectures to reduce the computation time of the iterative reconstruction algorithm. We illustrate the results on data computed from an experimental 3-D imaging system. © 2016 Society for Imaging Science and Technology.

关键词： Graphics processing unit

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Distributed kalman filter in a network of linear dynamical systems

arXiv

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arXiv 2017年

作者： Marelli, Damián Zamani, Mohsen Fu, Minyue Department of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University 388 Yuhangtang Road Hangzhou Zhejiang Province310058 French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Ocampo Esmeralda Rosario2000 Argentina School of Electrical Engineering and Computer Science University of Newcastle University Drive CallaghanNSW2308 Australia

This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step. Copyright © 2017, The Authors. All rights reserved.

关键词： Kalman filters

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Wind Ramp Event Prediction with Parallelized Gradient Boosted Regression Trees

Wind Ramp Event Prediction with Parallelized Gradient Booste...

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International Joint Conference on Neural Networks

作者： Saurav Gupta Nitin Anand Shrivastava Abbas Khosravi Bijaya Ketan Panigrahi Department of Electrical Engineering Indian Institute of Technology New Delhi India Center for Intelligent Systems Research Deakin University Australia

ISBN: (纸本)9781509006212

Accurate prediction of wind ramp events is critical for ensuring the reliability and stability of the power systems with high penetration of wind energy. This paper proposes a classification based approach for estimating the future class of wind ramp event based on certain thresholds. A parallelized gradient boosted regression tree based technique has been proposed to accurately classify the normal as well as rare extreme wind power ramp events. The model has been validated using wind power data obtained from the National Renewable Energy Laboratory database. Performance comparison with several benchmark techniques indicates the superiority of the proposed technique in terms of superior classification accuracy.

关键词： Wind power generation Wind forecasting Regression tree analysis Support vector machines Wind energy Forecasting Reliability

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Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions

arXiv

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arXiv 2017年

作者： Liu, Miao Sivakumar, Kavinayan Omidshafiei, Shayegan Amato, Christopher How, Jonathan P. IBM T. J. Watson Research Center Yorktown HeightsNY United States Department of Electrical Engineering Princeton University PrincetonNJ United States Laboratory of Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States College of Computer and Information Science Northeastern University BostonMA United States

This paper presents a data-driven approach for multi-robot coordination in partially-observable domains based on Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) and macro-actions (MAs). Dec-POMDPs provide a general framework for cooperative sequential decision making under uncertainty and MAs allow temporally extended and asynchronous action execution. To date, most methods assume the underlying Dec-POMDP model is known a priori or a full simulator is available during planning time. Previous methods which aim to address these issues suffer from local optimality and sensitivity to initial conditions. Additionally, few hardware demonstrations involving a large team of heterogeneous robots and with long planning horizons exist. This work addresses these gaps by proposing an iterative sampling based Expectation-Maximization algorithm (iSEM) to learn polices using only trajectory data containing observations, MAs, and rewards. Our experiments show the algorithm is able to achieve better solution quality than the state-of-the-art learning-based methods. We implement two variants of multi-robot Search and Rescue (SAR) domains (with and without obstacles) on hardware to demonstrate the learned policies can effectively control a team of distributed robots to cooperate in a partially observable stochastic environment. Copyright © 2017, The Authors. All rights reserved.

关键词： Markov processes

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