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Erratum to: Measurement of differential cross sections and W+/W− cross-section ratios for W boson production in association with jets at = 8 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第10期2020卷 1-20页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Bakker, P. J. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z. Baroncelli, A. Bar Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz United States of America Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene United States of America Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas — LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston United States of America Joint Institute for Nuclear Research JINR Dubna Dubna Russia IN

Two additions impacting tables 3 and 4 in ref. [1] are presented in the following. No significant impact is found for other results or figures in ref. [1].

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Measurement of repeat effects in Chicago's criminal social network

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Applied Computing and informatics 2016年第2期12卷 154-160页

作者： Kump, Paul Alonso, David Haro Yang, Yongyi Candella, Joseph Lewin, Jonathan Wernick, Miles N. Medical Imaging Research Center and Dept. of Electrical and Computer Engineering Illinois Institute of Technology 3300 S. Federal St. Chicago 60616 IL United States Chicago Police Department 3510 S. Michigan Ave. Chicago 60653 IL United States

The “near-repeat” effect is a well-known criminological phenomenon in which the occurrence of a crime incident gives rise to a temporary elevation of crime risk within close physical proximity to an initial incident. Adopting a social network perspective, we instead define a near repeat in terms of geodesic distance within a criminal social network, rather than spatial distance. Specifically, we report a statistical analysis of repeat effects in arrest data for Chicago during the years 2003–2012. We divide the arrest data into two sets (violent crimes and other crimes) and, for each set, we compare the distributions of time intervals between repeat incidents to theoretical distributions in which repeat incidents occur only by chance. We first consider the case of the same arrestee participating in repeat incidents (“exact repeats”) and then extend the analysis to evaluate repeat risks of those arrestees near one another in the social network. We observe repeat effects that diminish as a function of geodesic distance and time interval, and we estimate typical time scales for repeat crimes in Chicago. © 2016 The Authors

关键词： Crime analysis Predictive policing Social network analysis Violent crime

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Inexpensive robot for experimental validation of planning and control algorithms

Inexpensive robot for experimental validation of planning an...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： José Lamarca Marius Kloetzer Cristian Mahulea Dept. of Computer Science and Systems Engineering University of Zaragoza Spain Dept. of Automatic Control and Applied Informatics Technical University of Iasi Romania Aragón Institute for Engineering Research University of Zaragoza Spain

ISBN: (纸本)9781509027217

This paper describes the structure of a mobile robot suitable for laboratory experiments. The robot is developed with the ideas of minimizing the production costs and of executing motion commands received from an external computer that runs the (possible computational intensive) planning algorithms. The proposed system is a differential wheeled robot built based on an Arduino platform, it has a small physical size and it is capable of wireless communication. These characteristics make it useful for validating planning algorithms for mobile robots in computer-guided laboratory experiments, while lowering the expenses required by such a setup. Moreover, in order to compensate the communication delay between the central computer and the robot, an estimation algorithm is implemented on the robot for obtaining a smoother motion.

关键词： Mobile robots Wheels computers Planning Trajectory Pins

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A survey on network resiliency methodologies against weather-based disruptions 8

A survey on network resiliency methodologies against weather...

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8th International Workshop on Resilient Networks Design and Modeling, RNDM 2016

作者： Tornatore, Massimo Andre, Joao Babarczi, Peter Braun, Torsten Folstad, Eirik Heegaard, Poul Hmaity, Ali Furdek, Marija Jorge, Luisa Kmiecik, Wojciech Mas MacHuca, Carmen Martins, Lucia Medeiros, Carmo Musumeci, Francesco Pasic, Alija Rak, Jacek Simpson, Steven Travanca, Rui Voyiatzis, Artemios Politecnico di Milano Department of Electronics Information and Bioengineering Milan Italy Lisbon Portugal Hungary University of Bern Bern Switzerland Norwegian University of Science and Technology Trondheim Norway Universidade de Aveiro Dept. of Electronics Information and Bioengineering Milan Portugal KTH Royal Institute of Technology Stockholm Sweden Instituto Politécnico de Bragancą INESC Coimbra Portugal Wroclaw University of Technology Poland Technical University Munich Germany Dept. of Electrical and Computer Engineering INESC University of Coimbra Portugal Dept. of Electrical and Computer Engineering and INESC University of Coimbra Coimbra Portugal Politecnico di Milano Department of Electron. Information and Bioengineering Milan Italy MTA-BME Future Internet Research Group Budapest Uni. of Technology and Economics Hungary Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Poland Lancaster University United Kingdom Dept. of Civil Engineering Universidade de Aveiro 3810-193 Portugal SBA Research Vienna Austria

ISBN: (纸本)9781467390231

Due to the increasing dependence on network services of our society, research has recently been concentrating on enhancing traditional protection strategies to withstand large-scale failures, as in case of disaster events. The recently-formed EU-funded RECODIS project aims at coordinating and fostering research collaboration in Europe on disaster resiliency in communication networks. In particular, the Working Group (WG) 2 of the RECODIS project focuses on developing new network-resiliency strategies to survive weather-based disruptions. As a first step, WG2 members have conducted a comprehensive literature survey on existing studies on this topic. This paper classifies and summarizes the most relevant studies collected by WG2 members in this first phase of the project. While the majority of studies regarding weather-based disruptions deals with wireless network (as wireless channel is directly affected by weather conditions), in this survey we cover also disaster-resiliency approaches designed for wired network if they leverage network reconfiguration based on disaster 'alerts', considering that many weather-based disruptions grant an 'alert' thanks to weather forecast. © 2016 IEEE.

关键词： Disasters

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A Supervisory Approach to Microgrid Demand Response and Climate Control

A Supervisory Approach to Microgrid Demand Response and Clim...

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Mediterranean Conference on Control and Automation

作者： Christos D. Korkas Simone Baldi Iakovos Michailidis Yiannis Boutalis Elias B. Kosmatopoulos Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece and Informatics & Telematics Institute Center for Research and Technology Hellas (ITI-CERTH) Thessaloniki 57001 Greece Delft Center for Systems and Control Delft University of Technology Delft 2628CD The Netherlands Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece

ISBN: (纸本)9781467383479

Microgrids equipped with small-scale renewable-energy generation systems and energy storage units offer challenging opportunity from a control point of view. In fact, in order to improve resilience and enable islanded mode, microgrid energy management systems must dynamically manage controllable loads by considering not only matching energy generation and consumption, but also thermal comfort of the occupants. Thermal comfort, which is often neglected or oversimplified, plays a major role in dynamic demand response, especially in front of intermittent behavior of the renewable energy sources. This paper presents a novel control algorithm for joint demand response management and thermal comfort optimization in a microgrid composed of a block of buildings, a photovoltaic array, a wind turbine, and an energy storage unit. In order to address the large-scale nature of the problem, the proposed control strategy adopt a two-level supervisory strategy: at the lower level, each building employs a local controller that processes only local measurements;at the upper level, a centralized unit supervises and updates the three controllers with the aim of minimizing the aggregate energy cost and thermal discomfort of the microgrid. Comparisons with alternative strategies reveal that the proposed supervisory strategy efficiently manages the demand response so as to sensibly improve independence of the microgrid with respect to the main grid, and guarantees at the same time thermal comfort of the occupants.

关键词： Buildings Microgrids Mathematical model Meteorology Optimization Load management Renewable energy sources

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PennyLane: Automatic differentiation of hybrid quantum-classical computations

arXiv

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arXiv 2018年

作者： Bergholm, Ville Izaac, Josh Schuld, Maria Gogolin, Christian Ahmed, Shahnawaz Ajith, Vishnu Alam, M. Sohaib Alonso-Linaje, Guillermo AkashNarayanan, B. Asadi, Ali Arrazola, Juan Miguel Azad, Utkarsh Banning, Sam Blank, Carsten Bromley, Thomas R. Cordier, Benjamin A. Ceroni, Jack Delgado, Alain Matteo, Olivia Di Dusko, Amintor Garg, Tanya Guala, Diego Hayes, Anthony Hill, Ryan Ijaz, Aroosa Isacsson, Theodor Ittah, David Jahangiri, Soran Jain, Prateek Jiang, Edward Khandelwal, Ankit Kottmann, Korbinian Lang, Robert A. Lee, Christina Loke, Thomas Lowe, Angus McKiernan, Keri Meyer, Johannes Jakob Montañez-Barrera, J.A. Moyard, Romain Niu, Zeyue O’Riordan, Lee James Oud, Steven Panigrahi, Ashish Park, Chae-Yeun Polatajko, Daniel Quesada, Nicolás Roberts, Chase Sá, Nahum Schoch, Isidor Shi, Borun Shu, Shuli Sim, Sukin Singh, Arshpreet Strandberg, Ingrid Soni, Jay Száva, Antal Thabet, Slimane Vargas-Hernández, Rodrigo A. Vincent, Trevor Vitucci, Nicola Weber, Maurice Wierichs, David Wiersema, Roeland Willmann, Moritz Wong, Vincent Zhang, Shaoming Killoran, Nathan Xanadu 777 Bay Street Toronto Canada Wallenberg Centre for Quantum Technology Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg412 96 Sweden Indian Institute of Information Technology Kottayam India NASA Ames Research Center Moffett FieldCA94035 United States Mountain ViewCA94043 United States data cybernetics Martin-Kolmsperger-Str 26 Landsberg86899 Germany Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University PortlandOR97202 United States Dept. of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Physics Indian Institute of Technology Roorkee Uttarakhand Roorkee India qBraid 5235 South Harper Court ChicagoIL60615 United States Factal Analytics Level 2 Chimes Building Plot 61 Sector - 44 Haryana Gurgaon122003 India Centre for High Energy Physics Indian Institute of Science Karnataka Bengaluru560012 India ICFO - Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Av. Carl Friedrich Gauss 3 Castelldefels Barcelona08860 Spain Chemical Physics Theory Group Department of Chemistry University of Toronto Canada DUG Technology 76 Kings Park Rd West PerthWA6005 Australia Rigetti Computing 2919 Seventh Street BerkeleyCA94710 United States Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute for Advanced Simulation Jülich Supercomputing Centre Forschungszentrum Jülich Jülich52425 Germany University of Amsterdam Netherlands School of Physical Sciences National Institute of Science Education and Research HBNI Odisha Jatni752 050 India Cervest United Kingdom Centro Brasileiro de Pesquisas Físicas Rua Dr. Xavier Sigaud 150 Rio de Janeiro22290-180 Brazil Zurich8092 Switzerland Neo4j UK Ltd United Kingdom Zapata Computing Inc. United States ITC Infotech Bangalore India Department of Microtechnology and Nanoscienc

PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices, supporting both qubit and continuous-variable paradigms. PennyLane’s core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation. PennyLane thus extends the automatic differentiation algorithms common in optimization and machine learning to include quantum and hybrid computations. A plugin system makes the framework compatible with any gate-based quantum simulator or hardware. We provide plugins for hardware providers including the Xanadu Cloud, Amazon Braket, and IBM Quantum, allowing PennyLane optimizations to be run on publicly accessible quantum devices. On the classical front, PennyLane interfaces with accelerated machine learning libraries such as TensorFlow, PyTorch, JAX, and Autograd. PennyLane can be used for the optimization of variational quantum eigensolvers, quantum approximate optimization, quantum machine learning models, and many other applications. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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Operational space robot control for motion performance and safe interaction under Unintentional Contacts

Operational space robot control for motion performance and s...

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European Control Conference (ECC)

作者： Yiannis Karayiannidis Leonidas Droukas Zoe Doulgeri Dept. of Signals and Systems Chalmers University of Technology Gothenburg Sweden Center for Autonomous Systems Royal Institute of Technology (KTH) Stockholm Sweden Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Academic Research Associate at Center for Research and Technology Hellas (CERTH) Thessaloniki Greece

A control law achieving motion performance of quality and compliant reaction to unintended contacts for robot manipulators is proposed in this work. It achieves prescribed performance evolution of the position error under disturbance forces up to a tunable level of magnitude. Beyond this level, it deviates from the desired trajectory complying to what is now interpreted as unintentional contact force, thus achieving enhanced safety by decreasing interaction forces. The controller is a passivity model based controller utilizing an artificial potential that induces vanishing vector fields. Simulation results with a three degrees of freedom (DOF) robot under the control of the proposed scheme, verify theoretical findings and illustrate motion performance and compliance under an external force of short duration in comparison with a switched impedance scheme.

关键词： Robots Collision avoidance Switches Force Trajectory Safety

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Simulation-based implementation and evaluation of a system of systems optimization algorithm in a building control system

Simulation-based implementation and evaluation of a system o...

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Mediterranean Conference on Control and Automation

作者： Roozbeh Sangi Thomas Schild Magnus Daum Johannes Futterer Rita Streblow Dirk Muller Iakovos Michailidis Elias Kosmatopoulos RWTH Aachen University E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate Aachen German Democritus University of Thrace Dept. of Electrical and Computer Engineering Xanthi Greece and Informatics & Telematics Institute Center for Research and Technology Hellas (ITI-CERTH) Thessaloniki Greece

ISBN: (纸本)9781467383479

The objective of this research is to evaluate the performance of a system of systems optimization algorithm, namely, L4G-PCAO, in building energy systems. Since the test bed of this research is an office building with more than two hundred occupiers, the heating and cooling demands of the building must always be fully satisfied. Consequently, changes in the currently-installed control system cannot be made forthrightly. Therefore, fresh ideas like implementation of new control strategies or optimization algorithms should be firstly put to the test via dynamic simulation, which makes engineers capable of examining new control and optimization strategies. The performance should then be analyzed and evaluated before implementing in the use case. This paper presents a strategy for simulation-based implementation of L4G-PCAO in a building energy system and also evaluates its performance. The results show that it is not only possible to conserve energy by applying this newly-developed optimization algorithm to existing control systems, but also it can shift the usage of energy sources in a more environment-friendly direction.

关键词： Building energy modelling and Simulation Building energy and control systems L4G-PCAO algorithm Local for global Performance evaluation Simulation-based building energy optimization Technical System of Systems (TSoS)

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A Benchmark for Cross-Weather Traffic Scene Understanding

A Benchmark for Cross-Weather Traffic Scene Understanding

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IEEE International Conference on Intelligent Transportation Systems

作者： Shuai Di Honggang Zhang Xue Mei Danil Prokhorov Haibin Ling School of Information and Communication Engineering Beijing University of Posts and Telecommunications China Toyota Research Institute North America Ann Arbor USA Center for Data Analytics & Biomedical Informatics Dept. of Computer & Information Sciences Temple University Philadelphia USA

ISBN: (纸本)9781509018901

Understanding traffic scene images taken from vehicle mounted cameras provides important information for high level tasks such as autonomous driving and advanced driver assistance. The problem is hard due to challenges from weather and illumination variation. To facilitate the research against such challenges, in this paper we present a new benchmark for cross-weather traffic scene understanding. The dataset consists of 1,356 traffic scene images collected at 226 different locations. For each location, there are six images taken by a vehicle mounted camera under different weather/illumination conditions including sunny day, night, snowy day, rainy night and cloudy days. We manually annotated each image with scene understanding labels such as road, sky, building, etc. To the best of our knowledge, this is the first carefully collected benchmark for cross-weather traffic scenes. In addition, we also provide results from two popular scene parsing systems as the baselines. We expect the benchmark to help boost research in improving robustness of traffic scene understanding algorithms.

关键词： Roads Clouds Automobiles Strips Buildings Vegetation Vegetation mapping

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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