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engineering Intelligent systems 2015年第4期23卷 209-216页

作者： Carrasco, Juan J. Millán-Giraldo, Mónica Caravaca, Juan Díaz, Ignacio Sanchis, Javier Soria-Olivas, Emilio Intelligent Data Analysis Laboratory E.T.S.E University of Valencia Avda Universitat S/N Burjassot Valencia46100 Spain Electrical Engineering and Computer Systems Department University of Oviedo University Campus of Viesques Gijón Asturias33204 Spain Instituto Universitario de Automática e Informática Industrial Universitat Politécnica de Valencia Camino de Vera S/N Valencia46022 Spain

Reduction in energy consumption is of paramount importance due to the influence that it has on the economic, politics and on the use of natural resources. Within this field, energy efficiency in buildings sector constitutes one of the main concerns due to the fact that approximately 40% of total world energy consumption corresponds to this sector. Predicting the indoor temperature in advance can help to act more efficiently on Heating, Ventilation fans and Air Conditioning (HVAC) systems, and thus to reduce the consumption. This work tackles the application of machine learning methods to forecast indoor temperature in an office building, using several prediction horizons. The obtained results showed the validity of the used approximation. ©2015 CRL Publishing Ltd.

关键词： Energy efficiency

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Effect of number of versions on receiving high citations

TechRxiv

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TechRxiv 2020年

作者： Ale Ebrahim, Nader Salehi, Hadi Mohammadjafari, Marjan Embi, Mohamed Amin Bakhtiyari, Kaveh Danaee, Mahmoud Shakiba, Masoud Shahbazi-Moghadam, Masoomeh Zavvari, Azam Department of Industrial Engineering Faculty of Engineering Kerman Branch Islamic Azad University Kerman Iran Faculty of Literature and Humanities Najafabad Branch Islamic Azad University Isfahan Najafabad Iran Bangi 43600 Malaysia Department of Computer & Cognitive Science Facultyof Engineering University of Duisburg-Essen Duisburg Germany Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia University of Malaya Malaysia Faculty of Agriculture Roudehen Branch Islamic Azad University Roudehen Iran Center for Software Technology and Management Faculty of Information Science and Technology Universiti Kebangsaan Malaysia UKM Bangi Selangor 43600 Malaysia Perdana School of Science Technology and Innovation Policy Universiti Teknologi Malaysia Malaysia

Nowadays, the h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based upon the set of the scientist's most cited papers and the number of citations that they have received in other publications. Besides, the most commonly used measure of journal quality is Impact Factor. This is a number which attempts to measure the impact of a journal in terms of the average number of citations to recent articles published in the journal. So, receiving more citation is very important for authors and journals to get high h-index and impact factor. In this paper, we tried to analyses the effect of the number of available version from the web on receive more citations. We analyzed 10162 papers which are published in Scopus database in year 2010. Then we developed a software to collect the number of citations and versions of each paper from Google Scholar automatically. The results show that … © 2020, CC BY.

关键词： Indexing (of information)

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Fault-Tolerant Quaternion Neural Network Fast Terminal Sliding Mode Control for Guidance and Navigation of UAV’s under Actuator Faults

Fault-Tolerant Quaternion Neural Network Fast Terminal Slidi...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Fernando E. Serrano Ahmad Taher Azar Saim Ahmed Nashwa Ahmad Kamal Ibraheem Kasim Ibraheem Instituto de Investigación en Energía Universidad Nacional Autónoma de Honduras Tegucigalpa Honduras Instituto de Robóticae Informática Industrial IRI-CSIC Universidad Politécnica de Cataluña Barcelona España College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Automated Systems and Soft Computing Lab (ASSCL) Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Faculty of Engineering Cairo University Giza Egypt Department of Electrical Engineering College of Engineering University of Baghdad Baghdad Iraq Department of Electronics and Communication Engineering Uruk University Baghdad Iraq

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

This research presents a terminal sliding mode controller and quaternion neural network observer for unmanned aerial vehicle (UAV) guidance and navigation under actuator fault. Initially, to determine which of a quadrotor’s four actuators is failing, a quaternion neural network observer is created. The quadrotor dynamic model includes the DC motor dynamics, which is taken into account when designing the fault-tolerant observer. The quaternion neural network presents four failure modes pertaining to an actuator state in which instability and divergence from the healthy state occur when one of the actuators fails. Next, a fault-tolerant terminal sliding mode controller is engineered to deliver the necessary controller action when all actuators are functioning normally, or if one or more quadrotor UAV actuators malfunction. The rapid terminal sliding mode controller is built in order to acquire the diverse control laws when one or many actuators fail or when the system is in healthy state. The suitable Lyapunov functional at various time instants is taken into account throughout the construction of this fault-tolerant controller to restore optimal performance. In addition to the theoretical outcomes of this investigation, a simulation is run to demonstrate the effectiveness of the observer/controller approach and to contrast it with other sliding mode and neural network observer/controller combinations. The research study’s conclusions and discussions are given at the end.

关键词： Fault diagnosis Actuators Fault tolerance Quaternions Fault tolerant systems Neural networks Observers

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A Full Frequency Range Average Model for Vienna-Type Rectifiers

A Full Frequency Range Average Model for Vienna-Type Rectifi...

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39th IEEE Power Electronics Specialists Conference (PESC 2008), vol.10

作者： R. Burgos R. Lai S. Rosado F. Wang D. Boroyevich J. Pou Center for Power Electronic Systems Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA Terrassa Industrial Electronics Group Universitat Politecnica de Catalunya Catalonia Spain

This paper presents a new mathematical model for three-level non-regenerative Vienna-type rectifiers exploiting the equivalence of this topology with three-level neutral-point-clamped (NPC) converters. Specifically, it models the rectifier operation using a positive- and one negative-rail switching function--the standard approach for NPC converters. This equivalent modeling renders the state space model of Vienna-type rectifiers structurally time invariant, enabling its conversion into the synchronous d-q frame, and its averaging over a switching cycle basis. The resultant model is consequently valid up to half of the switching frequency. An in-depth small-signal analysis is then presented showing that only the d-d channel and dc port of the rectifier present truly time-invariant dynamics, given the intrinsically pulsating power transfer between its ac and dc terminals;quasi-stationary small-signal analysis is thus mandatory for this type of topology. Simulation and experimental results with a 20 kW motor drive and 2 kW experimental prototype are used for validation purposes.

关键词： Vienna rectifier average model small-signal analysis quasi-stationary small-signal analysis

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Local rademacher complexity-based learning guarantees for multi-task learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2018年第1期19卷

作者： Niloofar Yousefi Yunwen Lei Marius Kloft Mansooreh Mollaghasemi Georgios C. Anagnostopoulos Department of Electrical Engineering and Computer Science University of Central Florida Orlando FL Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Department of Computer Science Technische Universität Kaiserslautern Kaiserslautern Germany Department of Industrial Engineering & Management Systems University of Central Florida Orlando FL Department of Electrical and Computer Engineering Florida Institute of Technology Melbourne FL

We show a Talagrand-type concentration inequality for Multi-Task Learning (MTL), with which we establish sharp excess risk bounds for MTL in terms of the Local Rademacher Complexity (LRC). We also give a new bound on the LRC for any norm regularized hypothesis classes, which applies not only to MTL, but also to the standard Single-Task Learning (STL) setting. By combining both results, one can easily derive fast-rate bounds on the excess risk for many prominent MTL methods, including--as we demonstrate--Schatten norm, group norm, and graph regularized MTL. The derived bounds reflect a relationship akin to a conservation law of asymptotic convergence rates. When compared to the rates obtained via a traditional, global Rademacher analysis, this very relationship allows for trading off slower rates with respect to the number of tasks for faster rates with respect to the number of available samples per task.

关键词： excess risk bounds local rademacher complexity multi-task learning

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HRI Pioneers Workshop 2013 13

HRI Pioneers Workshop 2013

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Solace Shen Henny Admoni Caroline Harriott Yunkyung Kim Matt Marge Marynel Vázquez Astrid Rosenthal-von der Pütten Matt Beane Yasuhiko Hato Daniel Lazewatsky Robin Read Steve Vozar Department of Psychology University of Washington Seattle USA Department of Social Psychology University of Duisburg-Essen Duisburg Germany Department of Computer Science Yale University New Haven USA Sloan School of Management Massachusetts Institute of Technology Cambridge USA Department of Electrical Engineering & Computer Science Vanderbilt University Nashville USA Graduate School of Science & Technology Keio University Yokohama Japan Department of Industrial Design Korea Advanced Institute of Science and Technology Daejeon South Korea Industrial & Manufacturing Engineering Oregon State University Corvallis USA Language Technologies Institute Carnegie Mellon University Pittsburgh USA Centre for Robotics & Neural Systems University of Plymouth Plymouth UK Robotics Institute Carnegie Mellon University Pittsburgh USA Department of Mechanical Engineering University of Michigan Ann Arbor USA

ISBN: (纸本)9781467330558

The 2013 Human-Robot Interaction (HRI) Pioneers Workshop, which will be held in conjunction with the 8 th ACM/IEEE International Conference on Human-Robot Interaction, is the premiere venue for student research in the field. This highly selective workshop seeks to foster creativity, communication, and collaboration between the world's top student researchers in the field of human-robot interaction. Pioneers Workshop participants will have the opportunity to learn about the current state of HRI, to present their research, and to network with one another and with select senior researchers in a setting that is less formal and more interactive then the main conference. The theme for this year is Re-envisioning HRI: Dealing With the Elephants in Our Room. The workshop aims to bring forward difficult to discuss issues to help the field achieve more balanced perspectives and a clearer picture of what sort of future we are building.

关键词： Educational institutions Conferences Human-robot interaction Psychology computer science Service robots

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The CARAMEL Project: a Secure Architecture for Connected and Autonomous Vehicles

The CARAMEL Project: a Secure Architecture for Connected and...

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European Conference on Networks and Communications (EuCNC)

作者： Christian Vitale Nikos Piperigkos Christos Laoudias Georgios Ellinas Jordi Casademont Pouria Sayyad Khodashenas Andreas Kloukiniotis Aris S. Lalos Konstantinos Moustakas Pablo Barrientos Lobato Javier Moreno Castillo Petros Kapsalas Klaus-Peter Hofmann KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Industrial Systems Institute Athena Research and Innovation Center Patras Greece Dept. of Electrical and Computer Engineering University of Patras Patras Greece i2CAT Foundation Barcelona Spain Universitat Politècnica de Catalunya Barcelona Spain Atos IT Solutions and Services Iberia S.L. Madrid Spain FICOSA Barcelona Spain Panasonic Automotive Langen Germany T-Systems International GmbH Frankfurt Germany

ISBN: (数字)9781728143552

ISBN: (纸本)9781728143569

The main goals of the CARAMEL project are to enhance the protection of modern vehicles against cybersecurity threats related to automated driving, smart charging of Electric Vehicles, and communication among vehicles or between vehicles and the roadside infrastructure. This work focuses on the latter and presents the CARAMEL architecture for improving the security and privacy of communication for connected and autonomous driving. The proposed architecture includes: (i) multi-radio access technology capabilities, with simultaneous 802.11p and LTE-Uu support; (ii) a MEC platform, where algorithms for detecting attacks are implemented; (iii) an intelligent On-Board Unit with anti-hacking features inside the vehicle; (iv) a Public Key Infrastructure that validates in real-time the integrity of vehicle's data transmissions. As an indicative application scenario, the interaction between the entities of the CARAMEL architecture is showcased in the case that the GPS locations used by vehicles are spoofed.

关键词： computer architecture Europe computer security Privacy Safety Servers

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Deep segmentation networks predict survival of non-small cell lung cancer

arXiv

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arXiv 2019年

作者： Baek, Stephen He, Yusen Allen, Bryan G. Buatti, John M. Smith, Brian J. Tong, Ling Sun, Zhiyu Wu, Jia Diehn, Maximilian Loo, Billy W. Plichta, Kristin A. Seyedin, Steven N. Gannon, Maggie Cabel, Katherine R. Kim, Yusung Wu, Xiaodong University of Iowa Department of Industrial and Systems Engineering Iowa CityIA52242 United States University of Iowa Department of Radiation Oncology Iowa CityIA52242 United States University of Iowa Department of Electrical and Computer Engineering Iowa CityIA52242 United States University of Iowa Department of Business Analytics Iowa CityIA52242 United States University of Iowa Department of Biostatistics Iowa CityIA52242 United States Stanford University Stanford Cancer Institute Palo AltoCA94304 United States

Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography/computed tomography (PET/CT) images have predictive power for NSCLC outcomes. To this end, easily calculated functional features such as the maximum and the mean of standard uptake value (SUV) and total lesion glycolysis (TLG) are most commonly used for NSCLC prognostication, but their prognostic value remains controversial. Meanwhile, convolutional neural networks (CNN) are rapidly emerging as a new method for cancer image analysis, with significantly enhanced predictive power compared to hand-crafted radiomics features. Here we show that CNNs trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value. In a retrospective study on pre-treatment PET-CT images of 96 NSCLC patients before stereotactic-body radiotherapy (SBRT), we found that the CNN segmentation algorithm (U-Net) trained for tumor segmentation in PET and CT images, contained features having strong correlation with 2- and 5-year overall and disease-specific survivals. The U-Net algorithm has not seen any other clinical information (e.g. survival, age, smoking history, etc.) than the images and the corresponding tumor contours provided by physicians. In addition, we observed the same trend by validating the U-Net features against an extramural data set provided by Stanford Cancer Institute. Furthermore, through visualization of the U-Net, we also found convincing evidence that the regions of metastasis and recurrence appear to match with the regions where the U-Net features identified patterns that predicted higher likelihoods of death. We anticipate our findings will be a starting point for more sophisticated non-intrusive patient specif

关键词： Diseases

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Mobility-on-demand versus fixed-route transit systems: An evaluation of traveler preferences in low-income communities

arXiv

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arXiv 2019年

作者： Yan, Xiang Zhao, Xilei Han, Yuan van Hentenryck, Pascal Dillahunt, Tawanna Taubman College of Architecture and Urban Planning University of Michigan 2000 Bonisteel Blvd Ann ArborMI48109 United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology 755 Ferst Drive NW AtlantaGA30332 United States School of Information University of Michigan 105 S State St Ann ArborMI48109 United States Electrical Engineering and Computer Science University of Michigan 1301 Beal Avenue Ann ArborMI48109-2122 United States

Emerging transportation technologies, such as ride-hailing and autonomous vehicles, are disrupting the transportation sector and transforming public transit. Some transit observers envision future public transit to be integrated transit systems with fixed-route services running along major corridors and on-demand ridesharing services covering lower-density areas. A switch from a conventional fixed-route service model to this kind of integrated mobility-on-demand transit system, however, may elicit varied responses from local residents. This paper evaluates traveler preferences for a proposed integrated mobility-on-demand transit system versus the existing fixed-route system, with a particular focus on disadvantaged travelers. We conducted a survey in two low-resource communities in the United States, namely, Detroit and Ypsilanti, Michigan. A majority of survey respondents preferred a mobility-on-demand transit system over a fixed-route one. Based on ordered logit model outputs, we found a stronger preference for mobility-on-demand transit among males, college graduates, individuals who have never heard of or used ride-hailing before, and individuals who currently receive inferior transit services. By contrast, preferences varied little by age, income, race, or disability status. The most important benefit of a mobility-on-demand transit system perceived by the survey respondents is enhanced transit accessibility to different destinations, whereas their major concerns include the need to actively request rides, possible transit-fare increases, and potential technological failures. Addressing the concerns of female riders and accommodating the needs of less technology-proficient individuals should be major priorities for transit agencies that are considering mobility-on-demand initiatives. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

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Cooperative Communications in Multi-hop Wireless Networks: Joint Flow Routing and Relay Node Assignment

Cooperative Communications in Multi-hop Wireless Networks: J...

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2010 Proceedings IEEE INFOCOM

作者： Sushant Sharma Yi Shi Y. Thomas Hou Hanif D. Sherali Sastry Kompella Department of Computer Science Virginia Tech Blacksburg VA USA Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg VA USA Information Technology Division U.S. Naval Research Laboratory Washington DC USA

ISBN: (纸本)9781424458363

It has been shown that cooperative communications (CC) have the potential to significantly increase the capacity of wireless networks. However, most of the existing results are limited to single-hop wireless networks. To illustrate the benefits of CC in multi-hop wireless networks, we solve a joint optimization problem of relay node assignment and flow routing for concurrent sessions. We study this problem via mathematical modeling and solve it using a solution procedure based on the branch-and-cut framework. We design several novel components to speed-up the computation time of branch-and-cut. Via numerical results, we show the significant rate gains that can be achieved by incorporating CC in multi-hop networks.

关键词： Wireless networks wireless multi-hop networks Trunk Node cooperative communication computational time Communication Research Network routing branches mathematical modeling Joints Joints

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