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arXiv 2018年

作者： Wang, Shuai Baillieul, John Division of Systems Engineering Boston University BostonMA02115 United States Departments of Mechanical Engineering Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA02115 United States

Corrective Transmission Switching can be used by the grid operator to relieve line overloading and voltage violations, improve system reliability, and reduce system losses. Power grid optimization by means of line switching is typically formulated as a mixed integer programming problem (MIP). Such problems are known to be computationally intractable, and accordingly, a number of heuristic approaches to grid topology reconfiguration have been proposed in the power systems literature. By means of some low order examples (3-bus systems), it is shown that within a reasonably large class of "greedy" heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence based on a large number of simulations using using IEEE 118- bus systems indicates that among three heuristics, a globally greedy heuristic is the most computationally intensive, but has the best chance of reducing generation costs while enforcing N-1 connectivity. It is argued that, among all iterative methods, the locally optimal switches at each stage have a better chance in not only approximating a global optimal solution but also greatly limiting the number of lines that are switched. Copyright © 2018, The Authors. All rights reserved.

关键词： Heuristic methods

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CdS Nanocrystallines: Synthesis, Structure and Nonlinear Optical Properties

CdS Nanocrystallines: Synthesis, Structure and Nonlinear Opt...

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International Conference on Modern Problems of Radio engineering, Telecommunications and computer Science

作者： Oleksandr Yanchuk Oleg V. Marchuk Galyna Myronchuk Iryna A. Moroz Nazariy Andrushchak Oleksii A. Vyshnevskyi Iwan V. Kityk Andriy V. Kityk Katarzyna Ozga Jaroslaw Jedryka Artur Wojciechowski Anatoliy Andrushchak Department of Inorganic and Physical Chemistry Lesya Ukrainka Eastern European National University Lutsk Ukraine Department of Materials Science Lutsk National Technical University Lutsk Ukraine Department of Computer-Aided Design Systems Lviv Polytechnic National University Lviv Ukraine M. P. Semenenko Institute of Geochemistry Mineralogy and Ore Formation NAS of Ukraine Kyiv Ukraine Faculty of Electrical Engineering Czestochowa University of Technology Czestochowa Poland Department of Telecommunication Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9781728155661

ISBN: (纸本)9781728155678

We report the synthesis, structure and nonlinear optical properties of cadmium sulphide (CdS) nanocrystallines (NCs) synthesized electrochemically both with and without detergent ATLAS G3300. Relevant structural and morphological features are explored by X-ray diffraction and scanning electron microscopy (SEM) techniques. The efficiency of the second harmonic generation (SHG) appears to be strongly dependent on the energy density of the incident fundamental laser radiation and NC sizes.

关键词： chalcogenides nanocrystalline CdS SEM XRD SHG Second-harmonic generation Nonlinear optical properties Chalcogenides Nanocrystalline Scanning Electron Microscope X-ray diffraction energy density Laser radiation

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Unsupervised feature learning toward a real-time vehicle make and model recognition

arXiv

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arXiv 2018年

作者： Nazemi, Amir Shafiee, Mohammad Javad Azimifar, Zohreh Wong, Alexander School of Electrical & Computer Engineering Shiraz University Shiraz Iran Systems Design Engineering Dept. University of Waterloo Waterloo Canada

Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to address this challenge, however they can perform in restricted conditions. Here, we formulate the vehicle make and model recognition as a fine-grained classification problem and propose a new configurable on-road vehicle make and model recognition framework. We benefit from the unsupervised feature learning methods and in more details we employ Locality-constraint Linear Coding (LLC) method as a fast feature encoder for encoding the input SIFT features. The proposed method can perform in real environments of different conditions. This framework can recognize fifty models of vehicles and has an advantage to classify every other vehicle not belonging to one of the specified fifty classes as an unknown vehicle. The proposed MMR framework can be configured to become faster or more accurate based on the application domain. The proposed approach is examined on two datasets including Iranian on-road vehicle dataset and CompuCar dataset. The Iranian on-road vehicle dataset contains images of 50 models of vehicles captured in real situations by traffic cameras in different weather and lighting conditions. Experimental results show superiority of the proposed framework over the state-of-the-art methods on Iranian on-road vehicle datatset and comparable results on CompuCar dataset with 97.5% and 98.4% accuracies, respectively. Copyright © 2018, The Authors. All rights reserved.

关键词： Image classification

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Comparing LBP, HOG and Deep Features for Classification of Histopathology Images

Comparing LBP, HOG and Deep Features for Classification of H...

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International Joint Conference on Neural Networks

作者： Taha J. Alhindi Shivam Kalra Ka Hin Ng Anika Afrin Hamid R. Tizhoosh Systems Design Engineering University of Waterloo Canada Electrical and Computer Engineering University of Waterloo Canada Kimia Lab University of Waterloo Canada

Medical image analysis has become a topic under the spotlight in recent years. There is a significant progress in medical image research concerning the usage of machine learning. However, there are still numerous questions and problems awaiting answers and solutions, respectively. In the present study, comparison of three classification models is conducted using features extracted using local binary patterns, the histogram of gradients, and a pre-trained deep network. Three common image classification methods, including support vector machines, decision trees, and artificial neural networks are used to classify feature vectors obtained by different feature extractors. We use KIMIA Path960, a publicly available dataset of 960 histopathology images extracted from 20 different tissue scans to test the accuracy of classification and feature extractions models used in the study, specifically for the histopathology images. SVM achieves the highest accuracy of 90.52% using local binary patterns as features which surpasses the accuracy obtained by deep features, namely 81.14%.

关键词： Feature extraction Support vector machines Machine learning Histograms Cancer Decision trees Neural networks

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A dataset and preliminary results for umpire pose detection using SVM classification of deep features

arXiv

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arXiv 2018年

作者： Ravi, Aravind Venugopal, Harshwin Paul, Sruthy Tizhoosh, Hamid R. Department of Systems Design Engineering University of Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Canada Kimia Lab University of Waterloo Canada

In recent years, there has been increased interest in video summarization and automatic sports highlights generation. In this work, we introduce a new dataset, called SNOW, for umpire pose detection in the game of cricket. The proposed dataset is evaluated as a preliminary aid for developing systems to automatically generate cricket highlights. In cricket, the umpire has the authority to make important decisions about events on the field. The umpire signals important events using unique hand signals and gestures. We identify four such events for classification namely SIX, NO BALL, OUT and WIDE based on detecting the pose of the umpire from the frames of a cricket video. Pre-trained convolutional neural networks such as Inception V3 and VGG19 networks are selected as primary candidates for feature extraction. The results are obtained using a linear SVM classifier. The highest classification performance was achieved for the SVM trained on features extracted from the VGG19 network. The preliminary results suggest that the proposed system is an effective solution for the application of cricket highlights generation. Copyright © 2018, The Authors. All rights reserved.

关键词： Video recording

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The association for the advancement of artificial intelligence 2020 workshop program

The association for the advancement of artificial intelligen...

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作者： Bang, Grace Barash, Guy Bea, Ryan Cali, Jacques Castillo-Effen, Mauricio Chen, Xin Cynthia Chhaya, Niyati Dhoopar, Rohan Dumancic, Sebastijan Espinoza, Huáscar Farchi, Eitan Fioretto, Ferdinando Fuentetaja, Raquel Galley, Michel Geib, Christopher Hernández-Orallo, José Huang, Xiaowei Keren, Sarah Kim, Seokhwan Jaidka, Kokil Liu, Xiaomo Lu, Tyler Ma, Zhiqiang Mallah, Richard McDermid, John Michalowski, Martin Mirsky, Reuth Héigeartaigh, Seán Ó. Ramachandran, Deepak Segovia-Aguas, Javier Shaban-Nejad, Arash Shehory, Onn Shwartz, Vered Srivastava, Siddharth Talamadupula, Kartik Tang, Jian Zhang, Dell Zhang, Jian S&P Global. Western Digital University of Southampton United Kingdom Blue Prism Group PLC Lockheed Martin's Advanced Technology Laboratories ArlingtonVA United States University of Hong Kong Hong Kong Adobe Research Google Research Katholieke Universiteit Leuven Belgium Commissariat à ĺÉnergie Atomique France IBM Research Department of Electrical Engineering and Computer Science Syracuse University United States Universidad Carlos III de Madrid Spain Microsoft Research AI SIFT LLC Universitat Politècnica de València Spain Leverhulme Centre for the Future of Intelligence United Kingdom Department of Computer Science University of Liverpool United Kingdom National University of Singapore Singapore Harvard School of Engineering and Applied Sciences in the of Fields of Multiagent Environment Design and Goal Recognition Design Amazon Alexa AI Future of Life Institute United States University of York Assuring Autonomy International Program United Kingdom University of Minnesota School of Nursing MinneapolisMN United States University of Texas at Austin AustinTX United States Institut de Robòtica i Informàtica Industrial Spanish Council for Scientific Research Technical University of Catalonia Spain Oak Ridge National Laboratory Center for Biomedical Informatics Department of Pediatrics University of Tennessee Health Science Center United States Bar Ilan University Israel University of Washington SeattleWA United States Autonomous Agents and Intelligent Robots lab of the School of Computing Informatics Decision Systems Arizona State University United States DiDi AI Labs School of Industrial and System Engineering Georgia Institute of Technology United States University of London United Kingdom Microsoft Azure

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. Copyright © 2020, Association for the Advancement of Artificial Intelligence. All rights reserved.

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Mobile social services with network externality: From separate pricing to bundled pricing

arXiv

引用

arXiv 2018年

作者： Wang, Xuehe Duan, Lingjie Zhang, Junshan Pillar of Engineering Systems and Design Singapore University of Technology and Design 487372 Singapore School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

Today, many wireless device providers choose to sell devices bundled with complementary mobile social services, which exhibit strong positive network externality. Taking a reverse engineering approach, this paper aims to quantify the benefits of selling devices and complementary services under the following three strategies: separate pricing, bundled pricing, and hybrid pricing (both the separate and bundled options are offered). A comprehensive comparison of the above three strategies is carried out for two popular service models, namely physical connectivity sharing and virtual content sharing, respectively. These two sharing service models are two popular examples under the emerging trend of sharing economy. We first study the physical service model where the provider (e.g., FON) offers users customized WiFi devices for indoor Internet access, and allows service subscribers to physically access all device owners' WiFi when traveling. Observing that all device-owners contribute to the connectivity sharing, we show, via a Stackelberg game theoretic approach, that bundled pricing outperforms separate pricing as long as the total cost of device and service is reasonably low to stimulate network externality. Further, hybrid pricing strictly dominates bundled pricing thanks to the pricing flexibility to keep high marginal profit of device-selling. Next, we investigate the virtual sharing service model where the provider (e.g., Apple) sells devices and device-supported applications. Different from the connectivity service model, in this model service subscribers directly contribute to the virtual content sharing, and the network externality can be fairly strong. We prove that hybrid pricing degenerates to bundled pricing if the network externality degree is larger than the average device valuation, which is in stark contrast with the connectivity service model in which hybrid pricing always outperforms bundled pricing. Copyright © 2018, The Authors. All rights reserved.

关键词： Sales

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Work in Progress – Establishing a Master Program in Cyber Physical systems: Basic Findings and Future Perspectives

Work in Progress – Establishing a Master Program in Cyber P...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of Science on Cyber Physical systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： computer science Internet of Things Industries Knowledge engineering Embedded systems Europe Collaboration

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A hybrid agent-based secondary control for microgrids with increased fault-tolerance needs

A hybrid agent-based secondary control for microgrids with i...

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Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2018

作者： Bintoudi, Angelina D. Bintoudi, Angelina D. Zyglakis, Lampros Apostolos C. Tsolakis Ioannidis, Dimosthenis Al-Agtash, S. Al-Agtash, S. Martinez-Ramos, Jose L. Onen, Ahmet Azzopardi, Brian Hadjidemetriou, Lenos Martensen, Nis Mounir, Khiat Borg, Nicholas Fragale, Nunziatina Demoulias, Charis Tzovaras, Dimitrios Information Technologies Institute Center for Research and Technology Hellas Thessaloniki Greece Department of Computer Engineering German Jordanian University Amman Jordan Department of Computer Engineering Santa Clara University CA United States Department of Electrical Engineering Universidad de Sevilla Seville Spain Department of Electrical and Electronics Engineering Abdullah Gul University Kayseri Turkey MCAST Triq Kordin Malta KIOS Research Center of Excellence University of Cyprus Nicosia Cyprus Energynautics GmbH Darmstadt Germany Département de Génie Électrique Laboratoire SCAMRE Ecole Nationale Polytechnique d'Oran Algeria Electronic Systems Design Ltd Malta GeoSYS Ltd San Gwann Malta Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9781839531330

This paper proposes a hybrid secondary control architecture for microgrids with AC-coupled droop-controlled units, based on both centralised and distributed control principles. The proposed secondary control is based on a multi-agent system (MAS), complemented by a microgrid centralised controller (MGCC). The system is able to adjust the droop curves dynamically in order to achieve voltage/frequency restoration as well as active/reactive power optimal allocation, based on the actual status of the controllable units, in particular, the state-of-charge of batteries and maximum power point of photovoltaics. The distributed nature of the agents is also fully exploited because the proposed framework retains operability even under fault on secondary MGCC. To evaluate the proposed framework, a scenario-based performance analysis has been tested over a simulated AC islanded microgrid, where communication from the MGCC is suddenly interrupted and the MAS is required to reconfigure in order to maintain the same control objectives. MATLAB/Simulink simulations have been realised using detailed physical form models for a small-scale microgrid, while the implementation of the MGCC and MAS is accomplished through Java Agent Development (JADE) framework. © 2018 Institution of engineering and Technology. All rights reserved.

关键词： Multi agent systems

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Perturbed Tumor Immunotherapy Domain of Attraction Estimation via the Arc-Length Function

Perturbed Tumor Immunotherapy Domain of Attraction Estimatio...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Mojtaba Zarei Kimia Javadi Ahmad Kalhor Cyber-Physical Systems Lab (CPSL) Departments of Electrical and Computer Engineering Duke University NC USA Faculty of Computer and Electrical Engineering K.N.Toosi University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781538679531;9781538679524

This paper aims at the estimation of the Domain of Attraction (DoA) of the free tumor equilibrium point of perturbed tumor immunotherapy model via the Arc-Length Function (ALF). The ALFs are categorized among the maximal Lyapunov functions which are able to provide a more accurate estimation of the DoA in comparison to their other counterparts such as Rational Lyapunov Functions (RLFs), Sum Of Square (SOS) polynomial Lyapunov functions, and Optimal Quadratic Lyapunov Functions (OQLFs). There is no analytical method to construct the ALFs, however, some numerical methods have been proposed in the literature. Based on the existing method, one can approximate the ALF with a certain degree of a polynomial function. That the system under study has a polynomial structure was the main basis of the previously proposed method to estimate the DoA via the ALFs. However, the intended model in this paper describing the tumor-immune system competition dynamics contains non-polynomial terms. To cope with the aforementioned problem, the Taylor expansion of the non-polynomial terms are considered and by solving an optimization problem, one can calculate the corresponding lower boundary of the level set with the approximated ALF as an estimation of the DoA. In order to represent the performance of the employed method, the obtained result is compared with the reported result in the literature.

关键词： Tumors Direction-of-arrival estimation Lyapunov methods Estimation Immune system Mathematical model Cancer

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