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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Virtual sensing of room activity using passive environmental sensors

Virtual sensing of room activity using passive environmental...

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International Conference on Internet of Things 2024 (ICIoT 2024)

作者： Yeqin Li David Chieng Chiew Foong Kwong Boon Giin Lee Yunfan Zhang Yin Wang Ting-Jung Lin Next-Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering University of Nottingham Ningbo People's Republic of China School of Computer Science University of Nottingham Ningbo People's Republic of China Department of Electrical and Computer Engineering Duke University USA HealthyPhoton Technology Co. Ltd. Ningbo 315042 People's Republic of China

ISBN: (数字)9781837242177

A data-driven approach has been developed to classify indoor activities using only commonly available passive environmental sensors, such as CO2, temperature, humidity, and passive infrared (PIR). An integrated IoT system comprising of sensor nodes, edge node and an intelligent server is designed and developed to provide real-time activity classification. Spectral Clustering and bidirectional long short-term memory (BiLSTM) are employed to achieve automatic labeling and room state prediction. The results show that the overall classification accuracy ranges from 88% to 96% for five target states across three distinct environments using CO2 and PIR values as input variables. Additionally, incorporating more input variables has been evaluated to access the ability of real-time classification of proposed model. An innovative monitoring mode can provide a different approach for detecting activities and occupancy in the future.

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CNN-based Hand Gesture Recognition for Contactless Elevator Button Control

CNN-based Hand Gesture Recognition for Contactless Elevator ...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Taeho-Lee Viduranga Munasinghe Yan-Mei Li Tae Sung Kim Hyuk-Jae Lee Next-Generation Semiconductor Convergence and Open Sharing System Seoul National University Seoul Korea Department of Electrical and Computer Engineering Seoul National University Seoul Korea Department of Electronic Engineering Sun Moon University Asan Korea

Recently, with the outbreak of the COVID-19 pandemic, various quarantine measures have been implemented to reduce the spread of the virus. As a part of efforts, the preference for touchless technology has been emerging. In this paper, we propose a touchless elevator control system using CNN-based hand gesture recognition. Experimental results show that the hand recognition AP and FPS on the Jetson TX2 board are 81.87% and 11.8FPS, respectively. We demonstrate that an elevator model could be controlled by virtual elevator buttons utilizing CNN-based hand gesture recognition. The proposed method can be applied to commercial elevators as an approach to prevent the spread of viruses from elevator buttons.

关键词： COVID-19 Deep learning computer viruses Pandemics Graphics processing units Gesture recognition Control systems

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Double Media-Based Modulation Scheme for High-Rate Wireless Communication systems

arXiv

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arXiv 2024年

作者： Ozden, Burak Ahmet Aydin, Erdogan Cogen, Fatih Department of Electrical and Electronics Engineering Istanbul Medeniyet University Istanbul34857 Turkey Department of Computer Engineering Yildiz Technical University Istanbul34220 Turkey Istanbul Medeniyet University Department of Electrical and Electronics Engineering Uskudar Istanbul34857 Turkey 6GEN Laboratory Next-Generation R&D Network Technologies Istanbul34854 Turkey

Current wireless communication technologies are insufficient in the face of ever-increasing demands. Therefore, novel and high-performance communication systems are needed. In this paper, a novel high data rate and high-performance index modulation scheme called double media-based modulation (DMBM) is proposed. The DMBM system doubles the number of mirror activation patterns (MAPs) and the number of transmitted symbols compared to the traditional MBM system during the same symbol period. In this way, the spectral efficiency of the DMBM is doubled and the error performance improves as the number of bits carried in the indices increases. Performance analysis of the DMBM scheme is evaluated for M-ary quadrature amplitude modulation (M-QAM) on Rayleigh fading channels. The error performance of the proposed DMBM system is compared with spatial modulation (SM), quadrature SM (QSM), MBM, and double SM (DSM) techniques. Also, the throughput, complexity, energy efficiency, spectral efficiency, and capacity analyses for the proposed DMBM system and SM, QSM, MBM, and DSM systems are presented. All analysis results show that the proposed DMBM system is superior to the compared systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadrature amplitude modulation

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Wireless Channel Scenario Identification Using Convolutional Neural Networks

Wireless Channel Scenario Identification Using Convolutional...

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IEEE Conference on Vehicular Technology (VTC)

作者： Govind R. Gopal Jie Chen William J. Hillery Jun Tan Serdar Özen Qiping Zhu Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA Nokia Standards Nokia of America Corporation Naperville IL USA Next Generation and Standards Intel Corporation Santa Clara CA USA

Wireless channel scenario identification carries importance as it assists in network design aspects such as receiver modeling and channel prediction. In this work, we consider the identification of indoor and outdoor scenarios using convolutional neural networks (CNNs) with channel measurements as the input data. First, we consider the channel measurements obtained as independent realizations (the snapshot dataset) and utilize a 2-D CNN to classify between indoor and outdoor channels. Then, the channel measurements taken for successive time samples (the time series dataset) are classified using 3-D CNNs. Finally, comparison of the CNN-based approaches is performed with a traditional machine learning-based k-nearest neighbors (k-NN) algorithm, which takes skewness, kurtosis, and delay spread of the channel data as the input features. The CNN-based method for the snapshot data yields around 87% accuracy and performs better than the baseline k-NN method yielding around 76%. For the time series dataset, the CNN-based method with up to a 85% accuracy shows a marked improvement over the 60% accuracy achieved by the k-NN algorithm.

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Kinematic analysis of a 5-DOF positioner for precision additive manufacturing

Kinematic analysis of a 5-DOF positioner for precision addit...

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ASME 2020 International Design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2020

作者： Saadatzi, Mohammad Hossein Popa, Dan O. Next Generation Systems Research Group Dept. of Electrical and Computer Eng University of Louisville Louisville KY40208 United States

ISBN: (纸本)9780791883990

Additive manufacturing, as a viable industrial-production technology, requires multi-DOF positioning with high precision and repeatability for either the printer head, or the part being printed. In this paper we present a novel methodology to analyze the error propagation informing the design of a high-precision robotic 5-DOF positioner for applications in additive manufacturing. We designed our positioner through serial attachment of linear and rotational stages by comparing the precision of three different kinematic arrangements of stages. Within order to minimize positioning errors in Cartesian space, the kinematic sensitivity of the mechanisms end-effector relative to the maximum expected error of each joint was computed, and the kinematic configuration with smallest 6D positioning error at the end-effector was selected. The methodology employed in this paper for the error propagation analysis of serial kinematic chains has a great level of generality and can facilitate the design and optimization of a wide-class of multi-DOF positioners. Copyright © 2020 ASME

关键词： End effectors

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Solutions for Digital Interaction of a Resilient Energy Community in a Service-oriented Framework 12

Solutions for Digital Interaction of a Resilient Energy Comm...

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12th International Conference and Exposition on electrical and Power engineering, EPE 2022

作者： Sanduleac, Mihai Ionescu, Constantin Mandis, Alexandru Gropa, Victor Efremov, Cristina Sanduleac, Vlad Department of Power Systems Faculty of Energy Engineering University Politehnica of Bucharest Bucharest Romania Dep. of Energy Generation and Use Faculty of Energy Engineering University Politehnica of Bucharest Bucharest Romania Faculty of Energetics and Electrical Engineering Technical University of Moldova Chisinau Moldova Department of Computer Science and Engineering Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania

ISBN: (数字)9781665489942

ISBN: (纸本)9781665489942

Energy communities are emerging entities which need their own Information and Communication System. Resilience is a key metric of such communities, and it has to be implemented for both energy supply versus public network outages and for its information system versus cyber-attacks, acting as cyber-citadels which have to resist external malicious attacks while having also digital interactions with external entities. The paper presents solutions for a resilient energy community with appropriate implementations of digital interaction for data exchange, in order to acquire external energy service for specialized companies and to deliver also information and communication-related services for external users. Principles of a Contractual Data Protection Regulation are presented, as an adaptation of data protection tailored for automated energy services and based on secure data exchange. The principles are verified in a demonstration project which has also external entities with digital interaction. © 20XX IEEE.

关键词： Cybersecurity

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TSPD: A Robust Online Time Series Two-Stage Peak Detection Algorithm

TSPD: A Robust Online Time Series Two-Stage Peak Detection A...

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2023 IEEE International Conference on Service-Oriented System engineering (SOSE)

作者： Aditi Gupta Adeiza J. Onumanyi Satyadev Ahlawat Yamuna Prasad Virendra Singh Department of Electrical Engineering Indian Institute of Technology (IIT) Jammu Jammu India Next Generation Enterprises and Institutions Council for Scientific and Industrial Research (CSIR) Pretoria South Africa Department of Computer Science and Engineering Indian Institute of Technology (IIT) Jammu Jammu India Department of Electrical Engineering Indian Institute of Technology (IIT) Bombay Mumbai India

Peak detection (PD) is a valuable technique in time series analysis that can be employed to identify significant local maxima or minima within the time series. Peaks are significant points in a signal or spectrum that are of interest, as they can represent important features in various applications such as chromatography, spectroscopy, biomedical signal processing, and image analysis, to name a few. However, due to the unpredictable and fluctuating nature of many real-time sources, current peak detection algorithms usually fail to detect stable peaks across varied real-time time series. Furthermore, they experience a dip in performance when trying to develop a general algorithm applicable across various application areas. To address this challenge, we have developed a novel and robust online two-stage peak detection algorithm (TSPD). Our TSPD algorithm can adapt to a wide range of application areas by adjusting only two tunable parameters in its computational process. To demonstrate the efficacy of our algorithm, we conducted experiments using seven real-world datasets and demonstrated the improved performance of the TSPD algorithm over other notable existing techniques.

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Proposal for Simplifying Smart Metering Data Access for Authorised Energy Service Providers and Other Third-Parties Upon End-Consumer Request and Consent

Proposal for Simplifying Smart Metering Data Access for Auth...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Valeria Maksimovich Michal Vrana Martin Vojtek Michal Ptacek Alina Demchenko Gleb Nesterenko School of Industrial Engineering of Barcelona (ETSEIB) Universitat Politècnica de Catalunya Barcelona Spain Department of Electrical Power Engineering (FEKT UEEN) Brno University of Technology Brno Czech Republic Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Next Generation Network The International Council on Large Electric Systems (CIGRE) Astana Kazakhstan

The smart meter data unlock new saving and earning opportunities for both individual households and energy communities. The infrastructure, complexity, and administrative procedures involved with third-party smart meter data access vary greatly between EU member states. The current data access process poses a significant barrier to energy-saving tools and platforms. The customer data request and consent is not opaque, long-lasting, and complicated to perform. In addition, the data access process most of the time is not linked to the e-citizen digital identity which represents a missed opportunity for a simple procedure of consumer content and identification. The authors of this study have selected three representative countries with varying levels of smart meter penetration and infrastructure for data storage and exchange and third-party data access to the energy Data Exchange Platforms (DEPs). The authors analysed third-party data access methods, outlined their shortcomings, and ultimately proposed the third-party data access process that is the most efficient, automatic and unbureaucratic. The implementation of the proposed approach will allow third parties, with the consent of consumers, to easily access smart meter data and effectively provide consumers with various services related to energy audit and energy saving.

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A Novel Collision Detection Protocol for Wireless Full-duplex Networks

A Novel Collision Detection Protocol for Wireless Full-duple...

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IEEE International Conference on Networking, Sensing and Control

作者： Qinglin Zhao Li Feng MengChu Zhou Haisheng Yu Yi Sun School of Computer Science and Engineering Macau University of Science and Technology Macau China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark USA International Institute of Next Generation Internet Macau University of Science and Technology Macau China Institute of Computing Technology Chinese Academy of Sciences Beijing China

Conventional wireless networks are half-duplex and most of them use contention-based protocols. These protocols usually adopt a principle of contention with collision avoidance and infer a collision occurrence very late from the absence of an acknowledgement after data transmission, thus causing low network performance. Wireless full-duplex enables simultaneous transmission (TX) and reception (RX) on the same channel. By exploiting this functionality, this work proposes a novel design that enables contention with collision detection (CCD) to improve the network performance. With this design, in contention, a node exploits its TX antenna to transmit a signal for channel contention, while exploiting its RX antenna to sense if other nodes are transmitting too. By checking the status of TX and RX antennas, the node can detect the contention collision before data transmission and hence obtains an opportunity to avoid data collision effectively. This work then develops a theoretical model to analyze the collision probability of this design. Extensive simulation results verify the effectiveness of our proposed design in improving wireless network performance.

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