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arXiv 2023年

作者： Tazehkand, Behzad Mozaffari Aghdam, Mohammad Reza Ghavidel Abdolee, Reza The Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran The Department of Electrical and Electronics Engineering Özyegin University Istanbul34794 Turkey The Department of Computer Science California State University Channel Islands CA United States

One of the main challenges with generalized frequency division multiplexing (GFDM) systems is prototype filter design. A poorly designed filter increases inherent and out-of-band (OOB) interferences. In this paper, we introduce a novel optimal prototype filter for GFDM systems that eliminates the negative effects of intrinsic interferences. We introduce a complex-valued pulse shape similar to a single-sideband (SSB) modulation scheme, which significantly improves bandwidth efficiency. Specifically, we introduce an optimization problem to design an optimal pulse shape filter to reduce all intrinsic interference to zero. We derive analytical expressions to evaluate the bit error rate (BER) of the system and show how the designed optimal prototype filter outperforms its current counterparts. © 2023, CC BY.

关键词： Bit error rate

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Probabilistic Constellation Shaping for OFDM-Based ISAC Signaling

Probabilistic Constellation Shaping for OFDM-Based ISAC Sign...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Du, Zhen Liu, Fan Xiong, Yifeng Han, Tony Xiao Yuan, Weijie Cui, Yuanhao Yao, Changhua Eldar, Yonina C. School of Electronic and Information Engineering Nanjing University of Information Science & Technology Nanjing China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China School of Information and Electronic Engineering Beijing University of Posts and Telecommunications Beijing China Huawei Technologies Ltd. Shenzhen China Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot Israel

ISBN: (纸本)9798350370218

Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simultaneous sensing and communications (S&C) operations. However, the sensing performance of an OFDM communication signal is substantially affected by the randomness of the data symbols mapped from bit streams. Therefore, achieving a balance between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, in this paper we analyze the ambiguity function of the OFDM communication signal modulated by random data. Subsequently, a probabilistic constellation shaping (PCS) method is proposed to devise the probability distributions of constellation points, which is able to strike a scalable S&C tradeoff of the random transmitted signal. Finally, the superiority of the proposed PCS method over conventional uniformly distributed constellations is validated through numerical simulations. © 2023 IEEE.

关键词： ambiguity function ISAC OFDM PCS

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Efficient handling of ACL policy change in SDN using reactive and proactive flow rule installation ( vol 14 , 14976 , 2024 )

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SCIENTIFIC REPORTS 2024年第1期14卷 1-19页

作者： Hussain, Mudassar Amin, Rashid Gantassi, Rahma Alshehri, Asma Hassan Frnda, Jaroslav Raza, Syed Mohsan Department of Computer Science and Creative Technologies Global College of Engineering and Technology CPO Ruwi 112 P.O Box 2546 Muscat Sultanate of Oman Department of Computer Science and IT University of Chakwal Chakwal 48800 Pakistan Department of Computer Science University of Engineering and Technology Taxila 47050 Pakistan Department of Electrical Engineering Chonnam National University Gwangju 61186 South Korea Department of Computer Science College of Computer Engineering and Science Prince Sattam Bin Abdulaziz University Alkharj 16273 Saudi Arabia Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and Communications University of Zilina 01026 Zilina Slovakia Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava 70800 Ostrava Czech Republic SAMOVAR Telecom SudParis Institut Polytechnique de Paris 91120 Paris France

Software-defined networking (SDN) is a pioneering network paradigm that strategically decouples the control plane from the data and management planes, thereby streamlining network administration. SDN's centralized network management makes configuring access control list (ACL) policies easier, which is important as these policies frequently change due to network application needs and topology modifications. Consequently, this action may trigger modifications at the SDN controller. In response, the controller performs computational tasks to generate updated flow rules in accordance with modified ACL policies and installs flow rules at the data plane. Existing research has investigated reactive flow rules installation that changes in ACL policies result in packet violations and network inefficiencies. Network management becomes difficult due to deleting inconsistent flow rules and computing new flow rules per modified ACL policies. The proposed solution efficiently handles ACL policy change phenomena by automatically detecting ACL policy change and accordingly detecting and deleting inconsistent flow rules along with the caching at the controller and adding new flow rules at the data plane. A comprehensive analysis of both proactive and reactive mechanisms in SDN is carried out to achieve this. To facilitate the evaluation of these mechanisms, the ACL policies are modeled using a 5-tuple structure comprising Source, Destination, Protocol, Ports, and Action. The resulting policies are then translated into a policy implementation file and transmitted to the controller. Subsequently, the controller utilizes the network topology and the ACL policies to calculate the necessary flow rules and caches these flow rules in hash table in addition to installing them at the switches. The proposed solution is simulated in Mininet Emulator using a set of ACL policies, hosts, and switches. The results are presented by varying the ACL policy at different time instances, inter-packet de

关键词： ACL policy change Management Proactive flow rule installation Reactive flow rule installation SDN Security

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Efficient CNN-Based Automatic Modulation Classification in UWA Communication Systems Using Constellation Diagrams and Gabor Filtering

Efficient CNN-Based Automatic Modulation Classification in U...

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Electronic engineering (ICEEM), International Conference on

作者： Mohamed A. Abdel-Moneim S. El-Rabaie Fathi E. Abd El-Samie Khaled Ramadan Nariman Abdel-Salam Khalil F. Ramadan Department of Telecommunication Faculty of Engineering Egyptian Russian University Cairo Egypt Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf Egypt Communication and Computer Engineering Department The Higher Institute of Engineering at Al-Shorouk City Cairo Egypt Communications and Electronics Engineering Department Faculty of Engineering Canadian International College (CIC) Giza Egypt

Underwater Acoustic (UWA) communication channels are varying in nature due to various underwater conditions. The efficiency of the UWA communication system can be increased by changing transmission parameters over UWA channels based on the state of the channel. The aim of Automatic Modulation Classification (AMC) is to recognize efficiently the modulation schemes from signals received over UWA channels. In this paper, we propose an efficient method that combines equalization, Gabor filtering of constellation diagrams, thresholding and deep convolutional neural networks (CNNs) for modulation classification over the Signal-to-Noise Ratio (SNR) range of -10 to 30 dB in UWA systems. Simulation results of the proposed method indicated an acceptable performance over a wide SNR range.

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Robust Adaptive Feedback Linearization Control Using Online Neural-Network Estimators for Uncertain Linear Induction Motor Drive System 13

Robust Adaptive Feedback Linearization Control Using Online ...

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13th International Symposium on Linear Drives for Industry Applications, LDIA 2021

作者： El-Sousy, Fayez F.M. Elmorshedy, Mahmoud F. Amin, Mahmoud M. Mohammed, Osama A. Electrical Engineering Department Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia Department of Electrical Power and Machines Engineering Faculty of Engineering Tanta University Tanta Egypt Electrical and Computer Engineering Department Manhattan College Manhattan RiverdaleNY10471 United States Electrical and Computer Engineering Department Florida International University MiamiFL33174 United States

ISBN: (纸本)9781728172101

This paper proposes a robust adaptive feedback linearization control (RAFLC) using Takagi-Sugeno-Kang (TSK)-type recurrent Petri fuzzy-neural-network (T-RPFNN) to obtain better dynamic and steady-state performance for the linear induction motor (LIM) drive system. The proposed control method includes a feedback linearization controller (FLC), a T-RPFNN estimators and an adaptive PI controller. In the RAFLC design, the FLC is used to stabilize the LIM drive system and the T-RPFNN estimators are utilized to approximate the nonlinear functions of the LIM and the gains of the adaptive controller. Besides, the adaptive PI controller is used to keep the control magnitude bounded and to reduce the chattering in the control inputs. Moreover, the Lyapunov stability analysis are used to drive the online adaptive control laws, hence the stability of the RAFLC scheme can be guaranteed. The dynamic behavior of LIM drive system using the proposed RAFLC not only assures the closed-loop stability, but also guarantees the robust performance for the overall system. An experimental setup is built to check the validity of the proposed RAFLC scheme. The experimental results endorse the proposed RAFLC robustness even at uncertain dynamics existence and external disturbances. © 2021 IEEE

关键词： Feedback linearization

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Development of a Smart IOT Enabled Arduino Glove Supporting Sign Language Communication

Development of a Smart IOT Enabled Arduino Glove Supporting ...

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International Conference on computer and Information Technology (ICCIT)

作者： Muhammad Shahriar Zaman Richard Victor Biswas Department of Computer Science and Engineering Faculty of Science and Technology American International University-Bangladesh (AIUB) Dhaka Bangladesh Department of Electrical and Electronic Engineering Faculty of Engineering American International University-Bangladesh (AIUB) Dhaka Bangladesh

Deafness is an unfortunate issue of our society impairing many people. Around 3 million people in Bangladesh suffer from partial or complete deafness. One key challenge for these individuals is communicating with regular people. Various sign languages are available but very few people are knowledgeable about it. Keeping this issue in consideration this project has been developed. The smart Arduino glove allows the user to express their ideas by translating their fingerspelling as well as the gestures into comprehensible messages. The system also allows identification of common sentences by identifying simple gestures. The suggested system if applied in daily life can bring a positive change in the lives of deaf-mute individuals.

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Deep Learning Algorithms for EEG-Based Driver Drowsiness Detection: A Comparative Investigation

Deep Learning Algorithms for EEG-Based Driver Drowsiness Det...

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Information Technology International Seminar (ITIS)

作者： Md Mahmudul Hasan Mirza Mahfuj Hossain Norizam Sulaiman Md Nahidul Islam Sayma Khandaker Faculty of Electrical and Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Malaysia Department of Computer Science and Engineering Jashore University of Science and Technology Jashore Bangladesh

ISBN: (数字)9798331521295

ISBN: (纸本)9798331521301

Due to the significant variability in electroencephalogram (EEG) signals across individuals and recording sessions, developing a calibration-free system for detecting driver drowsiness presents a considerable challenge. While numerous deep learning techniques have been employed to analyze EEG signals for this purpose, most existing studies rely on deep learning models with limited success in accurately detecting drowsiness. In this research, we explored the application of five deep learning algorithms such as Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM), to improve the detection of driver drowsiness. Our applied models achieve detection accuracies of 73.46% for ANN, 80.09% for CNN, 65.74% for RNN, 83.95% for GRU, and 77.62% for LSTM across 11 subjects, outperforming conventional baseline approaches and state-of-the-art deep learning methods. Notably, the GRU model demonstrated superior accuracy in recognizing drowsiness from EEG signals compared to other applied models.

关键词： Deep learning Seminars Recurrent neural networks Accuracy Logic gates Brain modeling Electroencephalography Recording Convolutional neural networks Long short term memory

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Strategic Renewable Integration for Resilient Power Systems: Insights from Kefallonia Island

Strategic Renewable Integration for Resilient Power Systems:...

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International Conference on High Voltage engineering and Application, ICHVE

作者： E.G. Goulioti E.M. Voumvoulakis V.T. Kontargyri C.A. Christodoulou N.P. Papanikolaou School of Electrical and Computer Engineering High Voltage and Electrical Measurement Laboratory National Technical University of Athens 9 Iroon Polytechniou Str. Zografou Campus Athens Greece Hellenic Electricity Distribution Operator S.A. 20 Perraivou & 5 Kallirrois Str. Athens Greece Department of Electrical and Electronics Engineering Faculty of Engineering University of West Attica Athens Greece Department of Electrical and Computer Engineering Electrical Machines Laboratory Democritus University of Thrace Xanthi Greece

ISBN: (数字)9798350374988

ISBN: (纸本)9798350374995

The current evolution of power systems from a unidirectional to a multi-directional power flow system, in which Distributed Energy Resources (DERs) are increasing, directly impacts the way they are being operated to ensure the security and quality of electrical supply and the resilient performance of the electrical grid as a whole. Additionally, the functional capability of the active distribution network is continually challenged by extreme weather conditions and unforeseen events. As such, the imperative for developing and implementing advanced resilience strategies within distribution networks has never been more critical, ensuring they are not only robust but also agile in the face of increasingly unpredictable challenges. In the wake of extreme events, fast recovery and system stability of the network are investigated. Optimal utilization of available resources is the key to system resilience. Studying the performance of the power network of Kefallonia island in two case studies (single-fault and multiple-fault), the results prove that among the available resources that are required for the resilience and the minimization of the catastrophic consequences due to extreme events, microgrids should be incorporated as a building block for the future grid.

关键词： Renewable energy sources Microgrids Power system stability Minimization Stability analysis Planning Security

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Analysis and development of smart production and distribution line system in smart grid based on optimization techniques involving digital twin

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Measurement: Sensors 2024年 34卷

作者： Arumugam, Thangaraja Kamble, Nitin Kundlik Guntreddi, Venkataramana Vishnu Sakravarthy, N. Shanthi, S. Ponnusamy, Sivakumar Business School Vellore Institute of Technology Tamilnadu Chennai India Department of Robotics and Automation Engineering D Y Patil College of Engineering Akurdi Maharashtra Pune411044 India Department of Electrical Telecommunication and Computer Engineering School of Engineering and Applied Sciences Kampala International University Isakha Uganda Department of Mechanical Engineering Sri Eshwar College of Engineering Tamilnadu Coimbatore India School of Computer Science & Engineering Presidency University Karnataka Bengaluru560064 India Department of Computer Science and Engineering K.S.R. College of Engineering Tiruchengode TamilNadu Namakkal India

The term Digital Twin (DT) is defined as the virtual demonstration of an object that is represented through real-time datasets. DT is done through artificial intelligence to enhance decision-making techniques. DT includes the process of simulation, amalgamation, observation, analysis, and conservation. The DT is simply the exact reproduction of the physical structures. DT is used in the identification and evaluation of problems through real-time analysis. It is important to have prior analysis and evaluation of the object before existing in the real world. These digital twins help in the manufacturing and implementation of the production line system. DT includes the production line with the station division and the hours needed for the operating conditions for the assembly process. The systems are integrated to reduce the overall cost parameter. The physical simulation model is employed to obtain higher performance with reduced cost. An artificial neural network with a genetic algorithm is used for the optimization process to achieve a production line system using digital twins. © 2024 The Authors

关键词： Genetic algorithms

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Fault-tolerant controller design with connectivity maintenance in fractional-order multi-agent systems using a super-twisting sliding mode algorithm

Franklin Open

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Franklin Open 2024年 8卷

作者： Aazam Manesh, Farshid Pourgholi, Mahdi Amini Boroujeni, Elham Technical and Vocational School Technical and Vocational University Ilam Iran Faculty of Electrical Engineering Shahid Beheshti University Tehran P.O. Box *** Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran

This article explores fault analysis in distributed fractional multi-agent systems, specifically addressing fault detection in nonlinear fractional-order multi-agent systems by introducing a sliding surface. To achieve fault detection, we employ a super-twisting sliding mode observer designed for accurate fault estimation within individual agents. Building on this, we present a new fractional-order sliding surface accompanied by a potential function, strategically designed to ensure connectivity maintenance. Drawing on the estimated fault and the fractional-order sliding surface, we propose a fault-tolerant controller. This controller operates within a finite time frame, simultaneously guaranteeing fault tolerance and connectivity maintenance. To demonstrate the effectiveness of our approach, we conduct simulations on three numerical examples. These examples represent heterogeneous systems with both directed and undirected graph topologies, showcasing the versatility and applicability of our proposed methodology. © 2024 The Author(s)

关键词： Connectivity maintenance Distributed consensus Fault estimation and detection Fault-tolerant control Fractional order system Multi-agent system Super-twisting sliding mode

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