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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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A Millimeter-Wave Scattering Channel Model for Indoor Human Activity Sensing

IEEE Open Journal of Antennas and Propagation

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IEEE Open Journal of Antennas and Propagation 2024年

作者： Liu, Mingqing Cui, Zhuangzhuang Miao, Yang Kim, Minseok Pollin, Sofie University of Cambridge Department of Engineering CambridgeCB3 0FA United Kingdom KU Leuven Department of Electrical Engineering Leuven3001 Belgium University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede7522 NB Netherlands Niigata University Graduate School of Engineering Japan

In sixth-generation (6G) application scenarios like industry 5.0, augmented reality (AR), autonomous transportation, and eHealth, there is a growing demand for Human Activity Recognition (HAR). Meanwhile, with the deployment of millimeter-wave (mmWave) technologies in fifth-generation (5G) cellular communications, higher-resolution sensing becomes feasible. Utilizing mmWave for communication and HAR has garnered attention, necessitating accurate modeling of sensing channels. This paper proposes a mmWave scattering channel model for indoor HAR, which facilitates system design, optimization, and implementation. In the proposed model, we integrate primitive-based human body scattering where the human body is indicated by a set of primitives, and cluster-based environment scattering models, enabling detailed modeling of self-shadowing and double-bounce environment scattering. Additionally, we develop a simulation framework encompassing signal transmission, sensing channels, and processing, allowing adjustment of system parameters. Simulation results indicated by micro-Doppler signatures including multi-link effects show good agreements with measurements, validating the effectiveness of the proposed model. Meanwhile, the time consumption of the proposed simulation workflow for generating micro-Doppler signatures for most human activities is within 10 minutes. © 2020 IEEE.

关键词： 5G mobile communication systems

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Micro-Expression Recognition Based On 3DCNN Combined With GRU and New Attention Mechanism

Micro-Expression Recognition Based On 3DCNN Combined With GR...

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IEEE International Conference on Image Processing

作者： Chun-Ting Fang Tsung-Jung Liu Kuan-Hsien Liu Department of Electrical Engineering and Graduate Institute of Communication Engineering National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Micro-expressions, as a form of non-verbal emotional expressions, play a key role in interpersonal interaction. However, they are also quite challenging and not easy to analyze. In this paper, we propose a dual-branch shallow 3DCNN architecture that combines Gated Recurrent Unit (GRU) and enhances the Channel Attention Module (CAM) in Convolutional Block Attention Module (CBAM) to make it more suitable for recognizing micro facial expressions. Experiments show that the proposed method can achieve good results with a relatively simple architecture. The source code and pre-trained models are available at https://***/dannyFan-0201/ICIP_2024.

关键词： Convolutional codes Gold Attention mechanisms Image recognition Source coding Face recognition Logic gates

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Medium-Term Load Forecasting Model Using Radial Basis Function Algorithm

Medium-Term Load Forecasting Model Using Radial Basis Functi...

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computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Astrid Pamela Suriadi Suriadi Tarmizi Tarmizi Graduate School of Electrical Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

This study developed two medium-term electricity load forecasting models for Banda Aceh city using Radial Basis Function method and Artificial Neural Network. There are three load groups used to create the model, including social, household and industrial load groups. The dataset used consists of 4 (four) input variables and one target. This research developed 3 training functions that were applied to both models to obtain the best forecast model. The training functions include Lavenberg-Marquardt, Gradient Descent and Adaptive Learning Rate, and Gradient Descent with momentum and adaptive learning rate. Based on the simulation and its MAPE value, the radial basis function algorithm is highly suitable for implementing mid-term electricity load forecasting modeling.

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Effect of Cotton Dust Morphology on Photovoltaic Module Performance

Effect of Cotton Dust Morphology on Photovoltaic Module Perf...

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Emerging Trends in Smart Technologies (ICETST), 2020 International Conference on

作者： Basit Ali M. Faisal Khan Kashif Ishaque Graduate School of Engineering Sciences & Information Technology Faculty of Engineering Sciences & Technology Hamdard University Karachi Pakistan Department of Electrical Engineering Bahria University Karachi Pakistan Department of Electrical Engineering Faculty of Engineering Sciences & Technology Hamdard University Karachi Pakistan Department of Electrical and Computer Engineering Muhammad Ali Jinnah University Karachi Pakistan

ISBN: (数字)9798331515850

ISBN: (纸本)9798331515867

The use of renewable energy is increasing due to the high cost of conventional fuels and climate issues. Textile industries, specifically in Asian region, are shifting towards large PV plants in order to acquire cheap and clean energy. However, cotton dust presence in the textile mill environment causes performance issues for PV modules. This study examines the cotton dust particle effect on PV module by employing an experimental methodology. An indoor experimental setup is utilized to test the PV modules in two schemes, that are clean and dusty. The experiment is conducted for eight days with an hourly interval. It is observed that PV power output reduces significantly up to 15% in eight days as compared to clean PV module. The deposited cotton dust particles are also physically examined through compound microscope in order to determine its physical nature. It is being observed that cotton particles are composed of long, smooth fibers with irregular shapes. The particles are highly influenced by humidity, and their own high content of cellulose makes them vulnerable to stick on the PV surface and forming clumps and aggleromates that develop the hotspots on the PV surface. Along with that, as time progresses the cotton dust opaqueness also increases, ultimately reducing the transmittance and decreasing PV module performance. This study helps to devise a unique cleaning patterns and methods for textile units to enhance performance output.

关键词： Surface cleaning Shape Microscopy Surface morphology Morphology Moisture Humidity Cotton Solar panels Textile industry

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An Optimal Framework for SDN Based on Deep Neural Network

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computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Subwavelength on-chip light focusing with bigradient all-dielectric metamaterials for dense photonic integration

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InfoMat 2022年第2期4卷 139-151页

作者： Zhihao Ren Bowei Dong Qifeng Qiao Xinmiao Liu Jinyuan Liu Guangya Zhou Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingaporeSingapore NUS Suzhou Research Institute(NUSRI) SuzhouChina Department of Mechanical Engineering National University of SingaporeSingaporeSingapore NUS Graduate School-Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingaporeSingapore

Photonic integrated circuits(PICs)provide a promising platform for miniaturized on-chip optical systems for communication,computation,and sensing *** dense integration of photonic components is one of the keys to exploit the advantages of *** light focusing is a fundamental and indispensable function in PICs,focusing light at the micro/nanometer-scale is ***,a bigradient on-chip metalens(BOML)is proposed to achieve ultrasmall focal lengths and spot sizes at the subwavelength scale for dense *** design of BOML combines gradient geometry and gradient refractive index into one metalens by simultaneously engineering the length and width of subwavelength silicon *** a small device footprint of only 168μm,the BOML achieves efficient on-chip focusing with the recordbreaking figure-of-merits,which are the ratio of wavelength to focal length/spot size(0.268 and 2.83)and numerical aperture(1.78).Leveraging on the Fresnel design,the footprint of BOML is further reduced by 55.1%,and the numerical aperture is enhanced to *** demonstration of mode conversion and beam steering with efficiency over 80%and a tilting range of 7.2°holds the potential for highly dense on-chip photonic systems for optical communication,optical sensing,nonlinear optics,and neural networks for deep learning.

关键词： all-dielectric metamaterials beam steering mid-infrared on-chip focusing photonic integrated circuits

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Wideband Beamforming for Frequency Selective RRS Aided Near-Field Communications

Wideband Beamforming for Frequency Selective RRS Aided Near-...

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IEEE Conference on Wireless Communications and Networking

作者： Zicheng Lin Shuhao Zeng Hongliang Zhang School of Electronic Engineering and Computer Science Peking University Beijing China Department of Electrical and Computer Engineering Princeton University NJ USA School of Electronic and Computer Engineering Peking University Shenzhen Graduate School China School of Electronics Peking University Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

To satisfy the high data rate requirements, cellular systems will evolve towards the direction of higher carrier frequencies and larger antenna arrays. The conventional phased arrays are hard to fulfill such a vision due to its excessive power consumption induced by numerous phase shifters. To address this issue, Reconfigurable Refractive Surfaces (RRSs) provide a energy efficient solution without relying on phase shifters. With enlarged radiation aperture and increased working frequency, users are more likely to be located in the near field of the RRS. Moreover, the frequency selectivity of the RRS cannot be neglected given the wideband communications enabled by higher frequency bands. These two effects jointly aggravate the beam split problem where the signal strength of different frequency components cannot concentrate on the user, leading to a data rate degradation. In this paper, we study an RRS-based wideband near-field communication system with multiple users. Unlike most existing works, which only considered the beam split effect under near-field conditions, we jointly consider the influence of the frequency selectivity of RRS and near-field conditions on the beam split effect. To mitigate the beam split effect, the time-delay units are introduced in the RRS elements based on which a beamforming scheme is proposed to improve system data rate by jointly optimizing the digital beamformer, the phase shifts of RRS and the time-delay units. Simulation results demonstrate the effectiveness of our proposed scheme.

关键词： Phased arrays Power demand Array signal processing Simulation Phase shifters Transmitting antennas Energy efficiency Feeds Arrays Wideband

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Curriculum-Based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios

Curriculum-Based Reinforcement Learning for an Effective Mul...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Iure Rosa L. De Oliveira Kevin B. De Carvalho Alexandre S. Brandão Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Vicosa Viçosa Brazil

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training.

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Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

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