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Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

Computers, Materials & Continua 2024年第7期80卷 1163-1177页

作者： Amel Ali Alhussan Doaa Sami Khafaga El-Sayed M.El-kenawy Marwa M.Eid Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： Electric vehicle graylag goose optimization metaheuristics optimization machine learning

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Multi-Stage Contrastive Causal Learning Framework for Rolling Bearing Fault Diagnosis Under Different Working Conditions 5

Multi-Stage Contrastive Causal Learning Framework for Rollin...

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Chen, Guanhua Ding, Xu Wu, Hao Zhai, Hua Xu, Juan School of Computer Science and Information Engineering Hefei University of Technology Hefei China Hefei University of Technology Key Lab of Aerospace Structural Parts Forming Technology and Equipment Hefei China School of Mechanical Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9798331529192

Deep learning methods have shown remarkable performance in intelligent fault diagnosis. However, traditional models often rely heavily on large amounts of labeled data and exhibit limited generalization capabilities across different operating conditions. To address this issue, this paper revisits the latent representations of fault data from a causal perspective and proposes a structural causal model to guide the decoupling of time-domain and frequency-domain representations in deep learning models. Based on this, a multi-stage contrastive causal learning diagnosis framework is constructed. This framework leverages self-supervised time-frequency domain contrastive learning and supervised multi-domain contrastive learning to explore general causal representations, thereby effectively decoupling the features of fault data. Finally, by fine-tuning the model and training the classification head, the fault classification task is accomplished. Experimental results demonstrate that the proposed method achieves outstanding diagnostic performance on multiple fault-bearing datasets, showcasing its potential for widespread application in complex industrial scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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A 28-nm 10.4-fJ/b Cryogenic embedded DRAM with 3T1C Gain Cell and MBIST at 4-Kelvin 21

A 28-nm 10.4-fJ/b Cryogenic embedded DRAM with 3T1C Gain Cel...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Zheng, Jiapei Nie, Xinkai Zhi, Zhenghang Tang, Zhidong Liu, Qi Kou, Xufeng Chen, Chixiao Fudan University State Key Lab of Integrated Chips and Systems Frontier Institute of Chip and System Shanghai China ShanghaiTech University School of Information Science and Technology Shanghai China

ISBN: (纸本)9798350377088

Quantum error correction is essential for achieving large-scale quantum computing. Large-scale quantum state detection requires low-power embedded memory that can operate at 4K. Embedded Dynamic Random Access Memory is a strong candidate for cryogenic memory, offering high density and low power consumption. In this paper, we propose a cryogenic eDRAM using a 28nm CMOS process, which utilizes a 3T1C gain cell structure. Considering the short lifespan of the readout data, the refresh function of eDRAM is eliminated. Additionally, it integrates Memory Built-In Self-Test circuits for various testing purposes. We measured the performance of the eDRAM at 4K and achieved a read power of 4.9fJ/b and a write power of 15.9fJ/b. The median retention time reached 4.8ms, and the bandwidth reached 61.4Gb/s. © 2024 IEEE.

关键词： Quantum computers

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Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

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Computers, Materials & Continua 2023年第4期75卷 183-196页

作者： Samah Alshathri Ezz El-Din Hemdan Walid El-Shafai Amged Sayed Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Energy Engineering College of Engineering&TechnologyArab Academy for Science Technology&Maritime TransportSmart Village CampusEgypt

In recent years, Digital Twin (DT) has gained significant interestfrom academia and industry due to the advanced in information technology,communication systems, Artificial Intelligence (AI), Cloud Computing (CC),and Industrial Internet of Things (IIoT). The main concept of the DT isto provide a comprehensive tangible, and operational explanation of anyelement, asset, or system. However, it is an extremely dynamic taxonomydeveloping in complexity during the life cycle that produces a massive amountof engendered data and information. Likewise, with the development of AI,digital twins can be redefined and could be a crucial approach to aid theInternet of Things (IoT)-based DT applications for transferring the data andvalue onto the Internet with better decision-making. Therefore, this paperintroduces an efficient DT-based fault diagnosis model based on machinelearning (ML) tools. In this framework, the DT model of the machine isconstructed by creating the simulation model. In the proposed framework,the Genetic algorithm (GA) is used for the optimization task to improvethe classification accuracy. Furthermore, we evaluate the proposed faultdiagnosis framework using performance metrics such as precision, accuracy,F-measure, and recall. The proposed framework is comprehensively examinedusing the triplex pump fault diagnosis. The experimental results demonstratedthat the hybrid GA-ML method gives outstanding results compared to MLmethods like LogisticRegression (LR), Na飗e Bayes (NB), and SupportVectorMachine (SVM). The suggested framework achieves the highest accuracyof 95% for the employed hybrid GA-SVM. The proposed framework willeffectively help industrial operators make an appropriate decision concerningthe fault analysis for IIoT applications in the context of Industry 4.0.

关键词： Automated fault diagnosis control system ML AI CC IIoT digital twins genetic algorithm GA-ML technique

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Improved Detection and Interpretation of Multilingual Signboards in Natural Scene for Visually Impaired People

Improved Detection and Interpretation of Multilingual Signbo...

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2023 IEEE International Conference on Data and Software engineering, ICoDSE 2023

作者： Zaman, Qamar Khusro, Shah Tjoa, A Min University of Peshawar Department of Computer Science Peshawar25120 Pakistan Institute of Information Systems Engineering Vienna University of Technology Vienna1040 Austria

ISBN: (纸本)9798350381382

Visually impaired individuals face numerous challenges in localization, navigation, reading content, and communicating with others. Unlike sighted individuals who rely on vision in the physical environment to reach their destinations, visually impaired individuals require assistive technologies and smartphone-based applications that employ computer vision to overcome the issues of obstacle detection, read signboards, and navigate in natural scenes. Signboards with text information serve as crucial indicators for navigation and recognition in daily life. However, detecting and interpreting signboard text in natural scenes poses difficulties for visually impaired individuals. Researchers have made efforts to address issues such as text detection on signboards, reducing blurriness, removing backgrounds, improving lighting conditions, and enhancing accuracy and response time of recognition. The primary challenges lie in the detection and interpretation of multilingual and diverse content on signboards in real-time. The proposed system presents a methodology for real-time detection and interpretation of diverse content on signboards, including text in English and Urdu along with phone numbers, for visually impaired individuals. An Android-based application is developed to improve text detection and recognition methods for multilingual texts, providing vital navigation information to visually impaired individuals in real-time. The methodology and application are evaluated, and the results demonstrate promising outcomes. copy;2023 IEEE. © 2023 IEEE.

关键词： Navigation

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Telecom-band multiwavelength vertical emitting quantum well nanowire laser arrays

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Light(science & Applications) 2024年第10期13卷 2405-2413页

作者： Xutao Zhang Fanlu Zhang Ruixuan Yi Naiyin Wang Zhicheng Su Mingwen Zhang Bijun Zhao Ziyuan Li Jiangtao Qu Julie MCairney Yuerui Lu Jianlin Zhao Xuetao Gan Hark Hoe Tan Chennupati Jagadish Lan Fu Frontiers Science Center for Flexible Electronics Xi’an Institute of Flexible Electronics(IFE)and Xi’an Institute of Biomedical Materials&EngineeringNorthwestern Polytechnical University127 West Youyi Road710072 Xi’anChina Department of Electronic Materials Engineering Research School of PhysicsThe Australian National UniversityCanberra ACT 2600Australia Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical University710129 Xi’anChina Australian Centre for Microscopy and Microanalysis the University of SydneySydney NSW 2006Australia School of Engineering College of EngineeringThe Australian National UniversityCanberra ACT 2600Australia ARC Centre of Excellence for Transformative Meta-Optical Systems Research School of PhysicsThe Australian National UniversityCanberra ACT 2600Australia

Highly integrated optoelectronic and photonic systems underpin the development of next-generation advanced optical and quantum communication technologies,which require compact,multiwavelength laser sources at the telecom ***,we report on-substrate vertical emitting lasing from ordered InGaAs/InP multi-quantum well core–shell nanowire array epitaxially grown on InP substrate by selective area *** reduce optical loss and tailor the cavity mode,a new nanowire facet engineering approach has been developed to achieve controlled quantum well nanowire dimensions with uniform morphology and high crystal *** to the strong quantum confinement effect of InGaAs quantum wells and the successful formation of a vertical Fabry–Pérot cavity between the top nanowire facet and bottom nanowire/SiO_(2) mask interface,stimulated emissions of the EH11a/b mode from single vertical nanowires from an on-substrate nanowire array have been demonstrated with a lasing threshold of~28.2μJ cm^(−2) per pulse and a high characteristic temperature of~128 *** fine-tuning the In composition of the quantum wells,room temperature,single-mode lasing is achieved in the vertical direction across a broad near-infrared spectral range,spanning from 940 nm to the telecommunication O and C *** research indicates that through a carefully designed facet engineering strategy,highly ordered,uniform nanowire arrays with precise dimension control can be achieved to simultaneously deliver thousands of nanolasers with multiple wavelengths on the same substrate,paving a promising and scalable pathway towards future advanced optoelectronic and photonic systems.

关键词： arrays tuning quantum

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Average Performance Analysis of Multi-Class Classification Based on Error-Correcting Output Codes

Average Performance Analysis of Multi-Class Classification B...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Kobayashi, Manabu Kumoi, Gendo Yagi, Hideki Hirasawa, Shigeichi Center for Data Science Waseda University Tokyo Japan Nagaoka University of Technology Department of Information and Management Systems Engineering Niigata Japan University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9781665410205

In machine learning, one of the methods to solve multiclass classification problems is a framework called Error-Correcting Output Codes (ECOC), which constructs a multiclass classifier by combining a lot of binary classifiers. ECOC assigns binary codewords to each category, and the multiclass classification performance varies depending on the code. In this study, we treat each element of the codeword as a random variable and evaluate the average performance of ECOC. As a result, for M class classification if the number of binary classifiers is O(M), then the average error probability of various codes approaches that of MAP estimation. We show that the important points are the ratio between the number of binary classifiers and M and the difference between the maximum posterior probability and the second highest posterior probability for the categories. © 2024 IEEE.

关键词： Coding errors

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Near-zero-dispersion soliton and broadband modulational instability Kerr microcombs in anomalous dispersion

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Light(science & Applications) 2023年第2期12卷 220-231页

作者： Zeyu Xiao Tieying Li Minglu Cai Hongyi Zhang Yi Huang Chao Li Baicheng Yao Kan Wu Jianping Chen State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronic Information and Electrical EngineeringDepartment of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Optical Fibre Sensing and Communications(Education Ministry of China) University of Electronic Science and Technology of ChinaChengdu 611731China

The developing advances of microresonator-based Ker cavity solitons have enabled versatile applications ranging from communication,signal processing to high-precision *** dispersion is the key factor determining the Kerr comb *** the zero group-velocity-dispersion(GVD)regime,low-noise and broadband microcomb sources are achievable,which is crucial to the application of the Kerr *** the GVD is almost vanished,higher-order dispersion can significantly affect the Kerr comb *** many studies have investigated the Kerr comb dynamics near the zero-dispersion regime in microresonator or fiber ring system,limited by dispersion profles and dispersion perturbations,the near-zero-dispersion soliton structure pumped in the anomalous dispersion side is still elusive so ***,we theoretically and experimentally investigate the microcomb dynamics in fiber-based Fabry-Perot microresonator with ultra-small anomalous *** obtain 2/3-octave-spaning microcombs with~10 GHz spacing,>84 THz span,and>8400 comb lines in the modulational instability(MI)state,without any external nonlinear spectral *** widely-spanned Ml combs are also able to enter the soliton ***,we report the first observation of anomalous-dispersion based near-zero-dispersion solitons,which exhibits a local repetition rate up to 8.6 THz,an individual pulse duration<100 fs,a span>32 THz and>3200 comb *** two distinct comb states have their own *** broadband MI combs possess high conversion efficiency and wide existing range,while the near-zero-dispersion soliton exhibits relatively low phase noise and ultra-high local repetition *** work complements the dynamics of Kerr cavity soliton near the zero-dispersion regime,and may stimulate cross-disciplinary inspirations ranging from dispersion-controlled microresonators to broadband coherent comb devices.

关键词： resonator dispersion pumped

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Study on a Visible Light Communication and Positioning System Utilizing an Optical Diffusion Filter and Rolling Shutter Sensor 13

Study on a Visible Light Communication and Positioning Syste...

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13th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2023

作者： Okawara, Reo Ebihara, Tadashi Wakatsuki, Naoto Zempo, Keiichi Mizutani, Koichi University of Tsukuba Graduate School of Science and Technology Ibaraki Tsukuba Japan University of Tsukuba Institute of Systems and Information Engineering Ibaraki Tsukuba Japan

ISBN: (纸本)9798350320114

The demand for indoor positioning technology is currently increasing in various industries. Although positioning methods using sensors and functions installed on smartphones have been proposed in previous studies, no definitive indoor positioning technology has yet been established. Therefore, this paper presents a positioning system that performs visible light communication using a rolling shutter sensor installed in smartphones and an optical diffusion filter that diffuses light in one direction. The system calculates the camera position from information obtained through communication and the LED position in the captured image. The performance of the positioning method using four LEDs was evaluated in both simulations and experiments. The obtained results suggest that the proposed positioning system achieved a positioning error of less than 100 mm. The proposed method can become a viable alternative to provide seamless transition from outdoor to indoor positioning using current technologies such as global navigation satellite systems. © 2023 IEEE.

关键词： Optical Diffusion Filter Positioning Rolling Shutter Effect Rolling Shutter Sensor Visible Light Communication

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An Efficacy Analysis of Data using Fuzzy Logic and Fractal Encryption Techniques for Cloud Platform Data Security

An Efficacy Analysis of Data using Fuzzy Logic and Fractal E...

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2024 International Conference on Knowledge engineering and Communication systems, ICKECS 2024

作者： Dineshkumar, P. Jeeva, V. Nithiesh, C. Arun, P.J. Kumar, K. Sathish K. S. Rangasamy College of Technology Department of Information Technology Tiruchengode637 215 India Sri Sai Ram Engineering College Computer Science and Business Systems Chennai600044 India

ISBN: (纸本)9798350359688

In the realm of cloud computing, safeguarding data confidentiality is paramount. This paper introduces a novel approach to data security in cloud platforms, merging fuzzy logic and fractal encryption techniques. Fuzzy logic accommodates uncertain data, enabling adaptable encryption strategies tailored to cloud dynamics. Fractal encryption harnesses self-similarity in fractals to create intricate encryption keys, fortifying data protection. Together, they propose a robust solution to mitigate unauthorized access, data breaches, and cyber threats. Through theoretical exploration and practical testing, the efficacy of this approach is demonstrated, highlighting its potential to address cloud security challenges. The scalability and versatility of these methods make them applicable across diverse cloud infrastructures, ensuring comprehensive data protection. This paper advocates for the adoption of fuzzy logic and fractal encryption as proactive measures to enhance cloud platform security, fostering trust among users and stakeholders. © 2024 IEEE.

关键词： Cloud platforms

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