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Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Amir Hossein Khanmohammadi Salar Sadeghian Mohsen Hamzeh Adib Abrishamifar School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Electrical Engineering Iran University of Science and Technology Tehran Iran

ISBN: (数字)9798331533946

ISBN: (纸本)9798331533953

The boundary conduction mode (BCM) flyback power factor correction (PFC) converter is well-suited for low to medium power-level applications. It isolates input and output voltages while improving the power factor (PF) by modifying the transformer turns ratio. However, the converter switching frequency varies throughout the line cycle, and the frequency range depends on the input voltage and load conditions. Consequently, the electromagnetic interference (EMI) spectra show significant variations, making the EMI filter design more challenging. This paper presents a constant on-time (COT) control strategy that employs a variable inductor (VI) to limit the range of switching frequency fluctuations across the universal input voltage range ($85-264 \mathrm{~V}_{\mathrm{rms}}$).

关键词： Reactive power Switching frequency Electromagnetic interference Power factor correction Control systems Transformers Power electronics Steady-state Voltage control Inductors

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Examining the Effects of Applying AI to Enhance Big Data Retrieval Efficiency

Examining the Effects of Applying AI to Enhance Big Data Ret...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Sharma, Nakul S. Yadav, Dhananjay Shrivastava, Manish Mandal, Sanjeev Kumar Ravivarman, G. Jana, D Little Femilin Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Karnataka Bangalore India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai India

ISBN: (纸本)9798350329773

This studies paper explores how synthetic Intelligence (AI) technologies may be used to improve the efficiency of information retrieval from huge databases, as applied in a diffusion of industries. The paper will discuss the concept of AI as a tool to reduce information complexity, at the same time as inspecting current studies projects inside the subject and unique programs for the enterprise and patron worlds. It'll then discover the demanding situations that get up from applying AI and massive records technology, and description a suggested framework for first-rate practices. The paper will recall how AI may be utilized to enhance information seek outcomes in real-time, and provide an explanation for the diverse ways wherein this might be carried out. Subsequently, the paper will discuss the capability implications of the usage of AI for large statistics Retrieval efficiency, as well as its destiny applications. © 2023 IEEE.

关键词： Computational complexity

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An intelligent ranking model for multi-criteria decision making using fuzzy matrix method

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Recent Advances in computer science and Communications 2021年第5期14卷 1448-1460页

作者： Dahiya, Naveen Sangwan, Pardeep Department of Computer Science & Engineering Maharaja Surajmal Institute of Technology New Delhi India Department of Electrical & Computer Engineering Maharaja Surajmal Institute of Technology New Delhi India

Background: In daily life, one may encounter several problems whose solution is based on the consideration of several criteria altogether. To generate a solution for such problems is, in fact, a complex task. If one generates a solution, then there is no guarantee that the solution is optimal. It is really challenging to take into account all the criteria at the same time and generate a solution that is optimal. Several techniques have been proposed to solve multi-criteria deci-sion-making problems. Methods: In this paper, we propose an intelligent solution to multi-criteria decision-making problems by means of fuzzy aggregation using the matrix method. The proposed method finds application in solving such problems where the criteria are defined in the qualitative form (fuzzy linguistic variables) rather than in quantitative form (crisp). A novel application of the proposed approach to rank the employees in an organization is presented in the paper. Results: The proposed method is empirically validated by applying it to find the best employee in an institute of repute. Data collection is done in real-time to prove the utilization of the proposed approach in an efficient manner. Conclusion: The results obtained after the application of the proposed method to rank the employees are realistic as it takes into consideration the ambiguity involved in the human thought process. © 2021 Bentham science Publishers.

关键词： Personnel

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Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality

arXiv

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arXiv 2024年

作者： Liu, Jie Shang, Xuequn Han, Xiaolin Zheng, Kai Yin, Hongzhi School of Computer Science Northwestern Polytechnical University Xi'An China School of Electrical Engineering & Computer Science University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering & Computer Science The University of Queensland Brisbane Australia

Anomaly detection in dynamic graphs presents a significant challenge due to the temporal evolution of graph structures and attributes. The conventional approaches that tackle this problem typically employ an unsupervised learning framework, capturing normality patterns with exclusive normal data during training and identifying deviations as anomalies during testing. However, these methods face critical drawbacks: they either only depend on proxy tasks for representation without directly pinpointing normal patterns, or they neglect to differentiate between spatial and temporal normality patterns. More recent methods that use contrastive learning with negative sampling also face high computational costs, limiting their scalability to large graphs. To address these challenges, we introduce a novel Spatial-Temporal memories-enhanced graph autoencoder (STRIPE). Initially, STRIPE employs Graph Neural Networks (GNNs) and gated temporal convolution layers to extract spatial and temporal features. Then STRIPE incorporates separate spatial and temporal memory networks to capture and store prototypes of normal patterns, respectively. These stored patterns are retrieved and integrated with encoded graph embeddings through a mutual attention mechanism. Finally, the integrated features are fed into the decoder to reconstruct the graph streams which serve as the proxy task for anomaly detection. This comprehensive approach not only minimizes reconstruction errors but also emphasizes the compactness and distinctiveness of the embeddings w.r.t. the nearest memory prototypes. Extensive experiments on six benchmark datasets demonstrate the effectiveness and efficiency of STRIPE, where STRIPE significantly outperforms existing methods with 5.8% improvement in AUC scores and 4.62× faster in training time. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph embeddings

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Support Vector Machine Based Handwritten Hindi Character Recognition and Summarization

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computer Systems science & engineering 2022年第10期43卷 397-412页

作者： Sunil Dhankhar Mukesh Kumar Gupta Fida Hussain Memon Surbhi Bhatia Pankaj Dadheech Arwa Mashat Department of Computer Science&Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthan302017India Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Mechatronics Engineering Jeju National UniversityJeju63243Korea Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityRabigh21911Saudi Arabia

In today’s digital era,the text may be in form of *** research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language.A method is developed for identifying Hindi language characters that use morphology,edge detection,histograms of oriented gradients(HOG),and SVM classes for summary *** rank employs the summary to extract essential phrases based on paragraph position,phrase position,numerical data,inverted comma,sentence length,and keywords *** primary goal of the SVM optimization function is to reduce the number of features by eliminating unnecessary and redundant *** second goal is to maintain or improve the classification system’s *** experiment included news articles from various genres,such as Bollywood,politics,and *** proposed method’s accuracy for Hindi character recognition is 96.97%,which is good compared with baseline approaches,and system-generated summaries are compared to human *** evaluated results show a precision of 72%at a compression ratio of 50%and a precision of 60%at a compression ratio of 25%,in comparison to state-of-the-art methods,this is a decent result.

关键词： Support vector machine(SVM) optimization precision Hindi character recognition optical character recognition(OCR) automatic summarization and compression ratio

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Design and Implementation of a Cost-Effective Solar Photo Voltaic Food Dryer for Rural Botswana 1

Design and Implementation of a Cost-Effective Solar Photo Vo...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Mbenge, Thopho Samikannu, Ravi Begam, K Maruliya Sindhu, M.P. Ramkumar, M Siva Sivaramkrishnan, M. Botswana International University of Science and Technology Department of Electrical Computer and Telecommunications Engineering Palapye Botswana Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Sri Eshwar College of Engineering Department of Mathematics Tamil Nadu Coimbatore India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350359756

For many centuries, humans have been using energy from the sun to dry food stuff like fruits, meat, vegetables, and field crops by placing them on mats and putting them under the sun. Natural food drying has been a way of preserving food after the harvesting season. For most cases it has been proven that solar energy is highly efficient and environmentally friendly when used to maintain the quality of food stuffs. The only problem about natural food drying is that food becomes contaminated with dust, pests and airborne molds which makes it more harmful and unhealthier for consumption. To counter this problem, this project is about the design of a Solar Photo Voltaic (SPV) based food dryer that will help give a controlled working condition to produce better-looking, better-tasting, and more nourishing food, thereby increasing food value and their marketability. The control functions of temperature and humidity regulation are made possible by a PIC16F877A microcontroller. A detailed discussion of the simulation of the solar photovoltaic food dryer records that temperature and humidity can be regulated to any desirable values with temperature above 55 and humidity level below 5% attainable in the drying chamber. From this study, the results show that the design of a solar photovoltaic based food dryer suggested a promising attempt to ensure quality and efficiency when drying food. © 2023 IEEE.

关键词： Microcontrollers

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CRYPTONITE: Scalable Accelerator Design for Cryptographic Primitives and Algorithms

arXiv

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arXiv 2025年

作者： Maheswaran, Karthikeya Sharma Bossut, Camille Wanna, Andy Zhang, Qirun Hao, Cong School of Electrical and Computer Engineering Georgia Institute of Technology United States School of Computer Science Georgia Institute of Technology United States

Cryptographic primitives, consisting of repetitive operations with different inputs, are typically implemented using straight-line C code due to traditional execution on CPUs. Computing these primitives is necessary for secure communication;thus, dedicated hardware accelerators are required in resource and latency-constrained environments. High-Level Synthesis (HLS) generates hardware from high-level implementations in languages like C, enabling the rapid prototyping and evaluation of designs, leading to its prominent use in developing dedicated hardware accelerators. However, directly synthesizing the straight-line C implementations of cryptographic primitives can lead to large hardware designs with excessive resource usage or suboptimal performance. We introduce Cryptonite, a tool that automatically generates efficient, synthesizable, and correct-by-design hardware accelerators for cryptographic primitives directly from straight-line C code. Cryptonite first identifies high-level hardware constructs through verified rewriting, emphasizing resource reuse. The second stage automatically explores latency-oriented implementations of the compact design. This enables the flexible scaling of a particular accelerator to meet the hardware requirements. We demonstrate Cryptonite’s effectiveness using implementations from the Fiat Cryptography project, a library of verified and auto-generated cryptographic primitives for elliptic-curve cryptography. Our results show that Cryptonite achieves scalable designs with up to 88.88% reduced resource usage and a 54.31% improvement in latency compared to naively synthesized designs. © 2025, CC BY.

关键词： Public key cryptography

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Electrochemical Carbon Dioxide Reduction to Ethylene:From Mechanistic Understanding to Catalyst Surface engineering

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Nano-Micro Letters 2023年第10期15卷 382-415页

作者： Junpeng Qu Xianjun Cao Li Gao Jiayi Li Lu Li Yuhan Xie Yufei Zhao Jinqiang Zhang Minghong Wu Hao Liu Joint International Laboratory on Environmental and Energy Frontier Materials School of Environmental and Chemical EngineeringShanghai UniversityShanghai 200444People’s Republic of China Centre for Clean Energy Technology Faculty of ScienceUniversity of Technology SydneyBroadwaySydneyNSW 2007Australia Department of Electrical and Computer Engineering University of Toronto35 St George StreetTorontoON M5S 1A4Canada

Electrochemical carbon dioxide reduction reaction(CO_(2)RR)provides a promising way to convert CO_(2)to *** multicarbon(C_(2+))products,especially ethylene,are of great interest due to their versatile industrial ***,selectively reducing CO_(2)to ethylene is still challenging as the additional energy required for the C–C coupling step results in large overpotential and many competing ***,mechanistic understanding of the key steps and preferred reaction pathways/conditions,as well as rational design of novel catalysts for ethylene production have been regarded as promising approaches to achieving the highly efficient and selective CO_(2)*** this review,we first illustrate the key steps for CO_(2)RR to ethylene(e.g.,CO_(2)adsorption/activation,formation of~*CO intermediate,C–C coupling step),offering mechanistic understanding of CO_(2)RR conversion to *** the alternative reaction pathways and conditions for the formation of ethylene and competitive products(C_1 and other C_(2+)products)are investigated,guiding the further design and development of preferred conditions for ethylene *** strategies of Cu-based catalysts for CO_(2)RR-ethylene are further summarized,and the correlations of reaction mechanism/pathways,engineering strategies and selectivity are ***,major challenges and perspectives in the research area of CO_(2)RR are proposed for future development and practical applications.

关键词： Key steps in CO_(2)RR-ethylene Preferable reaction pathways Mechanism understanding Surface engineering strategies of Cu-based catalysts

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A Bi-population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium-scale Expensive Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1952-1966页

作者： Meiji Cui Li Li MengChu Zhou Jiankai Li Abdullah Abusorrah Khaled Sedraoui IEEE the School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China the Department of Electronics and Information Engineering Tongji UniversityShanghai 201804China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

This study presents an autoencoder-embedded optimization(AEO)algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems(MEPs).A huge search space can be compressed to an informative lowdimensional space by using an autoencoder as a dimension reduction *** search operation conducted in this low space facilitates the population with fast convergence towards the *** strike the balance between exploration and exploitation during optimization,two phases of a tailored teaching-learning-based optimization(TTLBO)are adopted to coevolve solutions in a distributed fashion,wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary ***,a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence *** proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to *** indicated in our experiments,TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base *** with the state-of-the-art algorithms for MEPs,AEO shows extraordinarily high efficiency for these challenging problems,t hus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization.

关键词： Autoencoder dimension reduction evolutionary algorithm medium-scale expensive problems teaching-learning-based optimization

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Preserving Privacy of User Identity Based on Pseudonym Variable in 5G

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computers, Materials & Continua 2022年第3期70卷 5551-5568页

作者： Mamoon M.Saeed Mohammad Kamrul Hasan Rosilah Hassan Rania Mokhtar Rashid A.Saeed Elsadig Saeid Manoj Gupta Electrical Engineering Department Faculty of EngineeringAlzaiem Alazahri UniversityKhartoumSudan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti KebangsaanMalaysia(UKM)43600BangiMalaysia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityPO Box 11099Taif21944Saudi Arabia Department of Electronics Engineering College of EngineeringSudan University of Science and TechnologyKhartoumSudan Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia

The fifth generation(5G)system is the forthcoming generation of the mobile communication *** has numerous additional features and offers an extensively high data rate,more capacity,and low ***,these features and applications have many problems and issues in terms of security,which has become a great challenge in the telecommunication *** paper aimed to propose a solution to preserve the user identity privacy in the 5G system that can identify permanent identity by using Variable Mobile Subscriber Identity,which randomly changes and does not use the permanent identity between the user equipment and home *** this mechanism,the user identity privacy would be secured and ***,it improves the synchronization between mobile users and home ***,its compliance with the Authentication and Key Agreement(AKA)structure was adopted in the previous *** can be deployed efficiently in the preceding generations because the current architecture imposes minimal modifications on the network parties without changes in the authentication vector’s message ***,the addition of any hardware to the AKA carries minor adjustments on the network *** this paper,the ProVerif is used to verify the proposed scheme.

关键词： 5G privacy and security user identity IMSI authentication and key agreement(AKA)

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