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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Vivek, Kolla Swetha, Gurrala Kumar M, V. T. Ram Pavan Veni, Anusuri Krishna Praveen, Neti Kale, Masthan Rao Dept. of Cse Andhra Pradesh Ongole India Dept. of Cse Telangana India Kakaraparti Bhavanarayana College Dept. of Computer Science Andhra Pradesh Vijayawada India Madanapalle Institute of Technology & Science Dept. of Computer Science & Engineering - Data Science Andhra Pradesh Madanapalle517325 India Srkr Engineering College Dept. of Computer Science and Design Andhra Pradesh Bhimavaram India Dept. of Cse Andhra Pradesh Ongole India

ISBN: (纸本)9798331509675

Smart cities have emerged as a response to the fast expansion of metropolitan areas;these places strive to improve the lives of their residents while simultaneously promoting environmentally responsible growth. To maximize urban services, the Internet of Things (IoT) is an essential technology that allows for the seamless integration of sensors, devices, and systems. This allows smart cities to become a reality. With an emphasis on smart transportation, energy management, healthcare, environmental monitoring, and public safety, this paper explores the critical role of IoT in smart cities. Data security, privacy, scalability, and interoperability are some of the problems that arise when smart cities use IoT, despite the revolutionary potential it has. These obstacles are thoroughly examined in this work, along with possible solutions to these problems. This study gives a thorough overview of the IoT and its impact on smart city development, innovation, and urban resilience by focusing on the present situation, applications, and unanswered questions. © 2025 IEEE.

关键词： Digital Technology Drainage Monitoring Fire detection Smart City Waste Management

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Microwave Marvels: Design and Computational Analysis of an Ultra-thin Metamaterial Absorber for C, X and K Band 6

Microwave Marvels: Design and Computational Analysis of an U...

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6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Tasnim, Nowshin Rattre, Naziya Hasan Shawon, Sarowar Morshed Alam, Mohammed Shamsul Alam, Touhidul Chittagong University of Engineering & Technology Dept. of Computer Science & Engineering Chittagong4349 Bangladesh International Islamic University Chittagong Dept. of Computer Science & Engineering Chittagong4318 Bangladesh University of Science & Technology Chittagong Dept. of Computer Science & Engineering Chattogram4202 Bangladesh Universiti Kebangsaan Malaysia Bangi43600 UKM Malaysia

ISBN: (纸本)9798350385779

Metamaterial absorbers are an advancement in material science as they provide more advantages in comparison to conventional materials. Achieving miniaturization with a multilayered structure is the primary challenge here. In this study, a novel metamaterial absorber design is proposed for microwave application. The proposed design is shaped as a squad of four segments where each segment contains an octagonal split ring and a central ring. The multi-layered design of the absorber helps to secure a high absorption rate. An extensive range of research is done to determine particular measurement units, and geometric shapes with the help of CST Studio Suit 2019. Here both ground and patch are designed using copper and the separator is designed with Roger. Moreover, the thickness of the absorber is only 3.4 mm which ensures its ultra-thin and lightweight nature. With an elaborated numerical analysis, it has been shown that the proposed absorber provides 90% to 99% absorption at the C, X, and K bands. Moreover, a concise computational analysis is accomplished with FR4 lossy, Rogers RT6010LM lossy, and Rogers RT5870LM lossy as dielectric constant. The key contribution of this research is the high absorption rate, coupled with minimal thickness and simple structure. © 2024 IEEE.

关键词： Metamaterials

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Attention Mechanism with Bayesian Decision Theory for Drug Prediction

Attention Mechanism with Bayesian Decision Theory for Drug P...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Sankaran, A. Sathiyamurthy, K. Puducherry Technological University Dept. of Computer Science and Engineering India Puducherry Technological University Faculty of Computer Science and Engineering India

ISBN: (纸本)9798331510022

Biomedical literature lacks integration of dynamic drug interaction data for personalized prescriptions. This proposed work is a new hybrid model that enhances drug safety prescriptions by taking into account individual patient features and drug interactions. It does this by hybrid attention mechanisms with Bayesian Decision Theory (BDT), which employs Bayesian statistical thinking instead of the dot-product approach. This approach is driven by the growing complexity of patient profiles and the limitations of current algorithms, which often fail to dynamically change the relevance of individual aspects. This method seeks 94% accuracy, effectively prioritizing safer drug combinations and personalizing drug recommendations. This integration leads to more consistent and customized drug prescriptions, which ultimately improve patient outcomes and advance the field of personalized healthcare. © 2024 IEEE.

关键词： Drug interactions

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Evaluating the Performance of Machine Learning Models in Handwritten Signature Verification

Evaluating the Performance of Machine Learning Models in Han...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Akter, Tahmina Akter, Mst. Sharmin Mahmud, Tanjim Chakma, Rishita Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350361537

Handwritten signatures remain a widely used method for personal authentication in various official documents, including bank checks and legal papers. The verification process is often labor-intensive and time-consuming, necessitating the development of efficient methods. This study evaluates the performance of machine learning models in handwritten signature verification using the ICDAR 2011 Signature and CEDAR datasets. The investigation involves preprocessing, feature extraction using CNN architectures, and optimization techniques. The most effective models undergo a rigorous evaluation process, followed by classification using supervised ML algorithms, such as linear SVM, random forest, logistic regression, and polynomial SVM. The results indicate that the VGG16 architecture, optimized with the Adam optimizer, achieves the satisfactory performance metrics. This study demonstrates the potential of ML methodologies to enhance the efficiency and accuracy of signature verification, offering a robust solution for document authentication. © 2024 IEEE.

关键词： Decision trees

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Predictive Modeling of Cryptocurrency Prices Using Machine Learning Algorithms 15

Predictive Modeling of Cryptocurrency Prices Using Machine L...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mahmud, Tanjim Akter, Tahmina Chakma, Rishita Barua, Tikle Hossain, Mohammad Shahadat Andersson, Karl Dept. of Computer Science and Engineering Rangamati Science and Technology University Rangamati4500 Bangladesh Dept. of Computer Science and Engineering Port City International University Chittagong Bangladesh Dept. of Computer Science and Engineering University of Chittagong Chittagong4331 Bangladesh Cybersecurity Laboratory Luleå University of Technology Luleå97187 Sweden

ISBN: (纸本)9798350370249

Cryptocurrencies, such as Bitcoin, Binance, Ethereum, FTX, and XRP, are decentralized digital assets known for their volatile nature and potential as investment instruments. Accurate price prediction is crucial for informed investment decisions. This study explores the feasibility of various modeling techniques on diverse data structures and features for predicting the prices of these cryptocurrencies. We utilize daily and high-frequency price data to classify and predict prices using deep learning and machine learning techniques, including LSTM, Bi-LSTM, GRU, linear regression, and SGD regression. Our findings indicate that daily price projections achieve an accuracy of 0.99, outperforming more complex deep learning and machine learning models. Compared to benchmark results, our approach demonstrates superior performance, with the highest scores achieved by the applied statistical methods and advanced algorithms. This research highlights the effectiveness of deep learning and machine learning models in cryptocurrency price forecasting, offering a foundation for further exploration in the field and emphasizing the significance of sample size in predictive modeling. ©2024 IEEE.

关键词： Adversarial machine learning

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Smart Vehicle Procurement System using Blockchain Technology 3

Smart Vehicle Procurement System using Blockchain Technology

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Kumar, Boddu Manoj Rajeswari, G. Duraipandian, Kavitha David, Shiela Dept. of Computer Science and Engineering with specialization in Blockchain Technology Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331527549

Blockchain technology has become more widespread in our lives revolutionizing various industries through improved security, transparency, and operational efficiency. Its decentralized ledger system is particularly effective in areas like finance and supply chain management ensuring data integrity and reducing the need for middlemen. This study explores how blockchain technology is used in the process of buying vehicles highlighting its benefits compared to methods. Traditional vehicle purchases involve a network of dealers, banks and regulators leading to inefficiencies, higher costs and potential fraud. The usual process involves steps like financing checking vehicle history and changing ownership. Each requiring extensive paperwork and third-party intervention. In contrast using blockchain for vehicle purchases can simplify things through contracts that automate tasks like verifying history securely transferring ownership instantly settling payments. The unchangeable nature of records ensures that all transaction data remains secure against tampering fostering trust between buyers and sellers. Furthermore, blockchain can cut costs significantly by removing the need for middlemen such, as escrow services and title companies while reducing burdens. The advanced security elements built into technology help reduce the chances of fraudulent actions like altering odometer readings or selling stolen cars. This study showcases a comparison illustrating how blockchain can simplify the process of buying vehicles offering an economical and secure experience. © 2025 IEEE.

关键词： Decentralized finance

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Masked Ciphertext Comparison without Masking Conversions using Register Rotation and Chinese Remainder Theorem 15

Masked Ciphertext Comparison without Masking Conversions usi...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Kim, Geumtae Seo, Eunyoung Lee, Yongwoo No, Jong-Seon Seoul National University Dept. Electrical and Computer Engineering Seoul Korea Republic of Dept. Electrical Engineering and Computer Science Daegu Korea Republic of Inha University Dept. Electrical and Computer Engineering Incheon Korea Republic of

ISBN: (纸本)9798350364637

In this paper, we propose a novel method for masked comparison using register rotation technique without masking conversions. In key encapsulation mechanisms (KEMs), ciphertext comparison is essential to ensure the security, but it is one of the most computationally expensive operations in masking environment. Previous works on masked ciphertext comparison have mainly focused on masking conversion and its post-processing. However, the proposed method introduces another register-based approach, which eliminates the need for time-consuming masking conversion and solely relies on register rotation using Chinese remainder theorem (CRT). © 2024 IEEE.

关键词： Ciphertext

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A systematic review of decentralized finance protocols

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International Journal of Intelligent Networks 2023年第1期4卷 171-181页

作者： Shah, Kaushal Lathiya, Dhruvil Lukhi, Naimish Parmar, Keyur Sanghvi, Harshal Dept. of Computer Science and Engineering Pandit Deendayal Energy University Gujarat Gandhinagar382007 India Dept. of Computer Science and Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat395007 India Dept. of CEECS Florida Atlantic University Boca Raton United States

Decentralized finance (DeFi) has revolutionized the financial industry in recent years. Industries such as banking, insurance, and investment are experiencing a significant shift due to the growth of DeFi. The decentralized finance market is expanding exponentially, emphasizing the potential of digital currencies and decentralized platforms in providing an alternative to the traditional finance paradigm. It eliminates the need for costly intermediaries, reduces transaction fees, and increases accessibility to financial services for everyone, regardless of their geographic location or economic status. With the enormous increase in cryptocurrency investment, individuals and institutions have started to use DeFi. In this context, understanding the architecture and working mechanisms of different DeFi protocols becomes crucial in creating new and innovative products. This review paper explores various DeFi protocols, including derivatives, decentralized exchanges (DEX), lending and borrowing, asset management, and stablecoins. It analyses their internal structure and composability, providing insights into how these protocols can be combined to create new and innovative DeFi products and explore the potential of DeFi in providing an alternative to the traditional finance paradigm. © 2023 The Authors

关键词： Asset management

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SmartCitrus: An Efficient Deep Learning Approach for Real-Time Detection and Classification of Citrus Leaf Diseases

SmartCitrus: An Efficient Deep Learning Approach for Real-Ti...

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2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Emon, Shaharear Hossain Islam, Iftea Khairul Nahin, Tasfia Jahan Ahmed, Ahnaf Mahdin Orchi, Nabiha Tasnim Alam, Md Ashraful Dipto, Shakib Mahmud Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh Brac University Cvis Research Lab Dept. of Computer Science and Engineering Dhaka Bangladesh University of Liberal Arts Dept. of Computer Science and Engineering Dhaka Bangladesh Brac University Cvis Research Lab Dhaka Bangladesh

ISBN: (纸本)9798350350289

Bangladesh is a prominent citrus exporter. Annually, the country has been exporting citrus fruits to over 60 countries. Distinguishing various diseases affecting citrus leaves requires a significant investment of time, effort, and specialized knowledge. Consequently, it is essential to create an innovative method for detecting citrus diseases. In this study, we have devised a valuable methodology by employing CNN models to identify diseases in citrus leaves. By employing a distinctive ensemble strategy, we successfully trained the model using varying numbers of classes in each stage. In reality, it allowed us to utilize suitable varieties of leaves for various ailments. Furthermore, it has enhanced the rate at which models learn during the later stages. In addition, it has reduced the level of model intricacy in comparison to frequently employed ensemble models. The identification of plant diseases in the present study involved the utilization of leaf photographs and algorithms for segmentation and feature extraction. Ultimately, we have successfully attained a 96 % accuracy rate for each class, signifying a substantial potential for mitigating production losses. © 2024 IEEE.

关键词： Citrus fruits

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Effect of pulsed current cathodic protection on pipeline steel API 5L X65 corrosion mitigation: An investigation and machine learning-assisted modeling

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Corrosion Communications 2023年第4期12卷 29-45页

作者： Hosein Eslamian Mehdi Javidi Mohammad Reza Zamani Mohammad Mahdi Dana Eghbal Mansoori Department of Materials Science and Engineering School of Engineering Shiraz University School of Metallurgy and Materials Engineering College of Engineering University of Tehran Computer Science Eng.and IT Dept. School of Electrical and Computer Engineering Shiraz University

Pulsed current cathodic protection(PCCP) could be more effective than direct current cathodic protection(DCCP)for mitigating corrosion in buried structures in the oil and gas industries if appropriate pulsed parameters are chosen. The purpose of this research is to present the corrosion prevention mechanism of the PCCP technique by taking into account the effects of duty cycle as well as frequency, modeling the relationships between pulse parameters(frequency and duty cycle) and system outputs(corrosion rate, protective current and pipe-to-soil potential) and finally identifying the most effective protection conditions over a wide range of frequency(2–10 kHz) and duty cycle(25%-75%). For this, pipe-to-soil potential, pH, current and power consumption, corrosion rate, surface deposits and investigation of pitting corrosion were taken into account. To model the input-output relationship in the PCCP method, a data-driven machine learning approach was used by training an artificial neural network(ANN). The results revealed that the PCCP system could yield the best protection conditions at 10 kHz frequency and 50% duty cycle, resulting in the longest protection length with the lowest corrosion rate at a consumption current 0.3 time that of the DCCP method. In the frequency range of 6–10 kHz and duty cycles of 50%-75%, SEM images indicated a uniform distribution of calcite deposits and no pits on cathode surface.

关键词： Pulsed current cathodic protection Duty cycle Frequency Artificial neural network API X65 pipeline steel

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