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2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Begum, Almas Rajendra Thilahar, C. Monikaa, R. Gopinath, M. Ruth Naveena, N. Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Saveetha Engineering College Department of Computer Science and Engineering Chennai India Easwari Engineering College Department of Computer Science and Engineering Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Information Technology Chennai India Hindustan Institute of Technology and Science Department of Mathematics Chennai India

ISBN: (纸本)9798331522988

Vehicle communication systems facilitate both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connections, playing a crucial role in Intelligent Transportation Systems. Accurate estimation of signal-to-noise ratio (SNR) is necessary for modern communication systems to be reliable and efficacious. This study aims to identify which machine learning model achieves the highest accuracy in predicting SNR. The analysis focuses on three different models: Random Forest, Gradient Boosting, and Linear Regression. The models were built using a comprehensive dataset containing wireless measurements from the iV2V industrial testbeds. The iV2I+ dataset records data from an industrial site where it acquires around 16∼h of the autonomous cleaning robot connected to a private cellular network, meanwhile, the iV2V has accumulated about 10 hours in side-link situations between three Automated Guided Vehicles (AGVs). It is an appropriate dataset for machine learning purposes because it provides information on positional data, wireless Quality of Service (QoS) measurements, and physical layer characteristics in detail. The models were analyzed based on performance measures including R2 Score, Root Mean Squared Error (RMSE), and Mean Squared Error (MSE). The Random Forest model outperformed all other models we tested with an MSE of 0.0058, which translates to an RMSE of 0.0762 and an R2 score over the roof.9997 Yes, they performed well also but Random Forest outperformed Gradient Boosting and Linear Regression in all the metrics. Random Forest was the good model that this study could get which is constructed by other models as well, depicting its goodness for designing machine learning algorithms to forecast SNR over a vehicular communication system. Results provide means to develop methods for enhanced communication efficiency and reliability that can be helpful while building safer, more effective transportation systems where ITS plays a significant role. © 2024 IEEE.

关键词： Vehicle to infrastructure

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Introduction to the Special Issue on the Bottleneck of Blockchain Techniques Scalability,Security and Privacy Protection

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computer Modeling in engineering & Sciences 2024年第12期141卷 1933-1937页

作者： Shen Su Daojing He Neeraj Kumar Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China School of Computer Science and Technology Harbin Institute of Technology(Shenzhen)Shenzhen518055China Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147004India

Blockchain technology has been extensively studied over the past decade as a foundation for decentralized information-sharing platforms due to its promising *** the success of existing blockchain architectures like Bitcoin,Ethereum,Filecoin,Hyperledger Fabric,BCOS,and BCS,current blockchain applications are still quite *** struggles with scenarios requiring high-speed transactions(e.g.,online markets)or large data storage(e.g.,video services)due to consensus efficiency *** restrictions pose risks to investors in blockchain-based economic systems(e.g.,DeFi),deterring current and potential *** protection challenges make it difficult to involve sensitive data in blockchain applications.

关键词： services Ether limitations

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Molecules with a TEMPO-based head group as high-performance organic friction modifiers

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Friction 2023年第2期11卷 316-332页

作者： Jinchi HOU Masaki TSUKAMOTO Seanghai HOR Xingyu CHEN Juntao YANG Hedong ZHANG Nobuaki KOGA Koji YASUDA Kenji FUKUZAWA Shintaro ITOH Naoki AZUMA Department of Complex Systems Science Graduate School of InformaticsNagoya UniversityNagoya 464-8601Japan Institute of Materials and Systems for Sustainability Nagoya UniversityNagoya 464-8601Japan Department of Micro-Nano Systems Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8603Japan

High-performance organic friction modifiers(OFMs)added to lubricating oils are crucial for reducing energy loss and carbon *** establish a new class of OFMs,we measured the friction and wear properties of N-(2,2,6,6-tetramethyl-1-oxyl-4-piperidinyl)dodecaneamide referred to as *** effect of its head group chemistry,which is characterized by a rigid six-membered ring sandwiched by an amide group and a terminal free oxygen radical,was also investigated with both experiments and quantum mechanical(QM)*** measurement results show that C12Amide-TEMPO outperforms the conventional OFMs of glyceryl monooleate(GMO)and stearic acid,particularly for load-carrying capacity,wear reduction,and stability of friction over *** friction and wear reduction effect of C12Amide-TEMPO is also greatly superior to those of C12Ester-TEMPO and C12Amino-TEMPO,in which ester and amino groups replace the amide group,highlighting the critical role of the amide *** QM calculation results suggest that,in contrast to C12Ester-TEMPO,C12Amino-TEMPO,and the conventional OFMs of GMO and stearic acid,C12Amide-TEMPO can form effective boundary films on iron oxide surfaces with a unique double-layer structure:a strong surface adsorption layer owing to the chemical interactions of the amide oxygen and free radical with iron oxide surfaces,and an upper layer owing to the interlayer hydrogen-bonding between the amide hydrogen and free radical or between the amide hydrogen and ***,the intralayer hydrogen-bonding in each of the two layers is also *** suggest that in addition to strong surface adsorption,the interlayer and intralayer hydrogen-bonding also increases the strength of the boundary films by enhancing the cohesion strength,thereby resulting in the high tribological performance of *** findings in this study are expected to provide new hints for the optimal molecular design of OFMs.

关键词： organic friction modifiers(OFMs) TEMPO friction and wear surface adsorption molecular reactivity boundary lubrication

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SecureDec: A Decentralized Scheduling Pipeline with Federated Learning and Efficient Encryption for Electricity-Gas Coupled Systems

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IEEE Transactions on Smart Grid 2025年第4期16卷 2858-2870页

作者： Liu, Haizhou Liu, Haitian Hu, Qinran Zhang, Xuan Sun, Hongbin Shahidehpour, Mohammad The School of Electrical Engineering Southeast University Nanjing210096 China The Shenzhen International Graduate School Tsinghua University Shenzhen518055 China The Department of Electrical Engineering Tsinghua University Beijing100084 China The College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan030024 China The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes SecureDec, a decentralized and secure computational pipeline for the day-ahead scheduling of electricity-gas coupled systems. At the lower level, we propose SecureADMM for the decentralized optimization of the coupled subsystems, where all exchanged variables in decentralized ADMM are properly secured with ex-ante Diffie-Hellman (D-H) keys. The generation of D-H keys, being the most time-consuming step in encryption, can be independently performed ahead of optimization, allowing subsystems to collaboratively update variables without compromising optimization efficiency. As the convergence of ADMM is contingent on the quality of starting points, at the upper level, we introduce multi-entity SecureBoost, a decentralized federated learning framework, to predict the warm starts of SecureADMM in a similarly decentralized and privacy-preserving manner. A two-stage statistical packing algorithm is incorporated in the preceding SecureBoost training process to improve the efficiency in data protection, which reduces the frequency of time-consuming encryption/decryption by 2–6 times. Case studies demonstrate that the convergence of SecureDec is up by 50.0% higher than the conventional ADMM due to hyper-accurate warm starts provided by SecureBoost. Further, 63.9% and 96.7% efficiency boosts are observed in the federated learning and day-ahead optimization of an electricity-gas coupled system, respectively, with no compromises in information privacy and scheduling quality. The pipeline is further scalable to larger systems, and demonstrates potentials in addressing non-convergence in the conventional ADMM. © 2010-2012 IEEE.

关键词： Associated gas

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Enhancing Image Quality with GAN Super Resolution Evaluation 5

Enhancing Image Quality with GAN Super Resolution Evaluation

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kumari, Saumya Jha, Resham Ray, Aarushi Bilgaiyan, Saurabh Gourisaria, Mahendra Kumar Sharma, Ashish School of Computer Engineering Kiit Deemed to Be University Odisha Bhubaneswar India Gla University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350379945

The present study presents a novel approach to enhance the quality of celebrity photos by utilizing an innovative framework known as Profile SR-GAN. The aim is to increase the resolution of low-quality celebrity photos, so they appear significantly better. In this work, Generative Adversarial Network (GAN) has been applied as it is highly efficient at generating images. Two key performance metrics have been used, PSNR and SSIM, to evaluate the effectiveness of our approach. In comparison to the noise in the original low-quality photographs, PSNR enables us to determine how clear the high-resolution images are. SSIM analyzes brightness, contrast, and general structure to assist us compare the original and upgraded photos. The effectiveness of GAN model has been demonstrated in enhancing the image resolution through our detailed study. This research study has gained a greater knowledge of this technique's effectiveness and its potential uses in many contexts. © 2024 IEEE.

关键词： Generative adversarial networks

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Game Therapy for Specially-Abled Individuals with PPO Reinforcement Learning in VR-based Educational Games 5

Game Therapy for Specially-Abled Individuals with PPO Reinfo...

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5th International Conference on Data Intelligence and Cognitive informatics, ICDICI 2024

作者： Joypriyanka, M. Surendran, R. Sathish Kumar, P.J. Sivasangari, A. Saveetha Institute of Medical and Techinical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India Sathyabama Institue of Science and Technology School of Computing Chennai India

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389609

This research study presents a new application of reinforcement learning (RL), specifically Proximal Policy Optimization (PPO), in creating immersive virtual reality (VR) games aimed at aiding skill acquisition and emotional regulation for individuals with anger management difficulties. People with Down syndrome, Autism Spectrum Disorder, Cerebral Palsy (CP), Intellectual Disabilities (ID), and Stroke Survivors are mainly considered. The study examines how PPO-trained agents improve cognitive, social, and emotional regulation. Techniques include thorough hyperparameter optimization for the PPO algorithm with two sets. Iterative agent training in Unity and AWS Sagemaker uses cloud computing resources for parallelized training. Emotional regulation and positive behaviour change are assessed empirically and through user studies. Virtual reality (VR) cooperative RL games may offer comprehensive treatments for anger management, according to the results, which show promising gains in emotional regulation and teamwork. By enhancing interest and effectiveness in satisfying emotional regulation demands, the study demonstrates that AI-driven therapies and "gamified therapy,"which mixes game components into therapy, can revolutionize mental health. © 2024 IEEE.

关键词： Reinforcement learning

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Comparative analysis of Start-up Success Rate Prediction Using Machine Learning Techniques 3

Comparative analysis of Start-up Success Rate Prediction Usi...

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3rd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2024

作者： Belgaum, Mohammad Riyaz Viswanath, Ediga Kasi Chakradhar, Pavukolla Goud, Ediga Chenna Kesava Chandu, Kuruva G. Pullaiah College of Engineering and Technology Department of Computer Science and Engineering Kurnool India Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia

ISBN: (纸本)9798350391565

Software startups create innovative products or services using programming, which can lead to a need for products from potential customers. Researchers suggest that trial and error methodology can increase the success rate of these organizations by evaluating assumptions about client needs before fostering a product. However, programming new businesses typically do not require trial and error. The study aims to predict the success of startup companies in their early development stages by analyzing their success based on initial funding. A study of 106 unsuccessful software start-ups was conducted to predict the success rate. The experimentation progression model (X Pro) was developed to show that effective experimentation requires understanding trial and error, setting objectives, conducting tests, analyzing results, and acting based on new knowledge. The findings provide insights into supporting procedures and approaches that enhance trial- and-error reception in developing new business models. Researchers can become aware of potential factors leading to startup disappointment and take precautions to avoid them. The research focuses on using web-based open sources, including social networking services and the web, to model the task. The study uses machine learning techniques like Random Forest, Gradient Boost Classifier, XG Boost, and Ada Boost Classifier. The analysis provides insights into the types of useful signals discovered on the web and market mechanisms underlying the funding process. This approach offers a more comprehensive approach to predicting startup success. © 2024 IEEE.

关键词： Ada (programming language)

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A CNN-GA Hybrid Approach for Efficient Analysis of Size and Shape of Nanoparticle

A CNN-GA Hybrid Approach for Efficient Analysis of Size and ...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Sushma, K.S.N. Sarkar, Argha Sanyal, Gautam School Of Computer Science And Engineering Reva University Bengaluru India National Institute Of Technology Department Of Computer Science And Engineering Durgapur India

ISBN: (纸本)9798350371567

Addressing the challenge of manually analyzing nanoparticle characteristics, such as size and shape, researchers have increasingly turned to deep learning methodologies. This research paper introduces a novel approach, a synergistic combination of CNN-GA architecture, to efficiently analyze the physical properties of nanoparticles. The integration of CNN for feature extraction from image data and GA for fine-tuning hyperparameters and attributes proves to be a powerful tool. Unlike the traditional manual design of CNN architectures, this semi-automatic approach allows researchers to design robust architectures without necessitating in-depth CNN expertise, facilitating the achievement of benchmark results in nanoparticle characterization. © 2024 IEEE.

关键词： Genetic algorithms

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Optimizing Multilayer Perceptron Classifiers for Predictive Heart Disease Diagnosis: A Hyperparameter Tuning Approach 8

Optimizing Multilayer Perceptron Classifiers for Predictive ...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Vadlamudi, Anvitha Talasila, Smeeth Althaph, Bollapalli Challa, Nagendra Panini Vadlamudi, Gnana Abhinay School of Computer Science and Engineering VIT-AP University Amaravati India Department of Computer Science and Engineering New York United States

ISBN: (纸本)9798331505462

Heart diseases, collectively known as cardiovascular diseases (CVDs), remain one of the foremost health challenges across the globe, taking millions of lives each year. This study evaluates the effectiveness of Multilayer Perceptron (MLP) classifiers in predicting CVDs using the Heart Disease Dataset from Kaggle. We implemented a structured approach using data pre-processing, model training with baseline MLP classifiers, and hyperparameter optimization utilizing Random and Grid Search techniques. The optimized models, particularly the MLP Classifier trained with Grid Search, outperformed the baseline, achieving up to 98.54 % accuracy and 100% precision. However, analysis of learning curves indicated the need for further model refinement to enhance generalization on unseen data. This study underscores the importance of hyperparameter tuning in developing effective MLP classifiers for CVDs prediction and suggests directions for future research, including exploring advanced optimization methods and regularization techniques. © 2024 IEEE.

关键词： Cardiology

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DESIGN AND TUNING ASPECTS OF A PSS BASED ON THE COMPLETE NONLINEAR SYNCHRONOUS GENERATOR MODEL 14

DESIGN AND TUNING ASPECTS OF A PSS BASED ON THE COMPLETE NON...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Alexandridis, Theodosis A. Barbagianni, Maria G. Alexandridis, Antonio T. School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical and Computer Engineering University of Patras Greece

ISBN: (纸本)9781837242689

A new insight is given in the analysis of the standard power system stabilizer (PSS) design problem that results in some important methodology novelties. The problem is investigating in a new manner based on the complete nonlinear model of the synchronous generator (SG), in combination with the well-known lead-lag compensator characteristics. According to the deployed theoretical analysis, a novel, simple and reliable PSS design procedure is established that is expected to contribute to the system stability and good response with clearly smooth and fast damping on the local frequency oscillatory behaviour of the SG. Following the proposed methodology, different design and gain tuning cases are examined by conducting extended simulations. All the comparisons between the results, fully confirm the theoretical analysis and indicate the superiority of the proposed design procedure. © The Institution of engineering & Technology 2024.

关键词： Damping

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