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Retraction Note: Deep reinforcement learning for comprehensive route optimization in elastic optical networks using generative strategies

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Optical and Quantum electronics 2024年第10期56卷 1-2页

作者： Renjith, P. N. Sujatha, G. Vinoth, M. Vignesh, G. D. Ramkumar Prabhu, M. Mouleswararao, B. School of Computer Science and Engineering Vellore Institute of Technology Chennai India Kommuri Pratap Reddy Institute of Technology Ghatkeshar Medchal India Department of Electronics and Communication Engineering K. Ramakrishnan College of Engineering Trichy India Department of ECE St Joseph’s College of Engineering Chennai India Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

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Empirical Analysis of Energy Harvesting and Clustering Methods for D2D Communication Systems

Empirical Analysis of Energy Harvesting and Clustering Metho...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Kumar, Bura Vijay Vijayarangan, R. Thirumurugan, V. Sugumaran, S. Raghunathareddy, M.V. School of Computer Science and Artificial Intelligence Sr University Warangal India Cse Rvt Research Associates Chennai India Cse Vistas Chennai India Vishnu Institute of Technology Ece Department Bhimavaram India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350313413

Unmanned Aerial vehicle (UAV)-based post-disaster communications face significant problems due to their energy consumption and operational range. Energy harvesting is used to overcome these problems by providing power for communication during disasters and extending the lifespan of wireless communication for networks. In order to expand the network's overall coverage and offer continuous connection during the disaster and post-disaster periods, Device-to-Device (D2D) communication and clustering methods were used. And Emergency Communication System (ECS) that uses the best Cluster Head (CH) technology to increase transfer energy effectiveness for long-term connectivity of the network. The clustering method and reinforcement learning in D2D connections are able to collect energy to extend the network lifespan with the help of UAV model. These strategies are predicted to increase the network's constancy during the emergency situations. The enhanced features with the use of the best CHs, and the path loss was significantly decreased. Hence, it reduces the computing complexity of network architecture to recover from natural disasters and also save numerous lives. © 2023 IEEE.

关键词： cluster head Emergency communication system reinforcement learning unmanned aerial vehicle

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Enhancement of Security in IoT using Secure Hash Cryptography Algorithm with Double Encryption (SHCA-DE) 9

Enhancement of Security in IoT using Secure Hash Cryptograph...

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9th International Conference on Communication and electronics Systems, ICCES 2024

作者： Uganya, G. Rajalakshmi, D. Vangapandu, Ramarao Dinesh, M. Giri, Jayant Odeh, Mahmoud Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India Vignan's Institute of Engineering for Women Department of Computer Science and Engineering Vishakhapatnam India Saveetha University Department of Vlsi Microelectronics Saveetha School of Engineering Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (纸本)9798350377972

The 'Internet of things' is the developing technology to transfer the world into smart innovation. 'IoT' security is the most problematic issue in recent applications due to its properties including 'centralized architecture', 'limited capacity devices', and 'ambiguity'. So, blockchain with 'IoT' applications provides secure data communication compared to traditional 'IoT' applications. Blockchain is a recent growing technology that has features including 'decentralized structure', 'transparency', 'immutable records', 'increased capacity', and 'quick backtracks'. The 'cryptography hash algorithm' is very important to provide secure data transmission. It converted the different size input to fixed-size unalterable output to enhance the security. But still, it needs efficient algorithm to secure data transmission with safeguard of private key. The objective of this paper is to propose a secure hash cryptography algorithm with double encryption (SHCA-DE) to protect the private key message. Then, this proposed algorithm has been analyzed with MD5, SHA-256, and SHA3-512. From this analysis, the SHA3-512 performs well with proposed algorithm. © 2024 IEEE.

关键词： Encryption algorithms

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A Way Towards Next-Gen Networking System for the Development of 6G Communication System 4

A Way Towards Next-Gen Networking System for the Development...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Mohan, Chippy Singh, Devesh Pratap Singh, K. Ranjith Divya, N. Ramkumar, R. Abirami, S. Bangalore India Ies Institute of Technology and Management Ies University Electronics & Communication Engineering Department M.P Bhopal India Karpagam Academy of Higher Education Department of Computer Science TN India TN India Bannari Amman Institute of Technology Department of Ece Tamil Nadu Sathyamangalam India Hindustan Institute of Technology and Science Department of Information Technology Tamil Nadu Kelambakkam India

ISBN: (纸本)9798350360165

In this talk, the advancements announced by sixth-generation mobile communication (6G) as compared to the earlier fifth-generation (5G) system are carefully examined. The analysis, based in existing academic works, underscores the goal of improving diverse communication aims across various services. This study finds five crucial 6G core services designed to meet distinct goal requirements. To explain these services thoroughly, the framework presents two central features and delineates eight significant performance indices (KPIs). Furthermore, a thorough study of supporting technologies is performed to meet the stated KPIs. A unified 6G design is suggested, imagined as a combination of these supporting technologies. This design plan is then explained by the lens of five prototype application situations. Subsequently, possible challenges contained in the developing track of the 6G network technology are carefully discussed, followed by suggested solutions. The debate ends in an exhaustive examination of possibilities within the 6G world, seeking to provide a strategy plan for future research efforts. © 2024 IEEE.

关键词： 5G mobile communication systems

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CNN-LSTM Based on Crow Search Optimization Algorithm for Product Review Classification

CNN-LSTM Based on Crow Search Optimization Algorithm for Pro...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Yamsani, Nagendar Jothi, B. Srinivasan, N. Dineshkumar, R. Ramachandra, A.C. Sr University School of Computer Science and Artificial Intelligence Warangal India Srm Institute of Science and Technology Kattankulathur Department of Computational Intelligence Chennai India School of Computing Sathyabama Institute of Science and Technology Department of Cse Chennai India Saveetha School of Engineering Sriperumbudur Department of Ece Thandalam India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350313413

Product reviews means an everyone's opinion or views towards particular products or services that delivered to a specific company. In modern global, reviews of online product play a vital part in the estimation process of product in a company and their customers. The extracted features are selected by using the Chi-Squared technique and for the classification of product review proposed a model by utilizing the combined deep learning techniques like Convolutional Neural Network (CNN) and Long- Short Term Memory (LSTM) and it optimized by Crow Search Algorithm (CSA). CNN is used for capturing the local information and LSTM neural network is used for the long-distance dependencies. By utilizing the benefits of CNN and LSTM and it is optimized by CSA for the effective classification of product review. The proposed model performance is estimated by using the performance metrics like Accuracy, Recall, Specificity, Sensitivity and F1-score are 98.35%, 93.20%, 97.57%, 94.82% and 95.78% respectively. The proposed model is compared with other existing model in terms of performance metrics which shows the better performance results. © 2023 IEEE.

关键词： Chi-Squared Convolutional Neural Network Crow Search Algorithm Long-Short Term Memory and Product Review

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Wireless Capsule Endoscopy Bleeding Images Classification using CNN Based Model

Wireless Capsule Endoscopy Bleeding Images Classification us...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Kumar, Gotte Ranjith Jeyasudha, J. Ravi, G. Jagadesh, T. Madhura, G.K. Sr University School of Computer Science & Artificial Intelligence Warangal India Srm Insitute of Science and Technology Department of Computational Intelligence Chennai India Sona College of Technology Dept of Ece Salem India Kpr Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India Nitte Meenakshi Institute of Technology Department of Ai and Ml Bengaluru India

ISBN: (纸本)9798350313413

Wireless Capsule Endoscopy (WCE) is an effective utensil with probe alimentary region diseases and executes effortless visualizing in intestine. Numerous enterprises produce its broad connection and adaptation challenging things comparable efficacity, forbearance, immunity, and consummation. Self-regulated study of the WCE handed datafile is of immense significance for discriminating peculiarity. Detecting a case's gastrointestinal region through WCE outcomes a huge datafile that involves a significant quantum moment with an exceptional competence put from the therapeutic knowledge. So many computers-backed, eyesight-grounded results can be recommended to determine this controversy, so far it don't give asked position in delicacy, farther advancements just the same as demanded. Combine with deep neural network to develop a proposed model called BIR (bleedy image recognizer) to classify images of bleeding detected by a WCE. The BIR model is combination of MobileNet and a custom-built BERT model. BIR utilizes the MobileNet model for original-position calculation for its lesser calculation energy demand and latterly the affair is fed to the BERT model for farther processing. utilized a datafiles consisting of 1650 pictures captured by WCE for the purpose of training and testing the BIR mode. © 2023 IEEE.

关键词： BERT models Bleedy image recognizer computer vision deep learning gastrointestinal tract infection Wireless capsule endoscopy

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Development of an Instrumented Glove for the Characterization of Human Wrist Tremor 7

Development of an Instrumented Glove for the Characterizatio...

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7th International Conference on electronics, Communication and Aerospace Technology, ICECA 2023

作者： Lakineni, Prasanna Kumar Dhana Sony, J. Sharma, Ruchi Chitra, M. Jose Anand, A. Anchitaalagammai, J.V. GITAM School of Technology Department of Computer Science and Engineering GITAM University Visakhapatnam India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Biomedical Engineering Chennai600062 India JECRC Foundation Department of AI&DS Rajasthan Jaipur302022 India Rajalakshmi Institute of Technology Dept of ECE Tamilnadu Chennai India KCG College of Technology Karapakkam Department of Electronics and Communication Engineering Chennai600097 India Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Madurai India

ISBN: (纸本)9798350340600

It is common for human beings to present some diseases and disorders as they age, due to neuromusculoskeletal disorders. One of the problems that can appear is the human tremor. There are numerous strategies for tremor attenuation. Among the most common methods, the use of medications, local surgical procedures, electrical stimulation and the use of active orthoses stand out. In this context, robotic rehabilitation is of interest to science more and more. Among the methods for inhibiting tremor, active orthoses are the most efficient and non-invasive means. With that in mind, and also in terms of their quality of life, studies on orthoses to suppress tremor were carried out. Due to the complexity of the device, the present study aims to develop and evaluate an instrumented glove, properly constructed to characterize human wrist tremor in patients affected with such dysfunction. To this end, the basic operating principle of the active orthosis is presented, seeking to highlight more specifically the instrumented glove with its motion and muscle actuation sensors. © 2023 IEEE.

关键词： Biomedical signal processing

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Sign Language Recognition System using Convolutional Neural Network 2

Sign Language Recognition System using Convolutional Neural ...

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2nd IEEE International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication engineering, ICATIece 2022

作者： Dudhane, T.M. Chenthil, T.R. Kanaga Priya, P. Jothibasu, M. Shri Chhatrapati Shivajiraje College of Engineering Pune India Jeppiaar Engineering College Electronics and Communication Engineering India KPR Institute of Engineering and Technology Computer Science and Engineering India PSG Institute of Technology and Applied Research Department of ECE Neelambur Coimbatore641062 India

ISBN: (纸本)9781665493963

Sign language is the common communication language for the hearing and speech-impaired community. It is hard for most people to communicate in sign language without an interpreter. Sign language refers to the tracking and identification of meaningful human expressions made with the hands, arms, fingers, heads, etc. The method used in this case converts the sign language movements into a spoken language that the listener may easily understand. The communication using sign language is useful for the peoples depend on gestural sign language but it is more complex for the other publics. The existing systems are not efficient since they are struggling with skin tone detection. But, adding a filter symbol can be recognized regardless of skin tone. In this work, primarily focused on analyzing convolutional neural networks (CNN). There are four kinds of layers: convolution layers, fully connected layers, pooling/subsampling layers and nonlinear layers for learning new characteristics. © 2022 IEEE.

关键词： Audition

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A Taxonomy of Defenses against Memory Corruption Attacks 44

A Taxonomy of Defenses against Memory Corruption Attacks

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44th International Convention on Information, Communication and Electronic Technology, MIPRO 2021

作者： Novkovic, Bojan University of Zagreb Faculty of Electrical Engineering and Computing Department of Electronics Microelectronics Computer and Intelligent Systems Zagreb Croatia

ISBN: (纸本)9789532331011

Vulnerabilities caused by memory corruption related bugs are a pervasive threat, continually undermining the security of the whole computing environment. The lack of memory safety mechanisms in indispensable systems programming languages like C or C++ leaves plenty of room for programmer-induced errors which often result in catastrophic security breaches. We analyze the root causes of these vulnerabilities, providing a concise overview of memory corruption bugs and related attacks. Although present in a number of programming languages, we use the C/C++ programming language as a basis for our analyses. We categorize existing defensive mechanisms based on the attack techniques they focused on preventing and give a brief insight into state-of-the-art defenses introduced throughout the years, with a special focus on operating system defenses. © 2021 Croatian Society MIPRO.

关键词： C++ (programming language)

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Machine Learning Approaches for Advanced Threat Detection in Cyber Security 5

Machine Learning Approaches for Advanced Threat Detection in...

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5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Saravanan, V. Upender, Talluri Ruby, E. D. Kanmani Deepalakshmi, P. Reddy, Desidi Narsimha Ananthi, S.N. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Nano Electronics Materials and Sensors Tamilnadu Chennai India Cmr College of Engineering and Technology Department of Cse Medchal Telangana Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science Technology Department of Ece India Tamil Nadu Krishnankoil India Soniks Consulting Llc TX United States S.A. Engineering College Department of Computer Science and Engineering Chennai77 India

ISBN: (纸本)9798350376685

The dynamic nature of cyber threats demands that threat detection mechanisms be continuously improved in order to protect digital assets and infrastructures. In cybersecurity, this study investigates the use of machine learning (ML) algorithms for enhanced threat detection. This work intends to improve threat detection systems' accuracy, speed, and adaptability by utilizing ML algorithms' capabilities. The abstract begins by outlining the significance of machine learning in transforming traditional cybersecurity measures. It highlights the limitations of conventional signature-based methods, which often fail to detect novel and sophisticated threats. In contrast, ML-based approaches offer dynamic and proactive defenses capable of identifying previously unseen attack vectors. Furthermore, the paper delves into the practical implementation of ML models in real-world cybersecurity environments. It covers data collection and preprocessing techniques critical for training accurate and reliable models, as well as the challenges associated with maintaining and updating these models to adapt to evolving threat landscapes. The importance of feature selection and engineering in improving model performance is also emphasized. To validate the effectiveness of ML approaches, the study presents case studies and experimental results from various cybersecurity applications. The abstract concludes by addressing the future prospects and potential advancements in machine learning for cybersecurity. It discusses the role of emerging technologies, such as deep learning and federated learning, in enhancing threat detection capabilities. Additionally, it considers the ethical and privacy concerns associated with deploying ML models in cybersecurity and the need for robust governance frameworks. In summary, this study presents a thorough analysis of machine learning techniques for enhanced threat detection in cybersecurity, including useful applications, advantages, and difficulties. © 202

关键词： Federated learning

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