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检索条件"任意字段=6th IEEE International Conference on Computer and Communication Engineering Technology, CCET 2023"

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2023 ieee 6th international conference on computer and communication engineering technology, ccet 2023

2023 IEEE 6th International Conference on Computer and Commu...

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6th ieee international conference on computer and communication engineering technology, ccet 2023

ISBN: (纸本)9798350340686

the proceedings contain 47 papers. the topics discussed include: design and simulation of baseband coaxial cable communication system based on OFDM technology;exploring IoT and deep learning for smart city technology;an efficient phase interferometer direction-finding algorithm based on circular array;a hypernetwork-based method for omnidirectional image quality assessment;beamforming design for multi-cell SWIPT-enabled wireless networks;frequency compatibility analysis of public mobile communication system using 824-835MHz band for civil unmanned aerial vehicle;performance analysis of power data compression based on Beidou short messages;and implementation of Burmese language news classification system by using SVM and LSTM machine learning algorithm.

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Overview of Accent Conversion Techniques Based on Deep Learning 6

Overview of Accent Conversion Techniques Based on Deep Learn...

引用

6th ieee international conference on Image Processing, Applications and Systems, IPAS 2025

作者： Shrestha, Aayam Ghorshi, Seyed Panahi, Issa The University of Texas at Tyler Department of Electrical and Computer Engineering TylerTX United States The University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX United States

ISBN: (纸本)9798331506520

In modern communication, speech technology plays a vital role, with accent being one of the key features that reflects the nuances of spoken technology. However, differences in accent can make communication difficult, especially in global contexts like language learning and human computer interaction. Accent conversion approaches often solve these issues by transforming the accent of speaker to that of the other speakers, while maintaining linguistic information and speaker identity. this technology holds great applications to speech recognition, language learning, and cross-lingual communication. this paper explores the use of advanced deep learning techniques in accent conversion systems which have improved both the naturalness and intelligibility of converted speech. Additionally, we discuss the methods generally used for performance evaluation of these systems. © 2025 ieee.

关键词： Deep learning

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Seawater Channel Frequency for Data Transmission through Water 6

Seawater Channel Frequency for Data Transmission Through Wat...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sheeba, Adlin Swetha, P. Vetri Selvi, S. Subasini, C.A. Department of Computer Science and Engineering St. Joseph’s Institute of Technology Chennai India

ISBN: (纸本)9798331522667

Underwater data transmission forms a feasible method for underwater communication. However, laboratory experiments significantly differ from natural aquatic settings due to physical size constraints. During the last few decades, artificial scattering agents have been used to simulate underwater data communications under various conditions, but the similarity between experimental water and natural water remains unreliable, especially in frequency domain characteristics. this paper introduces a framework for the evaluation and optimization of frequency domain characteristics of data transmission across seawater channels under experimental conditions. this research study systematically analyse different agents and particle sizes to bridge the gap between experimental setups and real-world applications. this research further proposes a real-time communication system that can transmit biomedical data from sea researchers to a monitoring system onboard vessel. through comparative analysis, novelty is established, and its practical implications for marine research and underwater exploration are emphasized. © 2025 ieee.

关键词： Seawater

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MathCrypt Secure Algorithm 6

MathCrypt Secure Algorithm

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sobitha Ahila, S. Kedia, Amish Singh, Manmeet Department of Computer Science Vellore Institute of Technology Chennai Chennai India

ISBN: (纸本)9798331522667

In an era where data security is paramount, this research presents MathCrypt, a novel symmetric encryption-decryption algorithm designed to address vulnerabilities in traditional cryptographic methods. Unlike conventional approaches, MathCrypt leverages numerical root-finding methods combined with the Diffie-Hellman algorithm to enhance security and computational efficiency. By integrating the Bisection, Newton-Raphson, and Secant methods into the encryption process, MathCrypt ensures robust protection against reverse-engineering attacks while maintaining scalability for large datasets. Performance evaluations demonstrate that iterative methods like Secant and Newton-Raphson significantly reduce encryption times compared to conventional approaches. this paper provides a detailed analysis of the proposed algorithm, comparing numerical techniques, and showcasing its potential for real-world cryptographic applications. the findings underline the feasibility and effectiveness of MathCrypt, paving the way for further advancements in secure communication systems. © 2025 ieee.

关键词： Encryption algorithms

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Quantum-Driven Hybrid Network Architecture Leveraging 5G for High-Speed and Resilient Data Transmission 6

Quantum-Driven Hybrid Network Architecture Leveraging 5G for...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Kumar, Kusuma Ashok Mohandas, R. Suneel, Sajja Mahalakshmi, M.R. Kumar, Avinash Singh, Manmohan Department of Physics B V Raju Institute of Technology Medak District Telangana state Narsapur502313 India Chennai Institute of Technology Chennai India Institute of Aeronautical Engineering Dundigal Telangana Hyderabad500043 India Department of ECE Sri Muthukumaran Institute of Technology Tamil Nadu Chennai600 069 India Department of Computer Science and Engineering IES College of Technology Bhopal India

ISBN: (纸本)9798331522667

the integration of quantum communication principles with 5G technology presents a groundbreaking approach to addressing the growing demand for high-speed, secure, and resilient communication systems. this paper proposes a Quantum-Driven Hybrid Network Architecture that leverages Quantum Key Distribution (QKD) for unparalleled security and combines it with 5G's ultra-fast data transmission capabilities. the architecture integrates key components such as QKD modules, 5G infrastructure, and edge computing, organized into a layered framework comprising quantum, network control, and application layers. Simulation results demonstrate significant improvements in throughput (up to 23.5%), latency reduction (up to 25%), and error rate reduction in high-noise environments (from 0.25% to 0.05%). the proposed system also exhibits enhanced security, achieving a 100% success rate in mitigating eavesdropping and man-in-the-middle attacks. Using resource-efficient mechanisms, the hybrid network achieves an overall accuracy of 97.8% in secure and resilient data transmission. this work validates the potential of quantum-enhanced 5G systems to meet the challenges of future communication networks. © 2025 ieee.

关键词： Quantum communication

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Design of Approximate Multiplier using Highly Compressed 5_2 Counter 6

Design of Approximate Multiplier using Highly Compressed 5_2...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Nelmin, Bathlin N. Shaji, R.S. Hariprasad, S. Shettygari, Sudeshna Vasan, J.K. Vijayan, V. Department of Electronics and Communication Engineering University College of Engineering Nagercoil India Department of Computer Science and Engineering St. Xavier’s Catholic College of Engineering Nagercoil India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9798331522667

Approximate computing effectively impacts low-power VLSI circuits by reducing circuit overhead. It introduces minimal error in the output, which does not significantly affect the application. this paper proposes an approximate multiplier constructed using 5_3 and 5_2 counters. the proposed 5_2 counter delivers two outputs instead of three, thereby achieving 60% compression. the overhead of the 5_2 counter circuit is reduced, achieving a power delay product (PDP) improvement of 18%. this reduction comes with an addition of an 6% error rate. the newly designed multiplier has less delay, where the Mean error distance (MED) is kept as low as possible. the complexity of the 5_2 counter is also reduced since the counter uses only a full adder and three gates. this is achieved by applying various error optimization mechanisms. the error parameters, (i) Error Distance (ED), and (ii) Mean Error Distance (MED) are analyzed and compared with existing works. the proposed multipliers are involved in image contrast application with better Peak Signal to Noise Ratio (PSNR) value. © 2025 ieee.

关键词： Delay circuits

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Advancing Healthcare with Federated Learning: Strengths, Challenges, and Methodological Concerns 6

Advancing Healthcare with Federated Learning: Strengths, Cha...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Marada, Anusha Farooqui, Yassir A. Chauhan, Ankit Department of Computer Engineering PIET Parul University Gujarat Vadodara India

ISBN: (纸本)9798331522667

Federated Learning (FL), which permits decentralized data analysis while protecting patient privacy, is quickly becoming a crucial paradigm in the healthcare industry. FL complies with strict privacy rules like GDPR and HIPAA by enabling machine learning models to train on local datasets without disclosing sensitive data. In order to in vestigate the use of FL in healthcare, this study summarizes the results of several research, with a particular emphasis on wearable technology data, medical imaging, and Electronic Health Records (EHRs). We as sess several algorithms, including Gradient Boosting Machines (GBMs) and Convolutional Neural Networks (CNNs), determining their prowess in managing complex healthcare data as well as the drawbacks they en counter, such as computational demands, high communication overhead, and non-identically Distributed (non-IID) data. conventional assessment methodologies and moral standards. this evaluation outlines the essen tial improvements for FL’s scalability and dependability across varied healthcare contexts, while also highlighting FL’s potential to change healthcare. © 2025 ieee.

关键词： Federated learning

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Integrated IoT based Smart Agriculture Monitoring System 6

Integrated IoT based Smart Agriculture Monitoring System

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Saraswathi, R. Vijaya Rahul, L. Lokeswar, S. Varma, R. Vathsav Ajay, U. Computer Science and Engineering VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad India

ISBN: (纸本)9798331522667

the adoption of IoT technology in agriculture is revolutionizing traditional farming, making it a data-driven and resource-efficient field. Proposed paper introduces an IoT-based smart agriculture monitoring system designed to provide farmers with accurate real-time insights for improved crop and resource management. the system incorporates a network of sensors to monitor essential environmental variables like soil moisture and temperature. these signals are processed by a microcontroller and securely transmitted to a cloud platform for advanced analytics. A mobile-friendly application offers actionable insights, notifications, and remote access, facilitating informed decision-making. Built on a Wi-Fi-based infrastructure, the system ensures reliable communication even in areas with inconsistent internet connectivity. Field implementations reveal notable advancements in resource utilization, crop yields, and labor efficiency. Additionally, an embedded AI module forecasts crop prices with 92% accuracy, enabling farmers to optimize sale timings for increased profitability in competitive markets. this comprehensive solution highlights the transformative potential of IoT in fostering sustainable and profitable agricultural practices. © 2025 ieee.

关键词： Smart agriculture

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Applying Johnson's Algorithm for Efficient Shortest Path Analysis in Big Data 6

Applying Johnson's Algorithm for Efficient Shortest Path Ana...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Mohankumar, N. Reddy, P.L. Kishan Kumar Uthayakumar, C. Parkavi, S. Rajmohan, M. Srinivasan, C. Maharastra Pune India Andhra Pradesh Guntur India Department of Electronics and Communication Engineering Vivekanandha College of Engineering For Women Tamil Nadu Tiruchengode India Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College Tamil Nadu Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798331522667

In this paper, Johnson's Algorithm is employed for Big Data shortest route analysis. Its efficiency and efficacy in managing massive datasets to improve data processing and decision-making is studied. To solve big dataset’s computing problems, Johnson's Algorithm, which efficiently finds shortest routes in networks with negative edge weights, is used. this method optimizes route analysis operations in Big Data settings to extract insights faster and more accurately. the study shows Johnson's Algorithm's viability and advantages in big data analytics, possibly enabling its use in network routing, transportation optimization, and social network analysis. three cases are shown in Sample City Distance Matrix data. the initial Original Distance Matrix data was collected in a random sample of 5 cities and showed a 10-43 km range. In the second Reweighted Matrix with Potential Values instance, data from 5 random cities was collected to calculate the shortest route with a minimum and maximum km of 5-30 km. the data from the third Final Shortest Path Matrix in a random sample of 5 cities is relevant for transportation planning and network optimization with a minimum and maximum distance of -3 and -21 kilometers. © 2025 ieee.

关键词： Data accuracy

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Design and Development of IoT Smart Driving Protocol for Unmanned Ground Vehicles 6

Design and Development of IoT Smart Driving Protocol for Unm...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Seelam, Santhosh Kumar Nagakishore Bhavanam, S. Midasala, Vasujadevi Reddy, Edara Sreenivasa Department of Computer Science and Engineering University College of Engineering and Technology Acharya Nagarjuna University Andhra Pradesh Guntur India Jabalpur Madhya Pradesh Barela India Department of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India

ISBN: (纸本)9798331522667

UGVs have enormous potential in industries such as defense, agriculture, and autonomous transportation. Efficiency and effectiveness can be achieved by UGVs through the sophistication of their control systems, mainly with regard to navigation and decision-making. In this study, a new IoT-based smart direction control system is proposed for UGVs. the system presented herein integrates state-of-the-art sensor fusion techniques against the backdrop of a robust and adaptive communication framework for enhanced navigation accuracy and reduced latency, with the overall goal of improving system efficiency. Equipped with GPS, IMU, and LiDAR sensors, our system provides accurate environmental perception and real-time adaptability to various terrains. the heart of this device is a high-performance, military-grade microcontroller, which ensures the reliability and handling of numerous data streams simultaneously with minimal latency. On the software side, modular design makes use of edge computing and machine learning algorithms to facilitate adaptive control and real-time decision-making. the performance was verified by rigorous testing in simulated environments and real-world field trials. the results show an improvement in the navigation accuracy and system responsiveness compared to previous solutions. A comparative deep analysis shows the superiority of our approach to hardware design, software integration, and prototype testing. © 2025 ieee.

关键词： Adaptive control systems

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