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Securing Sensitive Data: How Blockchain Transforms Privacy in Healthcare, Law, and Education

Securing Sensitive Data: How Blockchain Transforms Privacy i...

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Bale, Ajay Sudhir Arulananth, T.S. Saranya, S. Gadag, Tejashwini Sathiamoorthy, J. Ponnuru, Sudhakiran New Horizon College of Engineering Dept. of Ece Karnataka Bengaluru India Mlr Institute of Technology Department of Electronics and communication Engineering Telangana Hyderabad500043 India Bms Institute of Technology & Management Dept. of Mathematics Bengaluru India School of Computer Science Engineering Reva University Bengaluru India Rmk Engineering college Department of Computer science and Design Kavarapettai India

ISBN: (纸本)9798331543617

In the field of healthcare, law, and education, Blockchain technology (BT) is emerging as a transformative force. This paper helps to explore the usage of BT to enhance the privacy and security in the above said domains. In healthcare industry, blockchain offers privacy and secure management of the vital electronic health records (EHR) and patient health records (PHR), boosting the data integrity and access control. In the law sector, blockchain-enabled smart contracts are providing new possibilities for the transactions automation, transparency, and security of the transactions, thoroughly facing the challenges in terms of jurisdiction and compliance with regulations like GDPR. In the field of education, blockchain technology is improvising the record-keeping, degree verification, and collaborative learning environments. The paper helps to examine the features like the effectiveness, efficiency, and security aspects of blockchain implementations in these sectors, focusing on both the potential benefits and the challenges imposed that need to be addressed for the widespread adoption in real time. © 2024 IEEE.

关键词： Electronic health record

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Hybrid near- and far-field three-stage beam training with beam split for RIS-assisted OFDM communications

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Frontiers of Information Technology & Electronic engineering 2024年第12期25卷 1664-1678页

作者： Zhichao CHENG Shupei ZHANG Shu FU Boya DI School of Electronics Engineering and Computer Science Peking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks School of ElectronicsPeking UniversityBeijing 100871China Department of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

With the development of millimeter-wave(mmWave)communication systems,large-scale reconfigurable intelligent surfaces(RISs)have gained considerable attention as a promising technology for signal strength enhancement and coverage ***,as the antenna scale and bandwidth increase,RIS-assisted wideband orthogonal frequency division multiplexing(OFDM)communication systems face challenges due to the near-field range expansion and the beam split effect over the high-frequency band,complicating the acquisition of channel state information(CSI).To tackle these challenges,we present a codebook-based three-stage beam training scheme by using the beam split effect to bypass CSI ***,by analyzing the beam split effect in RIS-assisted OFDM communication systems,we propose a beam-split-aware codebook capable of covering both the near and far fields with fewer codewords compared to conventional narrow-band *** such a codebook,a three-stage beam training mechanism is adopted to obtain the optimal codeword with low time overhead,thereby facilitating subsequent *** results demonstrate that the proposed scheme outperforms existing near-and far-field codebook-based schemes in terms of the beam training resolution and sum rate in the hybrid near–far field.

关键词： Near-far field Beam split Codebook design Beam training Reconfigurable intelligent surfaces

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A Comprehensive Evaluation of Fake Face Recognition Scheme using Artificial Intelligence Oriented Learning Scheme 1

A Comprehensive Evaluation of Fake Face Recognition Scheme u...

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1st International Conference on Pioneering Developments in computer Science and Digital Technologies, IC2SDT 2024

作者： Subashree, S. Rose S, Remya Valarmathy, A.S. Joseph, Princy Dennis, P. Jasmin Ravi, S. E.G.S. Pillay Engineering College Department of Computer Science and Engineering Tamil Nadu Nagapattinam India R.M.D. Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India CMR College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Vi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India Saveetha University Department of VLSI Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350365016

Fake face recognition has emerged as a critical area of research due to the proliferation of synthetic media and its potential misuse in various domains. This study presents a thorough evaluation of a novel Fake Face Recognition Scheme utilizing Artificial Intelligence Oriented Learning Scheme (AIOLS) coupled with Generative Adversarial Network (GAN)-GoogleNet integration. The aim is to discern authentic facial images from synthetic or tampered ones with high accuracy. In this research, we employed a dataset comprising a diverse range of authentic and synthetic facial images. The proposed scheme incorporates the power of GANs for generating synthetic facial images and leverages GoogleNet, a state-of-the-art deep convolutional neural network, for discriminative feature extraction. The integration within the AIOLS framework facilitates efficient learning and adaptation to complex patterns present in fake facial images. The evaluation of our scheme was conducted through rigorous experimentation on the dataset, employing various performance metrics. Notably, the accuracy obtained was measured at an impressive 96.7%, signifying the effectiveness of our approach in distinguishing between real and fake facial images. Additionally, other metrics such as precision, recall, and F1-score were also computed to provide a comprehensive assessment of the scheme's performance. © 2024 IEEE.

关键词： Generative adversarial networks

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Parkinson's Disease Detection by Machine Learning

Parkinson's Disease Detection by Machine Learning

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Nalini, M. Kinol, Mary Joy Bommi, R.M. Vijayaraj, N. Sri Sairam Engineering College Electronics and Instrumentation Engineering Chennai India Saveetha School of Engineering Simats Department of Ece Chennai India Chennai Institute of Technology Department of Ece Chennai India School of Computing Vel Tech Rangarajan Dr. Sangunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350394580

Parkinson's disease is a special type of neurological condition which is quite common and has an impact on people's lives all over the world. For the condition to be successfully treated and managed, early detection, attention and diagnosis are very essential. Recent research has demonstrated that early signs of Parkinson's disease might include changes in speech, such as those in speaking rate and voice quality. In this study, this paper suggests a brand-new method for identifying this Parkinson's disease using speech alterations. In this paper, we introduce a machine-learning model that can analyze speech samples and reliably identify Parkinson's illness. Our methods are based on the examination of several speech characteristics, including pitch, jitter, and shimmer, which are well-known to be impacted by the illness. Our results show that our method performs well when applied to a dataset of speech samples from people with and without this disease. © 2023 IEEE.

关键词： Artificial Intelligence Early Detection Machine Learning algorithms Parkinson's Disease Speech Changes SVM

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Advancements in Wireless Networks: Transition from 5G to Beyond 2

Advancements in Wireless Networks: Transition from 5G to Bey...

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Thangavel, Gunasekaran Malarvizhi, C. Banu, M. Ameena Anthonisamy, Arun Hemalatha, M. Manikandan, Raja University of Technology and Applied Sciences Department of Electronics and Communication Engineering Muscat Oman Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Chembarambakkam India NPR College of Engineering and Technology Department of Electronics and Communication Engineering Natham India Panimalar Engineering College Department of Computer Science and Business System Tamil Nadu Chennai600123 India Nandha Arts and Science College Department of Information Technology Tamil Nadu Erode638052 India K. Ramakrishnan College of Technology Department of ECE Tamil Nadu Trichy India

ISBN: (纸本)9798331534950

Earlier generations of mobile technology experienced exponential growth in mobile customers, disruptive ecosystems like Internet of Things applications, and massive channel capacity needed to connect trillions of devices. 5G networks are a vital solution. 5G aims to provide 10 Gbps to a single user, as well as quality of service, increased spectrum efficiency, ultra-reliable communication, extended device battery life, massive machine-type communication (mMTC), and a 1000-fold capacity gain. Due to the heavy traffic volume and high resource consumption of 5G applications like augmented reality (AR), virtual reality (VR), and wireless body area networks, there are major barriers to channel capacity and potential service disruptions for other users. New strategies are needed to increase spectral efficiency and channel capacity. This paper explores many major new wireless technologies that aim to increase spectral efficiency and channel capacity to meet growing user demands and improve network performance. This paper also examines these technologies' benefits and research challenges. Massive Multi-Input Multi-Output (mMIMO) technology's effectiveness and potential distinguish it for 5G and Beyond 5G (B5G) networks, offering a variety of benefits and characteristics. This article can also assist researchers who are conducting in-depth studies, as well as wireless network operators who aim to streamline the development of 5G and B5G networks. © 2024 IEEE.

关键词： 5G mobile communication systems

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A Comprehensive Evaluation of Deep Learning based Melanoma Detection and Classification Scheme 2

A Comprehensive Evaluation of Deep Learning based Melanoma D...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and electronics, ICIITCEE 2024

作者： Ramesh, T. Vigneash, L. Samraj, S. Shalom, S. Preena Jacinth Maheshwari, B. Kamatchi, S. R.M.K Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Arjun College of Technology Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Eee Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Ece Tamil Nadu Chennai India

ISBN: (纸本)9798350306415

As the global population ages, skin cancer has emerged as one of the leading malignancies. The earlier skin cancer is detected, the better the prognosis. Increases in automated healthcare diagnosis systems can be directly attributed to the widespread adoption of deep learning algorithms in other sectors. In this study, deep learning is proposed as a means of accurate lesion zone extraction. While interventional treatments like surgery, radiation, and chemotherapy form the basis of cancer diagnosis, research suggests that emerging computer technologies, namely image processing mechanisms, can aid physicians in the crucial early stages of cancer treatment. In this study, we offer a technique for automatically identifying skin cancer in dermoscopy pictures. The suggested model, which made use of convolutional functions and depth wise separable convolutions, has been given the name Modified Learning based Melanoma Detection (MLMD). The framework's accuracy in classification is unquestionably higher than that of the network's initial learning phase and other possible dome topologies. Simulations comparing the suggested method to other similar modern techniques for malignancy detection show that the suggested technique achieves higher accuracy. To clearly evaluate the efficacy of the suggested model, it is cross-validated using the traditional learning method known as Convolutional-Neural-Network (CNN). © 2024 IEEE.

关键词： Classification Deep Learning Healthcare Melanoma Detection MLMD Modified Learning based Melanoma Detection Prediction Skin Cancer

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Comparative Analyses of Multi-Wavelength Converters Based on Electro Absorption Modulators at Various Data Rates

Comparative Analyses of Multi-Wavelength Converters Based on...

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2023 IEEE World Conference on Applied Intelligence and Computing, AIC 2023

作者： Kaur, Taranjeet Kaur, Jatinder Jambu, Mohit Saxena, Aditi Shah, Sanjeev Kumar Saxena, Antima Chandigarh Engineering College Department of Ece Jhanjeri Mohali140307 India Gulzar Group of Institutes Eee Department Punjab Khanna141401 India Gla University Department of Ece Mathura281406 India Uttaranchal Institute of Technology Uttaranchal University Electronics and Communication Engineering Dehradun248007 India Ies College of Technology Department of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350310061

The performance analysis of an electro absorption modulator based multi-wavelength converter that uses a radio frequency generator has been investigated at various input powers (ranging from -3 dBm to 10 dBm) and at various data rates (5 Gbps, 10 Gbps, and 20 Gbps). This was done in order to eliminate the need for an additional pump signal by utilising the RZ (Return to Zero) modulation format. This was done in order to make the solution a more cost-effective one. In this article, a comprehensive investigation of the trade-off between diverse power and varied data rate has been carried out. The input power and data rate are the two most essential operational parameters for wavelength conversion. Because of this, the effect of input power and data rate on the performance of wavelength conversion is investigated in great depth by monitoring the timing diagrams of the signal that has been wavelength converted. © 2023 IEEE.

关键词： Cost effectiveness

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Modified Whale Optimization Algorithm for Task Scheduling in Cloud Computing 2

Modified Whale Optimization Algorithm for Task Scheduling in...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Girirajan, B. Nijaguna, G.S. Pramodhini, R. Adnan, Myasar Mundher Shivakanth, Gandla SR University Department of ECE Telangana Warangal India S.E.A. College of Engineering and Technology Department of Information Science and Engineering Bangalore India Nitte Meenakshi Institute of Technology Yelahanka Department of Electronics and Communication Engineering Bengaluru India The Islamic University Najaf Iraq Koneru Laksmaiah Education Foundation Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350317558

In recent years, an efficiency of task scheduling is evolved as a major challenge in cloud platforms. Especially, identifying the optimal resources for input tasks is the major challenges faced by the task scheduler. So, in this research, a Modified Whale Optimization Algorithm (MWOA) is proposed to improve the behaviour in task scheduling by applying the parameters such as resource allocation and load balancing. Capacity criteria based MWOA algorithm determines the effective Virtual Machine (VM) for execution of tasks in queue. An effectiveness of proposed WOA algorithm is analysed by the utilization of performance measures such as memory storage, execution time, cost and makespan. The attained results from the proposed WOA algorithm are outperformed in various predictable optimization algorithms such as Storm, Spark, Flink and Kafka. The results of proposed WOA algorithms demonstrates the better performances in minimum execution time of 612ms, and memory storage of 309Kb on Kafka platform. © 2024 IEEE.

关键词： Load Balancing Modified Whale Optimization Algorithm Optimal resources Resource Allocation Task Scheduling

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Industrial and Home Automation using Facebook Messenger Chatbot and PaaS 3

Industrial and Home Automation using Facebook Messenger Chat...

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

作者： Selvalakshmi, S. Ravi, S. Kumar, A.T.A. Kishore Devi, S. Durga Sunheriya, Neeraj Attar, Hani Rmk Engineering College Department of Electronics and Instrumentation Engineering Chennai India Saveetha School of Engineering Department of Vlsi Microelectronics Chennai India School of Engineering Department of Ece Andhra Pradesh Tirupati India Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Cse Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Zarqa University Department of Energy Engineer Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331509675

A set of communication protocols that allows interconnected devices on the internet to communicate with each other. A proposed IHM-FMP model integrates Messenger Chat bot functionality and Platform as a Service (PaaS) architecture for efficient home automation and security. Utilizing hardware components like Raspberry Pi, relay modules, and sensors, along with TCP/IP protocol for internet connectivity, the system enables remote control of home appliances and security features. Through Messenger Chat bot integration, users can easily command devices via Facebook Messenger, enhancing accessibility. The PaaS method ensures control with layers for remote access and management. Experimental results demonstrate the model's superiority in network throughput, delay, routing overhead, transmission accuracy, and energy efficiency compared to existing techniques. This holistic approach to home automation and security offers convenience, accessibility, and robust performance, making it an effective solution for modern households. © 2025 IEEE.

关键词： Chatbots

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MPC Controller Design For Multiple Input And Multiple Output System

MPC Controller Design For Multiple Input And Multiple Output...

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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Lavanya, M. Jayamanmadharao, M. Sonia, Bankuru Praveen, R.V.S. Sarkar, Rashel Chitra, D. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electrical & Electronics Engineering Thandalam India Aditya Institute of Technology and Management Department of Ece Tekkali India Department of Eee Visakhapatnam India Organization - LTIMindtree India The Assam Royal Global University Department of Computer Science and Engineering Assam India Panimalar Engineering College Mba Department Varadharajapuram India

ISBN: (纸本)9798350375442

This paper explores the application of Model Predictive Control (MPC) in multiple input and multiple output (MIMO) processes, focusing on redesigning the MPC system for a four-tank system known as Quadruple. MPC is utilized in process industries to forecast future controller outputs and minimize system costs by determining optimal future control actions. Control action rates and plant outputs are adjusted by modifying weight matrices. The specified prediction and control horizons serve as key control parameters. The redesign of the MPC system for the Quadruple system involves designing and implementing it using LABVIEW software. LABVIEW simplifies the complexity of MPC controller design and implementation. The primary objective of four-tank system is to maintain consistent fluid levels in each tank, with LABVIEW facilitating the implementation of automatic controllers for effective control in process plants. © 2024 IEEE.

关键词： Model predictive control

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