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检索条件"机构=R&D Department of Security Technology Platform"

共 114 条记录，以下是31-40 订阅

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Logistic regression for Personalized Hypertension risk Profiling in Cloud-Integrated Healthcare Systems

Logistic Regression for Personalized Hypertension Risk Profi...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Saravanan, S. ramya, S. Monikapreethi, S.K. Kavididevi, Venkatesh Kovarasan, rajesh Kambattan Sujatha, S. Department of Electrical and Electronics Engineering Muthayammal Engineering College Tamil Nadu Namakkal India Department of Cyber Security Paavai Engineering College Tamil Nadu Namakkal India Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Tamil Nadu Chennai India Department of Information Technology Vardhaman College of Engineering Telangana Hyderabad India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350374933

Advanced analytics for personalized chronic disease risk profiles are becoming possible as healthcare systems combine cloud-based technology. This work applies logistic regression (Lr) models to cloud-integrated healthcare systems for personalized hypertension risk profiling. A large dataset of heterogeneous patient records was used to train and evaluate the Lr model, including clinical characteristics and lifestyle variables. To assess the Lr model's predictive accuracy in identifying high-risk hypertension patients and to provide a framework for personalized risk stratification that can be seamlessly integrated into cloud-based healthcare systems. The model's performance was rigorously cross-validated and compared to risk assessment methods. The Lr approach predicted hypertension risk better than older techniques. Healthcare professionals and patients found the cloud integration of the personalized risk profiling system convenient, scalable, and accessible. It shows that cloud-based analytics may improve preventive healthcare by personalizing treatments to risk profiles. Lr techniques can optimize personalized hypertension risk management in cloud-integrated systems, advancing data-driven healthcare. © 2024 IEEE.

关键词： Cloud Integration Healthcare Systems Hypertension risk Personalized Medicine Predictive Modeling

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A Comprehensive Analysis of Smart Home Applying Natural Language Processing Using Internet of Technologies 2

A Comprehensive Analysis of Smart Home Applying Natural Lang...

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2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Ahamad, Shahanawaj Shah, deepalkumar Udhayakumar, r. rajeswari, T.S. Khatiwada, Pankaj Alanya-Beltran, Joel University of Hail College of Computer Science and Engineering Saudi Arabia Gujarat University Jg College of Computer Applications India VelTech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of English India Koneru Lakshmaiah Education Foundation Department of English AP Vaddeswaram India NTNU: Norwegian University of Science and Technology Department of Information Security and Communication Technology Norway Universidad Tecnológica Del Peru Electronic Department Peru

ISBN: (纸本)9781665437899

The Internet of Thigs is mainly considered as the key technology tools which enables in connecting many devices through the use of internet, this has enabled in overall exchange of data and information, support in receiving the instruction and enable in acting upon it in an effective manner. With the advent of IoT, many devices are connected to the internet which enable in assisting the individuals to operate the devise virtually, share data and program required actions. This study is focused in understanding the key determinants of creating smart homes by applying natural language processing (NLP) through IoT. The major determinants considered are Integrating voice understanding into devices;Ability to control the devices remotely and support in reducing the energy bills. The present study focuses in sourcing the data from both sources and information are collected through the usage of questionnaire and the information are quantitatively applied through 5-point Likert scale. The researchers use extensive data analysis tools using AMOS for understanding the path diagram using structural equation model. © 2022 IEEE.

关键词： Internet of things

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Optimizing diagnostic Accuracy in Ultrasound Imaging Through Cloud-Enabled deep Learning Techniques

Optimizing Diagnostic Accuracy in Ultrasound Imaging Through...

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Soft Computing for security Applications (ICSCSA), International Conference on

作者： V. Kalpana Girija M K. Tharageswari d. Yobu J. revathi r. Aruna Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India School of Engineering and Technology Jeppiaar University Chennai India Department of Computer Science and Engineering Karpagam Academy of Higher Education Coimbatore India Computer Science and Engineering Cyber Security J.J College of Engineering and Technology Tricy India Department of Mathematics Kongu Engineering College Erode India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515737

This research aims to study predicting and optimizing the diagnostic accuracy by cloud-enabled deep learning techniques in ultrasound imaging for kidney disease diagnosis. The main findings are that CNN gives 92% accurate outcomes in terms of sensitivity, precision, specificity, AUC-rOC, and other terms used for predictive outcomes in the current research. The other outcomes are 88% accuracy and 91% specificity in predicting kidney diseases by using the rNN model. The other two models used for learning are transfer learning and federated learning which also provide good outcomes which are 94% accurate and 91% accurately in diagnosing with the above-said models. These learning approaches optimize or increase the accuracy rates such as 93% by the transfer learning approach and 90% accuracy outcomes by the federated learning mechanism. These above-given models have been taken based on advanced technologies that are used to predict or forecast the diseases through learning processes. The success of these learning mechanisms is explained by the reliable processes used in the learning of the models that are possible by the neural network used in the learning mechanisms. The high accuracy rates of the models show the successfulness of such clinics, who are in rural areas and are unable to meet their necessary outcome-oriented goals, then measures can be taken for running tele-clinics using the above models of learning techniques to diagnose the diseases at the correct time by ‘n’ number of people in rural areas. Mine is one of them working as a health worker for which measures need to be taken for finding an accurate solution that operates on cloud-enabled deep learning. This model help run family life and be able to diagnose certain conditions at desired rural clinics out of the above learning models. These tools of learning are studied on cloud-based deep learning techniques and performed well in diagnosing kidney diseases on rural tele-medicine and these learning techni

关键词： deep learning Accuracy Ultrasonic imaging Federated learning Telemedicine Transfer learning Imaging Predictive models Kidney diseases

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Optimized retrieval of data from Cloud using Hybridization of Bellstra Algorithm

Optimized Retrieval of Data from Cloud using Hybridization o...

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Communication & Computing (WCONF), World Conference on

作者： K. Yashwanth Kumar N. Jagadish Kumar d. dhinakaran S. M. Udhaya Sankar U. Janish Kumar V. Yuvaraj Department of Information Technology Velammal Institute of Technology Panchetti Chennai India Department of CSBS Sri Sairam Engineering College Chennai India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of CSE(Cyber Security) R.M.K College of Engineering and Technology Chennai India

Vast volumes of data may be stored efficiently and affordably on the cloud. The data's true worth rests in the capacity to rapidly and effectively access it when we need it. In cloud computing, data retrieval is essential since data are usually shared by several data centers making it difficult to assure the great performance and most systematic use of resources. In this proposed paper a novel approach has been introduced to optimized retrieval of data from cloud is proposed. Hybridized dijkstra and Bellman-ford algorithms has used for optimal retrieval of data. Here, nodes represent places where data is stored and edges for the network connections that connect them. Then the shortest distance has been calculated even with negative weighted edges and data are retrieved. The proposed algorithm has an enhanced performance when compared to Binary search and BTree.

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IoT Based Automated Irrigation System for Agricultural Activities

IoT Based Automated Irrigation System for Agricultural Activ...

引用

International Conference on Advanced Computing, ICAC

作者： M. Keerthana d. dhinakaran M. Ananthi r. Harish S. M. Udhaya Sankar M. Sai Sree Department of Information Technology Velammal Institute of Technology Panchetti Chennai India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of CSBS Sri Sairam Engineering College Chennai India Department of CSE(Cyber Security) R.M.K College of Engineering and Technology Chennai India

The automated irrigation systems (AIS) using IoT is a contemporary technology that boosts crop productivity and also save water. By using IoT we have found out best solution for farmer’s hard work. A sophisticated irrigation system uses the appropriate quantity of water in the proper location by operating gate valve. It reduces effort and saves time. Furthermore, it makes a nations food self-sufficient. The typical watering system requires a lot of time however AIS automation reduces this time. By employing IoT sensors and devices to monitor and manage the water supply, it is intended to automate the process of watering crops. This system gathers data on temperature, humidity, as well as soil moisture in actual time, and utilizes this information to establish the timing and amount of irrigation for the crops. Modern agriculture may benefit from the adoption of IoT-based smart irrigation systems since they can reduce water use significantly, boost crop yields, and improve resource management. It may also gauge the amount of water in a field of land for this reason, automated irrigation system has been designed with sensors, fast chargers and battery, it needed the appropriate quantity of current. Users’ computers and smartphones may simply access any processes which occurs on land.

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A Comprehensive Usage of AI in Prevention of Social Engineering Attack

A Comprehensive Usage of AI in Prevention of Social Engineer...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Vishal Jain Bishwajeet Pandey Laura Aldasheva Pranav Shukla Pushpanjali Pandey damini Jain Technical Head- Cyber Security Global Institute of Cyber Security Noida India Department of MCA GL Bajaj College of Technology and Management Greater Noida India Dept of IS&CS Astana IT University Astana Kazakhstan Software Engineer 2 Deloitte Lucknow India Department of R&D Gyancity Research Consultancy Greater Noida India Managing Director CyberiumX Delhi India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

AI has become a tool for social engineering attackers, enhancing the likelihood of successful attacks. However, as the saying goes, "diamonds cut diamonds." In this research, we have enlisted the usage of AI to initiate, launch, counter and prevent social engineering attacks. We have explored not only traditional forms of social engineering attacks with AI, such as phishing, eavesdropping, shoulder surfing, dumpster diving, piggybacking, and tailgating but also the latest forms of AI-enabled social engineering attacks, known as vishing, baiting, Smishing, Whaling, Quishing and Quid Pro Quo. This research paper also conducted a systematic literature review of AI-based defending techniques like AI Sentry,

关键词： Hands Computer hacking Phishing Prevention and mitigation Message services diamond Artificial intelligence Computer crime Faces Systematic literature review

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A research on Metaverse and its Application

A Research on Metaverse and its Application

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Communication & Computing (WCONF), World Conference on

作者： B.G. Sai Aswin S. Vishnubala d. dhinakaran N. Jagadish Kumar S. M. Udhaya Sankar A.M. Mohamed Al Faisal Department of Information Technology Velammal Institute of Technology Panchetti Chennai India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of CSBS Sri Sairam Engineering College Chennai India Department of CSE(Cyber Security) R.M.K College of Engineering and Technology Chennai India

As a potential development of the internet and virtual reality technologies, the idea of the Metaverse has received a lot of interest recently. The goal of this abstract is to give a thorough understanding of the Metaverse by examining its concept, distinguishing characteristics, prospective uses, and societal ramifications. First, the abstract begins by exploring the definition and fundamental components of the Metaverse. The abstract talks about the value of standards and interoperability in maintaining a consistent Metaverse experience across various platforms and gadgets. Next, the abstract then lists the distinctive characteristics of the Metaverse. These consist of user-generated content, real-time interactions, persistent virtual worlds, and artificial intelligence *** potential uses of the Metaverse in numerous domains are further explored in the abstract. This summary concludes by giving a thorough description of the Metaverse and highlighting its potential as a ground-breaking technical development. It highlights the value of cross-disciplinary cooperation and proactive participation from diverse stakeholders to responsibly create the Metaverse’s future while preserving a balance between innovation, morality, and societal well-being.

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Levarging Blockchain for Transparency in Agriculture Supply Chain Management Using IoT and Machine Learning

Levarging Blockchain for Transparency in Agriculture Supply ...

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Communication & Computing (WCONF), World Conference on

作者： M. Harini d. dhinakaran d. Prabhu S. M. Udhaya Sankar V. Pooja P. Kokila Sruthi Department of Information Technology Velammal Institute of Technology Panchetti Chennai India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of CSBS Sri Sairam Engineering College Chennai India Department of CSE(Cyber Security) R.M.K College of Engineering and Technology Chennai India

India’s agriculture industry is diversified and has the capacity to feed the second-largest population in the world. despite of its significance the existing agriculture methodology suffers due to various issues like no proper supply chain management and the transparency in the data. Thus, blockchain technology has greatly increased in popularity across a variety of industries due to its distinctive qualities of immutability, transparency, and security. The work is concerned with remarkable growth of the agriculture sector with the help of blockchain technology. Blockchain technology can assist in lowering the number of middlemen in the supply chain, which will lower transaction costs and boost farmer profit margins. Blockchain technology can also help reduce fraud, improve food safety and quality management, and guarantee fair prices for farmers. It involves the use of IOT sensors to generate data from the crops like climatic changes, soil moisture etc. The generated data is analyzed by using machine learning algorithms like image processing for crop disease prediction. The organized content is subsequently saved as a block in the blockchain ledger. A smart contract is made between the stakeholders involved which leads to the transparency of the transaction and this promotes a good growth in the supply chain management. It also makes it easy for the farmers to claim their insurance as each data is stored in an immutable and transparent ledger. Thus, the proposed methodology of combining blockchain with agriculture boost the efficiency and potential of the agriculture sector.

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A Comprehensive Usage of AI in Prevention of Social Engineering Attack 14

A Comprehensive Usage of AI in Prevention of Social Engineer...

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14th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2025

作者： Jain, Vishal Pandey, Bishwajeet Aldasheva, Laura Shukla, Pranav Pandey, Pushpanjali Jain, damini Global Institute of Cyber Security Noida India Department of MCA GL Bajaj College of Technology and Management Greater Noida India Dept of IS&CS Astana IT University Astana Kazakhstan Deloitte Lucknow India Department of R&D Gyancity Research Consultancy Greater Noida India CyberiumX Delhi India

ISBN: (纸本)9798331531935

关键词： Sociology

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Fish Farm Monitoring System Using IoT

Fish Farm Monitoring System Using IoT

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： K.V. Kishore d. dhinakaran N. Jagadish kumar S. M. Udhaya Sankar K. Chandu L. Maria Michael Visuwasam Department of Information Technology Velammal Institute of Technology Chennai India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of CSBS Sri Sairam Engineering College Chennai India Department of CSE(Cyber Security) R.M.K College of Engineering and Technology Chennai India Artificial Intelligence and Data Science R.M.K College of Engineering and Technology Chennai India

Fish aquaculture is an essential sector of the economy; it has seen rapid expansion in recent years. It can be challenging to manage a fish farm, though, as it demands continual attention to environmental parameters like water quality and temperature. In this study, we offer a monitoring system for fish farms that leverages IoT technology to gather and process data from sensors placed inside a fish farm. When any parameters are outside the specified range, the system notifies the farmer and provides real-time monitoring of water quality, temperature, and other environmental conditions. The method comprises a network of wireless sensors connected to a central computer and installed across the fish farm. The server gathers and analyses the sensor data before giving the farmer real-time access via a web-based interface. The fish farmer can utilize this interface to keep an eye on the fish farm's water quality and temperature as well as to change the feeding schedule and other environmental factors as needed. The system has undergone testing in a commercial fish farm, and the outcomes indicate that it successfully keeps track of the environmental conditions there. The technology can increase fish farming's productivity and profitability while minimizing its adverse environmental effects.

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