Results for 'Selvan Arul'

26 found
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  1.  44
    Scalable Encryption Protocol for Searchable Data Management in IoT Systems.S. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):409-415.
    As the Internet of Things (IoT) continues to expand, ensuring secure and efficient data storage and retrieval becomes a critical challenge. IoT devices, often constrained by limited computational resources, require lightweight encryption protocols that balance security and performance. This paper presents an optimized encryption protocol designed specifically for lightweight, searchable data in IoT environments. The proposed protocol utilizes advanced optimization techniques to enhance the efficiency and security of searchable encryption, enabling rapid data retrieval without compromising the integrity and confidentiality of (...)
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  2.  65
    Efficient Aggregated Data Transmission Scheme for Energy-Constrained Wireless Sensor Networks.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):445-460.
    Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. The proposed approach is validated through extensive simulations, demonstrating significant improvements in energy consumption, packet delivery ratio, and overall network performance. The results suggest that the optimized aggregated packet transmission method can effectively extend the lifespan of duty-cycled WSNs while ensuring reliable data communication. Future (...)
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  3.  64
    Cloud-Based Secure Storage: A Framework for Efficient Encryption, Decryption, and Data Dispersion.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):427-434.
    The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, ensuring that no single server (...)
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  4.  64
    Advanced Driver Drowsiness Detection Model Using Optimized Machine Learning Algorithms.S. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):396-402.
    Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...)
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  5.  32
    PHISHING CONTENT CLASSIFICATION USING DYNAMIC WEIGHTING AND GENETIC RANKING OPTIMIZATION ALGORITHM.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):471-485.
    Phishing attacks remain one of the most prevalent cybersecurity threats, affecting individuals and organizations globally. The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the detection (...)
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  6.  51
    Bridging Professional and Personal Lives: The Role of Telemedicine in Doctors' Work-Life Equilibrium.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):520-535.
    The rapid adoption of telemedicine has transformed healthcare delivery, especially during the COVID-19 pandemic. This digital shift has enabled medical professionals to offer consultations and manage patients remotely, ensuring continuity of care while reducing exposure risks. However, the integration of telemedicine has presented both opportunities and challenges for doctors, particularly in terms of their work-life balance. This paper explores the digital adaptation of doctors in public and private hospitals concerning telemedicine practices and its impact on their work-life harmony. The study (...)
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  7. RAINFALL DETECTION USING DEEP LEARNING TECHNIQUE.M. Arul Selvan & S. Miruna Joe Amali - 2024 - Journal of Science Technology and Research 5 (1):37-42.
    Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...)
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  8.  79
    AI-Driven Emotion Recognition and Regulation Using Advanced Deep Learning Models.S. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):383-389.
    Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...)
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  9.  60
    Optimized Attribute-Based Search and Secure Storage for Cloud Computing Environments.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):361-370.
    In the modern digital era, cloud storage has become an indispensable service due to its scalability, accessibility, and cost-effectiveness. However, with the vast amount of sensitive information stored on cloud platforms, ensuring data security and privacy remains a critical challenge. Traditional encryption techniques, while secure, often hinder efficient data retrieval, especially when using keyword searches. To address this, attribute-based keyword search (ABKS) offers a promising solution by allowing secure, fine-grained access control and efficient keyword searches over encrypted data.
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  10.  68
    Artificial Intelligence in HR: Driving Agility and Data-Informed Decision-Making.Madhavan Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):506-515.
    In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions in hiring, (...)
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  11.  47
    3D Convolutional Neural Networks for Accurate Reconstruction of Distorted Faces.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (4):560-570.
    The core objective of this project is to recognize and reconstruct distorted facial images, particularly in the context of accidents. This involves using deep learning techniques to analyze the features of a distorted face and regenerate it into a recognizable form. Deep learning models are wellsuited for this task due to their ability to learn complex patterns and representations from data the input data consists of distorted facial images, typically obtained from MRI scans of accident victims. These images may contain (...)
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  12.  61
    Innovative Approaches in Cardiovascular Disease Prediction Through Machine Learning Optimization.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):350-359.
    Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized through (...)
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  13.  81
    (1 other version)A PBL REPORT FOR CONTAINMENT ZONE ALERTING APPLICATION.M. Arul Selvan - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):233-246.
    The World Health Organization has declared the outbreak of the novel coronavirus, Covid-19 as pandemic across the world. With its alarming surge of affected cases throughout the world, lockdown, and awareness (social distancing, use of masks etc.) among people are found to be the only means for restricting the community transmission. In a densely populated country like India, it is very difficult to prevent the community transmission even during lockdown without social awareness and precautionary measures taken by the people. Recently, (...)
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  14. IoT-Integrated Smart Home Technologies with Augmented Reality for Improved User Experience.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):389-394.
    The paper also discusses the technical architecture, including the network protocols, data management strategies, and user interface design considerations necessary to implement such a system. Additionally, it addresses the challenges related to data security, privacy, and system interoperability. Finally, the paper outlines potential future enhancements, such as the incorporation of AI-driven predictive analytics and advanced AR features, to further elevate the smart home experience.
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  15. SVM-Enhanced Intrusion Detection System for Effective Cyber Attack Identification and Mitigation.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):397-403.
    The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational overhead. By leveraging (...)
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  16. Deep Learning Techniques for Comprehensive Emotion Recognition and Behavioral Regulation.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):383-389.
    Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...)
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  17. Transforming Consumer Behavior Analysis with Cutting-Edge Machine Learning.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):360-368.
    The research outlines a workflow that incorporates data collection, preprocessing, model training, and optimization. Real-world datasets from retail and e-commerce sectors are utilized to validate the proposed methodology, showcasing substantial improvements in model performance. The results indicate that optimized models not only provide better predictions of consumer behaviour but also enhance customer segmentation and targeting strategies. The study concludes with recommendations for future research, including the exploration of hybrid optimization techniques and the application of these methods in real-time analytics.
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  18. Multipath Routing Optimization for Enhanced Load Balancing in Data-Heavy Networks.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):377-382.
    In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...)
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  19.  94
    Automated Cyberbullying Detection Framework Using NLP and Supervised Machine Learning Models.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-432.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify cyberbullying (...)
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  20. (1 other version) FIRE MANAGEMENT SYSTEM FOR INDUTRIAL SAFETY APPLICATIONS.M. Arul Selvan - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):247-259.
    The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the GSM network system. The system uses various sensors to detect fire, smoke, and gas, then transmits the message using GSM module. After the message, send by the module the help arrives in 15 minutes. The (...)
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  21.  67
    Efficient Data Center Management: Advanced SLA-Driven Load Balancing Solutions.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):368-376.
    In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and simulated (...)
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  22.  57
    Wireless IoT Sensors for Environmental Pollution Monitoring in Urban Areas.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):434-441.
    The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future work (...)
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  23.  85
    Robust Cyber Attack Detection with Support Vector Machines: Tackling Both Established and Novel Threats.M. Arul Selvan - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):160-165.
    The proposed IDS model is aimed at detecting network intrusions by classifying all the packet traffic in the network as benign or malicious classes. The Canadian Institute for Cyber security Intrusion Detection System (CICIDS2017) dataset has been used to train and validate the proposed model. The model has been evaluated in terms of the overall accuracy, attack detection rate, false alarm rate, and training overhead. DDOS attacks based on Canadian Institute for Cyber security Intrusion Detection System (KDD Cup 99) dataset (...)
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  24.  50
    AN INTRUSION DETECTION SYSTEM MODEL FOR DETECTING KNOWN AND INNOVATIVE CYBER ATTACKS USING SVM ALGORITHM.Selvan Arul - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):150-157.
    Nowadays, intrusions have become a major problem faced by users. To stop these cyber attacks from happening, the development of a reliable and effective Intrusion Detection System (IDS) for cyber security has become an urgent issue to be solved. The proposed IDS model is aimed at detecting network intrusions by classifying all the packet traffic in the network as benign or malicious classes. The Canadian Institute for Cyber security Intrusion Detection System (CICIDS2017) dataset has been used to train and validate (...)
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  25. Syiden kisat Leibnizin mielenfilosofiassa.Markku Roinila - 2007 - In Heta Gylling, Ilkka Niiniluoto & Risto Vilkko (eds.), Syy. Gaudeamus.
    G. W. Leibnizin mielenfilosofiassa ymmärrykselle on jatkuvasti läsnä erilaisia taipumuksia erilaisiin päämääriin. Nämä taipumukset tai syyt toimia jollakin tavoin saattavat perustua selviin ja tarkkoihin havaintoihin ja olla tiedostettuja ennakkotahtomuksia. Näiden lisäksi mielessämme on epälukuinen määrä epäselviin havaintoihin perustuvia tiedostamattomia ja hetkittäisiä passioita, oikkuja tai hurahduksia. Kun henkilö ryhtyy harkitsemaan toimintaansa, nämä erilaiset taipumukset ja ennakkotahtomukset alkavat ottaa mittaa toisistaan. Prosessin tuloksena on lopullinen tahtomus tai riittävä syy. Kun ymmärrys on muodostanut suosituksen, tahto seuraa Leibnizin mukaan sitä ja toteuttaa ao. toiminnan. (...)
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  26. Collected Papers (on Neutrosophic Theory and Applications), Volume VIII.Florentin Smarandache - 2022 - Miami, FL, USA: Global Knowledge.
    This eighth volume of Collected Papers includes 75 papers comprising 973 pages on (theoretic and applied) neutrosophics, written between 2010-2022 by the author alone or in collaboration with the following 102 co-authors (alphabetically ordered) from 24 countries: Mohamed Abdel-Basset, Abduallah Gamal, Firoz Ahmad, Ahmad Yusuf Adhami, Ahmed B. Al-Nafee, Ali Hassan, Mumtaz Ali, Akbar Rezaei, Assia Bakali, Ayoub Bahnasse, Azeddine Elhassouny, Durga Banerjee, Romualdas Bausys, Mircea Boșcoianu, Traian Alexandru Buda, Bui Cong Cuong, Emilia Calefariu, Ahmet Çevik, Chang Su Kim, Victor (...)
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