SATHYA V

Scopus Publications

Secure Federated Multimodal Learning with Attention-Weighted Transformers and Homomorphic Encryption for Privacy-Preserving Neuroimaging Analysis
N. Balaji, V. Sathya, P. Sirenjeevi, Velliangiri Sarveshwaran
Biomedical Signal Processing and Control, 2026
Energy–Cost–SLA Aware Cloud Scheduling via Adaptive Non-dominated Sorting Genetic Algorithm-III and Neighborhood Refinement
Vijayasekaran G., Sathya V., Sumathi S., Lavanya M.
Journal of Trends in Computer Science and Smart Technology, 2026
The optimization of resource allocation in a cloud computing environment is a problem that has been challenging due to heterogeneous tasks with varying resource requirements and different optimization objectives for execution time, energy consumption, service level agreements (SLAs) and so on. In this paper, a hybrid multi-objective optimization algorithm called AH-NSGAIII-VND is proposed for solving a multi-objective optimization problem in a cloud computing environment. The proposed algorithm integrates a global search process using a variant of a multi-objective evolutionary algorithm called Non-Dominated Sorting Genetic Algorithm III (NSGA-III) and a local search process using a variant of a local search algorithm called Variable Neighborhood Descent (VND). The problem of resource allocation in a cloud computing environment is formulated as a multi-objective optimization problem considering makespan, energy consumption, cost, service level agreements (SLAs) and resource utilization. Researchers compared the results of the PSO, GA, and GWO optimization methods to the baseline using CloudSim-based model conditions on the changing workload scale. Experimental results indicate that cloud supply governance efficiency is enhanced with the AH-NSGAIII-VND architecture. It achieves around 11.3%, 12.8%, and 28% lower costs than the baseline NSGA-III approach while increasing overall asset utilization by over 5 percentage points. Moreover, with increasing workload, the proposed model exhibits improved convergence behavior and scalability. These results confirm that global evolutionary optimization supported by adaptive local search successfully reinstates or enhances the efficiency of resource allocation.
Enhancing Real-Time Object Detection and Recognition: A Hybrid BP-LSTM Deep Learning Approach for Advanced Computer Vision Systems
R. Pushpakumar, V. Sathya, S. Hariprasath, G. Kumar, Seshasai S. Jaswanth, D. S. Jayalakshmi
Communications in Computer and Information Science, 2026
A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images
Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya
Scientific Reports, 2025
Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools. This paper presents a novel hybrid deep learning framework that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for diabetic retinopathy (DR) early detection and progression monitoring using retinal fundus images. Utilizing the sequential nature of disease progression, the proposed method integrates temporal information across multiple retinal scans to enhance detection accuracy. The proposed model utilizes publicly available DRIVE and Kaggle diabetic retinopathy datasets to evaluate the performance. The benchmark datasets provide a diverse set of annotated retinal images and the proposed hybrid model employs a CNN to extract spatial features from retinal images. The spatial feature extraction is enhanced by multi-scale feature extraction to capture fine details and broader patterns. These enriched spatial features are then fed into an RNN with attention mechanism to capture temporal dependencies so that most relevant data aspects can be considered for analysis. This combined approach enables the model to consider both current and previous states of the retina, improving its ability to detect subtle changes indicative of early-stage DR. Proposed model experimental evaluation demonstrate the superior performance over traditional deep learning models like CNN, RNN, InceptionV3, VGG19 and LSTM in terms of both sensitivity and specificity, achieving 97.5% accuracy on the DRIVE dataset, 94.04% on the Kaggle dataset, 96.9% on the Eyepacs Dataset. This research work not only advances the field of automated DR detection but also provides a framework for utilizing temporal information in medical image analysis.
Global research trends in Environmental adaptation techniques focusing on climate change through scientometric lens
G. Shyamala, R. Gobinath, B. Hemalatha, DivyaSri Akkalla, S. Shenbaga Ezhil, V. Sathya
Discover Sustainability, 2025
Climate change is a significant threat to ecosystems and communities, and challenges global sustainability; therefore, more research on climate change adaptations should be conducted. This scientometric study presents databases on global trends in academic research, specific contributions, and thematic evolution of environmental adaptations to climate change. Using the Scopus database of publications, this study focuses on publications between 2009 (January) and 2024 (August), with an emphasis on the interpretation of primary research interests, authors, contributions from countries, and collaborative networks. According to the findings, there has been a shift in focus to more adaptive management in agricultural and biological diversity practices, with more emphasis on the integration of ecological, technological, and social science disciplines. This work also reveals that countries have gaps in regional research, especially in developing countries, and highlights the need to work collectively across the globe. Through citation analysis, thematic evolution, and future research recommendations, this study enriches the knowledge of the line of research on environmental adaptation and underlines its significance in addressing climate change effects.
Optimizing combustion efficiency and emission reduction in low temperature combustion engines using biodiesel-nano additive alcohol blends: A review
C. Vijai, Dinesh Babu M, Naresh Babu M, Sathiyamoorthi R, Sathyanarayanan S, Sathya V, KamakshiPriya K, Habtamu Alemayehu
Results in Engineering, 2025
The increasing levels of harmful emissions and the depletion of fossil fuel resources have sparked global interest in biodiesel as an alternative fuel. This review explores the potential of biodiesel derived from non-edible resources and waste products, enhanced by nano-additives and higher alcohol fuels, to support Low Temperature Combustion (LTC) engine technologies. Nano-additives like titanium dioxide and magnesium oxide enhance fuel properties, while higher alcohols reduce soot and hydrocarbon (HC) emissions. Advanced combustion modes are used to minimize nitrogen oxide (NOx) and particulate emissions. This review underscores the significant role of biodiesel with additives in enhancing lower combustion, although Low temperature combustion engines demand advanced control over fuel composition and combustion conditions for optimal performance. Effective strategies like Exhaust Gas recirculation (EGR) and Variable Injection Timing helps in controlling the harmful emission levels in LTC Engines. EGR reduces NOx emissions but increases HC and CO beyond 30%. Early injection rates (before 23° BTDC) increased NOx, while late injection (after 27° BTDC) increases HC and CO. Combining EGR (15-25%) with optimized injection timing (23°-27° BTDC) provides the best emission control in LTC engines. Hence Blending biodiesel, alcohols, and nano-additives helps to reduce emissions in LTC engines. It was found that Higher alcohols improve combustion efficiency, reduce NOx & PM, but increase CO & HC at high blends while with addition of Nanoparticles optimization of combustion, lower emissions, and enhancement of thermal efficiency are achieved. n-Pentanol and Copper Oxide (CuO) were found to be better Alcohol and Nanoparticle additive with respect to High energy content, Better Volatility and Stability, enhanced combustion and Emission control. Within the LTC strategies RCCI was found to be best with respect to maximum thermal efficiency, lower emissions, superior load adaptability which is a concern in HCCI and PCCI modes and fuel flexibility to be used in a wide range of fuel combinations to optimize combustion efficiency, emissions, and performance. However, trade off exists between NOx and HC levels even with enhanced combustion which can be controlled with optimized combustion chamber design, optimized fuel injection system with proper Air Fuel Ratio and after treatment systems like SCR and DPF.
Sunflower-based butterfly optimization algorithm with enhanced RNN for the harmonics elimination in multilevel inverter
V. Mohan, G. Krithiga, M. Thamil Alagan, V. Sathya
Discover Applied Sciences, 2025
Multilevel inversion describes a power conversion technique that reduces Total Harmonic Distortion (THD) by gradually increasing the output voltage and approaching a sine wave. The fundamental goal of Multi Level Inverters (MLIs) is to produce an approximate sinusoidal voltage from many levels of dc voltages, which are typically supplied from capacitor voltage sources that convert DC input voltage to AC output voltage. A key goal is to obtain a pure sinusoidal waveform at the output of the Multi Level Inverter (MLI). In a cascaded MLI, the Selective Harmonic Elimination (SHE) and Pulse Width Modulation (PWM) approach is employed to mitigate lower harmonics by maintaining the needed fundamental voltage. To determine Switching Angles (SA), an objective function is generated from the SHE problem. In this paper, the Sunflower based– Butterfly Optimization Algorithm (SF-BOA) is presented as a method for evaluating transcendental nonlinear equations using an MLI in a SHE approaches. SF-BOA’s optimized switching angle is used for 11-level three-phase PWM control using the Cascaded H Bridge architecture for harmonic reduction of the entire modulation index. Although Artificial Intelligence (AI) systems can effectively solve a non-linear transcendental equation, their time consumption together with the convergence capability differs. Enhanced Recurrent Neural Network (ERNN) shows a kind of recurrent neural network in which the hidden neurons are tweaked by SF-BOA with the goal of minimizing THD. As per the simulation data, the SF-BOA approach is much appropriate and suitable than other compared algorithms like Harris Hawks Optimization (HHO), Whale optimization algorithm, Marine Predator Algorithm (MPA), Multi Group Marine Predator Algorithm (MGMPA).
Artificial intelligence in personalized education: Revolutionizing learning paths and student engagement
S. Devi Dhivya, R. Balakrishna, T. Selva Banu Priya, T. Thilagam, V. Sathya, et al.
AI Personalization Equity and the Future of Learning, 2025
Education is changing with AI, and the intelligent tutoring, adaptive learning, and recommendation systems are transforming the education based on personalization. This chapter surveys current trends, recent technologies and use cases for what is to come in the future of education. It is using AI driven system to analyze student behavior and provide real time content, quizzes and feedback. Recommendation systems, intelligent tutors, and learning paths take shape due to machine learning; natural language processing enters the picture with intelligent tutors; and reinforcement learning also improves the learning paths. Even with benefits, there are concerns about data privacy, bias, and technical difficulties. That is, advanced AI models, multilinear data and AR/VR may unite to improve personalisation in future. This chapter examines the impact and potential, and even challenges of AI about revolutionizing learning.
Advancing environmental modeling: Integrating AI, big data, and predictive analytics for sustainable solutions
S. Revathi, P. Pushpa, S. Saranya, V. Rekha, S. P. Santhoshkumar, Anto Gracious L. A., V. Sathya
AI Methods for Environmental Protection and Resource Conservation, 2025
Environmental modeling has a major importance in analyzing the changes in the environment, climate, and resource allocation. The current environmental models with the use of new technologies such as AI, machine learning, big data, and IoT improves the precision of climate change predictions, emissions, protection of species, and prevention of calamites. These models use data and information generated in real-time and computer models to arrive at policy recommendations. However, there are some limitations like data uncertainty, computational complexity, and the gaps between the existing and implemented policies that reduce their efficiency. Future research needs to address the issues of combining different types of AI, continuous monitoring of the AI-driven processes, and sharing of AI models due to the concerns related to the accessibility and accuracy of the results. At the international level, the development of environmental modeling hence requires interventions from interdisciplinary fields as the policy frameworks.
Advancing sustainable development through green economics
Dhivya Devi S., K. Balasubramanian, A. Adaikkammai, T. Thilagam, R. Vinoth, V. Sathya, Siva Subramanian R.
AI Methods for Environmental Protection and Resource Conservation, 2025
Green economy is the only way forward for sustainable development, stability of the economy and protection of the environment. The current paper aims to analyze principles, sectors and technologies that are significant for green economic growth. It includes renewable energy, circular economy, green finance together with sustainable agriculture alongside the problems like high costs of investments, insufficient policies and implementing policies and plans, and societal disparities. Some of the trending upcoming technologies such as artificial intelligence, blockchain and carbon capture are shaping sustainability. The paper also establishes the importance of governments, businesses and civil society organisations in promoting a just transition. To realise these objectives, further concepts are focused on policies, green investments, and green technologies for creating low-carbon and resource efficient economy of the world.
AI driven personalization in education: Transformative practices and emerging trends
D. Suresh, P. Lokesh, B. Yamini, B. Yuvasri, V. Sathya, P. Girija, Subramanian R. Siva
Transformative AI Practices for Personalized Learning Strategies, 2025
AI and the future of economic systems: Analyzing technological, ethical, and governance dimensions
R. Bhuvanya, T. Kujani, P. Matheswaran, B. Yamini, B. Yuvasri, V. Sathya, Siva Subramanian R.
Reshaping the Economy with AI, 2025
Machine learning in cybersecurity: Challenges, applications, and future directions
D. Prabhu, L. Sudha, Pandi Kumari M. R., A. Adaikkammai, P. Aparna, Siva Subramanian R., V. Sathya
Exploiting Machine Learning for Robust Security, 2025
Empowering smart cities: A comprehensive survey on the role of IoT in urban infrastructure
A. Ponmalar, A. Muthuram, M. Dhivya, V. M. Gobinath, V. Sathya, L. A. Anto Gracious, P. Girija
Leveraging Urban Computing for Sustainable Urban Development, 2025
Intelligent waste management in smart cities: Technologies, challenges, and future prospects
R. Ganeshan, B. Yamini, Somsubhra Saha, V. Muthu, D. Lekha, M. Nalini, V. Sathya
Leveraging Urban Computing for Sustainable Urban Development, 2025
Evaluation of Paper Industry waste sludge and nano materials on properties of concrete
G. Shyamala, B. Hemalatha, Gunavathie MA, S. Shenbaga Ezhil, V. Sathya, M. Gobinath, M. Dinesh Babu
E3s Web of Conferences, 2025
Advancing STEAM education: Integrative approaches, challenges, and future directions
Durai Vasanth R., Srilalitha Ravikumar, Somsubhra Saha, K. Sudha, R. Vinoth, Siva Subramanian R., V. Sathya
Transformative Approaches to Steam Integration in Modern Education, 2025
AgroInsight Pro: Sustainable Agriculture Analytics & Decision Support System using GEN-AI
Ch. Sai Krishna, S. Pavan Sai, P. Dinesh Roy, V. Sathya
Proceedings 4th International Conference on Smart Technologies Communication and Robotics 2025 Stcr 2025, 2025
Smart-Shield: A Hybrid ML-AI Framework for Advanced Phishing Detection using Gradient Boosting and LLM Analysis
Pusarla Venkata Sai Kumar, Mende Nikhil Yadav, Eppa Chaithanya Reddy, V Sathya
Proceedings of 5th International Conference on Pervasive Computing and Social Networking Icpcsn 2025, 2025
Assistive New Gen Smart Blind Stick Using React
C. M. Nalayini, Jeevaa Katiravan, V. Sathya, Subathra Jayaraj, Udayaravina Rajan
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2025
Digital Twins Tools and Technologies in Smart Manufacturing
K. Jayashree, S. Muralidharan, V. Sathya, M. Rajakumaran, C.M. Nalayini
Artificial Intelligence Enabled Digital Twin for Smart Manufacturing, 2025
PrivGuardNet: A Federated Transformer-based Intrusion Detection System with Differential Privacy for Scalable Cybersecurity Defense
Soumya TR, Thamba Meshach W, P. Jayasree, P. Poonkuzhali, V. Sathya, Syed Ismail Abdul Lathif
Proceedings of 8th International Conference on Computing Methodologies and Communication Iccmc 2025, 2025
Optimizing QoS in Power Line Communications through Multi-Ant Colony Optimization
Sathya V, Kaniezhil. R, Venkatesan. R, Srinivasan. B, Elakkiya Rajasekar, Rajendiran. P
2025 3rd International Conference on Computational Intelligence and Network Systems Cins 2025, 2025
Deep Learning Techniques for Cyber Bullying Detection in Social Networks
V Tamil Selvi, Sherin Rappai, D. Kalpana, V. Sabaresan, N Pratheeksha Hegde, V Sathya
2025 International Conference on Automation and Computation Autocom 2025, 2025
Enhanced Multi-Scale Convolutional Neural Network with Attention Mechanism for Accurate and Efficient Automated Hematological Diagnostics from Blood Smear
Santosh Kumar B, CH Hussaian Basha, Jini Kumari M, Pradeep Kumar S, V. Sathya, K Rajaram
3rd International Conference on Electronics and Renewable Systems Icears 2025 Proceedings, 2025
An Efficient TabNet-Based Obesity Classification and Risk Prediction System Optimized with Dove Flocking Optimizer
V. Usha, V. Sathya, T. Anitha, M. Senthil Kumar, A. Lizy, Sandeep Karagatla
2025 IEEE International Conference on Emerging Trends in Computing and Communication Etcom 2025, 2025
Energy Efficient Big Data Processing: A Comprehensive Survey on Techniques, Trends, and Future Directions
D. Ravindran, G. Mariammal, S. Udhayashankar, K. Dhivya, D. Lekha, T. Maheshwaran, V. Sathya
Energy Efficient Algorithms and Green Data Centers for Sustainable Computing, 2025
Virtual and Augmented Reality in the Automobile Industry: Applications and Future Directions
J. Samuel Manoharan, M. Arunkumar, Sathiya A, M. Hemamalini, V. Sathya, T. P. Anish, R. Siva Subramanian
Virtual and Augmented Reality Applications in the Automobile Industry, 2025
Energy Efficient Protocols and Devices in IoT: Approaches for Sustainable Performance
M. Ezhilvendan, Aniket Gangadharrao Patil, S. M. Sassirekha, A. Mathankumar, T. P. Anish, V. Sathya, P. Gajalakshmi
Energy Efficient Algorithms and Green Data Centers for Sustainable Computing, 2025
Exploring AI Computing: Applications, Challenges, and Future Trends
Aniket Gangadharrao Patil, B. Senthilkumaran, R. Vidhya Muthulakshmi, V. Sathya, S. Balapriya, T. P. Anish, R. Siva Subramanian
AI for Large Scale Communication Networks, 2025
Ring vs compact spinning
Asian Textile Journal, 2025
Advancing healthcare through artificial intelligence: Applications, challenges, and future directions
S. Mangairkarasi, T. Venkata Ramana, R. Vaishnavi, S. Agalya, V. Sathya, R. Siva Subramanian
Responsible AI for Digital Health and Medical Analytics, 2024
The role of robotics in smart manufacturing: Increasing efficiency and reducing costs
Kathirvel Ayyaswamy, V. M. Gobinath, V. Sathya, Naren Kathirvel, Raj A. Anthony
Quantum AI Era of Neuromarketing, 2024
Advancing e-commerce security: Strategic innovations and future directions in AI and ML
L. A. Anto Gracious, L. Sudha, B. Chitra, Gaganpreet Kaur, V. Sathya, P. Kabitha, R. Siva Subramanian
Strategic Innovations of AI and ml for E Commerce Data Security, 2024
Advances in data processing, machine learning, and data security
N. Manjunathan, K. Aravindaraj, J. Anitha, V. K. Ramya Bharathi, V. Sathya, R. Senthil, R. Siva Subramanian
Strategic Innovations of AI and ml for E Commerce Data Security, 2024
Advances in 3D bioprinting for environmental remediation and hazardous materials treatment
Gobinath Vellalapalayam Manoharan, Naresh Babu Munuswamy, Jasmine Hephzipah Johnpeter, Sathya Veeramani, Hemalatha Balasubramanian
Environmental Science and Pollution Research, 2024
Blockchain-enabled smart health monitoring system in WBAN
V. Sathya, A. Dennis Ananth, M. Rajakumaran, S. Markkandeyan, R. Venkatesan
Applying Internet of Things and Blockchain in Smart Cities Industry and Healthcare Perspectives, 2024
Osteoarthritis disease prediction based on machine learning techniques
V. Sathya, Shalini Parthiban, M. Megavarshini, V. Shenbagaraman, R. Ramya
Enhancing Medical Imaging with Emerging Technologies, 2024
Wireless sensor network data gathering using a multi-fold gravitational search algorithm with a mobile agent
R. Saravanan, V. Sathya
International Journal of System of Systems Engineering, 2024
AI Applications in Production
C.M. Nalayini, V. Sathya, Shruthi Arunkumar, M. Dinesh Babu
Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing, 2024
Blockchain as the Backbone of a Connected Ecosystem of Smart Hospitals
C.M. Nalayini, V. Sathya, Shruthi Arunkumar, M. Dinesh Babu
Artificial Intelligence Enabled Blockchain Technology and Digital Twin for Smart Hospitals, 2024
IoT and Data Analytics in Healthcare
G. Sekar, John T Mesia Dhas, Anandaraj B, M. Nalini, V. Sathya, Siva Subramanian R
2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
5G Network with Hexagonal SDN Control for Highly Secure Multimedia Communication
E. M. Malathy, V. Sathya, Preetha Evangeline David, P. Ajitha, V. T. Noora, A. Ahilan
IETE Journal of Research, 2024
Enhancing Industrial Applications with LSTM-Based Predictive Analytics
Lalitha Ramachandran, S Girinath, N Padmavathi, G. Subramaniam, M. Siva Chitra, V Sathya
2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
Data Analytics in Management Empowering Decision-Making Through Insights
R. Bhuvanya, B. Yamini, K. Sivakumar, Gobinath V. M., V. Sathya, R. Siva Subramanian
Pioneering Approaches in Data Management, 2024
Unraveling the Quantum Computing Frontier: Advancements, Challenges, and Future Prospects
D. Ravindran, S. Revathi, V. Sowndharya, I. Farzhana, V. Sathya, P. Girija, Siva Subramanian
Integration of AI Quantum Computing and Semiconductor Technology, 2024
Transforming Healthcare With AI and Machine Learning: Applications and Impacts
D. Ravindran, G. Mariammal, M. Dhivya, Dhivya Devi S., Anish T. P., V. Sathya, Siva Subramanian R.
AI Driven Innovation in Healthcare Data Analytics, 2024
Convergence of Advanced Technologies for Sustainable Development and Smart Cities
A. Ponmalar, A. Muthuram, M. Therasa, V. Priya, V. Sathya, S. Subha, R. Siva Subramanian
AI and Green Technology Applications in Society, 2024
Development of smart textiles for furnishing applications
Man Made Textiles in India, 2024
Accurate Range Free Location based Partial Derivative and Stochastic Feedforward Neural Network Hyperbolic-based Agriculture Sensor Network Formation
R Saravanan, V. Sathya
Journal of Advanced Research in Applied Sciences and Engineering Technology, 2023
Intrusion detection in cyber physical systems using multichain
C. M. Nalayini, Jeevaa Katiravan, V. Sathya
Malware Analysis and Intrusion Detection in Cyber Physical Systems, 2023
RETRACTION:A novel predicting students performance approach to competency & hidden risk factor identifier using a various machine learning classifiers
V. Sathya, G.R. Mahendra Babu, J. Ashok, Ajanthaa Lakkshmanan
Journal of Intelligent and Fuzzy Systems, 2023
Provably dwindling three-party spurious classical and quantum key distribution protocols
Sathya V., Kirankumar Manivannan, Prema P., Saranya S., Sanjay Misra
Handbook of Research on Quantum Computing for Smart Environments, 2023
Robotic Process Automation (RPA) Applications and Tools for the Workforce Management System
V. Sathya, K. Jayashree, S. Malathi
Designing Workforce Management Systems for Industry 4 0 Data Centric and AI Enabled Approaches, 2023
Financial Cryptography and Its Application in Blockchain
V. Sathya, Sridhar Chandrasekaran, Govindasamy Madhaiyan
Homomorphic Encryption for Financial Cryptography Recent Inventions and Challenges, 2023
A comprehensive study and review of tuning the performance on database scalability in big data analytics
M.R. Sundarakumar, G. Mahadevan, R. Natchadalingam, G. Karthikeyan, J. Ashok, J. Samuel Manoharan, V. Sathya, P. Velmurugadass
Journal of Intelligent and Fuzzy Systems, 2023
Lifetime Escalation and Clone Detection in Wireless Sensor Networks using Snowball Endurance Algorithm(SBEA)
V. Sathya, S. Kannan
Ksii Transactions on Internet and Information Systems, 2022
An Obfuscation Technique for Malware Detection and Protection in Sandboxing
V. Sathya, Kirankumar Manivannan, V. Vani, Sridhar Chandrasekaran
Studies in Computational Intelligence, 2021
Fruit and Leaves Disease Prediction Using Deep Learning Algorithm
Sathya V, Rafidha H, Sumitha Rani G
International Research Journal of Multidisciplinary Technovation, 2019
Extending Endowed Multicasting over Mobile AD HOC Networks Using Random Voronoi Configurations
S. Nithyanandam, G. Sathiya Prabha, V. Sathya
IEEE Proceedings of the International Conference on Emerging Trends in Science Engineering and Technology Recent Advancements on Science and Engineering Innovation Incoset 2012, 2014
Data hiding in audio signal, video signal text and JPEG images
IEEE International Conference on Advances in Engineering Science and Management Icaesm 2012, 2012
Extending endowed multicasting over mobile AD HOC networks using random voronoi configurations
IEEE Proceedings of the International Conference on Emerging Trends in Science Engineering and Technology Recent Advancements on Science and Engineering Innovation Incoset 2012, 2012

SATHYA V

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Scopus Publications