Vijaya Padmanabha

Scopus Publications

A hybrid blockchain migration framework for converting traditional databases into blockchain-based EMR systems
Ahmed Al-Busaidi, Joseph Mani, Mohamed Sirajudeen Yoosuf, Vijaya P
Scientific Reports, 2026
Electronic Medical Records (EMRs) are crucial to modern healthcare. However, traditional relational databases fail to fulfill increased expectations for integrity, auditability, and compliance in regulated environments. This paper proposes a Hybrid Blockchain Migration Framework that integrates a conventional MySQL-based EMR system (OpenMRS) with a permissioned blockchain network (Hyperledger Fabric). Sensitive data fields are selectively mirrored to the blockchain, ensuring tamper-evident logging while retaining the high performance of SQL for routine operations. A middleware layer, implemented using Java Spring Boot, monitors changes in the EMR and commits cryptographic hashes and metadata to the blockchain in near real-time. We evaluate the hybrid system against both standalone MySQL and full-blockchain implementations using controlled benchmarks, analyzing latency, throughput, resource utilization, and auditability. Results show that the hybrid architecture sustains near-native responsiveness (median 2.1 ms versus 1.6 ms for pure MySQL and 60.5 ms for Fabric) and delivers 480 Transaction Per Second (TPS), while incurring only modest overhead (47% of i7-9750H CPU, 1.15 GB RAM) and enhancing data integrity and compliance with regulations such as Oman’s Personal Data Protection Law (PDPL). The framework is extensible to multi-institutional deployments and supports regulatory alignment, making it a viable pathway for blockchain adoption in clinical settings.
Automated Cattle Age Estimation Using Dentition Analysis and Deep Learning
Aneesh S Mayya Nitte, Anisha P Rodrigues Nitte, Roshan Fernandes Nitte, Sarika Jain, P. Vijaya
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
Proper age estimation has been seen to be vital in livestock management, breeding choices as well as market valuation, but the conventional age estimation approach by dentition is potentially costly in terms of manual handling and expert opinion, which results in inconsistency and subjectivity. To master these bounds, this work tells an automated computer-visionbased cattle dentition classification system using the YOLOv8 object detection framework. Cattle dental visuals were collected, marked into discrete dentition levels, and arranged into training, validation, and testing groups. The framework was trained by built-in augmentation approaches to improve stability under different lighting, angles, and actual-world farm criteria. Experimental outputs demonstrate trustworthy detection and sorting performance, reaching an mAP50 of 74.6% and mAP50-95 of 47.1%, showing a strong generalization around dentition classes. The proposed method offers a fast, stable, and scalable option to manual age calculation and shows stable potential for real-world deployment in cattle management applications.
Assessing OT Cybersecurity Readiness in Critical Infrastructure: Global Frameworks and GCC Applications
Al Khazama Al Araimi, Joseph Mani, Mohamed Sirajudeen Yoosuf, Ajay Vikram Singh, Vijaya P
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
Operational Technology (OT) systems in critical infrastructure are increasingly integrated with Information Technology (IT), exposing legacy industrial control environments to cyber threats. This paper assesses the readiness of Gulf Cooperation Council (GCC) region critical infrastructure operators to adopt and operationalize global OT cybersecurity frameworks and maturity models, focusing on the NIST Cybersecurity Framework (CSF), NIST SP 800-82 (OT security guide), IEC 62443 standards, and the DOE Cybersecurity Capability Maturity Model (C2M2). Through a comprehensive literature review and comparative analysis, we identify key barriers to framework implementation in the GCC, including shortages of skilled OT security professionals, siloed IT/OT organizational structures, and fragmented national policies. Our findings indicate that the energy sector in the GCC is relatively advanced in cybersecurity framework adoption, whereas other sectors such as water utilities and municipal transport lag behind in maturity. To bridge these gaps, we propose actionable strategies including a hybrid multi-layer framework adoption model, the establishment of GCC- specific maturity benchmarks and crosssector collaboration, and targeted workforce development programs. These recommendations aim to enhance OT cyber resilience across the GCC by aligning the best global practices with regional context and improving governance, capacity-building, and policy integration.
ROS2-Integrated Autonomous Vehicle Simulation with Behavioural Cloning and YOLOv8 Vision Perception
Moulya K B, Anisha P Rodrigues, Roshan Fernandes, Ajay Vikram Singh, P. Vijaya
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
To ensure that autonomous driving technologies are safe, reliable, and robust under various road conditions, they must undergo thorough testing. However, real-world testing can be expensive, risky, and limited by environmental factors. This study introduces a fully simulation-based framework for autonomous driving, incorporating behavioral cloning, YOLOv8 for traffic light recognition, and ROS2 for sensor communication within the Webots simulator. A neural network for behavioral cloning was developed and trained using manually gathered driving data to predict steering and throttle commands, providing end-to-end vehicle control. The YOLOv8 model detects red, yellow, and green traffic lights in real time, allowing vehicles to adhere to traffic rules. Additionally, a LIDAR-based module for obstacle detection was included to minimize collision risks and ensure safe navigation. Various experimental settings in Webots, such as a simple road without obstacles, an urban environment with intersections and traffic lights, and scenarios with obstacles, were created to evaluate the system. The experimental results show that the system can drive autonomously, follow traffic signals, and avoid obstacles. The proposed framework highlights modularity and extensibility, making it ideal for future research on autonomous navigation, intelligent transportation systems, and the development of simulation-driven AI solutions.
A Hybrid AES-GCM Based Structural Encryption Approach for IoT and Alphabet-Restricted Communication
Manjunath Kamath K, Akanksh J K, Sujal Sunil Badde, Shambhu K Jha, Vijaya Padmanabha
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
The including the IoT networks, cloud infrastruct rapid expansion of interconnected digital ecosystems,ures, and Real-time communication platforms have increased Significantly, there is a need for encryption schemes resistant to current and developing cryptanalytic attacks. Though AES-GCM is still most a popular standard because of its authenticated encryption, speed, robustness and binary ciphertext structure and deterministic nature. Behavior can inadvertently show patterns in repetitive or Streams of structured data. Constrained environments that have high For instance, plaintext redundancy: sensor telemetry, low-entropy IoT traffic, or communication channels with alphabet restrictions, Quite often, this issue becomes very significant. In this paper, a new hybrid architecture A proposal for encryption is provided that extends the traditional AES-GCM by adding a lightweight, reversible transformation layer to perform structural Obfuscation and alphabet-only compatibility. Of the many security features included in the framework are a memory hard Scrypt-based KDF, Base-26 ciphertext encoding, adaptive Vigenre-style substitution, block-level permutations, CSPRNG-driven rotations, deterministic noise injection, and HMAC SHA256 authentication. Experimental evaluations demonstrate high entropy levels <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$5.23-5.33$</tex> bits/char, reliable execution times (¡ 600 ms for 10 KB), complete reversibility, and robust defenses for these: statistical, brute-force, correlation; replay, and tampering attacks. The following proposed system has considerably improved confidentiality and structural unpredictability while remaining appropriate for IoT devices, secure messaging systems, cloud storage, and Environments restricted to alphabet-only payload compatibility.
Intelligent Theft Management System: A YOLO-Based Real-Time CCTV Monitoring for Jewellers
Moulya K B, Anisha P Rodrigues, Roshan Fernandes, P. Vijaya, Sarika Jain
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
The Intelligent Theft Management System (ITMS) offers a real-time, CCTV-driven security solution for detecting intrusions and theft in high-risk retail settings, particularly jewelry stores. It utilizes the YOLOv5 deep learning-based object detection model to recognize human presence in live video streams and automatically issue alerts when suspicious or unauthorized behavior is observed. CCTV video is analyzed on a frame-by-frame basis, enabling rapid and reliable detection across diverse lighting conditions and backgrounds. The system incorporates adjustable confidence thresholds, configurable alert channels (SMS and email), and a browser-based administrative dashboard for oversight and control. Experimental validation was performed using a mix of COCO-pretrained models and custom CCTV clips recorded in daylight, low-light, and nighttime scenarios. System performance was measured using precision, recall, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{F 1}$</tex>-score, and detection latency, confirming that YOLOv5 delivers high accuracy alongside real-time processing suitable for continuous surveillance. Overall, the results show that ITMS is an effective, scalable, and practical solution for automated theft detection that also helps minimize the need for manual monitoring.
Adaptive Cryptographic Confidential Computing Framework for Continuous Cloud Data Protection
Varshitha B A, Shravya R, Shreeraksha M, Ajay Vikram Singh, Vijaya Padmanabha
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
The Adaptive Cryptographic Confidential Computing framework introduced here aims to keep data protected throughout its entire journey in the cloud whether it is sitting in storage, moving between services or being processed in real time. In many existing systems, encryption tends to stop at storage or transmission which still leaves the data exposed while computations are taking place. The work addresses this gap by bringing together a small simulated confidential execution environment, Azure key vault for handling and rotating keys and the use of Managed Identities so that no passwords or static secrets are involved. A policy engine assigns a sensitivity level to the input and selects one of three AEAD algorithms. AES-256-GCM is applied for high sensitivity data, AES-128-GCM for moderate security needs and ChaCha20-Poly1305 for performance oriented environments. When tested on Azure for Students, the system behaved consistently with predictable throughput and only minor delays caused by key derivation steps. The secure execution checks worked reliably even with larger files of around <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 0 ~ M B}$</tex>. Since the design includes continuous encryption and automatic key rotation it aligns naturally with the requirements of common regulatory standards.
Design and Implementation of a Hybrid Post-Quantum Cryptography (PQC) Enabled VPN for Quantum Resistant Secure Communication
Shreya Irniraya, Bansi S Sinojia, Roshan Fernandes, Anisha P Rodrigues, Ajay Vikram Singh, P. Vijaya
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
The current VPN systems that use Classical Cryptography are becoming increasingly vulnerable to attacks on Quantum Computers. This paper examines the creation and implementation of a Quantum-Safe VPN solution that incorporates Post-Quantum Cryptography (PQC) via the Kyber 512 algorithm. The proposal includes a practical client/server implementation using WireGuard as the tunneling protocol and Tailscale for connectivity with an additional level of protection enabling the use of PQC for key exchange via the liboqs library. Selected performance metrics were determined (latency, handshake duration, CPU utilization, throughput) and compared with those of the Classical VPNs. The findings indicate that while PQC will add extra processing overhead (in particular, the Handshake process), it provides a significantly stable and secure channel for communications. Although throughput was less than with Classical VPNs, and CPU usage was increased, the PQC enabled VPN was found to provide acceptable reliability and produce zero packet losses. The results of this study have proven that integration of PQC in a VPN is achievable in real world applications and demonstrates the necessity for secure methods in future networking.
SwitchCrypt: Dynamic Hybrid Multi-Algorithm Encryption with Modified Ciphers and Algorithm Switching
Ashmi Kotian, Prajwal S Rao, Aditya Bhat K, T Srijan Shetty, Nitin Pandey, Vijaya Padmanabha
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
Modern digital services, particularly cloud-based platforms and large communication systems, are in need of encryption techniques that can match the level of sophistication in the attackers' methods. The use of a single cipher as the sole solution is no longer adequate because it usually faces difficulties from the contemporary analytical techniques and might not provide a uniform performance during the encryption and decryption processes. In view of these drawbacks, the SwitchCrypt framework came into being as a dynamic hybrid model that commingles several symmetric ciphers with asymmetric key encapsulation and at the same time, employing the real-time algorithm switching. The framework uses AES-XR, ChaCha20-Swap, and Blowfish-Rotate for segment-level protection, while RSA-2048 makes sure that the key material exchanged between parties is kept secure. Rather than encrypting the whole dataset as a single continuous stream, SwitchCrypt gets the input data into smaller segments and applies different symmetric algorithms to each part. This segmentation plus the multi-cipher strategy leads to a higher level of randomness in the ciphertext and thus makes it much harder to detect through pattern recognition or structural inference. To find out how well the system performs in real life, benchmarks were done with datasets from 1 KB to 5 MB. The tests determined throughput, accuracy, and scaling behavior. The outcomes revealed that ChaCha20-Swap recorded the highest throughput of 675.85 MB/s, followed by AES-XR, where the hybrid switching engine only added a tiny bit of overhead and kept the throughput steady for various file sizes. The overall results suggest that SwitchCrypt can provide fast, scalable, and strong protection that is suitable for high-security environments requiring continuous secure communication or enterprise-grade data protecting.
Face Detection and Emotion Recognition Using Convolutional Neural Network
Aryan Al Zadjali, Abrar Al Balushi, Ajay Vikram Singh, Mohamed Sirajudeen Yoosuf, Joseph Mani, Vijaya P
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
Face detection and emotion recognition have gained significant attention in the context of human-computer interaction and intelligent systems. This paper presents a Convolutional Neural Network (CNN)-based approach to automatic facial emotion recognition using a publicly available dataset of facial expressions. Images were preprocessed to a uniform resolution of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$48 \times 48$</tex> pixels and augmented to enhance model robustness. The CNN architecture integrates convolutional, pooling, batch normalization, and fully connected layers with dropout to enhance generalization. The model achieved a training accuracy of 87 % and a validation accuracy of approximately 70 %, highlighting both the promise and limitations of CNNs for this task. Results indicate effective capture of discriminative facial features but also highlight challenges in handling subtle and overlapping emotions such as fear and surprise. The findings provide a foundation for future work aimed at improving accuracy through deeper networks, attention mechanisms, and multimodal data integration. Our model achieved <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 70 \%$</tex> validation accuracy, which is <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$+\mathrm{X} \%$</tex> higher than a simple CNN baseline without batch normalization and dropout.
Design and Implementation of a Secure Log Management System with Integrated Intrusion Detection and Cryptographic Mechanisms
Manjunath Kamath K, Krithi G Rao, Advith Rai, Hridya Harindran K, Nitin Pandey, Vijaya Padmanabha
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
Identification of Important Features in Detection of Insider Abnormal Activities Dataset
Salah Al Malki, Khalid Al Hashmi, Mohammed Al Araimi, Ajay Vikram Singh, Mohamed Sirajudeen Yoosuf, Joseph Mani, Vijaya P
International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
DML-IDS: Distributed Multi-Layer Intrusion Detection System for Securing Healthcare Infrastructure
Mohamed Sirajudeen Yoosuf, P. Vijaya, Joseph Mani
Emerging Science Journal, 2025
Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm
Anjan Kumar, Laith Hussein Jasim, Padmanabha Vijaya, Dipak Patel, J. Gowrishankar, R. Sivaranjani, Ankur Srivastava, Mayank Kundlas, Sarbeswara Hota, Banafshe Hamidi
Scientific Reports, 2025
ECO-HYBRID: Sustainable Waste Classification Using Transfer Learning with Hybrid and Enhanced CNN Models
Sharanya Shetty, Saanvi Kallianpur, Roshan Fernandes, Anisha P. Rodrigues, Vijaya Padmanabha
Sustainability Switzerland, 2025
Leveraging Hybrid Deep Q-Learning for Early Identification of At-Risk Students
P. Vijaya, Joseph Mani, Basant Kumar, Hothefa Shaker, Rajeev Rajendran
Emerging Science Journal, 2025
Sustainability: A Unique Perspective Based on Physics and Philosophy
Rajeev Rajendran, P. Vijaya
Studies in Systems Decision and Control, 2025
The Benefits of Smart, Fully Automated Greenhouses Over Traditional Manual Greenhouses
Hamed Rashid Al Khanjari, P. Vijaya, P. Praba
Studies in Systems Decision and Control, 2025
Establishing a Sustainable Ecosystem for Cryptocurrency: Detecting Fraud Transactions Using Machine Learning Techniques
Joseph Mani, Mohamed Sirajudeen Yoosuf, Vijaya Padmanabha, Hothefa Shaker Jassim
Studies in Systems Decision and Control, 2025
Analysis and Exploitation of Active Directory Vulnerabilities Using Cobalt Strike: A Practical Approach
Khalid Alharthi, Joseph Mani, Vijaya Padmanabha, Basant Kumar
Studies in Systems Decision and Control, 2025
Enhancing Processor Efficiency with Machine Learning-Based Branch Prediction Techniques
Maheswari Raja, Rajalakshmi, P. Vijaya, Ajay Vikram Singh, K. Swetha
Lecture Notes in Electrical Engineering, 2025
Sustainable Cryptographic Keys Using LFSRs Models
Afaq Ahmad, Joseph Mani, Basant Kumar, P. Vijaya, Hothefa Shaker
Studies in Systems Decision and Control, 2025
House Price Prediction Using Machine Learning
Raiyan Al Wahaibi, Mohamed Sirajudeen Yoosuf, P. Vijaya, Joseph Mani, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
A Voice-Driven AI and IoT Device for Next-Generation Tourist Assistance
Harshit Toprani, Joseph Mani, Mohamed Sirajudeen Yoosuf, Vijaya P, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
SMS Spam Detection using Naïve Bayes and Logistic Regression
Rawnaq Al Aufi, Mohamed Sirajudeen Yoosuf, P. Vijaya, Joseph Mani, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
IoT-Based Health Monitoring and Emergency Response System for Elderly Care
Salma Altamtami, P. Vijaya, Mohamed Sirajudeen Yoosuf, Josephmani Puthenparampily, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
CNN-Based Traffic Sign Recognition System
Beylasan Al Ruzaiqi, Amal Krizou, Tasnim Al Busaidi, Haider Al-Lawati, Vijaya Padmanabha
2025 International Conference on Metaverse and Current Trends in Computing Icmctc 2025, 2025
CFALEA_LSTM: Adaptive Lotus Effect Algorithm Enabled Long Short-Term Memory for Rainfall Prediction Using Time Series Data
P. Vijaya, Satish Chander, Roshan Fernandes, Anisha P Rodrigues, B. Supriya
Communications in Computer and Information Science, 2025
Machine Learning Models for Apple Disease Detection With Texture Feature Fusion and Feature Selection
Prashant C, Biswaranjan Acharya, P. Vijaya, Bejoy B J, Raju G, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
Eel and Grouper Weighted Moving Average Enabled SpinalZFNet for Startup Success Prediction
P. Vijaya, Mohamed Sirajudeen Yoosef, Basant Kumar, Joseph Mani, Hothefa Jassim, Afaq Ahmed
Studies in Systems Decision and Control, 2025
Olympic Games Analysis and Visualization for Medal Prediction
Maheswari Raja, P. Sharmila, P. Vijaya, Roshan Fernandes, Anisha P Rodrigues, Manjunath Kamath K
2025 International Conference on Artificial Intelligence and Data Engineering Aide 2025 Proceedings, 2025
Ultrasound Image Despeckling Using Pixel-Wise Fusion Approach
P. Nikesh, G. Raju, T. V. Bijeesh, B. J. Bejoy, P. Vijaya, Ajay Vikram Singh
Lecture Notes in Electrical Engineering, 2025
A Study of Risk Management Process and its Impact on Project Success in the Oil and Gas Sector
Hothefa Shaker, Joseph Mani, Vijaya P, Mohamed Sirajudeen Yoosuf, Nitin Pandey, Shambhu Kumar Jha
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
Blockchain in Drone Systems: Advancements, Security Implications and Community Acceptance
Basant Kumar, M. Mohammed Mueen Pasha, J. Sandeep, P. Vijaya, Afaq Ahmed, Joseph Mani
Studies in Systems Decision and Control, 2025
Deep Learning in Forensic Sketch Analysis
Anisha P Rodrigues, Pratham S Shetty, Preethika Shet, Priyal Mariam Cornelio, Samarth N Baliga, Roshan Fernandes, P. Vijaya
2025 International Conference on Artificial Intelligence and Data Engineering Aide 2025 Proceedings, 2025
Local Language Handwritten Character Recognition
Anisha P Rodrigues, Akshay Prabhu K, Shailesh U Acharya, Adithya MS, Seejan Padmanabha Poojari, Roshan Fernandes, P. Vijaya
2025 International Conference on Artificial Intelligence and Data Engineering Aide 2025 Proceedings, 2025
Lightweight Intrusion Detection System on IoT Devices Using Machine Learning Techniques
Bhavesh Pahilajani, Yasser Al Alawi, Manaf Al Lamki, Mohamed Sirajudeen Yoosuf, Vijaya P, Joseph Mani, Ajay Vikram Singh
2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025
Hybrid Spinal-Fuzzy-DKN approach for breast cancer detection using magnetic resonance images
P. Vijaya
Research on Biomedical Engineering, 2024
Severity of lung infection identification and classification using optimization-enabled deep learning with IoT
P. Vijaya, Satish Chander, Roshan Fernandes, Anisha P. Rodrigues, R. Maheswari
Multimedia Systems, 2024
Machine learning for aerospace object categorization
Pavan Vignesh, R. Maheswari, P. Vijaya, U. Vignesh
AI and Blockchain Optimization Techniques in Aerospace Engineering, 2024
Contemporary Global Trends in Small Project Management Practices and Their Impact on Oman
Safiya Al Salmi, P. Vijaya
Communications in Computer and Information Science, 2024
Face Detection and Emotion Recognition
Anisha P Rodrigues, Roshan Fernandes, P. Vijaya
Cosmic 2024 IEEE International Conference on Computing Semiconductor Mechatronics Intelligent Systems and Communications Proceedings, 2024
Insights from Data Science and Machine Learning: Understanding Global Air Quality Dynamics
Ceur Workshop Proceedings, 2024
Predictive Correlation Frameworks for Optimized CPU Sensing and System Call Coordination
S Sheeba Rani, P. Vijaya, R. Maheswari, Sree Vishnu Varthini S
2nd IEEE International Conference on Recent Advances in Information Technology for Sustainable Development Icrais 2024 Proceedings, 2024
Early Prediction of At-Risk Students in Higher Education Institutions Using Adaptive Dwarf Mongoose Optimization Enabled Deep Learning
P. Vijaya, Rajeev Rajendran, Basant Kumar, Joseph Mani
Communications in Computer and Information Science, 2024
Comprehensive Data Analysis of Anticorrosion, Antifouling Agents, and the Efficiency of Corrosion Inhibitors in CO2 Pipelines
Vineeth Simhadri, Kukatlapalli Pradeep Kumar, P. Vijaya, Vinai George Biju
Novel Anti Corrosion and Anti Fouling Coatings and Thin Films, 2024
Tulu Language Text Recognition and Translation
Prathwini, Anisha P. Rodrigues, P. Vijaya, Roshan Fernandes
IEEE Access, 2024
Human Stress Detection
Roshan Fernandes, Anisha P Rodrigues, P. Vijaya, Vijaya Shetty S
Cosmic 2024 IEEE International Conference on Computing Semiconductor Mechatronics Intelligent Systems and Communications Proceedings, 2024
Utilizing Packet Tracer Simulation to Modern Smart Campus Initiatives for a Sustainable Future
Basant Kumar, Vijaya Padmanabha, Josephmani P., Rashmi Dwivedi
2024 IEEE 12th International Conference on Smart Energy Grid Engineering Sege 2024, 2024
Flamingo Search Sailfish Optimizer Based SqueezeNet for Detection of Breast Cancer Using MRI Images
P. Vijaya, Satish Chander, Roshan Fernandes, Anisha P. Rodrigues, Maheswari Raja
Cancer Investigation, 2024
Predictive Analytics Techniques in the Agricultural Industry: A Case Study
Anisha P Rodrigues, Roshan Fernandes, P. Vijaya, Maryam Al Washahi, Hothefa Shaker
2024 11th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2024, 2024
Preface
G. S. Vijay, M. C. Gowrishanker, Y. Nayak. Suhas
Communications in Computer and Information Science, 2024
Slithering Intelligence for Predicting Tectonic Plate Movement
Exploring the Micro World of Robotics Through Insect Robots, 2024
Intelligent System for Improving Scalability by Sharding for Agriculture Supply Chain
P. Saranya, Vijaya. P, R. Maheswari, Praba Palanisamy, Joseph Mani
2024 11th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2024, 2024
Towards Oman's Digital Transformation: A Comprehensive Analysis of Smart Government Development Index
Hothefa Shaker, Joseph Mani, P. Vijaya, Praba Palanisamy, Malik Al Shamli, Abbas Fadhil Aljuboori
1st International Conference on Innovative Engineering Sciences and Technological Research Iciestr 2024 Proceedings, 2024
CAViaR Secretary Bird Optimization Algorithm Enabled Transfer Learning for Melanoma Classification
P. Vijaya, Basant Kumar, Joseph Mani, Satish Chander, Roshan Fernandes, Hothefa Jassim, Dilip Kumar Singvi
Proceedings 8th IEEE EMBS Conference on Biomedical Engineering and Sciences Healthcare Evolution Through Technology and Artificial Intelligence Iecbes 2024, 2024
Audio Dub Detection Using Machine Learning
Roshan Fernandes, Akshata D Bhat, Adithya Rao K, Aditi Diwakar, Anisha P. Rodrigues, Divya Jennifer Dsouza, P. Vijaya
8th IEEE International Conference on Distributed Computing VLSI Electrical Circuits and Robotics Discover 2024 Proceedings, 2024
Dolphin-political optimized tversky index based feature selection in spark architecture for clustering big data
Satish Chander, P. Vijaya, Roshan Fernandes, Anisha P Rodrigues, Maheswari R
Advances in Engineering Software, 2023
AggTrust: New Approach for Aggregated Trust Value for IoT with Comparative Study
Kajol Rana, Ajay Vikram Singh, P. Vijaya
Proceedings of International Conference on Contemporary Computing and Informatics Ic3i 2023, 2023
Assistive image caption and tweet development using deep learning
Explainable Artificial Intelligence Xai Concepts Enabling Tools Technologies and Applications, 2023
Comparison of artificial intelligence models for prognosis of breast cancer
Explainable Artificial Intelligence Xai Concepts Enabling Tools Technologies and Applications, 2023
TAKEN: A Traffic Knowledge-Based Navigation System for Connected and Autonomous Vehicles
Nikhil Kamath B, Roshan Fernandes, Anisha P. Rodrigues, Mufti Mahmud, P. Vijaya, Thippa Reddy Gadekallu, M. Shamim Kaiser
Sensors, 2023
An Approach Using E-Khool User Log Data for E-Learning Recommendation System
P. Vijaya, M. Selvi
Journal of Information and Knowledge Management, 2022
A Parallel Fractional Lion Algorithm for Data Clustering Based on MapReduce Cluster Framework
Satish Chander, P. Vijaya, Praveen Dhyani
International Journal on Semantic Web and Information Systems, 2022
Recent Trust Management Models for Secure IoT Ecosystem
International Journal of Intelligent Systems and Applications in Engineering, 2022
A study on the evaluation of different regressors in Weather Prediction
Anisha P Rodrigues, Roshan Fernandes, P. Vijaya
International Conference on Artificial Intelligence and Data Engineering Aide 2022, 2022
Machine learning in genomics: identification and modeling of anticancer peptides
Girish Kumar Adari, Maheswari Raja, P. Vijaya
Data Science for Genomics, 2022
Intelligent Trust based Security Framework for Internet of Things
Kajol Rana, Ajay Vikram Singh, P. Vijaya
International Journal on Recent and Innovation Trends in Computing and Communication, 2022
Genetic factor analysis for an early diagnosis of autism through machine learning
A. Chaitanya Kumar, J. Andrew John, Maheswari Raja, P. Vijaya
Data Science for Genomics, 2022
Brain Tumor Detection using Machine Learning and Convolutional Neural Network
Bhuvaneshwari Shetty, Roshan Fernandes, Anisha P Rodrigues, P. Vijaya
International Conference on Artificial Intelligence and Data Engineering Aide 2022, 2022
Performance Study on Indexing and Accessing of Small File in Hadoop Distributed File System
Anisha P Rodrigues, Roshan Fernandes, P. Vijaya, Satish Chander
Journal of Information and Knowledge Management, 2021
Efficient virtual reality-based platform for virtual concerts
Roshan Fernandes, Arjun P. Gaonkar, Pratheek J. Shenoy, Anisha P. Rodrigues, Mohan B. A., Vijaya Padmanabha
Multimedia and Sensory Input for Augmented Mixed and Virtual Reality, 2021
Unsupervised learning methods for data clustering
Satish Chander, P. Vijaya
Artificial Intelligence in Data Mining Theories and Applications, 2021
An exploratory study of the key enabling factors of IT Projects Governance (ITPG) implementation in the public sector in Oman
Raqiya Ahmed Al Hilali, P. Vijaya
International Journal of Computing and Digital Systems, 2021
Academic students' performance prediction model: An Oman case study
P. Vijaya, Satish Chander, S.L. Gupta
International Journal of Information and Decision Sciences, 2021
Tunicate Swarm-Based Black Hole Entropic Fuzzy Clustering for Data Clustering using COVID Data
Satish Chander, P Vijaya
2020 IEEE 17th India Council International Conference Indicon 2020, 2020
Guest editorial
Praveen Dhyani Vijaya, Binu D
Data Technologies and Applications, 2020
Knowledge and data mining for recent and advanced applications using emerging technologies
Vijaya P, Binu D
Data Technologies and Applications, 2020
Introduction to the special issue on intelligence on scalable computing for recent applications
Vijaya P, Binu D
Scalable Computing, 2020
Introduction to the special issue on intelligence on scalable computing for recent applications
Scalable Computing, 2020
Jaya Spider Monkey Optimization-driven Deep Convolutional LSTM for the prediction of COVID'19
Satish Chander, Vijaya Padmanabha, Joseph Mani
Bio Algorithms and Med Systems, 2020
Editorial
International Journal of Bioinformatics Research and Applications, 2020
LENN: Laplacian Probability Based Extended Nearest Neighbor Classification Algorithm for Web Page Retrieval
P. Vijaya, Satish Chander, G. Raju
2019 International Conference on Data Science and Communication Icondsc 2019, 2019
LionRank: lion algorithm-based metasearch engines for re-ranking of webpages
P. Vijaya, Satish Chander
Science China Information Sciences, 2018
ADOFL: Multi-Kernel-Based Adaptive Directive Operative Fractional Lion Optimisation Algorithm for Data Clustering
Satish Chander, P. Vijaya, Praveen Dhyani
Journal of Intelligent Systems, 2018
A Systematic Review on Different Security Framework for IoT
Kajol Rana, Ajay Vikram Singh, P. Vijaya
5th International Symposium on Innovation in Information and Communication Technology Isiict 2018, 2018
MO-ADDOFL: Multi-objective-based adaptive dynamic directive operative fractional lion algorithm for data clustering
Satish Chander, P Vijaya, Praveen Dhyani
Proceedings of Majan International Conference Promoting Entrepreneurship and Technological Skills National Needs Global Trends Mic 2018, 2018
Metasearch engine: A technology for information extraction in knowledge computing
P. Vijaya, Satish Chander
Knowledge Computing and Its Applications Knowledge Computing in Specific Domains, 2018
Multi kernel and dynamic fractional lion optimization algorithm for data clustering
Satish Chander, P. Vijaya, Praveen Dhyani
Alexandria Engineering Journal, 2018
Fgv MO-ADDOFL: Multi-objective-based adaptive dynamic directive operative fractional lion algorithm for data clustering
Satish Chander, P. Vijaya, Praveen Dhyani
2017 International Conference on Infocom Technologies and Unmanned Systems Trends and Future Directions Ictus 2017, 2017
A multi-constraint based objective function and lion optimization for the data clustering
Satish Chander, P. Vijaya, Praveen Dhyani
2017 International Conference on Infocom Technologies and Unmanned Systems Trends and Future Directions Ictus 2017, 2017
Artificial neural network-based merging score for Meta search engine
P. Vijaya, G. Raju, Santosh Kumar Ray
Journal of Central South University, 2016
Fractional Lion Algorithm-an optimization algorithm for data clustering
Satish Chander, P. Vijaya, Praveen Dhyani
Journal of Computer Science, 2016
DOFL: Kernel based directive operative fractional lion optimisation algorithm for data clustering
Satish Chander, P. Vijaya, Praveen Dhyani
International Review on Computers and Software, 2016
S-MSE: Asemantic Meta search engine using semantic similarity and reputation measure
Journal of Theoretical and Applied Information Technology, 2014
An ontology based meta-search engine for effective web page retrieval
International Review on Computers and Software, 2013
Efficient bottom-up hybrid hierarchical clustering techniques for protein sequence classification
P.A. Vijaya, M. Narasimha Murty, D.K. Subramanian
Pattern Recognition, 2006
Efficient median based clustering and classification techniques for protein sequences
P. A. Vijaya, M. Narasimha Murty, D. K. Subramanian
Pattern Analysis and Applications, 2006
An Efficient Hybrid Hierarchical Agglomerative Clustering (HHAC) technique for partitioning large data sets
P. A. Vijaya, M. Narasimha Murty, D. K. Subramanian
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Analysis of leader based clustering algorithms for pattern classification
Proceedings of the 2nd Indian International Conference on Artificial Intelligence Iicai 2005, 2005
Leaders-Subleaders: An efficient hierarchical clustering algorithm for large data sets
P.A Vijaya, M Narasimha Murty, D.K Subramanian
Pattern Recognition Letters, 2004
An efficient technique for protein sequence clustering and classification
P.A. Vijaya, M.N. Murty, D.K. Subramanian
Proceedings International Conference on Pattern Recognition, 2004
An efficient incremental protein sequence clustering algorithm
IEEE Region 10 Annual International Conference Proceedings TENCON, 2003

Vijaya Padmanabha

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