Vivekanandam

@lincoln.edu.my

Pro Dean - School of AI Computing and Multimedia
Lincoln University College

Vivekanandam


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https://researchid.co/vivekanandam

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications
16

Scopus Publications

625

Scholar Citations

11

Scholar h-index

12

Scholar i10-index

Scopus Publications

  • Scalable parkinson’s disease prediction using mathematical modeling, hilbert transforms, and transformer-based deep learning
    THALAPATHIRAJ.S, VIVEKANANDAM B, RAJENDRA KUMAR TRIPATHI
    Journal of Theoretical and Applied Information Technology, 2026
    Parkinsons disease (PD) is a progressive neurological disorder necessitating early and precise diagnosis for effective therapy. However, traditional machine learning and convolutional neural network (CNN) methods generally have problems when used on heterogeneous biomedical data since they don't scale well, don't generalize well, and are harder to understand. To tackle these issues, this research presents a scalable hybrid system that combines mathematical modeling, Hilbert transform-based spatial embedding, and transformer-based deep learning architectures for predicting Parkinson's disease. The suggested Hilbert-based embedding adds biologically inspired spatial correlations that keep structural information and make features more stable. To efficiently capture both local and global dependencies, these improved features are subsequently processed using advanced transformer architectures including Swin Transformer and Vision Transformer (ViT). Testing the proposed framework on multimodal datasets that include spiral drawings, wave patterns, and functional MRI (fMRI) pictures shows that it is more accurate, precise, and recall than traditional CNN and machine learning models. The Swin Transformer with Hilbert embedding had the best performance, with an accuracy of 97.96%. This shows that it is more general and more robust. The findings demonstrate that the suggested mathematically based framework offers a scalable, interpretable, and clinically significant approach for the early prediction of Parkinson’s disease.
  • Understanding Cloud Computing in the Mobile and IoT Context
    M. Kavitha, P. Sangeetha, M. Satthiyaraju, B. Vivekanandam, S. Aarthi, D. Suseela
    Intelligent Mobile and Iot Ecosystems Bridging Cloud Fog Edge and AI, 2026
    The need to access data anytime and anywhere has produced the necessity to accept cloud computing for mobile and IoT devices more and more. This demands for a strong computing platform in the cloud to support the growing huge data requirements to address low-latency needs, high availability, and the emergence of mobile and IoT technologies. The more people pull at a particular cloud computer system, the better it becomes regarding structure, connection, work, and even artistry. Intelligent computing and context-aware services thus enhance user experience on mobile and IoT applications. Further, there are the AI-based XaaS solutions that promote the effectiveness and reliability of services provided by the cloud environment. Advanced innovations like serverless nodes, edge computing, and AI innovations adequately deal with the problems of security and privacy issues concerning data access so as to provide uninterrupted and secure operations in the dynamic environment.
  • Equitable edge coloring of unionized triangular patterns in graphs
    D. Kavitha Thenmozhi, B. Vivekanandam, K. Bhuvaneswari
    Security Issues in Communication Devices Networks and Computing Models Volume 2, 2025
    Equitable edge coloring is a type of network labeling with two main limitations: none of the neighboring edges can have the identical label (color), and the quantity of edges in two separate color classes can only differ by one. In this chapter, we aim to create patterns by combining several simple undirected graphs using the concept of equitable edge coloring. We demonstrate that the union of multiple triangular patterns can be equitably colored with the minimum Δ colors, regardless of whether the quantity of edges and vertices is even or uneven. This distribution of colors ensures that each color is used either times, achieving a balanced and efficient edge coloring.
  • Critical buckling analysis of functionally graded porous beam using Karush-Kuhn-Tucker conditions
    Advances in Computational Design, 2025
  • Privacy Protection: YOLOv11 Face Detection and Blurring for GDPR Compliance in Hotels
    Mohammed Ikramullah Khan, Vivekanandam B
    Journal of Innovative Image Processing, 2024
    Surveillance systems have undergone a drastic transformation over the years, with the advent of artificial intelligence (AI) in surveillance paving the way for better security and monitoring in public as well as private places, including hotels. But not without its considerable privacy implications since the introduction of the European Union (EU) law, the General Data Protection Regulation (GDPR), which aims to protect the privacy of EU citizens. The surveillance system collects sensitive guest data from personal information, facial data, and general appearance, making it paramount that hotels adhere to mandatory data protection laws such as the General Data Protection Regulation (GDPR) for visitors in the EU, to ensure that the data is not misused or accessed by unauthorized individuals. A privacy-protection framework for face detection and anonymization in hotel surveillance systems has been designed in this research to protect privacy from surveillance cameras based on YOLOv11, a top-tier convolutional neural network (CNN) model. The system checks for faces in video feeds/images and accurately applies a blurring mechanism, successfully anonymizing identities. The process is designed to comply with GDPR regulations while preserving essential capabilities of surveillance systems through anonymization. One of the inherent challenges is ensuring the privacy of the individuals going about their day-to-day business in front of such surveillance cameras, and at the same time, ensuring that the footage that could possibly be shared with authorities or even other stakeholders is useful. Such integration of YOLOv11 in hotel surveillance systems showcases the potential of artificial intelligence to provide security without compromising privacy.
  • Ubiquitous Learning Experience using VR in Electronic Science Education
    Dinesh Rajassekharan, Vivekanandam B.
    Journal of Trends in Computer Science and Smart Technology, 2024
    In this technology-driven society, designing, prototyping and miniaturization of electronic systems pose major challenges, which in turn makes the electronic science education more essential. The objective of electronic science education is to increase students’ awareness to gain more technical proficiency to understand the miniaturized electronic system design and troubleshoot electronic systems. The evolution of electronic science with advanced technological achievements also faces contemporary challenges that virtual reality technologies are well-positioned to address. Virtual reality in electronic science education enhances learning by providing immersive and interactive experiences. It allows students to explore complex concepts, simulate experiments, and engage in hands-on activities, fostering a deeper understanding of electronic science principles. VR can create a dynamic and engaging learning environment, making abstract concepts more tangible and promoting experiential learning in a virtual space. This research study aims to encourage the active students’ participation in learning about the traditional and modern practices involved in electronics systems analysis while experiencing the immersive interaction related to various real-time conditions and applications.
  • Novel Kuhn-Tucker conditions for vibration analysis in a functionally graded porous beam using the R-program
    Geetha Narayanan Kannaiyan, Vivekanandam Balasubramaniam, Bridjesh Pappula, Seshibe Makgato
    Results in Engineering, 2024
    Functionally graded materials provide a flexible and individualized strategy for material design, allowing for optimization of properties and performance for particular purposes. The investigation considers the effects of simply supported (SS), clamped-clamped (CC) and clamped-free (CF) configurations. The study examines the vibration characteristics of bi-directional functionally graded porous beams (BDFGPB) using the third-order shear deformation theory, considering both even and uneven porosity conditions. The Hamilton method is used to derive equilibrium equations for beams, which are then solved using the Kuhn-Tucker technique and R-program. The BDFGPB's validity was verified by comparing it with open literature, revealing deviations of 3.19%, 1.25%, and 2.15% in non-dimensional natural frequency for SS, CC, and CF boundary conditions. Furthermore, as the porosity index increases, the dimensionless natural frequency decreases, reducing beam stiffness and rigidity. This study demonstrates that porosity plays a critical role in the design of modern structures, as its ratio greatly impacts their performance and responsiveness.
  • Elastostatic behaviour of functionally graded porous beam: Novel Kuhn Tucker conditions with R program for mathematical computing
    Journal of Computational Applied Mechanics, 2024
  • NOVEL KUHN-TUCKER CONDITIONS WITH R-PROGRAM TO ANALYZE THE BUCKLING OF A FUNCTIONALLY GRADED POROUS BEAM
    Geetha Narayanan Kannaiyan, Vivekanandam Balasubramaniam
    Journal of Mechanics of Materials and Structures, 2024
  • ELASTOSTATIC BEHAVIOR OF FUNCTIONALLY GRADED BEAM – NOVEL KUHN TUCKER CONDITIONS FOR MATHEMATICAL COMPUTING
    Academic Journal of Manufacturing Engineering, 2024
  • Mask Region-based Convolution Neural Network (Mask R-CNN) Classification of Alzheimer’s Disease Based on Magnetic Resonance Imaging (MRI)
    , Anil Kumar Pallikonda, P Suresh Varma, B. Vivekanandam
    International Journal of Image Graphics and Signal Processing, 2023
  • Optimizing student engagement in edge-based online learning with advanced analytics
    Rasheed Abdulkader, Firas Tayseer Mohammad Ayasrah, Venkata Ramana Gupta Nallagattla, Kamal Kant Hiran, Pankaj Dadheech, Vivekanandam Balasubramaniam, Sudhakar Sengan
    Array, 2023
  • RETRACTED ARTICLE: Prewitt Logistic Deep Recurrent Neural Learning for Face Log Detection by Extracting Features from Images(Arabian Journal for Science and Engineering, (2023), 48, (2589))
    Sreekumar Krishnan Nair, Sathiya Kumar Chinnappan, Anil Kumar Dubey, Arjun Subburaj, Shanthi Subramaniam, Vivekanandam Balasubramaniam, Sudhakar Sengan
    Arabian Journal for Science and Engineering, 2023
  • Video-Based Deep Face Recognition Using Partial Facial Information
    B. Vivekanandam, Midhunchakkaravarthy, Balaganesh Duraisamy
    Lecture Notes in Networks and Systems, 2021
  • Face recognition from video frames using hidden Markov model classification model based on modified random feature extraction
    B Vivekanandam, M Rajesh Babu
    Journal of Computational and Theoretical Nanoscience, 2019
  • Adaptive face recognition under different pose and illumination variation in video survelliance
    Journal of Advanced Research in Dynamical and Control Systems, 2017

RECENT SCHOLAR PUBLICATIONS

  • A Deep Learning Framework for Early Detection and Treatment of Livestock Skin Diseases
    N Umapathi, V Balasubramaniam
    Sustainable Global Societies Initiative 1 (1) , 2025
    2025
  • Early Prediction of Parkinson’s Disease by Using MathematicalModeling and Hilbert ‎Transform
    RKT Thalapathiraj S,Vivekanandam B
    International Journal of Basic and Applied Sciences 14 (8), 453-460 , 2025
    2025
  • Transfer learning based osteoporosis prediction using enhanced medical imaging and fuzzy fusion
    N Kaur, S Khan, I Alazman, M Bin-Asfour, MN Alam, V Balasubramaniam, ...
    Scientific Reports , 2025
    2025
    Citations: 1
  • A Deep Learning Framework for Early Detection and Treatment of Livestock Skin Diseases
    U NAGAPPAN
    SGS-Engineering & Sciences 1 (4) , 2025
    2025
  • Scalable Parkinson’s Disease Prediction Using Mathematical Modeling, Hilbert Transforms, and Transformer-Based Deep Learning
    T SAMBANDAM, B Vivekanandam, R kumar Tripathi
    SGS-Engineering & Sciences 1 (4) , 2025
    2025
  • AI-Driven Early Identification of Parkinson’s Disease Using Machine Learning and Mathematical Modelling
    T SAMBANDAM, B Vivekanandam, R kumar Tripathi
    SGS-Engineering & Sciences 1 (2) , 2025
    2025
  • Equitable edge coloring of unionized triangular patterns in graphs
    DK Thenmozhi, B Vivekanandam, K Bhuvaneswari
    Security Issues in Communication Devices, Networks and Computing Models, 9-16 , 2025
    2025
  • Comprehensive Review of Parkinson's disorder Disease: From Diagnostics and Medication to Perspectives
    T SAMBANDAM, B Vivekanandam
    SGS-Engineering & Sciences 1 (1) , 2025
    2025
  • Machine Learning in Cardiovascular Disease Prediction: A Comparative Study of Classification Models
    AP Srivastava, B Vivekanandam, M Khan
    SGS-Engineering & Sciences 1 (1) , 2025
    2025
  • The Role of Edge Computing in Optimizing Cloud-Based Records Management for Rural Information Access in Akwa Ibom State, Nigeria
    BO Esang, B Vivekanandam
    International Journal of Emerging Issues in Social Science, Arts and … , 2025
    2025
    Citations: 1
  • Privacy Protection: YOLOv11 Face Detection and Blurring for GDPR Compliance in Hotels
    VB Mohammed Ikramullah khan
    Journal of Innovative Image Processing 4 (6), 397-417 , 2025
    2025
  • Dynamic Multimodal Control Algorithm for Virtual-Reality Enabled Human-Robot Collaboration in Surgery
    V Malati Basnet
    2025 International Conference on Intelligent Innovations in Engineering and … , 2025
    2025
  • Hybrid Deep Learning Architecture for Automated Chest X-ray Disease Detection with Explainable Artificial Intelligence
    JRA B. Vivekanandam1 , Kambala Vijaya Kumar2
    Healthcraft Frontiers 3 (2), 86-96 , 2025
    2025
  • Insider Threats in Banking Sector: Detection, Prevention, and Mitigation
    VB Sopheaktra Huy , Sokroeurn Ang , Mony Ho
    Journal of Cyber Security and Risk Auditing 2025 (4), 257-265 , 2025
    2025
  • Federated multi-modal learning for cross-platform image computation: A functional analysis and nonlinear optimization approach to privacy preservation
    S Janarthanam, RSK Boddu, B Vivekanadam, S Ubaydullayeva, ...
    Results in Nonlinear Analysis 8 (4), 1-11 , 2025
    2025
  • Insider Threats in Banking Sector: Detection, Prevention, and Mitigation
    S Huy, S Ang, M Ho, V Balasubramaniam
    J. Cyber Secur. Risk Audit 2025, 257-265 , 2025
    2025
    Citations: 1
  • Critical buckling analysis of functionally graded porous beam using Karush-Kuhn-Tucker conditions
    BPSM Geetha Narayanan Kannaiyan, Vivekanandam Balasubramaniam
    Advances in Computational Design 10 (1), 1-34 , 2025
    2025
    Citations: 6
  • Implementation of Digital Educational Technology: Issues for Managerial Consideration in Nigeria's Public Sector
    B Esang, B Vivekanandam
    International Journal of Emerging Issues in Social Science, Arts and … , 2024
    2024
    Citations: 3
  • Precise performance model for a complex system using the self-adaptive learning-based Autonomous test framework.
    HK Andi, B Vivekanandam, MR Babu, E Ananth, T Nandhini
    Frontiers in Health Informatics 13 (8) , 2024
    2024
  • Surveillance 5.0: Next-Gen Security Powered by Quantum AI Optimization
    V B
    Recent Research Reviews Journal 3 (1), 113-124 , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • Artificial Intelligence Algorithm with SVM Classification using Dermascopic Images for Melanoma Diagnosis
    B Vivekanandam
    Journal of Artificial Intelligence and Capsule Networks 3 (01), 34-42 , 2021
    2021
    Citations: 146
  • Analysis of Recent Trend and Applications in Block Chain Technology
    B Vivekanandam
    Journal of IoT in Social, Mobile, Analytics, and Cloud 2 (4), 200-206 , 2020
    2020
    Citations: 82
  • IoT based Biotelemetry for Smart Health Care Monitoring System
    B Vivekanandam
    Journal of Information Technology and Digital World 2 (3), 183-190 , 2020
    2020
    Citations: 78
  • Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
    B Vivekanandam
    Journal of Ubiquitous Computing and Communication Technologies (UCCT) 3 (2 … , 2021
    2021
    Citations: 62
  • Optimizing student engagement in edge-based online learning with advanced analytics
    R Abdulkader, FTM Ayasrah, VRG Nallagattla, KK Hiran, P Dadheech, ...
    Array 19, 100301 , 2023
    2023
    Citations: 41
  • Evaluation of Activity Monitoring Algorithm based on Smart Approaches
    B Vivekanandam
    Journal of Electronics and Informatics 2 (3), 175-181 , 2020
    2020
    Citations: 27
  • Speedy image crowd counting by light weight convolutional neural network
    B Vivekanandam
    Journal of Innovative Image Processing 3 (3), 208-222 , 2021
    2021
    Citations: 22
  • Facemask Detection Algorithm on COVID Community Spread Control using EfficientNet Algorithm
    B Vivekanandam
    Journal of Soft Computing Paradigm (JSCP) 3 (2), 110-122 , 2021
    2021
    Citations: 21
  • Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder
    B Vivekanandam
    Journal of Electrical Engineering and Automation (EEA) 3 (03), 214-229 , 2021
    2021
    Citations: 19
  • Fault Detection and Diagnosis in Air Handling Units with a Novel Integrated Decision Tree Algorithm
    B Vivekanandam
    Journal of trends in Computer Science and Smart technology (TCSST) 3 (01), 49-58 , 2021
    2021
    Citations: 17
  • Smart Parking with Fair Selection and Imposing Higher Privacy Constraints in Parking Owner and Driver Information
    B Vivekanandam
    IRO Journal on Sustainable Wireless Systems 3 (1), 11-20 , 2021
    2021
    Citations: 14
  • Ideal time-based voltage control using evolutionary algorithm in distributed generator centered networks
    B Vivekanandam
    Journal of Electronics and Informatics 2 (4), 233-238 , 2021
    2021
    Citations: 10
  • Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
    B Vivekanandam
    Journal of Electronics and Informatics 3 (2), 138-149 , 2021
    2021
    Citations: 9
  • Face Recognition from Video Frames Using Hidden Markov Model Classification Model Based on Modified Random Feature Extraction
    MRB B.Vivekanandam
    Journal of Computational and Theoretical Nanoscience 16 (5/6), 2439–2447 , 2019
    2019
    Citations: 8
  • Prewitt Logistic Deep Recurrent Neural Learning for Face Log Detection by Extracting Features from Images
    VBSS Sreekumar Krishnan Nair, Sathiya Kumar Chinnappan, Anil Kumar Dubey ...
    Arabian Journal for Science and Engineering 46 (4) , 2021
    2021
    Citations: 7
  • A Novel Hybrid HNN and Firefly Algorithm to Overcome Denial of Sleep Attack on Wireless Sensor Nodes
    B Vivekanandam
    Journal of Ubiquitous Computing and Communication Technologies (UCCT) 2 (04 … , 2020
    2020
    Citations: 7
  • Critical buckling analysis of functionally graded porous beam using Karush-Kuhn-Tucker conditions
    BPSM Geetha Narayanan Kannaiyan, Vivekanandam Balasubramaniam
    Advances in Computational Design 10 (1), 1-34 , 2025
    2025
    Citations: 6
  • Novel Kuhn-Tucker conditions for vibration analysis in a functionally graded porous beam using the R-program
    GN Kannaiyan, V Balasubramaniam, B Pappula, S Makgato
    Results in Engineering 22, 102064 , 2024
    2024
    Citations: 5
  • Novel Kuhn–Tucker conditions with R-program to analyze the buckling of a functionally graded porous beam
    GN Kannaiyan, V Balasubramaniam
    Journal of Mechanics of Materials and Structures 19 (3), 453-476 , 2024
    2024
    Citations: 4
  • A CREDIBLE WAY OF FACE RECOGNITION AND CLASSIFICATION SYSTEM IN VIDEO SCRUTINY
    MRB B.Vivekanandam
    Journal of Web Engineering 17 (6(2018)), 3701-3714 , 2018
    2018
    Citations: 4