Author : Padmavathi S M
Page No: 486 - 500
Abstract : 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 highlights the advantages telemedicine offers, such as increased flexibility, reduced commuting time, and better time management. It also examines the challenges doctors face, including the demands of always being digitally accessible, the learning curve of new technologies, and the difficulty in maintaining boundaries between personal and professional life. Using both quantitative and qualitative data, this research compares the telemedicine adaptation experiences of doctors in public versus private hospitals, considering factors such as hospital infrastructure, support systems, and patient load. Furthermore, the paper delves into the role of hospital management and policy in easing the digital transition and fostering a more harmonious work-life balance. By analyzing technological tools and frameworks in telemedicine, the research identifies areas where improvements can be made, offering recommendations for enhancing doctors' digital efficiency while promoting better work-life harmony. This study contributes to understanding how technology can be harnessed to benefit healthcare professionals, particularly in managing the dual demands of professional duties and personal well-being.
Keyword AI-Driven Telemedicine Platforms, Digital Health Adaptation, Remote Monitoring Technologies, Work-Life Integration in Healthcare, AI-Based Time Management Tools
Reference:

1. Selvan, M. A. (2024). Deep Learning Techniques for Comprehensive Emotion Recognition and Behavioral Regulation.
2. Selvan, M. A. (2024). SVM-Enhanced Intrusion Detection System for Effective Cyber Attack Identification and Mitigation.
3. Selvan, M. A. (2024). IoT-Integrated Smart Home Technologies with Augmented Reality for Improved User Experience.
4. Selvan, M. A. (2024). Multipath Routing Optimization for Enhanced Load Balancing in Data-Heavy Networks.
5. Selvan, M. A. (2024). Transforming Consumer Behavior Analysis with Cutting-Edge Machine Learning.
6. FELIX, A. S. M. M. D., & KALAIVANAN, X. D. M. S. Averting Eavesdrop Intrusion in Industrial Wireless Sensor Networks.
7. Selvan, M. A. (2021). Robust Cyber Attack Detection with Support Vector Machines: Tackling Both Established and Novel Threats.
8. Selvan, M. A. (2023). INDUSTRY-SPECIFIC INTELLIGENT FIRE MANAGEMENT SYSTEM.
9. Selvan, M. A. (2023). FIRE MANAGEMENT SYSTEM FOR INDUTRIAL SAFETY APPLICATIONS.
10. Selvan, M. A. (2023). CONTAINMENT ZONE ALERTING APPLICATION A PROJECT BASED LEARNING REPORT.
11. Selvan, M. A. (2023). A PBL REPORT FOR CONTAINMENT ZONE ALERTING APPLICATION.
12. Reka, R., R. Karthick, R. Saravana Ram, and Gurkirpal Singh. “Multi head self-attention gated graph convolutional network based multi‑attack intrusion detection in MANET.” Computers & Security 136 (2024): 103526.
13. Meenalochini, P., R. Karthick, and E. Sakthivel. “An Efficient Control Strategy for an Extended Switched Coupled Inductor Quasi-Z-Source Inverter for 3 Φ Grid Connected System.” Journal of Circuits, Systems and Computers 32.11 (2023): 2450011.
14. Karthick, R., et al. “An optimal partitioning and floor planning for VLSI circuit design based on a hybrid bio-inspired whale optimization and adaptive bird swarm optimization (WO-ABSO) algorithm.” Journal of Circuits, Systems and Computers 32.08 (2023): 2350273.
15. Rajagopal RK, Karthick R, Meenalochini P, Kalaichelvi T. Deep Convolutional Spiking Neural Network optimized with Arithmetic optimization algorithm for lung disease detection using chest X-ray images. Biomedical Signal Processing and Control. 2023 Jan 1;79:104197.
16. Karthick, R., and P. Meenalochini. “Implementation of data cache block (DCB) in shared processor using field-programmable gate array (FPGA).” Journal of the National Science Foundation of Sri Lanka 48.4 (2020).
17. Karthick, R., A. Senthilselvi, P. Meenalochini, and S. Senthil Pandi. “Design and analysis of linear phase finite impulse response filter using water strider optimization algorithm in FPGA.” Circuits, Systems, and Signal Processing 41, no. 9 (2022): 5254-5282.
18. Karthick, R., and M. Sundararajan. “SPIDER-based out-of-order execution scheme for HtMPSOC.” International Journal of Advanced Intelligence paradigms 19.1 (2021): 28-41.
19. Karthick, R., Dawood, M.S. & Meenalochini, P. Analysis of vital signs using remote photoplethysmography (RPPG). J Ambient Intell Human Comput 14, 16729–16736 (2023). https://doi.org/10.1007/s12652-023-04683-w
20. Madhan, E. S., Kannan, K. S., Rani, P. S., Rani, J. V., & Anguraj, D. K. (2021). A distributed submerged object detection and classification enhancement with deep learning. Distrib. Parallel Databases, 1-17.
21. Sakthivel, M. (2021). An Analysis of Load Balancing Algorithm Using Software-Defined Network. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(9), 578-586.
22. Padmanaban, K. (2021). A Novel Groundwater Resource Forecasting Technique for Cultivation Utilizing Wireless Sensor Network (WSN) and Machine Learning (ML) Model. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(2), 2186-2192.
23. Kanna, D. K., Devabalan, D. P., Hariharasitaraman, S., & Deepa, P. (2018). Some Insights on Grid Computing-A Study Perspective. International Journal of Pure and Applied Mathematics, 118(8), 47-50.
24. Kumar, V. S., & Naganathan, E. R. (2015). Segmentation of Hyperspectral image using JSEG based on unsupervised clustering algorithms. ICTACT Journal on Image and Video Processing, 6(2), 1152-1158.
25. Saravanan, V., Rajakumar, S., Banerjee, N., & Amuthakkannan, R. (2016). Effect of shoulder diameter to pin diameter ratio on microstructure and mechanical properties of dissimilar friction stir welded AA2024-T6 and AA7075-T6 aluminum alloy joints. The International Journal of Advanced Manufacturing Technology, 87, 3637-3645.
26. Abdulkarem, W., Amuthakkannan, R., & Al-Raheem, K. F. (2014, March). Centrifugal pump impeller crack detection using vibration analysis. In 2nd International Conference on Research in Science, Engineering and Technology (pp. 206-211).
27. Saravanan, V., Banerjee, N., Amuthakkannan, R., & Rajakumar, S. (2015). Microstructural evolution and mechanical properties of friction stir welded dissimilar AA2014-T6 and AA7075-T6 aluminum alloy joints. Metallography, Microstructure, and Analysis, 4, 178-187.
28. Amuthakkannan, R., Kannan, S. M., Selladurai, V., & Vijayalakshmi, K. (2008). Software quality measurement and improvement for real-time systems using quality tools and techniques: a case study. International Journal of Industrial and Systems Engineering, 3(2), 229-256.
29. Vijayalakshmi, K., Ramaraj, N., & Amuthakkannan, R. (2008). Improvement of component selection process using genetic algorithm for component-based software development. International Journal of Information Systems and Change Management, 3(1), 63-80.
30. Amuthakkannan, R. (2012). Parameters design and performance analysis of a software-based mechatronics system using Taguchi robust design–a case study. International Journal of Productivity and Quality Management, 10(1), 1-24.
31. Amuthakkannan, R., Kannan, S. M., Vijayalakshmi, K., & Ramaraj, N. (2009). Reliability analysis of programmable mechatronics system using Bayesian approach. International Journal of Industrial and Systems Engineering, 4(3), 303-325.
32. Saravanan, V., Banerjee, N., Amuthakkannan, R., & Rajakumar, S. (2015). Microstructure and mechanical properties of friction stir welded joints of dissimilar AA6061-T6 and AA7075-T6 aluminium alloys. Applied Mechanics and Materials, 787, 350-354.
33. Senthilkumar, M., Somasundaram, S., & Amuthakkannan, R. (2009). Power aware multiple QoS constraints routing protocol with mobility prediction for MANET. International Journal of Information Systems and Change Management, 4(2), 156-170.
34. Amuthakkannan, R., Kannan, S. M., Vijayalakshmi, K., & Jayabalan, V. (2007). Managing change and reliability of distributed software system. International Journal of Information Systems and Change Management, 2(1), 30-49.
35. Amuthakkannan, R., Babu, C. K., & Kannan, S. M. (2010). An approach to the minimisation of makespan in the textile industry using ant colony optimisation. International Journal of Services and Operations Management, 7(2), 215-230.
36. Khan Chand, Anupama Singh and N.C.Shahi(2012). Engineering Properties of Extruded Jaggery Based Snack From Soya Wheat Flour. Journal of Environment and Ecology.30 (2): 299-302.
37. Dhiraj Kumar Yadav, Khan Chand and Purnima Kumari (2022). Effect of fermentation parameters on physicochemical and sensory properties of Burans wine. Journal of System Microbiology and Biomanufacturing, 2 (1, Jan): 1-13.
38. Asfaq and Khan Chand(2020).Effect of moisture absorber and high-density polyethylene bags on shelf life of edible coated jaggery cubes during storage. Sugar Tech (Nov-Dec 2020), 22(6):1130–1137.
39. Chehelgerdi, M., Chehelgerdi, M., Allela, O. Q. B., Pecho, R. D. C., Jayasankar, N., Rao, D. P., … & Akhavan-Sigari, R. (2023). Progressing nanotechnology to improve targeted cancer treatment: overcoming hurdles in its clinical implementation. Molecular cancer, 22(1), 169.
40. Srivastava, A., & Rao, D. P. (2014). Enhancement of seed germination and plant growth of wheat, maize, peanut and garlic using multiwalled carbon nanotubes. Eur Chem Bull, 3(5), 502-504.
41. Singh, S., Rao, D. P., Yadava, A. K., & Yadav, H. S. (2011). Synthesis and characterization of oxovanadium (IV) Complexes with tetradentate schiff-base ligands having thenil as precursor molecule. Current Research in Chemistry, 3(2), 106-113.
42. Rao, D. P. (2019). A review on versatile applications of novel Schiff bases and their metal complexes. Letters in Applied NanoBioScience, 8(4), 675-681.
43. Rao, D. P., Yadav, H. S., Yadava, A. K., Singh, S., & Yadav, U. S. (2011). In-situ preparation of macrocyclic complexes of dioxomolybdenum (VI) involving a heterocyclic precursor. Journal of Coordination Chemistry, 64(2), 293-299.
44. Gangwar, M., Singh, A. P., Ojha, B. K., Shukla, H. K., Srivastava, R., & Goyal, N. (2020). Intelligent Computing Model For Psychiatric Disorder. Journal of Critical Reviews, 7(7), 600-603.
45. Rathore, A., Kushwaha, P. K., & Gangwar, M. (2018). A review on use of manufactured sand in concrete production. Int. J. Adv. Res. Dev, 3, 97-100.
46. Gangwar, M., Singh, A. P., Ojha, B. K., Srivastava, R., & Singh, S. (2020). Machine learning techniques in the detection and classification of psychiatric diseases. Journal of Advanced Research in Dynamical and Control Systems, 12(5), 639-646.
47. Gangwar, M., Mishra, R. B., & Yadav, R. S. (2014). Classical and intelligent computing methods in psychiatry and neuropsychitry: an overview. International Journal of Advanced Research in IT and Engineering, 3(12), 1-24.
48. Patil, R. S., & Gangwar, M. (2022, May). Heart Disease Prediction Using Machine Learning and Data Analytics Approach. In Proceedings of International Conference on Communication and Artificial Intelligence: ICCAI 2021 (pp. 351-361). Singapore: Springer Nature Singapore.
49. Gangwar, M., Mishra, R. B., Yadav, R. S., & Pandey, B. (2013). Intelligent computing methods for the interpretation of neuropsychiatric diseases based on Rbr-Cbr-Ann integration. International Journal of Computers & Technology, 11(5), 2490-2511.
50. Gangwar, M., Mishra, R. B., Yadav, R. S., & Pandey, B. (2012). Intelligent computing method for the interpretation of neuropsychiatric diseases. International Journal of Computer Applications, 55(17), 23-31.
51. Prakash, N., Balaji, V. R., & Sudha, M. (2016). Power quality improvement of grid inter connected hybrid system using STATCOM. International Journal of Advanced Engineering Technology, 7(2), 1225-1233.
52. Prakash, N., Balaji, V. R., & Sudha, M. (2016). Solar powered automated irrigation system for agriculture. International Journal of Advanced Engineering Technology, 7(II), 1225-1233.
53. Prakash, N., Ranithottunggal, D., & Sundaram, M. (2013). An Effective Wind Energy System base on Buck-Boost Controller. Researt Journal of Applied Sciences, Engineering and Technology, 6(5), 825-834.
54. SM, P., Sharma, M., Das, G., Mahajan, T., & Malik, S. (2021). Integration of human resource management and supply chain Network with specific reference to overall quality management. Turkish Online Journal of Qualitative Inquiry, 12(3).
55. Riyaz Khan, N. H., Venkatesh, S., & Padmavathi, S. Behavioural Analysis of Concrete Using Micro Silica and Hypo Sludge as Partial Replacement in Cement.
56. Padmavathi, S. M., Lakshmi, R. B., Srinivasa, G., & Venkatesh, S. Contemporary Issues, Potentials and Challenges of Education System in India: A Brief Overview.
57. Meena, S. B., Patil, P. R., Kandharkar, S. R., Hemalatha, N., Khade, A., Dixit, K. K., & Chinthamu, N. (2024). The Evolution Of Smart Grid Technologies: Integrating Renewable Energy Sources, Energy Storage, And Demand Response Systems For Efficient Energy Distribution. Nanotechnology Perceptions, 1098-1109.
58. Virmani, D., Ghori, M. A. S., Tyagi, N., Ambilwade, R. P., Patil, P. R., & Sharma, M. K. (2024, March). Machine Learning: The Driving Force Behind Intelligent Systems and Predictive Analytics. In 2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies (pp. 1-6). IEEE.
59. Khandelwal, A. R., Mutneja, L., Thakar, P., & Patil, P. (2019). Basics and Applications of Big Data.
60. Sonawane, D. C., Shirole, T. P., Patil, K. D., Patil, P. V., & Patil, A. K. (2017). Effective Pattern Discovery for Text Mining.
61. Gavhane, S., Patil, P., Patil, A., & Gadekar, S. (2015). Secure and Efficient Data Transmission Cluster Based Wireless Sensor Network. The International Journal of Science and Technoledge, 3(2), 47.
62. Koshariya, A. K., Kalaiyarasi, D., Jovith, A. A., Sivakami, T., Hasan, D. S., & Boopathi, S. (2023). Ai-enabled iot and wsn-integrated smart agriculture system. In Artificial Intelligence Tools and Technologies for Smart Farming and Agriculture Practices (pp. 200-218). IGI Global.
63. Lydia, E. L., Jovith, A. A., Devaraj, A. F. S., Seo, C., & Joshi, G. P. (2021). Green energy efficient routing with deep learning based anomaly detection for internet of things (IoT) communications. Mathematics, 9(5), 500.
64. Mamatha, B., Rashmi, D., Tiwari, K. S., Sikrant, P. A., Jovith, A. A., & Reddy, P. C. S. (2023, August). Lung Cancer Prediction from CT Images and using Deep Learning Techniques. In 2023 Second International Conference on Trends in Electrical, Electronics, and Computer Engineering (TEECCON) (pp. 263-267). IEEE.
65. Jovith, A. A., Mathapati, M., Sundarrajan, M., Gnanasankaran, N., Kadry, S., Meqdad, M. N., & Aslam, S. M. (2022). Two-Tier Clustering with Routing Protocol for IoT Assisted WSN. Computers, Materials & Continua, 71(2).
66. Sulthana, R., & Jovith, A. (2021). LSTM and RNN to Predict COVID Cases: Lethality’s and Tests in GCC Nations and India. International Journal of Performability Engineering, 17(3), 299.
67. Jovith, A. A., Raja, S. K., & Sulthana, A. R. (2020). Interference mitigation and optimal hop distance measurement in distributed homogenous nodes over wireless sensor network. Peer-to-Peer Networking and Applications, 13, 1109-1119.
68. Jovith, A. A., Sree, S. R., Rao, G. N., Kumar, K. V., Cho, W., Joshi, G. P., & Kim, S. W. (2023). DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems. Computers, Materials & Continua, 74(3).
69. Thenmozhi, R., Aslam, S. M., Jovith, A. A., & Avudaiappan, T. (2022). Modeling of Optimal Bidirectional LSTM Based Human Motion Recognition for Virtual Reality Environment. In Virtual and Augmented Reality for Automobile Industry: Innovation Vision and Applications (pp. 161-174). Cham: Springer International Publishing.
70. Mohsin, F. I. D. A., & Jovith, A. A. (2016). Anti-phishing strategy model for detection of phishing website in e-banking.
71. Gupta, H., & Jovith, A. A. Trusted Profile Identification and Validation Model. International Journal of Engineering Research and Development e-ISSN, 01-05.
72. Jovith, A. A., Ranganathan, C. S., Priya, S., Vijayakumar, R., Kohila, R., & Prakash, S. (2024, April). Industrial IoT Sensor Networks and Cloud Analytics for Monitoring Equipment Insights and Operational Data. In 2024 10th International Conference on Communication and Signal Processing (ICCSP) (pp. 1356-1361). IEEE.
73. Sahoo, S. S., Chatterjee, K., & Tripathi, P. M. (2019). A coordinated control strategy using supercapacitor energy storage and series dynamic resistor for enhancement of fault ride-through of doubly fed induction generator. International Journal of Green Energy, 16(8), 615-626.
74. Tripathi, P. M., Sahoo, S. S., & Chatterjee, K. (2019). Enhancement of low‐voltage ride through of wind energy conversion system using superconducting saturated core fault current limiter. International Transactions on Electrical Energy Systems, 29(4), e2798.
75. Tripathi, P. M., Sekhar Sahoo, S., & Chatterjee, K. (2019). Enhancing the fault ride through capability of DFIG‐based wind energy system using saturated core fault current limiter. The Journal of Engineering, 2019(18), 4916-4921.
76. Sahoo, S. S., Roy, A., & Chatterjee, K. (2016, December). Fault ride-through enhancement of wind energy conversion system adopting a mechanical controller. In 2016 National Power Systems Conference (NPSC) (pp. 1-5). IEEE.
77. Biswas, D., Sahoo, S. S., Tripathi, P. M., & Chatterjee, K. (2018, March). Maximum power point tracking for wind energy system by adaptive neural-network based fuzzy inference system. In 2018 4th International Conference on Recent Advances in Information Technology (RAIT) (pp. 1-6). IEEE.
78. Sahoo, S., Mishra, A., Chatterjee, K., & Sharma, C. K. (2017, March). Enhanced fault ride—Through ability of DFIG-based wind energy system using superconducting fault current limiter. In 2017 4th International Conference on Power, Control & Embedded Systems (ICPCES) (pp. 1-5). IEEE.
79. Roy, A., Sahoo, S. S., & Chatterjee, K. (2017, March). A reliability assessment model of a wind farm for generation adequacy studies of wind integrated power system. In 2017 Third International Conference on Science Technology Engineering & Management (ICONSTEM) (pp. 566-570). IEEE.
80. Sahoo, S. S., Tripathi, P. M., & Chatterjee, K. (2020). Low-cost non-superconducting DC-fault current limiter for the enhancement of low-voltage ride through capability of doubly fed induction generator. IETE Technical Review, 37(4), 418-437.
81. Kumar, A., Biswas, A., & Sahoo, S. S. (2015). Feasibility study of residential-scale stand-alone renewable energy systems (PV/BAT and PV/FC/BAT) in Silchar Assam. Int. J. Sci. Technol. Manage., 4(1), 50-57.
82. Sahoo, S. S., Tripathi, P. M., & Chatterjee, K. (2017, December). A Coordinated control strategy using Rotor current limiter and switchable type series passive resistive fault current limiter for enhanced fault ride-through. In 2017 7th International Conference on Power Systems (ICPS) (pp. 346-351). IEEE.
83. Mudaliyar, S. R., & Sahoo, S. S. (2015). Comparison of different eigenvalue based multi-objective functions for robust design of power system stabilizers. International Journal of Electrical and Electronic Engineering & Telecommunications, 1(2).
84. Khemraj, S., Thepa, P., Chi, A. P. D. H., Wu, W., & Samanta, S. (2022). Sustainable Wellbeing Quality of Buddhist Meditation Centre Management During Coronavirus Outbreak (COVID-19) in Thailand Using the Quality Function Deployment (QFD), and KANO Analysis. Journal of Positive School Psychology, 845-858.
85. Khemraj, S. (2023). Enhancing Competitive Advantage through Learning Capabilities and Innovative Human Resource Management. Intersecta Minds Journal, 2(1), 26-41.
86. Thepa, P. C. A., Khemraj, S., Khethong, P. K. S., Saengphrae, J., Chi, A. P. D. H., & Wu, W. Y. (2022). The Promoting Mental Health through Buddhadhamma for Members of the Elderly Club in Nakhon Pathom Province, Thailand. Turkish Journal of Physiotherapy and Rehabilitation, 32(3), 33334-33345.
87. Khemraj, S., Thepa, P. C. A., Patnaik, S., Chi, H., & Wu, W. Y. (2022). Mindfulness Meditation and Life Satisfaction Effective on Job Performance. NeuroQuantology, 20(1), 830-841.
88. Khemraj, S., Thepa, P. C. A., Chi, H., Wu, W. Y., Samanta, S., & Prakash, J. (2021). Prediction of world happiness scenario effective in the period of COVID-19 pandemic, by artificial neuron network (ANN), support vector machine (SVM), and regression tree (RT). NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal| NVEO, 13944-13959.
89. Khemraj, S., Pettongma, P. W. C., Thepa, P. C. A., Patnaik, S., Wu, W. Y., & Chi, H. (2023). Implementing Mindfulness In The Workplace: A New Strategy For Enhancing Both Individual And Organizational Effectiveness. Journal for ReAttach Therapy and Developmental Diversities, 6(2s), 408-416.
90. Khemraj, S., Pettongma, P. W. C., Thepa, P. C. A., Patnaik, S., Chi, H., & Wu, W. Y. (2023). An Effective Meditation Practice for Positive Changes in Human Resources. Journal for ReAttach Therapy and Developmental Diversities, 6(3s), 1077-1087.
91. Trung, N. T., Phattongma, P. W., Khemraj, S., Ming, S. C., Sutthirat, N., & Thepa, P. C. (2022). A Critical Metaphysics Approach in the Nausea Novel’s Jean Paul Sartre toward Spiritual of Vietnamese in the Vijñaptimātratā of Yogācāra Commentary and Existentialism Literature. Journal of Language and Linguistic Studies, 17(3).
92. Khemraj, S., Thepa, P. C. A., & Chi, H. (2021). Phenomenology In Education Research: Leadership Ideological. Webology (ISSN: 1735-188X), 18(5).
93. Bhujell, K., Khemraj, S., Chi, H. K., Lin, W. T., Wu, W., & Thepa, P. C. A. (2021). Trust in the Sharing Economy: An Improvement in Terms of Customer Intention. Indian Journal of Economics and Business, 20(1), 713-730.
94. Patnaik, S., Selvanayagam, N., Khemraj, S., Sadiq, F. U., Wu, W. Y., & Chi, H. (2023). Anxiety And Performance: An Insight From Cognitive Behavioral Angle. Journal for ReAttach Therapy and Developmental Diversities, 6(3s), 785-795.
95. Boopathy, D., & Balaji, P. (2023). EFFECT OF DIFFERENT PLYOMETRIC TRAINING VOLUME ON SELECTED MOTOR FITNESS COMPONENTS AND PERFORMANCE ENHANCEMENT OF SOCCER PLAYERS. Ovidius University Annals, Series Physical Education and Sport/Science, Movement and Health, 23(2), 146-154.
96. Mahesh, K., & Balaji, D. P. (2022). A Study on Impact of Tamil Nadu Premier League Before and After in Tamil Nadu. International Journal of Physical Education Sports Management and Yogic Sciences, 12(1), 20-27.
97. Devi, L. S., & Prasanna, B. D. (2017). EFFECT OF BKS IYENGAR YOGA ON SELECTED PHYSIOLOGICAL AND PSYCHOLOGICAL VARIABLES AMONG COLLEGE GIRLS. Methodology.
98. Boopathy, D., & Balaji, D. P. Training outcomes of yogic practices and aerobic dance on selected health related physical fitness variables among tamilnadu male artistic gymnasts. Sports and Fitness, 28.
99. Boopathy, D., & Prasanna, B. D. IMPACT OF PLYOMETRIC TRAINING ON SELECTED MOTOR FITNESS VARIABLE AMONG MEN ARTISTIC GYMNASTS.
100. Prabhu Kavin, B., Karki, S., Hemalatha, S., Singh, D., Vijayalakshmi, R., Thangamani, M., … & Adigo, A. G. (2022). Machine Learning‐Based Secure Data Acquisition for Fake Accounts Detection in Future Mobile Communication Networks. Wireless Communications and Mobile Computing, 2022(1), 6356152.
101. Kalaiselvi, B., & Thangamani, M. (2020). An efficient Pearson correlation based improved random forest classification for protein structure prediction techniques. Measurement, 162, 107885.
102. Thangamani, M., & Thangaraj, P. (2010). Integrated Clustering and Feature Selection Scheme for Text Documents. Journal of Computer Science, 6(5), 536.
103. Geeitha, S., & Thangamani, M. (2018). Incorporating EBO-HSIC with SVM for gene selection associated with cervical cancer classification. Journal of medical systems, 42(11), 225.
104. Narmatha, C., Thangamani, M., & Ibrahim, S. J. A. (2020). Research scenario of medical data mining using fuzzy and graph theory. International Journal of Advanced Trends in Computer Science and Engineering, 9(1), 349-355.
105. Gangadhar, C., Chanthirasekaran, K., Chandra, K. R., Sharma, A., Thangamani, M., & Kumar, P. S. (2022). An energy efficient NOMA-based spectrum sharing techniques for cell-free massive MIMO. International Journal of Engineering Systems Modelling and Simulation, 13(4), 284-288.
106. Thangamani, M., & Ibrahim, S. J. A. (2018, November). Ensemble Based Fuzzy with Particle Swarm Optimization Based Weighted Clustering (Efpso-Wc) and Gene Ontology for Microarray Gene Expression. In Proceedings of the 2018 International Conference on Digital Medicine and Image Processing (pp. 48-55).
107. Thangamani, M., & Thangaraj, P. (2013). Fuzzy ontology for distributed document clustering based on genetic algorithm. Applied Mathematics & Information Sciences, 7(4), 1563-1574.
108. Surendiran, R., Aarthi, R., Thangamani, M., Sugavanam, S., & Sarumathy, R. (2022). A Systematic Review Using Machine Learning Algorithms for Predicting Preterm Birth. International Journal of Engineering Trends and Technology, 70(5), 46-59.
109. Thangamani, M., & Thangaraj, P. (2010). Ontology based fuzzy document clustering scheme. Modern Applied Science, 4(7), 148.
110. Ibrahim, S. J. A., & Thangamani, M. (2018, November). Momentous Innovations in the prospective method of Drug development. In Proceedings of the 2018 International Conference on Digital Medicine and Image Processing (pp. 37-41).
111. Rajasekaran, M., & Thanabal, M. S. (2019). A Survey on Sensitive Association Rule Hiding for Privacy Evaluation of Methods and Metrics. INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume, 8.
112. Rajasekaran, M., Thanabal, M. S., & Meenakshi, A. (2024). Association rule hiding using enhanced elephant herding optimization algorithm. Automatika, 65(1), 98-107.
113. Rajasekaran, M., & Thanabal, M. S. (2021). Performance Analysis of Various Parameters in Sensitive Association Rule Hiding For Privacy in Distributed Collaborative Data Mining. Turkish Online Journal of Qualitative Inquiry, 12(10).
114. Rajasekaran, M., & Thanabal, M. S. (2017). Association rule mining and Blind Turing machine based privacy-preserving outsourced in vertically partitioned databases. Advances in Natural and Applied Sciences, 11(7), 409-416.
115. Mukiri, R. R., & Prasad, D. B. (2019, September). Developing Secure Storage of cloud with IoT Gateway. In Proceedings of International Conference on Advancements in Computing & Management (ICACM).
116. Venkatesh, C., Prasad, B. V. V. S., Khan, M., Babu, J. C., & Dasu, M. V. (2024). An automatic diagnostic model for the detection and classification of cardiovascular diseases based on swarm intelligence technique. Heliyon, 10(3).
117. Baskar, M., Rajagopal, R. D., BVVS, P., Babu, J. C., Bartáková, G. P., & Arulananth, T. S. (2023). Multi-region minutiae depth value-based efficient forged finger print analysis. Plos one, 18(11), e0293249.
118. Alapati, N., Prasad, B. V. V. S., Sharma, A., Kumari, G. R. P., Veeneetha, S. V., Srivalli, N., … & Sahitya, D. (2022, November). Prediction of Flight-fare using machine learning. In 2022 International Conference on Fourth Industrial Revolution Based Technology and Practices (ICFIRTP) (pp. 134-138). IEEE.
119. Ramesh, M., Mandapati, S., Prasad, B. S., & Kumar, B. S. (2021, December). Machine learning based cardiac magnetic resonance imaging (cmri) for cardiac disease detection. In 2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) (pp. 1-5). IEEE.
120. Kumar, B. S., Prasad, B. S., & Vyas, S. (2020). Combining the OGA with IDS to improve the detection rate. Materials Today: Proceedings.
121. Siva Prasad, B. V. V., Mandapati, S., Kumar Ramasamy, L., Boddu, R., Reddy, P., & Suresh Kumar, B. (2023). Ensemble-based cryptography for soldiers’ health monitoring using mobile ad hoc networks. Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije, 64(3), 658-671.
122. Alapati, N., Prasad, B. V. V. S., Sharma, A., Kumari, G. R. P., Bhargavi, P. J., Alekhya, A., … & Nandini, K. (2022, November). Cardiovascular Disease Prediction using machine learning. In 2022 International Conference on Fourth Industrial Revolution Based Technology and Practices (ICFIRTP) (pp. 60-66). IEEE.
123. Imoize, A. L., Islam, S. M., Poongodi, T., Kumar, R. L., & Prasad, B. S. (Eds.). (2023). Unmanned Aerial Vehicle Cellular Communications. Springer International Publishing.