Dr. R.BABY MUNIRATHINAM

@mallareddyecw.com

ASSOCIATE PROFESSOR, COMPUTER SCIENCE AND ENGINEERING
MALLA REDDY ENGINEERING COLLEGE FOR WOMEN

Dr. R.BABY MUNIRATHINAM


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https://researchid.co/babyrathinam
I AM MUNIRATHINAM. I HAVE COMPLETED M.C.A, M..
I HAVE COMPLETED MCA, AND M.PHIL IN MADURAI KAMARAJ UNIVERSITY AND COMPLETED PH.D IN ANNA UNIVERSITY, CHENNAI.
I AM HAVING EXPERIEENCE OF 18.5 YEARS AS AND ASSOCIATE PROFESSOR
I AM HAVING INDUSTRY EXPERIENCE OF 5 YEARS AS COMPUTER FACULTY .

EDUCATION

M.C.A., M..

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science Applications, Computer Science, Computer Science, Computer Networks and Communications
17

Scopus Publications

2

Scholar Citations

1

Scholar h-index

Scopus Publications

  • A Multimodal Deep Learning Approach to Decoding Student Participation in Online Classrooms
    T. Mutharasi, S. Vijayalakshmi
    Proceedings 2024 Oits International Conference on Information Technology Ocit 2024, 2024
    The COVID-19 has accelerated the e-learning usage, stressing a proper research of how students engage themselves in online classes. Previous works are mainly concerned with uni-modal treatment where data from only one modality such as facial expressions or eye-gaze is analyzed which provides a very narrow perspective of engagement. Towards this, we introduce a novel multimodal deep learning framework fusing facial expression and eye gaze, textual chat and interaction transcripts, along with contextual data on learning. This framework uses deep learning models for analysing multimodal data in real time so that timely interventions and feedbacks can be given to each learner. It also improves interpretability by including attention mechanisms, which show the level of importance of the different modalities and features in producing engagement estimates. We also show through real-world experiments on a carefully selected benchmark set the effectiveness of the presented framework with respect to unimodal as well as the state of the art multimodal techniques. And not only that, it is capable of identifying engagement and also giving instructional suggestions to help educators modify their course and make learning more engaging. This research opens the way to the creation of adaptive e-learning systems that could enhance student-centered online learning environment.
  • Predicting the academic progression in student’s standpoint using machine learning
    M. S. Sassirekha, S. Vijayalakshmi
    Automatika, 2022
    Graduate students are unaware of their final qualification for a course. Even though there were many models available, few works with feature selection and prediction with no control over the number of features to be used. As a result of the lack of an improved performance forecasting system, students are only qualified on the second or third attempt. A warning system in place could help the students reduce their arrear count. All students undertaking higher education should obtain the qualification at their desired level of education without delay to transit to their careers on time. Therefore, there should be a predictive system for students to warn during the course work period and guide them to qualify in a first attempt itself. Although so many factors were present that affected the qualifying score, here proposed a feature selection technique that selects a minimal number of well-playing features. Also proposed a model Supervised Learning Approach to unfold Student’s Academic Future Progression through Supervised Learning Approach for Student’s Academic Future Progression (SLASAFP) algorithm that recommends the best fitting machine learning algorithm based on the features dynamically. It has proven with comparable predictive accuracy.
  • Kernel Fuzzy Clustering with Output Layer Self-Connection Recurrent Neural Networks for Software Cost Estimation
    V. Resmi, S. Vijayalakshmi
    Journal of Circuits Systems and Computers, 2020
    In the current world, the software cost estimation problem has been resolved using various newly developed methods. Significantly, the software cost estimation problems can be dealt with effectively with the recently grown recurrent neural network (RNN) than the other newly developed methods. In this paper, an improved approach is proposed to software cost estimation using Output layer self-connection recurrent neural networks (OLSRNN) with kernel fuzzy c-means clustering (KFCM). The proposed OLSRNN method follows the basics of traditional RNN models for integrating self-connections to the output layer; thereby, the output temporal dependencies are better captured. Also, the performance of neural networks is improved using the kernel fuzzy clustering algorithm to enhance software estimation results. Ultimately, five publicly available software cost estimation datasets are adapted to verify the efficacy of the proposed KFCM-OLSRNN method using the validation metrics such as MdMRE, PRED (0.25) and MMRE. The experimental results proved the efficiency of the proposed method for solving the software cost estimation problem.
  • New Method of Internal Type-2 Fuzzy-Based CNN for Image Classification
    P. Murugeswari, S. Vijayalakshmi
    International Journal of Fuzzy Logic and Intelligent Systems, 2020
    In the last two decades, neural networks and fuzzy logic have been successfully implemented in intelligent systems. The fuzzy neural network (FNN) system framework infers the union of fuzzy logic and neural network system framework thoughts, which consolidates their advantages. The FNN system is applied in several scientific and engineering areas. Wherever there is uncertainty associated with the data, fuzzy logic places a vital rule. The fuzzy set can effectively represent and handle uncertain information. The main objective of the FNN system is to achieve a high level of accuracy by including the fuzzy logic in either the neural network structures, activation functions, or learning algorithms. In computer vision and intelligent systems, convolutional neural networks (CNNs) have more popular architectures, and their performance is excellent in many applications. In this paper, fuzzy-based CNN image classification methods are analyzed, and an interval type-2 fuzzy-based CNN is proposed. The experimental results indicated that the performance of the proposed method was good.
  • Analogy-based approaches to improve software project effort estimation accuracy
    V Resmi, S Vijayalakshmi
    Journal of Intelligent Systems, 2020
    In the discipline of software development, effort estimation renders a pivotal role. For the successful development of the project, an unambiguous estimation is necessitated. But there is the inadequacy of standard methods for estimating an effort which is applicable to all projects. Hence, to procure the best way of estimating the effort becomes an indispensable need of the project manager. Mathematical models are only mediocre in performing accurate estimation. On that account, we opt for analogy-based effort estimation by means of some soft computing techniques which rely on historical effort estimation data of the successfully completed projects to estimate the effort. So in a thorough study to improve the accuracy, models are generated for the clusters of the datasets with the confidence that data within the cluster have similar properties. This paper aims mainly on the analysis of some of the techniques to improve the effort prediction accuracy. Here the research starts with analyzing the correlation coefficient of the selected datasets. Then the process moves through the analysis of classification accuracy, clustering accuracy, mean magnitude of relative error and prediction accuracy based on some machine learning methods. Finally, a bio-inspired firefly algorithm with fuzzy analogy is applied on the datasets to produce good estimation accuracy.
  • An effective software project effort estimation system using optimal firefly algorithm
    V. Resmi, S. Vijayalakshmi, R. Subash Chandrabose
    Cluster Computing, 2019
  • Real Time Big Data Analytics to Derive Actionable Intelligence in Enterprise Applications
    Subramanian Sabitha Malli, Soundararajan Vijayalakshmi, Venkataraman Balaji
    Studies in Big Data, 2018
  • CCCa framework - Classification system in big data environment with clustering and cache concepts
    Sabitha Malli Subramanian, S. Vijayalakshmi, Balaji Venkataraman, P. Venkumar, R. M. Rathikaa Sre
    Advances in Intelligent Systems and Computing, 2018
  • Smart manufacturing through sensor based efficiency monitoring system (SBEMS)
    V. Balaji, P. Venkumar, M. S. Sabitha, S. Vijayalakshmi, R. M. Rathikaa Sre
    Advances in Intelligent Systems and Computing, 2018
  • Optical image encryption based on chunk transformation and a well-known ciphering
    International Journal of Applied Engineering Research, 2015
  • Improving search performance for tourism domain using semantic web and Bayesian network
    Information Japan, 2014
  • Semantic web based efficient search using ontology and mathematical model
    International Journal of Engineering and Technology, 2013
  • An unfangled approach to semantic search for E-tourism domain
    K. Palaniammal, M. Indra Devi, S. Vijayalakshmi
    International Conference on Recent Trends in Information Technology Icrtit 2012, 2012
  • Extracting sequential access pattern from pre-processed web logs
    S. Vijayalakshmi, V. Mohan, M. S. Sassirekha, O. R. Deepika
    Proceedings of 2011 International Conference on Process Automation Control and Computing Pacc 2011, 2011
  • Mining sequential access pattern with low support from large pre-processed web logs
    Vijayalakshmi
    Journal of Computer Science, 2010
  • Mining constraint-based multidimensional frequent sequential pattern in web logs
    European Journal of Scientific Research, 2009
  • Multidimensional frequent pattern mining using association rule based constraints
    S. Vijayalakshmi, S. Suresh Raja
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005

RECENT SCHOLAR PUBLICATIONS

  • A Time-Series and Machine Learning Frame work for Forecasting GDP and Unemployment using Global Economic Indicaors (2020-2024)
    DNADSB Dr.Vidya Rajasekaran, Vvyasal,Krithika Rajendran, Dr.R.Baby Munirathinam
    IEEE PUBLICATIONS 1 (978-1-6654-776-1/26/$31.00@2026, IEEE), 1 to 6 , 2026
    2026
  • Machine Learning Models Brain Tumour Predication Medical Imaging – Intellectual Fusion”
    DRRB MUNIRATHINAM
    The Institute of Advanced Engineering and Science (IAES) -Q4 Scopus Index … , 2025
    2025
  • Machine Learning Models Brain Tumour Predication Medical Imaging – Intellectual Fusion”
    DRRB MUNIRATHINAM
    Q4 Scopus Index of the publications , 2025
    2025
  • AI AND ML BASED SMART DRONE FOR EMERGENCY MEDICAL DELIVERY
    DRRB MUNIRATHINAM
    GENERAL OF PATENTS, DESIGNS AND TRADE MARK - INTERNATIONAL DESIGN … , 2025
    2025
  • ROBOTICS AND IOT - BOOK - SCIENTIFIC INTERNATIONAL PUBLISHING HOUSE- ROBOTICS AND IOT Perfect Paperback
    DRRB MUNIRATHINAM
    ISBN NO.978-93-6674-136-9 - LINK - https://www.amazon.in/dp … , 2025
    2025
  • ARTIFICIAL INTELLIGENCE CRIME' AN OVERVIEW OF MALICIOUS USE AND ABUSE OF AI
    1DR.R.BABY MUNIRATHINAM ,2A.TEJASWINI,3M.SAMREEN,4T.PRAVANYA 1Associate ...
    International Journal of Engineering, Science and Advanced Technology 24 … , 2024
    2024
  • RIS enabled NOMA for Resource Allocation in Beyond 5G Networks
    SCMFN Kirubakaran Namaskaram1 , Parijatham Rajagopal2 , Baby Munirathinam ...
    Journal of Engineering Science and Technology Review 17 (1), 8 - 15 , 2024
    2024
    Citations: 2
  • IMPROVING SPACECRAFT DECISION MAKING USING DEEPLEARNING WITH RULE MASTER-GENERATED RULES
    DNJ Dr. Baby Munirathinam1 , B. Lahari2 , Ch. Hemasai2
    International Journal of Research Volume 13 (Issue I,), Page No: 63- 73 , 2024
    2024
  • Securing data through DNA cryptography in cloud computing
    DK Dr.Baby Munirathinam1 , Tejaswini Dharni2 ,Sai Pranaya Gajula3
    INTERNATIONAL JOURNAL OF PURE AND APPLIED SCIENCE AND TECHNOLOGY - ISSN … , 2024
    2024
  • Deep And Parallel Network In Network Models For Accurate Encrypted Network Traffic Classification
    DNJ Dr. R.Baby Munirathinam1 , B. Lahari2 , Ch.Hemasai2
    International Journal of Research , ISSN NO:2236-6124 13 (Issue I,), Page … , 2024
    2024
  • An Improving Quality of Service in Wireless Networks using Consensus Algorithm
    DRB Munirathinam
    International Journal for Advanced Research in Science and Technology … , 2023
    2023
  • A NOVEL AI-POWERED SYSTEM QUANTIFIES SUICIDE INDICATORS AND IDENTIFIES SUICIDE-RELATED CONTENT IN ONLINE POSTS
    MRECDC Dr.R.Baby Munirathinam ,1Guide:Dr.BABY MUNIRATHINAM 2G.Sai Pranaya1 ...
    Turkish Journal of Computer and Mathematics Education 14 (No.03 (2023 … , 2023
    2023
  • Designing Secure And Efficient Biometric-Based Secure Access Mechanism For Cloud Services
    DRBMMREC women
    International Journal for Advanced Research in Science and Technology … , 2023
    2023
  • Resisting the Pandemic and Saving Economy by using Wireless Communication Technology
    DRBMMRECFOR WOMEN
    National conference on COVIDONOMICS which is conducted by St.Josephs … , 2022
    2022
  • BIG DATA ANALYTICS ON THE IMPACT OF COVID -19 FACTORS
    DRB MUNIRATHINAM
    NATIONAL E-CONFERENCE ON CHALLENGES AND CHANCES FOR INDIAN BUSINESS IN POST … , 2021
    2021
  • Scheduling Algorithms with Quality of Service in Wireless Networks
    RBMDRS VIJAYALAKSHMI
    (ICRDSEIT – 2020) - IST INTERNATIONAL CONFERENCE ON " Recent Developments … , 2020
    2020
  • PACKET-HIDING METHODS FOR PREVENTING SELECTIVE JAMMING ATTACKS
    R.BABY MUNIRATHINAM & DR.S.VIJAYALAKSHMI
    JOURNAL OF WEB ENGINEERING 17 (6), 2806-2821 , 2018
    2018
  • IMPROVING QUALITY OF SERVICES FOR MANETS USING AEAACK
    BMANDDRSVI LAKSHMI
    TAGA JOURNAL OF ENGINEERING, 5 , 2018
    2018
  • IMPROVING ENERGY EFFICIENT USING NOVEL SLEEP SCHEDULING APPROACH FOR WIRELESS AD-HOC NETWORKS
    RB MUNIRATHINAM, S VIJAYALAKSHMI
    IEEE DIGITAL LIBRARY I , 2016
    2016
  • Watch Dog Timer Node (WDTN) based Sensor Node - Master Operations in Wireless Sensor Networks (WSN)
    RB Munirathinam, S Vijayalakshmi
    Asian Journal of Research in Social Sciences and Humanities 6 (9), 2176-2190 , 2016
    2016

MOST CITED SCHOLAR PUBLICATIONS

  • RIS enabled NOMA for Resource Allocation in Beyond 5G Networks
    SCMFN Kirubakaran Namaskaram1 , Parijatham Rajagopal2 , Baby Munirathinam ...
    Journal of Engineering Science and Technology Review 17 (1), 8 - 15 , 2024
    2024
    Citations: 2
  • A Time-Series and Machine Learning Frame work for Forecasting GDP and Unemployment using Global Economic Indicaors (2020-2024)
    DNADSB Dr.Vidya Rajasekaran, Vvyasal,Krithika Rajendran, Dr.R.Baby Munirathinam
    IEEE PUBLICATIONS 1 (978-1-6654-776-1/26/$31.00@2026, IEEE), 1 to 6 , 2026
    2026
  • Machine Learning Models Brain Tumour Predication Medical Imaging – Intellectual Fusion”
    DRRB MUNIRATHINAM
    The Institute of Advanced Engineering and Science (IAES) -Q4 Scopus Index … , 2025
    2025
  • Machine Learning Models Brain Tumour Predication Medical Imaging – Intellectual Fusion”
    DRRB MUNIRATHINAM
    Q4 Scopus Index of the publications , 2025
    2025
  • AI AND ML BASED SMART DRONE FOR EMERGENCY MEDICAL DELIVERY
    DRRB MUNIRATHINAM
    GENERAL OF PATENTS, DESIGNS AND TRADE MARK - INTERNATIONAL DESIGN … , 2025
    2025
  • ROBOTICS AND IOT - BOOK - SCIENTIFIC INTERNATIONAL PUBLISHING HOUSE- ROBOTICS AND IOT Perfect Paperback
    DRRB MUNIRATHINAM
    ISBN NO.978-93-6674-136-9 - LINK - https://www.amazon.in/dp … , 2025
    2025
  • ARTIFICIAL INTELLIGENCE CRIME' AN OVERVIEW OF MALICIOUS USE AND ABUSE OF AI
    1DR.R.BABY MUNIRATHINAM ,2A.TEJASWINI,3M.SAMREEN,4T.PRAVANYA 1Associate ...
    International Journal of Engineering, Science and Advanced Technology 24 … , 2024
    2024
  • IMPROVING SPACECRAFT DECISION MAKING USING DEEPLEARNING WITH RULE MASTER-GENERATED RULES
    DNJ Dr. Baby Munirathinam1 , B. Lahari2 , Ch. Hemasai2
    International Journal of Research Volume 13 (Issue I,), Page No: 63- 73 , 2024
    2024
  • Securing data through DNA cryptography in cloud computing
    DK Dr.Baby Munirathinam1 , Tejaswini Dharni2 ,Sai Pranaya Gajula3
    INTERNATIONAL JOURNAL OF PURE AND APPLIED SCIENCE AND TECHNOLOGY - ISSN … , 2024
    2024
  • Deep And Parallel Network In Network Models For Accurate Encrypted Network Traffic Classification
    DNJ Dr. R.Baby Munirathinam1 , B. Lahari2 , Ch.Hemasai2
    International Journal of Research , ISSN NO:2236-6124 13 (Issue I,), Page … , 2024
    2024
  • An Improving Quality of Service in Wireless Networks using Consensus Algorithm
    DRB Munirathinam
    International Journal for Advanced Research in Science and Technology … , 2023
    2023
  • A NOVEL AI-POWERED SYSTEM QUANTIFIES SUICIDE INDICATORS AND IDENTIFIES SUICIDE-RELATED CONTENT IN ONLINE POSTS
    MRECDC Dr.R.Baby Munirathinam ,1Guide:Dr.BABY MUNIRATHINAM 2G.Sai Pranaya1 ...
    Turkish Journal of Computer and Mathematics Education 14 (No.03 (2023 … , 2023
    2023
  • Designing Secure And Efficient Biometric-Based Secure Access Mechanism For Cloud Services
    DRBMMREC women
    International Journal for Advanced Research in Science and Technology … , 2023
    2023
  • Resisting the Pandemic and Saving Economy by using Wireless Communication Technology
    DRBMMRECFOR WOMEN
    National conference on COVIDONOMICS which is conducted by St.Josephs … , 2022
    2022
  • BIG DATA ANALYTICS ON THE IMPACT OF COVID -19 FACTORS
    DRB MUNIRATHINAM
    NATIONAL E-CONFERENCE ON CHALLENGES AND CHANCES FOR INDIAN BUSINESS IN POST … , 2021
    2021
  • Scheduling Algorithms with Quality of Service in Wireless Networks
    RBMDRS VIJAYALAKSHMI
    (ICRDSEIT – 2020) - IST INTERNATIONAL CONFERENCE ON " Recent Developments … , 2020
    2020
  • PACKET-HIDING METHODS FOR PREVENTING SELECTIVE JAMMING ATTACKS
    R.BABY MUNIRATHINAM & DR.S.VIJAYALAKSHMI
    JOURNAL OF WEB ENGINEERING 17 (6), 2806-2821 , 2018
    2018
  • IMPROVING QUALITY OF SERVICES FOR MANETS USING AEAACK
    BMANDDRSVI LAKSHMI
    TAGA JOURNAL OF ENGINEERING, 5 , 2018
    2018
  • IMPROVING ENERGY EFFICIENT USING NOVEL SLEEP SCHEDULING APPROACH FOR WIRELESS AD-HOC NETWORKS
    RB MUNIRATHINAM, S VIJAYALAKSHMI
    IEEE DIGITAL LIBRARY I , 2016
    2016
  • Watch Dog Timer Node (WDTN) based Sensor Node - Master Operations in Wireless Sensor Networks (WSN)
    RB Munirathinam, S Vijayalakshmi
    Asian Journal of Research in Social Sciences and Humanities 6 (9), 2176-2190 , 2016
    2016

Publications

1. R. Baby Munirathinam & Dr. S.Vijayalakshmi, 2018, “Packet Hiding Methods for Preventing Selective Jamming Attacks” which is published in the Journal of Web Engineering, , No.6 (2018) pages 2806-2821. ISSN No. 1540-9589. ©Journal of Web Engineering, publisher (Rinton Press –Publisher in Science and Technology) Indexed in 2018 (Anna University – Anna University List of Journals)
2. R. Baby Munirathinam & Dr. S. Vijayalakshmi, 2018, “Enhancing The Quality of Services For Manets By Using Aeaack” is published in Taga Journal of Graphic Technology ISSN: 1748-0345 (Online) in Volume 14, pages 523-536 (2018) © Taga Journal of Graphic Technology – Publisher (Swansea Printing Technology Limited ) (Anna University – Updated list of Journals in Anna University). 192
3. R. Baby Munirathinam & Dr. S. Vijayalakshmi, 2016, “Watch Dog timer (WDTN) based Sensor node- Master Operations in wireless Sensor Networks (WSN)” published in Asian Journal of Research in Social Sciences and Humanities, Vol 6, No.9 Sept 2016, pages 2176- 2190 having ISSN 2249-7315. Publisher – Asian Research Consortium (Anna University - Updated Journal of Annexure I).
4. R. Baby Munirathinam & Dr. S. Vijayalakshmi, 2016, Scheduling in Autonomous Mobile Mesh Networks” having published in Advances in Natural and Applied Sciences, AmericanEurasian Network for Scientific Information - (AENSI-Publications), EISSN: 1998-1090, http:// / ANAS 2016 Special 10(10)

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

5. R. Baby Munirathinam & Dr. S. Vijayalakshmi, 2016, “Improving Energy Efficient using Novel Sleep Scheduling Approach for Wireless Adhoc-networks” published in IEEE Digital Library having ISBN. Information: DOI” 10/1109/ICCSP. 2016. Pages (2059-2065) Publisher: IEEE Digital Library.

INDUSTRY EXPERIENCE

I HAVE WROKED AS COMPUTER FACULTY IN VARIOUS COMPUTER CENTERS(1.1.2001 TO 25.8.2006)