Dr. R.MENAHA received B.E Computer Science engineering degree from Bharadhidhasan University, Trichy, India, in 2003. She completed M.E computer science engineering degree from Anna University, Chennai, India in 2012 and awarded Doctoral degree from Anna University, Chennai, India, in 2021. She currently works as Assistant Professor (SS) in College of engineering and technology, Pollachi, India. Her current research works includes machine learning, sentimental analysis, question answering system, heuristics approach, semantic similarity, word sense disambiguation, web mining.
EDUCATION
B.E, M.E, PhD
RESEARCH INTERESTS
Web Mining, Data Mining, Text Analysis, Machine Learning, Sentiment Analysis, Question Answering Systems
FUTURE PROJECTS
Question Answering Systems
Applications Invited
Sentiment Analysis
Applications Invited
Word Sense Disambiguation
Applications Invited
24
Scopus Publications
178
Scholar Citations
8
Scholar h-index
6
Scholar i10-index
Scopus Publications
Smart Gene Editing: AI and DS to Improve CRISPR-Cas9 Outcomes in Disease Therapy V. Balajishanmugam, N. Seethalakshmi, P. G. Palanimani, R. Menaha Advanced AI and Data Science Applications, 2025 CRISPR-Cas9 has transformed the science of gene editing by providing unparalleled accuracy in targeting and changing particular genomic regions. However, its full potential in disease therapy is hampered by issues such as off-target effects, efficiency fluctuation, and the intricacy of genetic connections. Integrating AI and data science (DS) into CRISPR-Cas9 processes offers a fresh method to solving these challenges. Learning from massive biological datasets enables AI to forecast off-target mutations, optimize target selection, and refine gene-editing techniques. Furthermore, data-driven models can help find genetic markers for illnesses and improve therapy methods by predicting patient-specific outcomes. This research investigates the potential of AI and DS to improve CRISPR-Cas9’s accuracy, efficiency, and safety, making it a more feasible alternative for complicated disease treatments. We aspire to produce more precise, efficient, and tailored gene-editing medicines using machine learning algorithms and other computational approaches, opening the door for precision medicine.
Decentralized Digital Media Generation: A Blockchain-Based Multimodal Generative AI Framework C. Nithiya, G. Revathy, R. Menaha, S. Prabhu Fusion of Multimodal Generative AI and Blockchain Technology in Digital Media, 2025 The combination of blockchain technology and multimodal generative AI is changing the face of digital media production. This chapter presents a revolutionary decentralized framework for digital media production that combines the security, transparency, and immutability of blockchain with the creative powers of multimodal generative AI. The suggested framework tackles critical issues with content authenticity, copyright protection, and data privacy, allowing creators to retain ownership and control over their digital assets. Blockchain smart contracts provide transparent licensing, royalty distribution, and media asset tracing. Meanwhile, multimodal generative AI allows for the creation of high-quality media material in a variety of formats, including text, photos, video, and audio.
A Study on XAI-Based Drug Identification System Menaha Ramakrishnan, Balahariraj Nagamanickam, Dharshini Ravikumar, Subiksha Muruganandam, Vijay Selvakumar Aip Conference Proceedings, 2025
AI-Driven Real-Time Feedback System for Enhanced Student Support: Leveraging Sentiment Analysis and Machine Learning Algorithms J. Prakash, R. Swathiramya, G. Balambigai, R. Menaha, J.S. Abhirami International Journal of Computational and Experimental Science and Engineering, 2024 The rapid evolution of educational technologies has led to a shift toward personalized and adaptive learning experiences. A critical component of such systems is the ability to provide timely and relevant feedback to students. This paper presents an AI-driven real-time feedback system designed to enhance student support through the integration of sentiment analysis and machine learning algorithms. The system leverages sentiment analysis to gauge the emotional tone of student interactions, such as forum posts, assignment submissions, and feedback. Machine learning algorithms, including decision trees, support vector machines (SVM), and deep learning models, are used to analyze and predict student engagement, performance, and emotional states. By combining both cognitive and emotional insights, the system delivers personalized, context-sensitive feedback that helps students overcome learning challenges and improve academic outcomes. The effectiveness of the system is evaluated using multiple datasets, showing significant improvements in student engagement, satisfaction, and performance.
Finding Experts in Community Question Answering System Using Trie String Matching Algorithm with Domain Knowledge R. Menaha, V. E. Jayanthi IETE Journal of Research, 2024 In recent days, different community question-answering systems have been evolving as online forums for knowledge sharing among users across the world. However, finding experts on the questions is a key issue in the community question-answering system. To address this issue, a novel approach is proposed in this paper for finding experts from the community question-answering website using an exact string-matching algorithm along with domain knowledge. The proposed system is designed with three phases: i) User Profile Modeling, ii) Question Preprocessing, and iii) Expert Recommendation. Initially, the matrix factorization model is adopted for user profile modeling where the tags and the answerer’s information are represented in the form of a matrix. Then, the domain-wise grouping of tags is done to minimize the search time of the tags. The question preprocessing is done using a keyword extraction algorithm to extract the keywords. Finally, the expert recommendation is accomplished using the trie string matching algorithm and key-value mapping process. For doing experiments, a stack overflow community question-answering website is utilized in this work. The performance of the system is measured and the results section proved that the system achieved 91.2% accuracy.
Enhanced Visual Cryptographic Schemes with Essential Access Structures and Pixel-Wise Operations Dr.M Dr.M.Revathi, , , , , , Devi D, Dr.R Dr.R.Menaha, R .., Mr S Mohan Journal of Cybersecurity and Information Management, 2024 By splitting a picture into many parts, which, when reassembled, disclose the original image without requiring complicated math, visual cryptography is a strong method for protecting visual information. Problems with pixel enlargement, decreased picture quality, and restricted access structures are common with traditional visual cryptography techniques. Our proposed improved visual cryptography approach incorporates pixel-wise operations and critical access structures to solve these challenges and increase flexibility, picture quality, and security. To reconstruct a picture, our technique calls for building visual cryptographic shares based on critical access structures that specify the exact combinations of shares needed. In order to maintain the image's resolution and reduce pixel expansion, we use pixel-wise processes. By improving the peak signal-to-noise ratio (PSNR) by up to 20% compared to conventional approaches, experimental data show that our strategy greatly improves picture quality. In addition, the suggested approach guarantees that individual shares do not disclose any information on the original picture, thereby maintaining high security requirements. Finally, it is clear that the enhanced visual cryptographic system is well-suited for a wide range of uses in safe communications and data security due to its strong solution for secure picture sharing, increased picture quality, and adjustable access control.
IOT Based Heart Rate Monitoring System Design for Heart Attack Detection P Sutha, A Periyanan, R Menaha, Ve Jayanthi, B Girish 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024 In recent days, the human demise has increased due to heart attack. An IOT based sensor system is proposed to detect the heart rate of a person to increase their lifespan. To measure the heart rate, the heart beat sensor is interfaced with a microcontroller. The threshold levels of heart beat is set by the user with the help of a proposed mobile application. Based on the patient age, heart beat limit is set and then the system starts monitoring. When the heart beat goes beyond the range an alert message is sent to the care taker or Physician. Thus an alert of abnormal condition of the patient is sent immediately to the Physician. So, the immediate care is taken and the person life is saved. The developed system is tested and works well for all the age groups.
Performance Optimization in Software-Defined Networks Based on IoT Networks K. Renu, R. Menaha, Ganagavalli K, N. Yamuna, Antony Vijay J, Glory E Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
Question answering system using web snippets R Menaha, A Udhaya Surya, K Nandhni, M Ishwarya Proceedings of the International Conference on Iot in Social Mobile Analytics and Cloud I Smac 2017, 2017
RECENT SCHOLAR PUBLICATIONS
Decentralized Digital Media Generation: A Blockchain-Based Multimodal Generative AI Framework C Nithiya, G Revathy, R Menaha, S Prabhu Fusion of Multimodal Generative AI and Blockchain Technology in Digital … , 2026 2026
An AI-Enabled Exam Proctoring Architecture Using Optimized CNN-BiLSTM Model for Fair and Secure Online Testing M Sumithra, K Karthikeyan, R Menaha, NBM Kumar, S Mohan, ... INTERNATIONAL JOURNAL OF ADVANCES IN SIGNAL AND IMAGE SCIENCES 11 (2), 58-79 , 2025 2025
Smart Gene Editing: AI and DS to Improve CRISPR-Cas9 Outcomes in Disease Therapy V Balajishanmugam, N Seethalakshmi, PG Palanimani, R Menaha Advanced AI and Data Science Applications, 91-104 , 2025 2025
Reviewing the effectiveness of lexicon-based techniques for sentiment analysis in massive open online courses R Menaha, K Ananthi International Journal of Data Science and Analytics 20 (3), 1631-1642 , 2025 2025 Citations: 9
A study on XAI-based drug identification system M Ramakrishnan, B Nagamanickam, D Ravikumar, S Muruganandam, ... AIP Conference Proceedings 3305 (1), 030002 , 2025 2025 Citations: 1
Impact of virtual influencers on brands promotion: A normative study G Sukumar, M Ramakrishnan, B Gurusamy, SBP Nagaraj, V Arivazhagan AIP Conference Proceedings 3305 (1), 030004 , 2025 2025
AI-Driven Real-Time Feedback System for Enhanced Student Support: Leveraging Sentiment Analysis and Machine Learning Algorithms AJS J. Prakash,R. Swathiramya,G. Balambigai,R. Menaha IJCESEN 10 (4), 1567-1574 , 2024 2024 Citations: 35
Drug Pills Identification System using Google Gemini LLM: A Generative AI approach R Menaha, R Abilaash, PN Mohanram, S Sukumar 2024 International Conference on Emerging Research in Computational Science … , 2024 2024
Enhanced Visual Cryptographic Schemes with Essential Access Structures and Pixel-Wise Operations SM M. Revathi, D. Devi , R. Menaha , R. Dineshkumar Journal of Cybersecurity and Information Management 14 (2), 300-310 , 2024 2024 Citations: 1
IOT Based heart rate monitoring system design for heart attack detection P Sutha, A Periyanan, R Menaha, V Jayanthi, B Girish 2024 4th International Conference on Advance Computing and Innovative … , 2024 2024 Citations: 6
Performance optimization in software-defined networks based on IoT networks K Renu, R Menaha, N Yamuna 2024 Ninth International Conference on Science Technology Engineering and … , 2024 2024 Citations: 1
Finding experts in community question answering system using trie string matching algorithm with domain knowledge R Menaha, VE Jayanthi IETE Journal of Research 70 (3), 2602-2614 , 2024 2024 Citations: 8
Securing Shared Data Based on Homomorphic Encryption Schemes K Renuka Devi, S Nithyapriya, G Pradeep, R Menaha, S Suganyadevi Homomorphic Encryption for Financial Cryptography: Recent Inventions and … , 2023 2023 Citations: 1
Heuristics‐based sequence labelling model for finding educational domain acronym expansions R Menaha, V Jayanthi Expert Systems 40 (6), e13216 , 2023 2023 Citations: 2
A Finger Vein Image-based Person Recognition System using BCH Codes to Access Medical Records R Menaha, VE Jayanthi, AL Mary, S Suganyadevi, S Aishwarya 2023 International Conference on Inventive Computation Technologies (ICICT … , 2023 2023 Citations: 1
Opioid Recommendation to Arthroplasty Patients, Using Pearson Correlation and Shapiro Wilk Test R Menaha, P Shruthika, AR Abdul Ashiq, M Akshay, V Santhosh XVIII International Conference on Data Science and Intelligent Analysis of … , 2023 2023
Map Building of Indoor Environment with Sensors using Neural Network SAL Mary, K Ulagapriya, A Poonguzhali, R Menaha, B David, ... 2023 Winter Summit on Smart Computing and Networks (WiSSCoN), 1-6 , 2023 2023
Hybrid cluster head selection approach for node lifetime enhancement in wireless sensor networks C Padmavathy, VS Akshaya, R Menaha, SP Raja 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022 2022 Citations: 5
Smart healthcare in IoT using convolutional based cyber physical system S Suganyadevi, SS Priya, R Menaha, S Sathiya, P Jha 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-6 , 2022 2022 Citations: 22
Improved political optimizer and deep neural network-based resource management strategy for fog enabled cloud computing M Prakash, V Vijayaganth, FD Shadrach, R Menaha, T Daniya, T Guha 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-6 , 2022 2022 Citations: 11
MOST CITED SCHOLAR PUBLICATIONS
AI-Driven Real-Time Feedback System for Enhanced Student Support: Leveraging Sentiment Analysis and Machine Learning Algorithms AJS J. Prakash,R. Swathiramya,G. Balambigai,R. Menaha IJCESEN 10 (4), 1567-1574 , 2024 2024 Citations: 35
Student Feedback Mining System Using Sentiment Analysis RY R.Menaha, R.Dhanaranjani, T.Rajalakshmi International Journal of Computer Applications Technology and Research 6 (1 … , 2017 2017 Citations: 26
Smart healthcare in IoT using convolutional based cyber physical system S Suganyadevi, SS Priya, R Menaha, S Sathiya, P Jha 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-6 , 2022 2022 Citations: 22
A cluster-based approach for finding domain wise experts in community question answering system R Menaha, VE Jayanthi, N Krishnaraj, N Praveen Sundra Kumar Journal of Physics: Conference Series 1767 (1), 012035 , 2021 2021 Citations: 17
Improved political optimizer and deep neural network-based resource management strategy for fog enabled cloud computing M Prakash, V Vijayaganth, FD Shadrach, R Menaha, T Daniya, T Guha 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-6 , 2022 2022 Citations: 11
A Survey on Acronym–Expansion Mining Approaches from Text and Web R Menaha, VE Jayanthi Smart Intelligent Computing and Applications, Smart Innovation, Systems and … , 2019 2019 Citations: 11
Reviewing the effectiveness of lexicon-based techniques for sentiment analysis in massive open online courses R Menaha, K Ananthi International Journal of Data Science and Analytics 20 (3), 1631-1642 , 2025 2025 Citations: 9
Question answering system using web snippets R Menaha, AU Surya, K Nandhni, M Ishwarya 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics … , 2017 2017 Citations: 9
Finding experts in community question answering system using trie string matching algorithm with domain knowledge R Menaha, VE Jayanthi IETE Journal of Research 70 (3), 2602-2614 , 2024 2024 Citations: 8
IOT Based heart rate monitoring system design for heart attack detection P Sutha, A Periyanan, R Menaha, V Jayanthi, B Girish 2024 4th International Conference on Advance Computing and Innovative … , 2024 2024 Citations: 6
Hybrid cluster head selection approach for node lifetime enhancement in wireless sensor networks C Padmavathy, VS Akshaya, R Menaha, SP Raja 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022 2022 Citations: 5
A hybrid model for finding abbreviation–definition pairs from biomedical abstracts using heuristics-based sequence labeling and perceptron linear classifier R Menaha, VE Jayanthi Expert Systems with Applications- Elsevier 166, 114049 , 2020 2020 Citations: 4
Heuristics‐based sequence labelling model for finding educational domain acronym expansions R Menaha, V Jayanthi Expert Systems 40 (6), e13216 , 2023 2023 Citations: 2
A web based approach: Acronym Definition Extraction R Menaha, M Barkavi, PG Prashanthini, R Narmadha International Research Journal of Engineering and Technology (IRJET) 3 (2 … , 2016 2016 Citations: 2
Semantic similarity between words using SWD and snippets R Menaha, G Anupriya International conference on current trends in advanced computing , 2013 2013 Citations: 2
A study on XAI-based drug identification system M Ramakrishnan, B Nagamanickam, D Ravikumar, S Muruganandam, ... AIP Conference Proceedings 3305 (1), 030002 , 2025 2025 Citations: 1
Enhanced Visual Cryptographic Schemes with Essential Access Structures and Pixel-Wise Operations SM M. Revathi, D. Devi , R. Menaha , R. Dineshkumar Journal of Cybersecurity and Information Management 14 (2), 300-310 , 2024 2024 Citations: 1
Performance optimization in software-defined networks based on IoT networks K Renu, R Menaha, N Yamuna 2024 Ninth International Conference on Science Technology Engineering and … , 2024 2024 Citations: 1
Securing Shared Data Based on Homomorphic Encryption Schemes K Renuka Devi, S Nithyapriya, G Pradeep, R Menaha, S Suganyadevi Homomorphic Encryption for Financial Cryptography: Recent Inventions and … , 2023 2023 Citations: 1
A Finger Vein Image-based Person Recognition System using BCH Codes to Access Medical Records R Menaha, VE Jayanthi, AL Mary, S Suganyadevi, S Aishwarya 2023 International Conference on Inventive Computation Technologies (ICICT … , 2023 2023 Citations: 1
