Dr . N. KALAIVANI
NAME OF THE FACULTY :Dr.N.KALAIVANI
DESIGNATION : ASSISTANT PROFESSOR
QUALIFICATION : MCA., M.Phil., Ph.D., SET.,
EXPERIENCE : 18 Years 5 Months
DEPARTMENT : INFORMATION TECHNOLOGY
Dr.N.Kalaivani, MCA.,M.Phil., Ph.D., SET., Assistant Professor of Information Technology. She has 18 years and 5 months of teaching experience. She has completed her MCA during the year 2004at Kongunadu Arts and Science College. She has obtained herMaster of Philosophy in Computer Science in the year 2014 at Kongunadu Arts and Science College,Coimbatore. She has completed her Degree of Doctorate in Computer Science in the year 2022 at Kongunadu Arts and Science College, Coimbatore.
Her research area includes Software Engineering and Data Mining. She has published6research papers in various National and International journals and presented 1 research paper in internationalconference.She hasorganized International Workshop and also conducted Quiz Competitions, Debugging and given Guest Lectures. She enriched her teaching careerby attending several Faculty Development Programme, Webinar, Seminar.
Member in Professional Bodies
Life member of Indian Science Congress Association (ISCA) and acted as a member in Board of Studies.
|S. NO||RESEARCH ARTICLES|
INTERNATIONAL / NATIONALJOURNALS(7)
- Kalaivani and R.Beena. (2018). “Overview of Software Defect Prediction using Machine Learning Algorithms.” International Journal of Pure and Applied Mathematics, Vol. 118, No. 20, pp. 3863-3873.
- Kalaivani and R.Beena. (2020). “Boosted Relief Feature Subset Selection and Heterogeneous Cross Project Defect Prediction using Firefly Particle Swarm Optimization.” International Journal of Recent Technology and Engineering, Vol. 8, No.5, pp. 2605-2613.
- Kalaivani and R.Beena. (2021). “Overview of Supervised Learning Techniques for Software Defect Prediction.” International Research Journal of Modernization in Engineering Technology and Science, Vol. 3, No. 10, pp. 1091-1095.
- Kalaivani and R.Beena. (2021). “Modelling a Behavioural Approach for Heterogeneous Cross Project Software Defect Prediction using Clustering Approach.” Gedrag & Organisatie Review, Vol. 34, No. 4, pp. 116-130.
- Kalaivani and R.Beena. (2021). “Boosting Multi-Kernel Convolutional Neural Networkfor Heterogeneous Cross Project Defect Prediction.” International Conference on Emerging Trends in Science and Technology (ETIST-2021) held at Nallamuthu Gounder Mahalingam College, Pollachi, India.
- Kalaivani and R.Beena. (2022). “Improved SMOTE and Optimized Siamese Neural Networks for Class Imbalanced Heterogeneous Cross Project Defect Prediction.” International Journal of Intelligent Engineering and Systems, Vol. 15, No. 2, pp. 79-88.
- N.Kalaivani and R.Beena. (2022). “Behavioral-based Kernel Neutrosophic Clustering for Heterogeneous Cross Project Defect Prediction.” ARPN Journal of Engineering and Applied Sciences (JEAS), Vol. 17, No. 5, pp. 571-577.