Control and Systems Engineering, Electrical and Electronic Engineering, Energy Engineering and Power Technology
33
Scopus Publications
581
Scholar Citations
12
Scholar h-index
14
Scholar i10-index
Scopus Publications
Gabor Transform-Based Deep Learning System Using CNN for Melanoma Detection S. Deivasigamani, C. Senthilpari, Siva Sundhara Raja. D, A. Thankaraj, G. Narmadha, K. Gowrishankar Computers, 2026 Melanoma is highly dangerous and can spread rapidly to other parts of the body. It has an increasing fatality rate among different types of cancer. Timely detection of skin malignancies can reduce overall mortality. Therefore, clinical screening methods require more time and accuracy for diagnosis. An automated, computer-aided system would facilitate earlier melanoma detection, thereby increasing patient survival rates. This paper identifies melanoma images using a Convolutional Neural Network. Skin images are preprocessed using Histogram Equalization and Gabor transforms. A Gabor filter-based Convolutional Neural Network (CNN) classifier trains and classifies the extracted features. We adopt Gabor filters because they are bandpass filters that transform a pixel into a multi-resolution kernel matrix, providing detailed information about the image. This study suggests a method with accuracy, sensitivity, and specificity of 98.58%, 98.66%, and 98.75%, respectively. This research supports SDGs 3 and 4 by facilitating early melanoma detection and enhancing AI-driven medical education.
DESIGN OF SMART WASTE SORTING SYSTEM USING DEEP LEARNING TECHNIQUES Journal of Engineering Science and Technology, 2025
Power Supply Path Search For Electric Supply Restoration Using Breadth First Search Algorithm Nikita Sharma, Rashmi M. R., S. Deivasigamani, K. Gowrishankar International Conference on Electrical Energy Systems Icees, 2025 Identification of the power supply path during normal operation and contingencies is one of the major concern in power distribution network. For uninterrupted power supply, it is very essential to identify the shortest alternate path when there is a fault in the regular line. This paper presents a power supply path searching method for a radial distribution system using the Breadth-First Search (BFS) algorithm. The proposed method is applied on the IEEE 33-bus distribution system to determine the restoration paths of buses during fault conditions. The BFS algorithm trace the shortest path from the central substation to other buses efficiently using the network as a graph and queue-based traversal. The model feeds power to all buses in the right order after fault isolation. The BFS algorithm is applied on the IEEE 33 bus system using Python programming, and the simulated results are presented in this paper. The appropriate path is discovered. The model supports automating power restoration planning in distribution networks.
Cross-Regional Emergency Power Dispatch Optimization: A Time-Varying Analysis with DFS-Based Path Identification Lakshana S., Rashmi M. R., Hoong Pin Lee, K. Gowrishankar 2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025 In an interconnected multi-area system, whenever there is a fault in line connecting two areas, it may be required to borrow the power from the next immediate region based on the availability of the generation. This paper proposes a cross-regional emergency power dispatch model to maximize social welfare with transmission constraints. In a multi-regional power system, actual dispatch paths are obtained using the Depth-First Search (DFS) algorithm. A linear programming model is employed to optimize power dispatch within 24 hours. Channel capacities, transmission losses, and time-varying weight coefficients are incorporated into the model to capture dynamic demand patterns. In this work, interconnected multi-area system with four interconnected areas Q, S, Z and J and five channels C1-C5 are considered. Q & S regions will have excess generation. Z and J areas always receive power. The results indicate that in a simulated outage, emergency paths such as Channel 5 (C5) satisfy the demand effectively. Social welfare reaches its maximum at 950,000 Yuan during peak demand periods, and the power supplied to receivers Z and J dynamically varies according to the time-varying weights. Sensitivity analysis demonstrates the impact of demand fluctuations, minimum flow limitations, and channel dispatch capacities. In multi-regional power systems, this model provides a trustworthy approach to emergency power dispatch.
VOLTAGE SAG MITIGATION USING MULTILEVEL INVERTER AS A DYNAMIC VOLTAGE RESTORER UPB Scientific Bulletin Series C Electrical Engineering and Computer Science, 2024
GENETIC ALGORITHM BASED DETECTION OF BREAST CANCER USING LEAST SQUARE-SUPPORT VECTOR MACHINE CLASSIFIER Arpn Journal of Engineering and Applied Sciences, 2023 Breast tumors are a dangerous disease among women worldwide. They are the second leading cause of death among all forms of cancers in women. Their early detection is critical to increasing the survival rate of women. Mammography is a reliable screening technique in the early detection of abnormal breast tissue severity. Radiologist abnormalities in the breast tissue, radiologists employ mammography. However, detecting breast abnormalities through digital diagnostic techniques by a radiologist could be time consuming. Consequently, computerized studying of digital mammography has emerged via the development of CAD systems. Several CAD systems have been developed for breast cancer detection. However, obtaining a satisfactory performance of CAD systems is a challenging task. We propose a CAD architecture for the classification of breast tissues as either benign or malignant using an LS-SVM classifier with various kernels namely linear, quadratic, polynomial, MLP, and RBF kernels. From the experimental outputs, it is clear that GA based LS-SVM classifier with RBF kernel outputs classification accuracy of 94.59% for normal/abnormal case classification is better, when it is compared with all other kernels. It is also stated that GA based LS-SVM classifier with RBF kernel produces a better classification accuracy of 98.26% for benign/malignant case classification when it is compared with other reported works.
Development of a Wearable Diagnostic and Therapeutic Device for Hypo and Hyperthermic Patients K. Gowrishankar, M.R. Rashmi, S. Deivasigamani Proceedings International Conference on Technological Advancements in Computational Sciences Ictacs 2023, 2023 Hypothermia and hyperthermia are body temperature related issues. Abnormal high body temperature is known as hyperthermia and if body is too cold it is hypothermia. These problems are encountered when a person is exposed to either very high or very low temperature. People exposed to extreme temperatures may suffer from heat strokes and dehydration. If this problem is not treated, it leads to severe effect even to death. So, this type of defect should be detected well in advance to take necessary precautions to minimize the impact. In this paper a smart jacket in which a Peltier module is placed inside the jacket for hyperthermic and hypothermic patients is proposed. A smart watch is used for diagnosis purpose and jacket is used as therapeutic purpose. The DS18B20 temperature sensor used to detect the body temperature using wrist watch. MAX30102 pulse rate sensor and DHT11 humidity sensors are also used. These sensors are connected to Arduino Nano microcontroller which takes sensor inputs and controls the temperature. If the patient's body temperature is lower than the normal temperature, then the smart watch sends signals through GSM module transmitter to the receiver in the jacket. Using Peltier effect, the jacket produces warmness/coldness. The first aid is given to the patient through the application of heat/cold.
A Novel SVM and K-NN Classifier Based Machine Learning Technique for Epileptic Seizure Detection Gowrishankar K., Muthukumar V., Sudhakara Pandian R., Deivasigamani S., Chun Kit Ang International Journal of Online and Biomedical Engineering, 2023 An EEG signal is used for capturing the signals from the brain, which helps in localization of epileptogenic region, thereby which plays a vital role for a successful surgery. The focal and non-focal signals are obtained from the epileptogenic region and normal region respectively. The localization of epileptic seizure with the help of focal signal is necessary while detecting seizures. Hence, the present article provides detailed analysis of EEG signals. The Focal and Non-focal signals are decomposed using EMD-DWT. A combination of EMD-DWT decomposition method in accordance with log-energy entropy gives an efficient accuracy in comparison to other entropy in differentiating the Focal from Non-focal signals. The extracted features are subjected to SVM and KNN classifiers whose performance will be calculated and verified with respect to accuracy, sensitivity and specificity. At the end, it will be shown that KNN produces the highest accuracy when compared to SVM classifier.
Detection of Early Fault in Power Electronic Converters through Machine Learning and Data Mining Techniques Pradeep K V, K. Gowrishankar, E. Sivanantham, Katta Subba Rao, Nagulapati Kiran, A. Vimal Proceedings of the 3rd International Conference on Artificial Intelligence and Smart Energy Icais 2023, 2023 The Power electronic system plays a significant role in versatile applications. The power electronic converters are largely used in energy conversion mechanisms. A fault is defined as the abnormal condition of the system that results in various consequences. The important constraints in the modelling of power electronic systems involve losses, Electromagnetic Interference (EMI) and harmonics. This includes the fault detection in the power electronic converters that includes three phase rectifier, d-dc converter and single-phase inverter. These parameter affects the overall efficiency and quality of the system. To overcome the fault in the power electronic converters, the machine learning with data mining techniques is adopted. This helps to predict the early fault and helps to increase the efficiency of the system.
GSM based dual power enhanced LED display notice board with motion detector International Journal of Engineering and Technology Uae, 2018
Neural network based mathematical model for feed management technique in aquaculture Journal of Advanced Research in Dynamical and Control Systems, 2017
MATLAB simulink model of fuzzy logic controller with PSS and its performance analysis IEEE International Conference on Advances in Engineering Science and Management Icaesm 2012, 2012
Gabor Transform-Based Deep Learning System Using CNN for Melanoma Detection S Deivasigamani, C Senthilpari, A Thankaraj, G Narmadha, ... Computers 15 (1), 54 , 2026 2026 Citations: 1
DESIGN OF SMART WASTE SORTING SYSTEM USING DEEP LEARNING TECHNIQUES M RAMASAMY, S DEIVASIGAMANI, MABIN IIYAS, A THANKARAJ, ... Journal of Engineering Science and Technology 20 (6), 1877-1894 , 2025 2025
Power Supply Path Search For Electric Supply Restoration Using Breadth First Search Algorithm N Sharma, MR Rashmi, S Deivasigamani, K Gowrishankar 2025 11th International Conference on Electrical Energy Systems (ICEES), 440-443 , 2025 2025
Machine learning-assisted prediction of associated risk factors for depression, anxiety and stress among nursing students SDHJ Hamad, Z Al-Bashabsheh, MJB Sakthivel, K Gowrishankar Cuestiones de Fisioterapia 54 (2), 284-294 , 2025 2025
VOLTAGE SAG MITIGATION USING MULTILEVEL INVERTER AS A DYNAMIC VOLTAGE RESTORER AS M. R. RASHMI, K. GOWRISHANKAR, S. DEIVASIGAMANI U.P.B. Sci. Bull., Series C Electrical Engineering and Computer Science 86 … , 2024 2024
Voltage sag mitigation using multilevel inverter as a dynamic voltage restorer MR Rashmi, K Gowrishankar, S Deivasigamani, A Suresh UPB Scientific Bulletin, Series C 86 (4), 316-328 , 2024 2024 Citations: 1
Enhanced Hybrid Power Grid System Using Adaptive Fuzzy Logic Controller by Supraharmonics Reduction G Kasilingam, S Deivasigamani, R Prabha, A Thankaraj, S Amirtharaj, ... International Journal of Applied Sciences & Development 3, 176-185 , 2024 2024 Citations: 2
Development of a Wearable Diagnostic and Therapeutic Device for Hypo and Hyperthermic Patients K Gowrishankar, MR Rashmi, S Deivasigamani 2023 3rd International Conference on Technological Advancements in … , 2023 2023 Citations: 2
Quality Assured Crowd Sourcing Coupled with Neural Networks KS Kumari, M Ashik, K Gowrishankar Proceedings of ICACTCE'23—The International Conference on Advances in … , 2023 2023
A Novel SVM and K-NN Classifier Based Machine Learning Technique for Epileptic Seizure Detection. CK Ang International Journal of Online & Biomedical Engineering 19 (7) , 2023 2023 Citations: 11
QCNN—A Conceptual Framework for Duplicate Removal in Big Data Using Quality Assured Crowd Sourcing Coupled with Neural Networks K Shantha Kumari, M Ashik, K Gowrishankar, P Kanmani International Conference on Advances in Communication Technology and … , 2023 2023 Citations: 1
Detection of Early Fault in Power Electronic Converters through Machine Learning and Data Mining Techniques KV Pradeep, K Gowrishankar, E Sivanantham, KS Rao, N Kiran, A Vimal 2023 Third International Conference on Artificial Intelligence and Smart … , 2023 2023 Citations: 3
QCNN- A Conceptual Framework for Duplicate removal in Big Data using Quality assured Crowd sourcing coupled with Neural networks MA K. Shanthakumari, P. Kanmani, K. Gowrishankar ICACTCE 23 Proceedings of ICACTCE'23 — The International Conference on … , 2023 2023
Study on Recognition of Heart Arrhythmias by Deep Learning Approach of the ECG Signals using Edge Devices DNP Dr. K. Gowrishankar, Dr. Anurag Rawat, Pratibha Singh European Chemical Bulletin 12 (04), 6651 – 6658 , 2023 2023
Optimal design of damping control of oscillations in power system using power system stabilizers with novel improved BBO algorithm G Kasilingam, J Pasupuleti, SK Kasirajan, A Nagarathinam, D Natesan Indonesian Journal of Electrical Engineering and Informatics (IJEEI) 10 (4 … , 2022 2022 Citations: 4
Role of Analytics in IoT: A Development of AAAS S Manikandan, K Gowrishankar, J Pasupuleti Reinvention of Health Applications with IoT, 93-108 , 2022 2022
Extended over modulation zone three-dimensional SVPWM for three-level neutral-point-clamped C Santhakumar, C Bharatiraja, K Gowrishankar, KMR Eswar, J Vinoth Materials Today: Proceedings 52, 1756-1762 , 2022 2022 Citations: 4
Extended Over Modulation Zone Three-Dimensional SVPWM for Three-Level Neutral- Point-Clamped JV C. Santhakumar, C. Baharathiraja, K.Gowrishankar, K.M. Ravi Eswar Materials Today: Proceedings 52 (03), 1756-1762 , 2022 2022
Performance analysis of a novel fusion adder/subtractor design JA Prathap, R Nithya, P Jegadeeshwari, G Kasilingam Journal of Physics: Conference Series 1818 (1), 012229 , 2021 2021 Citations: 2
Design of low-power coupled chopper instrumentation amplifier using pin pong ripple reduction for biomedical applications R Krishnamoorthy, D Kodandapani, G Kasilingam, NB Prakash, ... Materials Today: Proceedings 45, 2115-2120 , 2021 2021 Citations: 4
MOST CITED SCHOLAR PUBLICATIONS
Assessment of learning domains to improve student's learning in higher education. G Kasilingam, E Chinnavan Journal of Young Pharmacists 6 (1) , 2014 2014 Citations: 174
Control of boiler operation using PLC–SCADA KG Shankar Proceedings of the International MultiConference of Engineers and Computer … , 2008 2008 Citations: 82
Coordination of PSS and PID controller for power system stability enhancement–overview G Kasilingam, J Pasupuleti Indian Journal of Science and Technology 8 (2), 142-51 , 2015 2015 Citations: 40
A survey of light emitting diode (LED) display board G Kasilingam, M Ramalingam, C Sekar Indian journal of science and technology 7 (2), 185 , 2014 2014 Citations: 29
The power quality measurements and real time monitoring in distribution feeders CS Kumar, P Ramesh, G Kasilingam, D Ragul, C Bharatiraja Materials Today: Proceedings 45, 2987-2992 , 2021 2021 Citations: 22
Adaptive Fuzzy Controller to Control Turbine Speed K Gowrishankar, V Elancheralath Ubicc Jrournal 3 (5) , 2008 2008 Citations: 18
Single Machine Connected Infinite Bus System Tuning Coordination Control using Biogeography-Based Optimization Algorithm. G Kasilingam, J Pasupuleti, C Bharatiraja, Y Adedayo FME Transactions 47 (3) , 2019 2019 Citations: 17
A survey of voice aided electronic stick for visually impaired people GK Gurubaran, M Ramalingam International Journal of Innovative Research in Advanced Engineering (IJIRAE … , 2014 2014 Citations: 17
BBO algorithm-based tuning of PID controller for speed control of synchronous machine G Kasilingam, J Pasupuleti Turkish Journal of Electrical Engineering and Computer Sciences 24 (4), 3274 … , 2016 2016 Citations: 16
Neural network based mathematical model for feed management technique in aquaculture K Gowrishankar, K Nithiyananthan, PR Mani, G Venkatesan Journal of Advanced Research in Dynamical and Control Systems 18 (1), 1142-1161 , 2017 2017 Citations: 13
Development of prototype model for wireless based controlled pick and place robotic vehicle LK Hau, G Kasilingam, K Nithiyananthan TELKOMNIKA Indonesian Journal of Electrical Engineering 14 (1), 110-115 , 2015 2015 Citations: 13
Particle Swarm Optimization based PID Power System Stabilizer for a Synchronous Machine G Kasilingam International Journal of Electrical, Electronic Science and Engineering 8 (1 … , 2014 2014 Citations: 12
A Novel SVM and K-NN Classifier Based Machine Learning Technique for Epileptic Seizure Detection. CK Ang International Journal of Online & Biomedical Engineering 19 (7) , 2023 2023 Citations: 11
Implementation and assessment of outcome based education in engineering education G Kasilingam, K Nithiyananthan, PR Mani International Journal of Pure and Applied Mathematics 117 (17), 217-228 , 2017 2017 Citations: 10
Cluster Analysis Based Fault Identification Data Mining Models for 3 Phase Power Systems KN Tan Yong Sing, Syahrel Emran Bin Siraj, Raman Raguraman, Pratap Nair ... International Journal of Innovation and Scientific Research 24 (2), 285-292 , 2016 2016 Citations: 9
A comparative study of the ZN, adaptation law and PSO methods of tuning the PID controller of a synchronous machine G Kasilingam, GS Kasilingam, J Pasupuleti Int. Rev. Model. Simulations 7 (6), 918-926 , 2014 2014 Citations: 9
MATLAB simulink model of fuzzy logic controller with PSS and its performance analysis K Gowrishankar, MDM Khan IEEE-International Conference On Advances In Engineering, Science And … , 2012 2012 Citations: 8
Power System Stabilizer Optimiza–tion Using BBO Algorithm for a Better Damping of Rotor Oscilla–tions Owing to Small Disturbances J Pasupuleti, C Bharatiraja, Y Adedayo optimization (PSO) 20, 22 , 2019 2019 Citations: 7
Modelling and performance analysis of PID power system stabilizer using adaptation law in Simulink environment K Gowrishankar 2011 International Conference on Electronics, Communication and Computing … , 2011 2011 Citations: 7
GSM based dual power enhanced LED display notice board with motion detector K GowrishankarKasilingam, PR Mani, S Thomas International Journal of Engineering & Technology 7 (2.8), 559-566 , 2018 2018 Citations: 6
