S. Senthilkumar

Scopus Publications

Improving spectral efficiency in distributed massive MIMO in multi-user downlink millimeter wave
R. Rajaganapathi, S. Senthilkumar, Eatedal Alabdulkreem, Nuha Alruwais
Scientific Reports, 2026
Analog and digital precoding are used in distributed massive multiple-input multiple-output (MIMO) at millimeter wave (mmWave) frequencies to efficiently manage data transfer across several antennas and base stations (BSs) situated at different locations. This method enhances spectral efficiency(SE) in spite of having a smaller amount complexity and cost compared fully digital systems. This paper presents a fully connected hybrid precoding design for a downlink mmWave dispensed or distributed massive multi-user MIMO. The objective function for the optimization problem is the SE of the proposed system, subject to constraints on analog radio frequency (RF) precoding and power budget. The main aim is to maximize SE. Due to the nonconvex nature of the problem, a two-stage iterative algorithm is proposed to conclude the optimal analog and digital beamforming matrices and sum rate. The 1st stage obtains the optimal digital matrix assuming the analog RF precoder matrix is known, followed by acquiring the optimal analog RF precoder matrix in the next step. The Karush-Kuhn-Tucker (KKT) condition for each maximization problem are compute and examine to derive the solving algorithms for each stage. The simulation results display that the proposed design outperforms current methods in sum rate and approaches the performance of fully digital systems with reduced complexity compared to other alternatives.
Robust hybrid modulated massive MIMO-FSOC frame for reliable remote healthcare monitoring in atmospheric environment
R. Balakrishnan, S. Senthilkumar
Optik, 2026
A Raspberry Pi-based Intelligent System for Detecting Vitamin Deficiencies using Image Analysis and Lightweight Deep Learning Models
S. Kaviya, M. Kirthika, S. Senthilkumar, P. Arunkumar, R. Ramanan, M. Kavitha
Proceedings of the 2026 6th International Conference on Image Processing and Capsule Networks Icipcn 2026, 2026
Vitamin deficiencies contribute to millions of preventable health complications worldwide, ranging from vision loss and neurological dysfunction to reduced immunity and skeletal weakness. In low-resource communities, laboratory testing is often inaccessible or costly, resulting in undiagnosed and untreated deficiencies. Many deficiencies, however, leave identifiable visual traces on anatomical regions such as the eyes, tongue, nails, and skin. This research presents a fully offline, low-cost, and portable diagnostic device built using Raspberry Pi, Pi Camera, TensorFlow Lite deep learning, and fuzzy logic reasoning. The system takes pictures of certain parts of the body, processes them, and then uses a MobileNet-based model that is optimized for embedded inference to sort them. Fuzzy logic refines borderline predictions for improved diagnostic stability. The device displays deficiency results, provides nutritional recommendations, and generates structured PDF reports. Comprehensive evaluation demonstrates that the proposed system is an effective preliminary screening tool suitable for rural health screening, portable clinics, and educational institutions.
A Novel ANFIS Control Strategy for Effective Battery Charging Controlling Application
C. H. Hussaian Basha, S. Senthilkumar, Buddhadeva Sahoo, Fini Fathima, Mohammed Mujahid Irfan, Srikanth Velpula
Lecture Notes in Networks and Systems, 2026
Intrusion Detection System for Network Security Using Novel Adaptive Recurrent Neural Network-Based Fox Optimizer Concept
R. Manivannan, S. Senthilkumar
International Journal of Computational Intelligence Systems, 2025
The majority of daily networks and communications rely heavily on network security. Researchers in cybersecurity emphasize the necessity of developing effective intrusion detection systems (IDS) to safeguard networks. The importance of efficient IDS escalates as attackers devise new types of attacks and network volumes expand. Furthermore, IDS aims to ensure the integrity, confidentiality, and availability of data transmitted across networked systems by preventing unauthorized access. Following numerous studies utilizing machine learning (ML) to develop effective IDS, the focus has shifted towards deep learning (DL) techniques as artificial neural networks (ANNs) and DL systems have become prevalent. ANNs are capable of generating features autonomously, eliminating the need for manual intervention. This paper introduces an innovative adaptive recurrent neural network-based fox optimizer (ARNN-FOX) method. The primary objective of the ARNN-FOX system is to efficiently detect and classify network intrusions, thereby enhancing network security. Data normalization is conducted to scale the incoming data into a usable format. The gray level co-occurrence matrix (GLCM) method is proposed for selecting the optimal subset of features for the ARNN-FOX method. In the proposed approach, the fox algorithm (FOX) is utilized for the adjustment of hyperparameters in the ARNN model. The efficacy of the ARNN-FOX approach is assessed using benchmark datasets. Based on comparative results, the ARNN-FOX method demonstrates superior performance in parameters such as accuracy, specificity, sensitivity, F 1 Score, recall value, and precision values over existing models . The proposed ARNN-FOX-based IDS model for the network security in terms of accuracy is 15.12%, 8.79%, 6.45%, and 4.21% better than RNN, CNN-LSTM, DASO-RNN, and ChCSO-LSTM, respectively. Similarly, with respect to specificity, the suggested ARNN-FOX-based IDS model for network security outperforms RNN, CNN-LSTM, DASO-RNN, and ChCSO-LSTM by 32.43%, 8.89%, 3.16%, and 2.08%, respectively.
Energy efficient traffic data aggregation and routing for metropolitan optical access network
T. Senthil Kumar, Mohan. V, S. Senthilkumar
Scientific Reports, 2025
The Energy Efficient Regional Area Metropolitan Optical Access Network (MOAN) is a modern optical communication system specifically designed for metropolitan areas. It addresses the increasing demand for high-speed data transmission while optimizing energy consumption. In this paper, energy-efficient traffic data aggregation and energy-aware routing are presented to increase the network lifetime of the system. The traffic data aggregation reduces redundant transmissions, while energy-aware routing minimizes energy consumption by selecting energy-efficient paths. Initially, the wavelength utility-based dynamic wavelength allocation approach (WU-DWA) was developed to facilitate efficient resource utilization. Then, the data aggregation is performed in the context of traffic grooming using the adaptive principal component analysis (APCA)technique. APCA combines or grooms multiple low-bandwidth data streams into higher-capacity data channels to optimize the use of available network resources, such as wavelengths in optical networks or channels in general communication systems. The aggregated data is routed with the proposed energy efficient adaptive Tuna slap Swarm Optimization strategy (ATSSO). By using the proposed approach, the performance obtained in terms of energy consumption is 88, throughput is 131.63, average packet delay is 3.551, and energy savings are 29.99, respectively. The proposed approach is implemented, and the performance is evaluated in terms of standard performance metrics and analyzed using traditional approaches. The better performance indicates that the proposed approach is more efficient than existing approaches.
Development of an IoT-based MANET for Healthcare Monitoring System Using Data Loss Aware Routing Protocol
K. Balasubramanian, S. Senthilkumar, N. Kopperundevi, S. Sivakumar
International Journal of Computational Intelligence Systems, 2025
Healthcare needs a major shift to more measurable and affordable solutions. The answer to these challenges is to focus on restructuring the healthcare system to prevent illness, not illness, and on disease prevention and early detection. The Internet of Things (IoT) communicates with mobile ad hoc networks (MANETs) in a smart environment, making it more attractive and cost-effective for consumers. Recently, MANET-IoT systems have been used in many areas of live applications. In addition, most routing protocols are for MANET, but they are not compatible with MANET-IoT. However, one of the key apparatuses of the MANET-IoT system is the loss of records due to unreliable routing. In this article, we suggest an optimal cluster founded data loss aware routing protocol, MANET-IoT, for healthcare monitoring systems (OCDL-HM). First, we introduce efficient cluster formation using the butterfly-induced sunflower optimization (BSFO) algorithm, which enhances the energy efficiency of routing. Then, the cluster head (CH) of every cluster is computed through a cuckoo search based deep probability neural network (CS-DPNN) with different design metrics. The CH node is acting as an intermediate node between cluster members and the next neighbouring CH node. After that, the next neighbouring CH node is selected by a hybrid recurrent dynamic neural network (RDNN), which provides data lossless routing between nodes. Finally, the simulation results of proposed and existing routing protocols analyzed with different simulation scenarios in terms of energy consumption, packet loss ratio, network lifetime, number of active nodes, packet delivery ratio, throughput, and latency.
Solving Optimal Power Flow Problem in Hybrid Renewable Energy Systems Through Hybrid Optimization Algorithm
P. J. Suresh Babu, S. P. Mangaiyarkarasi, R. Gandhi Raj, S. Senthilkumar
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2025
Hybrid dolphin swarm sparrow search optimization based multi-objective cloud workflow scheduling
S. Subashree, M. Rajakumaran, G. Pushpa, S. Senthilkumar
Journal of Cloud Computing, 2025
In cloud computing, scheduling workflows for data-intensive tasks is challenging due to task dependencies, heterogeneous resources, and high computational demands, all of which affect cost, execution time, and energy usage. This research proposes a novel hybrid optimization algorithm called Dolphin Swarm Sparrow Search Optimization (DSSSO) to address these challenges. The DSSSO model combines the broad search capability of Dolphin Swarm Optimization with the precise tuning ability of Sparrow Search Algorithm, enabling effective exploration and exploitation in the solution space. Unlike existing scheduling models that primarily optimize makespan and cost, the proposed DSSSO explicitly integrates energy consumption and resource utilization into a unified multi-objective framework. This dual-phase design—leveraging dolphins for global exploration and sparrows for local exploitation—ensures both convergence stability and adaptability in heterogeneous cloud environments. The main objective is to minimize makespan, reduce energy consumption, and lower scheduling cost while maximizing resource utilization. The model is evaluated using benchmark scientific workflows such as CyberShake, Montage, Epigenomics, and LIGO. Simulation results show that DSSSO outperforms existing methods, achieving up to 12% lower makespan, 15% less energy consumption, and 10% better resource usage compared to algorithms like Hybrid Bat Optimization and Improved Bat Optimization.
Retraction Note: Development of grey wolf optimization based modified fast terminal sliding mode controller for three phase interleaved boost converter fed PV system (Scientific Reports, (2024), 14, 1, (9256), 10.1038/s41598-024-59900-z)
K. Krishnaram, T. Suresh Padmanabhan, Faisal Alsaif, S. Senthilkumar
Scientific Reports, 2025
Fig. 13 appears to be very similar to Fig. 9 in a previously-published article by different authors 1 . The Authors stated that they used the same laboratory; the laboratory, however, did not confirm this. The Editors no longer have confidence in the veracity of the data presented in this Article.
Enhanced recurrent capsule network with hyrbid optimization model for shrimp disease detection
A. Sundar Raj, S. Senthilkumar, R. Radha, R. Muthaiyan
Scientific Reports, 2025
Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks
G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar
Scientific Reports, 2025
An optimized hybrid deep learning model to detect Alzheimer disease
A. Sundar Raj, C. Gunasundari, S. Senthilkumar, S. Sivamani
Scientific Reports, 2025
Retraction Note: Experimental design and analysis of advanced three phase converter for PV application with WCO-P&O MPPT controller (Scientific Reports, (2024), 14, 1, (10984), 10.1038/s41598-024-61856-z)
K. Krishnaram, S. Sivamani, Zuhair Alaas, M. M. R. Ahmed, S. Senthilkumar, S. Antony Raj
Scientific Reports, 2025
A Novel Hybrid MPPT Technique for a PV System Operated Under Partial Shading Conditions with Three Phase Interleaved Boost Converter
K. Krishnaram, M. Rajakumaran, S. Senthilkumar, S. P. Mangaiyarkarasi, R. Gandhi Raj
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2025
Hybridization of metaheuristic algorithms for resource scheduling in distributed robotic control system
P. Anand Raj, M. Rajakumaran, S. Palani Murugan, S. Senthilkumar
Discover Applied Sciences, 2025
Bacterial foraging optimization building block distribution algorithm based dynamic allocation in multiple robotic system
P. Anand Raj, S. Palanimurugan, S. Senthilkumar
Discover Applied Sciences, 2025
Reliability based multi-objective optimized routing protocol for VANETs using pelican optimization algorithm
R. Muthaiyan, S. Senthilkumar, C. Vijesh Joe, M. Kavitha
Discover Applied Sciences, 2025
Hybrid attention residual deep convolution learning network for bio medical image analysis
A. Sundar Raj, Paruchuri Chandra Babu Naidu, S. Sivakumar, S. Senthilkumar
Journal of Intelligent and Fuzzy Systems, 2025
Deep learning–based classification of brain tumors from MRI images
International Journal of Advanced Technology and Engineering Exploration, 2025
IoT based Automated Irrigation System for Aquaponics and Land Farming
M. Kavitha, C. H. Hussaian Basha, B. Janani, B.S. Gopika, S. Sivamani, S. Senthilkumar
Proceedings of the 6th International Conference on Smart Electronics and Communication Icosec 2025, 2025
Graph Neural Networks for Functional Connectivity Analysis: Uncovering Neural Network Disruptions in Parkinson's Disease
R. Ayyappa, C. H. Hussaian Basha, S. Senthilkumar, K. Balasubramanian, S Arunkumar, S. Venkatesh
2025 3rd International Conference on Advancements in Electrical Electronics Communication Computing and Automation Icaeca 2025, 2025
Real-Time Speech Emotion Recognition Using Hybrid Transformer Networks for Mental Health Monitoring
P. Janani Durga, C. H. Hussaian Basha, Nelson Kennedy Babu Christopher, S. Senthilkumar, N. Rathina Kumar, M. Kavitha
Proceedings of the International Conference on Multi Agent Systems for Collaborative Intelligence Icmsci 2025, 2025
Development of VSS-FOCV, and IC MPPT Controllers for PEMFC Systems
Gurijala Sreedhar, CH Hussaian Basha, Shaik. Rafikiran, AVV Sudhakar, Faisal Alsaif, S. Senthilkumar
Proceedings of International Conference on Visual Analytics and Data Visualization Icvadv 2025, 2025
Transparent AI Solutions for Parkinson's Disease Diagnosis and Monitoring: A Multimodal Deep Learning Approach
S.G. Praveena, C. H. Hussaian Basha, S. Senthilkumar, R. Muthaiyan, E. Dinesh, S. Senthilkumar, M. Kavitha
2025 2nd International Conference on Computational Intelligence Communication Technology and Networking Cictn 2025, 2025
Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques
S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran
Discover Applied Sciences, 2025
Modeling of 4H-SiC MESFET by Including Thermal Effect, Surface and Substrate Trappings Using Botox Optimization Method
Nagalakshmi Yarlagadda, Satti Sudha Mohan Reddy, N. Karthikeyan, M. Sai Veerraju, S. Senthilkumar, G. B. Santhi, Sampada Viraj Dravid, Ajay Sudhir Bale, Kandi Bhanu Prakash
3rd International Conference on Power Electronics and Energy Icpee 2025, 2025
Development of grey wolf optimization based modified fast terminal sliding mode controller for three phase interleaved boost converter fed PV system
K. Krishnaram, T. Suresh Padmanabhan, Faisal Alsaif, S. Senthilkumar
Scientific Reports, 2024
Design of modified long short-term memory-based zebra optimization algorithm for limiting the issue of SHEPWM in multi-level inverter
G. Krithiga, S. Senthilkumar, Mohammed Alharbi, S. P. Mangaiyarkarasi
Scientific Reports, 2024
A hybrid deep learning approach to solve optimal power flow problem in hybrid renewable energy systems
G. Gurumoorthi, S. Senthilkumar, G. Karthikeyan, Faisal Alsaif
Scientific Reports, 2024
Performance optimization of interleaved boost converter with ANN supported adaptable stepped-scaled P&O based MPPT for solar powered applications
K. Krishnaram, T. Suresh Padmanabhan, Faisal Alsaif, S. Senthilkumar
Scientific Reports, 2024
An effective video inpainting technique using morphological Haar wavelet transform with krill herd based criminisi algorithm
M. Nuthal Srinivasan, M. Chinnadurai, S. Senthilkumar, E. Dinesh
Scientific Reports, 2024
Correction to: Design and analysis of solitary AC–AC converter using reduced components for efficient power generation system (Scientific Reports, (2024), 14, 1, (9323), 10.1038/s41598-024-60230-3)
K. Nandakumar, V. Mohan, Faisal Alsaif, S. Senthilkumar
Scientific Reports, 2024
Human monkeypox disease prediction using novel modified restricted Boltzmann machine-based equilibrium optimizer
D. Devarajan, P. Dhana lakshmi, S. Krishnaveni, S. Senthilkumar
Scientific Reports, 2024
Design and analysis of solitary AC–AC converter using reduced components for efficient power generation system
K. Nandakumar, V. Mohan, Faisal Alsaif, S. Senthilkumar
Scientific Reports, 2024
A quad DC source switched three-phase multilevel DC-link inverter topology
S. Sivamani, S. P. Mangaiyarkarasi, R. Gandhi Raj, S. Senthilkumar
Scientific Reports, 2024
A comprehensive performance analysis of advanced hybrid MPPT controllers for fuel cell systems
Ezzeddine Touti, Shaik Rafikiran, Besma Bechir Graba, Mouloud Aoudia, S. Senthilkumar
Scientific Reports, 2024
Experimental design and analysis of advanced three phase converter for PV application with WCO-P&O MPPT controller
K. Krishnaram, S. Sivamani, Zuhair Alaas, M. M. R. Ahmed, S. Senthilkumar, S. Antony Raj
Scientific Reports, 2024
An improved nested 3-phase 5-level MLI design with optimized output voltage and total harmonic distortion
Sivamani S, Mangaiyarkarasi S P, Senthilkumar S
Engineering Research Express, 2024
Improved restricted Boltzmann machine-based optimization model for the network security system in cloud environment
Manivannan R, Senthil kumar S, Senthil Kumar T
Engineering Research Express, 2024
Shrimp classification for white spot syndrome detection through enhanced gated recurrent unit-based wild geese migration optimization algorithm
L. Ramachandran, S. P. Mangaiyarkarasi, A. Subramanian, S. Senthilkumar
Virus Genes, 2024
Performance enhancement of cloud security with migration algorithm for choosing virtual machines in cloud computing
R Manivannan, S Senthilkumar, K Kalaivani, N Prathap
Engineering Research Express, 2024
Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm
V. Parthasaradi, A. Karunamurthy, C. H. Hussaian Basha, S. Senthilkumar
International Transactions on Electrical Energy Systems, 2024
A study on Efficiency of Bio Medical Data Extraction from PubMed Dataset using Elastic Search Engine
S. Subashree, P. Mahalakshmi, G. Pushpa, S. Senthilkumar, E. Saranya
2nd International Conference on Self Sustainable Artificial Intelligence Systems Icssas 2024 Proceedings, 2024
A Efficient Approach of Image Stegnorgrapy Using Advanced Encryption System and Deep Neural Network
S. Jim Hawkinson, A. Sundar Raj, S. Senthilkumar, R. Muthaiyan, K. Balasubramaniyan, M. Chinnadurai
3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics Icdcece 2024, 2024
Design and Implementation of Frame Work for Building Extraction using Fast Accurate Bilateral Filter, Fast Corner Method and Improved Gaussian Blur
D. Devarajan, R. Rajalakshmi, P. Sivakumar, S. Senthilkumar, M. Malathi, L. Ramachandran
2nd International Conference on Self Sustainable Artificial Intelligence Systems Icssas 2024 Proceedings, 2024
Detection System of Whaling Attack using Deep Learning Techniques
J. Vanitha, C. Mallika, A. Hema, K. Parkavi, K.K. Shandhosh Shree, S. Senthilkumar
2nd International Conference on Self Sustainable Artificial Intelligence Systems Icssas 2024 Proceedings, 2024
Self-charging Electric Vehicle by Using Dynamo, and Accident Detection System
S. Sri Abirami, M. Kavitha, S. Senthilkumar, G. Sundaravadivel, G. Karthikeyan, T. Siva Kumar
Proceedings of the 2024 3rd Edition of IEEE Delhi Section Flagship Conference Delcon 2024, 2024
An Advanced Rice Plant Disease Classification Through a Modified Efficient Net Deep Learning Model
M. Kavitha, Ch Hussaian Basha, V. Prashanth, S. Senthilkumar, V. Mohan, P. Arunkumar
2nd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2024, 2024
Data Security in Cloud Computing using Maritime Search and Rescue Algorithm
L. Anbazhagan, Ch Hussaian Basha, V Prashanth, S. Senthilkumar, M. Kavitha, T. Senthil Kumar
2nd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2024, 2024
Multi-Dialect Speech Recognition Using Transfer Learning and Transformer-Based Architectures: A Comprehensive Approach to Accurate and Efficient Dialect Identification
Malathi M., Senthilkumar S., C. H. Hussaian Basha, Sundaravadivel G., Kavitha M., Arunkumar P.
Renewable Energy Technologies and Modern Communications Systems Future and Challenges Conference Retmcs 2024, 2024
Nature-Inspired Moth Flame Optimization Based MPPT Algorithm for Solar PV System
S. Senthilkumar, C. H. Hussaian Basha, Saraswathy Bose, G. Sundaravadivel, M. Malathi, M. Kavitha
5th International Conference on Sustainable Communication Networks and Application Icscna 2024 Proceedings, 2024
Nature-Inspired Dragonfly MPPT Algorithm for Solar PV System
S. Senthilkumar, Gopika B S, S.P. Mangaiyarkarasi, R. Gandhi Raj, M. Nuthal Srinivasan, P.J. Suresh Babu
Renewable Energy Technologies and Modern Communications Systems Future and Challenges Conference Retmcs 2024, 2024
A Hyrbid Optimization based Secured Communication in Wireless Sensor Networks through Blockchain Technology
V. Lakshmi Praba, Ch Hussaian Basha, V Prashanth, S. Senthilkumar, M. Kavitha, L. Anbazhagan
2nd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2024, 2024
Super-Resolution Image using Enhanced Deep Residual Networks and the DIV2K Dataset
S. Senthilkumar, S. Vetriselvi, K. Kalaivani, P. Arunkumar, M. Malathi, S. Praveen Kumar
2nd International Conference on Self Sustainable Artificial Intelligence Systems Icssas 2024 Proceedings, 2024
Quantum Key Distribution-Based Security Framework for Wireless Sensor Networks: Enhancing Resilience Against Classical and Quantum Cyber Threats
S. Senthilkumar, R. Rajaganapathy, K.K. Shandhosh Shree, P. Krishnamoorthy, L. Ramachandran, M. Kavitha
2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
White Spot Syndrome Detection in Shrimp using Neural Network Model
K. Vembarasi, Vishnu Priya Thotakura, S. Senthilkumar, L. Ramachandran, V. Lakshmi Praba, S. Vetriselvi, M. Chinnadurai
Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
Hybrid Solar Paint Based on TiO2/CdS Nanomaterials
Nanotechnology Perceptions, 2024
Solar energy harvesting to optimise the power constraints in 5G systems
N. Chitra Kiran, S. Senthilkumar, G. Satish, Narendra Soni, Amit Ganatra, Essam A. Al-Ammar, Amjad Iqbal
Optical and Quantum Electronics, 2023
Early detection and identification of white spot syndrome in shrimp using an improved deep convolutional neural network
L. Ramachandran, V. Mohan, S. Senthilkumar, J. Ganesh
Journal of Intelligent and Fuzzy Systems, 2023
A Novel and Smart Administrative Door Lock and Open System using Face Recognition
S. Senthilkumar, E. Saranya, M. Kavitha, Anbarasi Selvakumar, S. Rajasri, R. Ramiya
2nd International Conference on Automation Computing and Renewable Systems Icacrs 2023 Proceedings, 2023
Smart Environment and Plant Disease Monitoring with Analysis System in Agricultural Field
M. Kavitha, S. Senthilkumar, K. Kalaivani, E. Saranya, P. Arunkumar, V. Malu
3rd IEEE International Conference on ICT in Business Industry and Government Ictbig 2023, 2023
Optimized Maximum Power Point Tracking Algorithm for Solar Photovoltaic with Dissimilar Environmental Conditions
S. Senthilkumar, M. Kavitha, P. Arunkumar, G. Pushpa, R. Ramanan, L. Anbazhagan
7th International Conference on I Smac Iot in Social Mobile Analytics and Cloud I Smac 2023 Proceedings, 2023
Design of microstrip antenna using high frequency structure simulator for 5G applications at 29 GHz resonant frequency
Senthilkumar Selvaraj, S. Selvaraj
International Journal of Advanced Technology and Engineering Exploration, 2022
RETRACTION:IoT based fault identification in solar photovoltaic systems using an extreme learning machine technique
V. Mohan, S. Senthilkumar
Journal of Intelligent and Fuzzy Systems, 2022
Analysis of Single-Diode PV Model and Optimized MPPT Model for Different Environmental Conditions
S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, M. Karthikeyan
International Transactions on Electrical Energy Systems, 2022
Wireless Bidirectional Power Transfer for E-Vehicle Charging System
S. Senthilkumar, Moazzam Haidari, G. Devi, A. Sagai Francis Britto, Rajasekhar Gorthi, Hemavathi, M. Sivaramkrishnan
International Conference on Edge Computing and Applications Icecaa 2022 Proceedings, 2022
Low delay error correction codes to correct stuck-at defects and soft errors
A. Asuvaran, S. Senthilkumar
2014 International Conference on Advances in Engineering and Technology Icaet 2014, 2014
Semi-analytical solution for soliton propagation in colloidal suspension
International Journal of Engineering and Technology, 2013

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