Suresh Muthusamy

Suresh Muthusamy (also called as received bachelors degree in Electrical and Electronics Engineering, masters degree in Power Electronics and Drives during the year 2009 and 2011 from Anna University, Chennai and Anna University, Coimbatore respectively. He then completed Ph.D. degree in Electrical Engineering from Anna University, Chennai during the year 2023 in the area of hybrid renewable energy systems. He worked as Assistant Professor in the Department of Electrical and Electronics Engineering at Kongu Engineering College (Autonomous), Perundurai, Erode, during the period June 2011 to January 2020. From January 2020 onwards, he has been working as Assistant Professor Senior Grade in the Department of Electronics and Communication Engineering at Kongu Engineering College (Autonomous), Perundurai, Erode. He published more than 110 research articles in well reputed and refereed national/international journals from Elsevier, Springer, Taylor & Francis, Wiley, SAGE publish

EDUCATION

Ph.D. from Anna University, Chennai under the Faculty of Electrical Engineering
M.E. from Anna university, Coimbatore
B.E. from Anna University, Chennai

RESEARCH, TEACHING, or OTHER INTERESTS

Renewable Energy, Sustainability and the Environment, Energy Engineering and Power Technology, Decision Sciences, Multidisciplinary

FUTURE PROJECTS

Scopus Publications

A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance
Krishnamoorthy Natarajan, Suresh Muthusamy, Mizaj Shabil Sha, Kishor Kumar Sadasivuni, Sreejith Sekaran, Christober Asir Rajan Charles Gnanakkan, and Ahmed A.Elngar
Springer Science and Business Media LLC
AbstractA disease is a distinct abnormal state that significantly affects the functioning of all or part of an individual and is not caused by external harm. Diseases are frequently understood as medical conditions connected with distinct indications and symptoms. According to a fairly wide categorization, diseases can also be categorized as mental disorders, deficient diseases, genetic diseases, degenerative diseases, self-inflicted diseases, infectious diseases, non-infectious diseases, social diseases, and physical diseases. Prevention of the diseases is of multiple instances. Primary prevention seeks to prevent illness or harm before it ever happens. Secondary prevention tries to lessen the effect of an illness or damage that has already happened. This is done through diagnosing and treating illness or injury as soon as feasible to stop or delay its course, supporting personal ways to avoid recurrence or reinjury, and implementing programs to restore individuals to their previous health and function to prevent long-term difficulties. Tertiary prevention tries to lessen the impact of a continuing sickness or injury that has enduring repercussions. Diagnosis of the disease at an earlier stage is important for the treatment of the disease. Hence, in this study, deep learning algorithms, such as VGG16, EfficientNetB4, and ResNet, are utilized to diagnose various diseases, such as Alzheimer's, brain tumors, skin diseases, and lung diseases. Chest X-rays, MRI scans, CT scans, and skin lesions are used to diagnose the mentioned diseases. Transfer learning algorithms, such as VGG16, VGG19, ResNet, InceptionV3, and EfficientNetB4, are utilized to categorize various diseases. EfficientNetB4 with the learning rate annealing, having obtained an accuracy of 94.04% on the test dataset, is observed. As a consequence, we observed that every network has unique particular skills on the multi-disease dataset, which includes chest X-rays, MRI scans, etc.,


Techno-economic feasibility analysis of an on-grid IOT-based rooftop solar photovoltaic system for prosumers with a real-time implementation: a detailed case study and analysis using HOMER software
Nishanthy Jayasankar, Charles Raja Sathia Samuel, Venkatesh Paramasivam, Arockia Edwin Xavier Santiago, Suresh Muthusamy, and Surya Kavitha Tirugatla
Springer Science and Business Media LLC



A new method for improving the solar photovoltaic unit efficiency through neem oil as coolant medium for high power applications—an experimental investigation
Karthikeyan Ganesan, Satheeshkumar Palanisamy, Suresh Muthusamy, Prabha Maheswari Muthusamy, Ponarun Ramamoorthi, Ranjith Kumar Ravi, Mizaj Shabil Sha, and Kishor Kumar Sadasivuni
Springer Science and Business Media LLC
AbstractThe utilization of electric energy is rising in the technological world. Solar PV (photovoltaic) cells convert sunlight into electricity, and sunlight radiation also has heat, reducing the panel's efficiency. The heat should control the limited value or otherwise reduce the panel's performance so that heat is moved to the cooling medium, thus maintaining the heat within the functioning limit. The proposed method is explained by the probability of cooling the monocrystalline and polycrystalline structures used as neem oil through an integrated oil container fitted into the unit's backside—the neem oil acts as phase-changing material (PCM). The solar PV rear side neem oil absorbs the heat of the solar PV panel. The neem oil is not filled in the backside tank completely for the reason that the oil needed some breathing gap. The breathing gap of PCM is to enhance the heat-withstand efficiency. The backside neem oil is replaced every 30 min. As an outcome, the front side of solar PV heat is reduced. Neem oil has not polluted the environment and is thus also used to exchange noxious mineral oils. The neem oil moved from the depository tank to the backside of the unit and together into an additional depositor tank, thus being able to be reused. The proposed method is investigated, and functioning comparison occurs in different PV types, such as monocrystalline and polycrystalline modules, with various kinds of edible oil. Thus, the critical outcomes of the monocrystalline and polycrystalline PV panels are to decrease the panel temperature by 2.29% and 4.34%, respectively, and enhance the efficiency of the PV panels by 15.0% and 17.8%, respectively.


An extensive review of preparation, stabilization, and application of single and hybrid nanofluids
Pritam Kumar Das, Apurba Kumar Santra, Ranjan Ganguly, Santosh Kumar Dash, Suresh Muthusamy, MizajShabil Sha, and Kishor Kumar Sadasivuni
Springer Science and Business Media LLC
AbstractThe researchers attract nanofluids due to their improved thermal and physical properties compared to the base fluid. The colloidal mixture of nanometre-sized particles with conventional fluid is known as nanofluids. Compared with single nanofluids, hybrid nanofluids show better enhancement in thermophysical properties. Combining nanoparticles into the host fluid is called a hybrid nanofluid. The preparation of nanofluid needs more importance. However, the physiochemical properties of the nanofluid mainly depend on the stability of the nanofluid. The article aims to provide detailed information about preparing different types of single and hybrid nanofluids dispersed in various base fluids, preparation techniques, stabilization processes, applications and challenges. Different types of surfactants and characterization methods are suggested to improve the stability of the prepared solution. It was observed that all types of nanoparticles and hybrid nanoparticles could be synthesized with different base fluids with the help of the sonication process, particle-to-surfactant ratio, magnetic stirrer and many more. The two-step method is mostly preferred by the researchers compared to the single-step method to prepare the nanofluid. Application of single and hybrid nanofluids has been highlighted in different areas; few challenges have also been identified and must be checked before implementation in the industry.


Optimal selection and design of grid-connected hybrid renewable energy system in three selected communities of Rivers State
Chidozie Ezekwem, Suresh Muthusamy, and Peace Chiamaka Ezekwem
Elsevier BV



An Extensive Review on Emerging Advancements in Thermography and Convolutional Neural Networks for Breast Cancer Detection
Jayagayathri Iyadurai, Mythili Chandrasekharan, Suresh Muthusamy, and Hitesh Panchal
Springer Science and Business Media LLC



A Novel Method for Design and Implementation of Systolic Associative Cascaded Variable Leaky Least Mean Square Adaptive Filter for Denoising of ECG Signals
Chitra Manickam, Murugesan Govindasamy, Suresh Muthusamy, and Muneeshwari Paramasivam
Springer Science and Business Media LLC



An event triggered control scheme for enhanced production of Escherichia coli and biomass concentration during fed-batch cultivation
Chitra Murugan, Sutha Subbian, Saravanan Kaliyaperumal, Kishor Kumar Sadasivuni, Md Irfanul Haque Siddiqui, Suresh Muthusamy, Marc A. Rosen, Chander Prakash, and Choon Kit Chan
Elsevier BV



A Novel Method for Illegal Driver Detection and Legal Driver Identification Using Multitask Learning Based LSTM Models for Real Time Applications
Mathankumar Manoharan, Karthik Muthukrishnan, Gunapriya Balan, Singaravelan Arumugam, Suresh Muthusamy, Meenakumari Ramachandran, Arun Balodi, V. Kumar Chinnaiyan, Sreejith Sekaran, and Christober Asir Rajan Charles Gnanakkan
Springer Science and Business Media LLC



An Experimental Analysis of Precipitated Silica in Petroleum-Contaminated Clay for the Strengthening of Soil Characteristics
Ponnusamy Kulanthaivel, Ammapalyam Ramasamy Krishnaraja, Suresh Muthusamy, Om Prava Mishra, Mizaj Shabil Sha, and Kishor Kumar Sadasivuni
Springer Science and Business Media LLC
AbstractIn recent times, the environmental impacts of petroleum-contaminated clay (PC clay) have intensified, leading to more severe detrimental effects. To address this issue, the use of precipitated silica (P silica) has proven to be an effective solution. P silica offers improved treatment for the contaminated clay and enhances the engineering properties of the soil. A series of experiments such as pH test, electrical conductivity test, unconfined compressive strength (UCS) test, California bearing ratio (CBR) test, free swell index (FSI) test, compaction test and Atterberg limit tests were conducted to compare the soil characteristics of the PC clay with and without the treatment of P silica. The PC clay soil specimens were tested after the inclusion of P silica with varying dosages of 0%, 3%, 6%, 9% and 12% by dry weight of clay soil. The inclusion of P silica at a dosage of 6% resulted in the optimum strength of 275.12 kPa. This dosage also led to a reduction in free swell index (FSI) and maximum dry density (MDD), indicating a flocculation mechanism caused by the presence of P silica. Additionally, there was an improvement in stiffness and strength parameters, as evidenced by the enhancement in CBR (California bearing ratio). Therefore, the effective utilization of P silica in contaminated clay soil provides a variety of applications in the geotechnical field.


Adaptive cruise control system with fractional order ANFIS PD+I controller: optimization and validation
Prabhakar Gunasekaran, Rajaram Sivasubramanian, Karuppasamy Periyasamy, Suresh Muthusamy, Om Prava Mishra, Ponarun Ramamoorthi, Kishor Kumar Sadasivuni, and Mithra Geetha
Springer Science and Business Media LLC
AbstractDesigning the control structures of fractional order PID controllers has proven to be effective in providing adaptability in set point tracing the performance of a nonlinear cruise control system. Wheel rolling resistance, wind drag force, and road gradient are incorporated into the design to better describe the system under consideration and to show how the nonlinear cruise control system behaves. This study presents a comparative investigation using simulation between control structures such as fractional order proportional–integral–derivative, fractional order integral minus proportional derivative, and fractional order proportional integral minus derivative. By preserving integral error indices as the goal function, a genetic algorithm is used to improve the controller gain parameters and fractional scaling values. To prevent integral windup conflicts and derivative boost issues, both traditional fractional order structures and adaptive neuro-fuzzy-based fractional order structures were used to create the adaptive cruise control system. The FO ANFIS PD plus I controller for the cruise control system exceeds the competition in servo and regulatory difficulties.


A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications
Naveen Sundar Gnanadesigan, Grace Angela Abraham Lincoln, Narmadha Dhanasegar, Suresh Muthusamy, Deeba Kannan, Surendiran Balasubramanian, Nebojsa Bacanin, and Kishor Kumar Sadasivuni
Springer Science and Business Media LLC



Investigation of viscoelastic behavior of Abaca-reinforced epoxy composites
Mohan Kumar Anand Raj, Rajasekar Rathanasamy, Parameshwaran Rathinasamy, Suresh Muthusamy, Md Irfanul Haque Siddiqui, Natrayan L, Jayant Giri, and Mohd Asif Shah
AIP Publishing
Natural fiber-based composites demonstrate excellent and comparable static and dynamic mechanical properties to conventional materials, such as steel and aluminum. They also extend their applications to aeronautical, sports equipment, and marine fields. This experimental study aims to find the effect of untreated and treated Abaca-reinforced epoxy composites on the viscoelastic behavior and the optimum combinations of fiber and resin to produce better bonding efficiency. The different specimens used for this study were pure epoxy, untreated, and chemically treated composite specimens. The four weight percentages of Abaca fibers are 10%, 20%, 30%, and 40% used to prepare composite specimens. Similarly, four different sodium hydroxide (NaOH) concentrations, 4, 6, 8, and 10 wt. %/vol. %, have been used for the chemical treatment of fibers. The storage modulus of Abaca-reinforced epoxy composite specimen has been investigated with respect to temperature and fiber content. The result shows that the 30% weight fraction of fibers with chemically (8 wt. %/vol. %) treated fiber-reinforced epoxy specimen produces 41.67% higher storage modulus than the 10% weight fraction of fibers content of composite specimens. Fourier-Transform Infrared Spectroscopy (FTIR) broad transmittance has been used to distinguish the raw and chemically treated fibers. FTIR results reveal the removal of functional groups after NaOH treatment.


A novel Adaptive Neural Network-Based Laplacian of Gaussian (AnLoG) classification algorithm for detecting diabetic retinopathy with colour retinal fundus images
Manjula Devi Ramasamy, Keerthika Periasamy, Suresh Periasamy, Suresh Muthusamy, Ponarun Ramamoorthi, Gunasekaran Thangavel, Sreejith Sekaran, Kishor Kumar Sadasivuni, and Mithra Geetha
Springer Science and Business Media LLC



A Novel Design and Development of Multilevel Inverters for Parallel Operated PMSG-Based Standalone Wind Energy Conversion Systems
Anbarasan Palani, Venmathi Mahendran, Krishnakumar Vengadakrishnan, Suresh Muthusamy, Om Prava Mishra, Ponarun Ramamoorthi, Muni Raj Maurya, and Kishor Kumar Sadasivuni
Springer Science and Business Media LLC
AbstractThe article presents the new power conversion for parallel-operated wind energy conversion systems. It has been formulated by new multilevel inverter (MLI) topologies with reduced switch counts, lowered conduction losses and a very good output voltage spectrum. The wind energy conversion systems included permanent magnet synchronous generator (PMSG), a diode bridge rectifier, a conventional boost converter and a novel multilevel inverter connected to an isolated load. The power conversion utilizing a novel multilevel DC to AC converter has been proven for its better efficiency, voltage utilization and power quality. The integration of wind energy conversion systems has been explored in MATLAB Simulink, and the hardware setup does the authentication of the MLI structure.


A Novel Approach Using Transfer Learning Architectural Models Based Deep Learning Techniques for Identification and Classification of Malignant Skin Cancer
Balambigai Subramanian, Suresh Muthusamy, Kokilavani Thangaraj, Hitesh Panchal, Elavarasi Kasirajan, Abarna Marimuthu, and Abinaya Ravi
Springer Science and Business Media LLC



An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
K. Mukilan, C. Rameshbabu, B. Baranitharan, Suresh Muthusamy, Ponarun Ramamoorthi, Kishor Kumar Sadasivuni, Kamil Oflaz, and Anish Khan
Springer Science and Business Media LLC
AbstractThe Engineering Procurement Construction (EPC) contract systems are widely employed in the construction industry. Among the prevalent issues in this sector, cash flow problems frequently lead to decreased productivity and efficiency. To address these challenges, a claim management system is developed based on the Improved Monarch Butterfly Optimization Algorithm (IMBOA) and the principles of EPC. Conventional construction models typically optimize only a single objective, such as time, cost, or delay, which may not effectively enhance overall performance. This study aims to develop a claim management system based on IMBOA and EPC principles to optimize multiple objectives, focusing on minimizing project costs and time delays while ensuring high-quality results. The basic methodology of this research involves integrating EPC and claim management principles with the IMBOA algorithm to create an efficient, high-quality system. This process starts with a comprehensive literature review on EPC, claims, MBOA, and related algorithms. Common disputes and claims in the construction industry are examined, and critical factors influencing these claims are identified. The Monarch Butterfly Optimization Algorithm (MBOA) and its improved version (IMBOA) are explored for their application in optimizing project performance. A case study in China's coal mining industry evaluates the effectiveness of the EPC approach, demonstrating that it minimizes time delays and costs. The IMBOA approach proposed in this study has the potential to mitigate 23% of risks and avoid 32% of risks associated with the action plan of China's coal mining industry. Furthermore, comparative analysis with other optimization models indicates that the developed IMBOA model yields superior results, reducing overall project time by 15% and cost by 18%.


ANN-optimized NR-SHE method for single-sourced, multi-configurable switched capacitor-based multilevel inverter for sustainable power applications
Anand Kumar Thangapandi, Umamaheswari Krishnasamy, Suresh Muthusamy, Kishor Kumar Sadasivuni, Meenakumari Ramachandran, Surendar Vadivel, Nebojsa Bacanin, and Ahmed A. Elngar
Springer Science and Business Media LLC



A Novel Proportional Integral Derivative (PID) Controller-Based Control Strategy for a Formula Student Vehicle
Geetha Anbazhagan, Santhakumar Jayakumar, Usha Sengamalai, Suresh Muthusamy, Mohit Bajaj, Sadhna Sudershana, Deepti Mishra, and Rabindra K. Barik
Springer Nature Singapore



A Novel Method for Implementing the IoT-Based Hybrid Energy System with Pollution Monitoring and Control in Coastal Roadways
R. Jai Ganesh, P. Sabarish, Natarajan Sirukarumbur Pandurangan, Suresh Muthusamy, Mohit Bajaj, Nachiketa Tarasia, M. Kandpal, and Rabindra K. Barik
Springer Nature Singapore



Economic assessment of efficient hydrogen production-based hybrid renewable energy system: OOA-RBFNN approach
Suresh Muthusamy, R. Suresh Kumar, N. Karthikeyan, and P. Rajesh
Springer Science and Business Media LLC



Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting
Milos Dobrojevic, Luka Jovanovic, Lepa Babic, Miroslav Cajic, Tamara Zivkovic, Miodrag Zivkovic, Suresh Muthusamy, Milos Antonijevic, and Nebojsa Bacanin
Tech Science Press
Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smart-phones, computers, or tablets. It can occur through various channels, such as social media, text messages, online forums


Ecological risk assessment of microplastic contamination in the Adyar River, Chennai: Distribution and source identification
J. Mohamed Afzal, P. Sanju, P. Saravanan, S. Muthusamy, and S. Selvam
Elsevier



A novel method for bioinformatics analysis in gene expression profiling framework for personalized healthcare applications
Kumareshan Natarajan, Prakash Natarajan, Suresh Muthusamy, and Ranjith Kumar Ravi
Springer Science and Business Media LLC



Thermal comfort inside a gable-roofed metallic shed in a higher educational institution: a case study and detailed analysis
Abubakkar Abdul Jaffar, Selvakumar Pandiaraj, Kumaresan Govindasamy, Kamal Sharma, Suresh Muthusamy, Mohammad Irfanul Haque Siddiqui, Erdem Cuce, and Mohd Asif Shah
Oxford University Press (OUP)
Abstract Central workshop is an integral part of any higher education institution, and it will be generally operated in a gable-roofed metallic shed. The users of the building are affected physiologically and psychologically due to the thermal discomfort conditions caused by improper ventilation. It is necessary to study the cause for discomfort and propose cost and effective methods to mitigate the problem. In this work, the thermal comfort inside a gable-roofed workshop was analyzed, and it was found that the discomfort was predominant from 2 PM to 5 PM. It was predicted that the conduction heat transfer could be reduced upto 55% with the help of passive cooling technique carried out using aluminium bubble wrap. During the life cycle cost study, the aluminium bubble wrap technique was found to be more economical over high-volume low-speed fan. The computer simulation aided in the prediction of overall heat transfer coefficient and conduction heat transfer through wall. The results from numerical study deviated by less than 0.1% when compared with that from the theoretical model.

RECENT SCHOLAR PUBLICATIONS

An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
K Mukilan, C Rameshbabu, B Baranitharan, S Muthusamy, ...
Neural Computing and Applications 37 (1), 169-184 2025



A novel mathematical approach for modeling the dielectric response surface of the transformer oil to predict the optimized functions of transformers in high-power applications
S Duraisamy, SK Thirumalaisamy, S Muthusamy, RA Raj, S Ponnusamy, ...
Electrical Engineering 107 (2), 1493-1508 2025



A novel method for fault detection and diagnosis in DFIG coupled grid connected wind energy systems using spiking deep residual network
D Stallon Samuel Raj, N Rajkumar Manokaran, S Muthusamy, K Jeyaraj, ...
Wind Engineering, 0309524X241307315 2024



ANN-optimized NR-SHE method for single-sourced, multi-configurable switched capacitor-based multilevel inverter for sustainable power applications
AK Thangapandi, U Krishnasamy, S Muthusamy, KK Sadasivuni, ...
Electrical Engineering, 1-19 2024



Correction to: Thermal comfort inside a gable-roofed metallic shed in a higher educational institution: a case study and detailed analysis
AA Jaffar, S Pandiaraj, K Govindasamy, K Sharma, S Muthusamy, ...
INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES 19, 2461-2461 2024



Economic assessment of efficient hydrogen production-based hybrid renewable energy system: OOA-RBFNN approach
S Muthusamy, RS Kumar, N Karthikeyan, P Rajesh
Electrical Engineering, 1-12 2024



Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting.
M Dobrojevic, L Jovanovic, L Babic, M Cajic, T Zivkovic, M Zivkovic, ...
Computers, Materials & Continua 80 (3) 2024



Optimal selection and design of grid-connected hybrid renewable energy system in three selected communities of Rivers State
C Ezekwem, S Muthusamy, PC Ezekwem
Scientific African 25, e02305 2024



A novel method for bioinformatics analysis in gene expression profiling framework for personalized healthcare applications
K Natarajan, P Natarajan, S Muthusamy, RK Ravi
Multimedia Tools and Applications, 1-33 2024



An extensive review of preparation, stabilization, and application of single and hybrid nanofluids
PK Das, AK Santra, R Ganguly, SK Dash, S Muthusamy, MS Sha, ...
Journal of Thermal Analysis and Calorimetry 149 (17), 9523-9557 2024



A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance
K Natarajan, S Muthusamy, MS Sha, KK Sadasivuni, S Sekaran, ...
Neural Computing and Applications 36 (30), 18979-18997 2024



A novel method for design and implementation of systolic associative cascaded variable leaky least mean square adaptive filter for denoising of ECG signals
C Manickam, M Govindasamy, S Muthusamy, M Paramasivam
Wireless Personal Communications 137 (2), 1029-1043 2024



An Extensive Review on Emerging Advancements in Thermography and Convolutional Neural Networks for Breast Cancer Detection
J Iyadurai, M Chandrasekharan, S Muthusamy, H Panchal
Wireless Personal Communications 137 (3), 1797-1821 2024



Thermal comfort inside a gable-roofed metallic shed in a higher educational institution: a case study and detailed analysis
AA Jaffar, S Pandiaraj, K Govindasamy, K Sharma, S Muthusamy, ...
International Journal of Low-Carbon Technologies 19 (1), 1660-1673 2024



A Novel Method for Illegal Driver Detection and Legal Driver Identification Using Multitask Learning Based LSTM Models for Real Time Applications
M Manoharan, K Muthukrishnan, G Balan, S Arumugam, S Muthusamy, ...
Wireless Personal Communications 136 (3), 1923-1944 2024



An Experimental Analysis of Precipitated Silica in Petroleum-Contaminated Clay for the Strengthening of Soil Characteristics
P Kulanthaivel, AR Krishnaraja, S Muthusamy, OP Mishra, MS Sha, ...
Iranian Journal of Science and Technology, Transactions of Civil Engineering 2024



An event triggered control scheme for enhanced production of Escherichia coli and biomass concentration during fed-batch cultivation
C Murugan, S Subbian, S Kaliyaperumal, KK Sadasivuni, MIH Siddiqui, ...
Heliyon 10 (12), 1-12 2024



Techno-economic feasibility analysis of an on-grid IOT-based rooftop solar photovoltaic system for prosumers with a real-time implementation: a detailed case study and analysis
N Jayasankar, CR Sathia Samuel, V Paramasivam, AEX Santiago, ...
Electrical Engineering 106 (5), 6615-6635 2024



A New Method for Detecting the Fatigue Using Automated Deep Learning Techniques for Medical Imaging Applications
NS Gnanadesigan, GAA Lincoln, N Dhanasegar, S Muthusamy, ...
Wireless Personal Communications 135 (2), 1009-1034 2024



A Novel Approach Using Transfer Learning Architectural Models Based Deep Learning Techniques for Identification and Classification of Malignant Skin Cancer
B Subramanian, S Muthusamy, K Thangaraj, H Panchal, E Kasirajan, ...
Wireless Personal Communications 134 (4), 2183-2201 2024

MOST CITED SCHOLAR PUBLICATIONS

Maximization of biodiesel production from sunflower and soybean oils and prediction of diesel engine performance and emission characteristics through response surface methodology
M Elkelawy, HAE Bastawissi, KK Esmaeil, AM Radwan, H Panchal, ...
Fuel 266, 117072 2020
Citations: 237



An efficient LoRa-based smart agriculture management and monitoring system using wireless sensor networks
SJ Suji Prasad, M Thangatamilan, M Suresh, H Panchal, CA Rajan, ...
International Journal of Ambient Energy 43 (1), 5447-5450 2022
Citations: 149



Prediction of strength and analysis in self-compacting concrete using machine learning based regression techniques
SA Rajakarunakaran, AR Lourdu, S Muthusamy, H Panchal, AJ Alrubaie, ...
Advances in Engineering Software 173, 103267 2022
Citations: 96



Effect of fin configuration parameters on performance of solar still: a review
D Mevada, H Panchal, K kumar Sadasivuni, M Israr, M Suresh, ...
Groundwater for Sustainable Development 10, 100289 2020
Citations: 94



Biodegradable magnesium metal matrix composites for biomedical implants: synthesis, mechanical performance, and corrosion behavior–a review
R Krishnan, S Pandiaraj, S Muthusamy, H Panchal, MS Alsoufi, ...
Journal of Materials Research and Technology 20, 650-670 2022
Citations: 89



A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications
ND Kathamuthu, S Subramaniam, QH Le, S Muthusamy, H Panchal, ...
Advances in Engineering Software 175, 103317 2023
Citations: 88



Performance analysis of evacuated tubes coupled solar still with double basin solar still and solid fins
H Panchal, K Kumar Sadasivuni, M Suresh, S Yadav, S Brahmbhatt
International Journal of Ambient Energy 41 (9), 1031-1037 2020
Citations: 86



A case study on thermo-hydraulic performance of jet plate solar air heater using response surface methodology
MM Matheswaran, TV Arjunan, S Muthusamy, L Natrayan, H Panchal, ...
Case Studies in Thermal Engineering 34, 101983 2022
Citations: 85



Use of solar photovoltaic with active solar still to improve distillate output: a review
K Pansal, B Ramani, K kumar Sadasivuni, H Panchal, M Manokar, ...
Groundwater for Sustainable Development 10, 100341 2020
Citations: 76



An extensive analysis of mechanical, thermal and physical properties of jute fiber composites with different fiber orientations
G Rangasamy, S Mani, SKS Kolandavelu, MS Alsoufi, AMM Ibrahim, ...
Case Studies in Thermal Engineering 28, 101612 2021
Citations: 74



A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms
R Rajamoorthy, G Arunachalam, P Kasinathan, R Devendiran, P Ahmadi, ...
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 44 2022
Citations: 71



A review of artificial intelligence-based optimization techniques for the sizing of integrated renewable energy systems in smart cities
AB Kanase-Patil, AP Kaldate, SD Lokhande, H Panchal, M Suresh, ...
Environmental technology reviews 9 (1), 111-136 2020
Citations: 68



An extensive review of performance enhancement techniques for pyramid solar still for solar thermal applications
G Angappan, S Pandiaraj, H Panchal, T Kathiresan, D Ather, C Dutta, ...
Desalination 532, 115692 2022
Citations: 66



An improved genetic algorithm-based optimal sizing of solar photovoltaic/wind turbine generator/diesel generator/battery connected hybrid energy systems for standalone applications
M Suresh, R Meenakumari
International Journal of Ambient Energy 42 (10), 1136-1143 2021
Citations: 65



Investigation of mechanical properties of dual-fiber reinforcement in polymer composite
MKA Raj, S Muthusamy, H Panchal, AMM Ibrahim, MS Alsoufi, ...
journal of materials research and technology 18, 3908-3915 2022
Citations: 63



Feature selection by hybrid brain storm optimization algorithm for covid-19 classification
T Bezdan, M Zivkovic, N Bacanin, A Chhabra, M Suresh
Journal of Computational Biology 29 (6), 515-529 2022
Citations: 62



Productivity enhancement of solar still with thermoelectric modules from groundwater to produce potable water: a review
H Panchal, KK Sadasivuni, C Prajapati, M Khalid, FA Essa, S Shanmugan, ...
Groundwater for Sustainable Development 11, 100429 2020
Citations: 56



Modelling and performance analysis of electric vehicle
B Sharmila, K Srinivasan, D Devasena, M Suresh, H Panchal, ...
International Journal of Ambient Energy 43 (1), 5034-5040 2022
Citations: 49



An enhanced multiobjective particle swarm optimisation algorithm for optimum utilisation of hybrid renewable energy systems
M Suresh, R Meenakumari, H Panchal, V Priya, ES El Agouz, M Israr
International Journal of Ambient Energy 43 (1), 2540-2548 2022
Citations: 48



A comparative energy and exergy efficiency study of hemispherical and single-slope solar stills
MEH Attia, AE Kabeel, A Bellila, AM Manokar, R Sathyamurthy, Z Driss, ...
Environmental Science and Pollution Research 28, 35649-35659 2021
Citations: 47