Ramkumar Vahalingam

@veltech.edu.in

Assistant Professor and CSE
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

Ramkumar Vahalingam


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https://researchid.co/ramkumarv

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Networks and Communications, Artificial Intelligence, Computer Science Applications, Computer Graphics and Computer-Aided Design
16

Scopus Publications

109

Scholar Citations

4

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • High flexibility transparent optical networks based on wavelength conversion line selection through multi light paths
    S. Kanniammal, Manimaran Arjunan, R. Thandaiah Prabu, S. B. Mohan, V. Ramkumar, A. Immanuvel, Benisha Maria Xavier, Shaik Hasane Ahammad, Ahmed Nabih Zaki Rashed
    Journal of Optics India, 2025
  • Cost-effective surgical innovations for low-resource settings: Advancing healthcare in underdeveloped regions
    Jeyanthi Palanivelu, Ramkumar Vahalingam, Hitesh Chopra, Tabarak Malik
    International Journal of Surgery Open, 2025
    Surgical innovations that are low-cost and sophisticated are essential for improving patient outcomes and expanding access to potentially life-saving procedures in low-resource areas where sophisticated medical infrastructures and technology are unattainable[1]. Low-resource environments present distinct obstacles, necessitating the creation and implementation of suitable, accessible, durable, and scalable surgical instruments and methodologies tailored to these specific healthcare issues. Progress has been made in the use of minimally invasive surgical procedures, including cost-effective alternatives to the pricey equipment often necessary for laparoscopic and robotic operations[2]. Laparoscopic procedures, formerly reliant on expensive vision systems and advanced tools, have become more affordable due to the development of hand-operated, low-cost alternatives that exhibit comparable efficacy to their pricier counterparts[3]. Cost-effective laparoscopic toolkits, designed for sterilization and reuse, are being used in underfunded hospitals to enable surgeons to do less invasive surgeries, resulting in reduced postoperative complications and shorter recovery times[4]. Additionally, solar-powered surgical lighting and sterilizing machines are being created to remain operational despite inconsistent electrical sources in various regions[5]. Another notable advancement pertains to anesthetic administration. Safe anesthesia is the thing that determines surgical results, yet in the majority of low-resource situations, anesthesia devices are costly, sophisticated, and prone to power outages[6]. Simplification, mobility, and oxygen-saving anesthetic equipment might overcome this issue. Universal Anesthesia Machine, for example, is particularly developed for locations where dependable energy and medicinal gases would be uncommon[7]. This gadget can function on room air, needing no energy or pressurized oxygen, and it is consequently of tremendous utility in distant settings. Other options include suture-free wound closure solutions like cyanoacrylate adhesives or low-cost stapling devices. The approaches do not need substantial training, save surgical time, and minimize infection risk, especially in locations where sterilizing facilities are restricted compared to conventional suturing methods[8]. These treatments are also less expensive and promote faster wound healing, resulting in shorter hospital stays. Aside from technological advancements, these mHealth platforms for surgical care have created new opportunities for integrated consulting. Using these tools, surgeons in remote locations may seek face-to-face consultation with experts in real-time while directing certain surgeries or monitoring postoperative care. Such platforms may also be used to improve the ability of different healthcare personnel in local settings by providing video lessons and interactive modules on fundamental surgical techniques–an effective method for expanding the local surgical workforce[9]. The increased use of AI/ML in mHealth systems has significantly simplified the procedure, since remote diagnostics, surgery planning, and patient monitoring can now be performed without the need for expensive high-tech infrastructure[10]. Innovation in sterilizing methods is critical in locations with limited access to clean water and energy. Low-cost, portable sterilizers that use solar electricity or chemical sterilization are increasingly being used to assure the safety of surgical equipment by reducing infections and difficulties after surgery. These sterilizers, which may be used in the field or tiny clinics, have significantly improved the safety of procedures performed in resource-limited settings[11]. In addition, training and education improve surgical results in underprivileged healthcare systems. Traditional surgical simulation tools were expensive and technologically complex, but new technologies are being developed that are simpler and hence less expensive. This allows local surgeons to do complex treatments without the need for costly equipment, ensuring that they have the skills required to provide safe care[12]. The primary focus is on low-resource innovations with simplicity, durability, and scalability at the heart. More economical and simple-to-maintain devices designed for these contexts might help healthcare practitioners minimize mortality and enhance surgical results. Further advancement and distribution of innovation will close the surgical care gap in poor nations and enhance global health equality.
  • Optimizing Smart Irrigation in Agriculture with a Fuzzy Logic and Genetic Algorithm Hybrid Model for Water Resource Management
    Akana Chandra Mouli Venkata Srinivas, C.L. Monica, Uppara Manjulamma, Bhimanand Pandurang Gajbhare, Ramkumar Vahalingam, Gourav Kalra
    2025 5th International Conference on Intelligent Technologies Conit 2025, 2025
    Smart irrigation is crucial for managing agricultural water resources in the face of climate change and extreme weather events. Efficient management is crucial in light of the water scarcity. Food safety and long-term agricultural development are both enhanced by smart farming systems that combine adaptive and mitigation techniques. Water conservation is aided by wireless networks, which increase irrigation efficiency. Included in the proposed system are operations for preprocessing data, selecting features, and training models. Normalization, standardization, imputation of missing data, and outlier elimination are all part of data preparation. Boruta feature selection keeps only the most crucial elements by eliminating the rest. The GAFLC model can forecast SIS performance using either fuzzy rules for classification or rough sets for feature selection. Fuzzy classification methods are optimized by adaptive evolutionary algorithms. Improving model performance, the AUC is $94.34 \%$, specificity is $97.18 \%$, recall is $98.52 \%$, and accuracy is $96.43 \%$. Based on these findings, pre-emption is clearly the way to go. In order to better manage agricultural resources and conserve water, the GAFLC model employs cutting-edge data processing and machine learning algorithms to enhance irrigation efficiency.
  • A Hybrid Random Forest and Neural Network Model for Enhanced Credit Card Fraud Detection in E-Commerce
    Irfan Abdul Karim Shaikh, Yeddula Bhaskar Reddy, Aruna Shankar, Kusuma Rajasekhar, Jeyaprakash N, Ramkumar Vahalingam
    2025 International Conference on Computing Technologies and Data Communication Icctdc 2025, 2025
    Credit card fraud continues to be a significant issue in e-commerce, resulting in financial losses and security risks. Conventional fraud detection techniques have challenges with imbalanced datasets and the adaptation of fraudulent strategies, requiring a more advanced methodology. This study presents a hybrid model combining Random Forest and Neural Network techniques that use feature selection, deep learning, and tuned hyperparameters to enhance fraud detection efficiency. Experimental findings indicate an accuracy of 99.2 %, precision of 98.8%, recall of 97.5%, and an AUC-ROC score of 99.3 %, greater than individual machine learning models. The method minimizes false positives and improves real-time fraud detection. This strategy provides enhanced generalization, resilience, and efficiency in real deployment compared to earlier methods. Future study may examine adaptive fraud detection techniques utilizing real-time streaming data and reinforcement learning to improve scalability.
  • Enhancing Teachers' Performance in Higher Education Through Human Resource Management Using a Hybrid SVM-Reinforcement Learning Model
    Sushil Kumar, Pratibha V Kashid, Vishakha Abhay Gaidhani, R. Melba Kani, Ramkumar Vahalingam, Manoj S
    2025 5th Asian Conference on Innovation in Technology Asiancon 2025, 2025
    Education can shape a person's character. Quality education is the finest approach to raise moral citizens who combat poverty and improve their community's social and economic conditions. A nation's social and economic progress depends on its education system. Even though there are numerous good schools along thoroughfares, they are still few. Success of educational institutions, especially universities, depends on faculty quality. This research evaluates institutional performance using key performance indicators and data preprocessing methods. The wrapper-based approach FS-ITLBO uses many instructors to discover the best feature subset in the feature space. An SVM model designed for reinforcement learning is used to assess higher education instructors' efficacy using data. The research optimises hyperparameters using reinforcement learning to increase SVM performance. Compared to competing models, the SVMRL has 97.45% simulated accuracy. This shows that the suggested strategy works for evaluating university instructors. The results show that measuring teachers' efficiency requires cutting-edge machine learning methods, particularly feature selection and reinforcement learning. FS-ITLBO and SVMRL models support institutional evaluations and decisions. This HRM-related research proposes a data-driven approach to higher education teacher performance evaluations.
  • Detection of Burst Header Packet Flooding Attacks via Optimization based Deep Learning Framework in Optical Burst Switching Network
    Ramkumar Vahalingam, Bhavani Rajagopal, S. S. Arumugam, Muneeswari Ganesa pandian
    Informacije MIDEM, 2023
    Optical Burst Switching (OBS) technique has the greatest potential for securing future Internet connections. In real-time applications, OBS adoption is motivated by the lack of Quality of Service (QoS) in OBS networks. The accuracy of existing methods for detecting the misbehaving nodes that cause Burst Heading Packet (BHP) flooding attacks is typically poor. To overcome these issues, a novel Elephant Herd Algorithm-based Deep Learning (EHA-DL) network has been proposed for detecting BHP flooding attacks. The proposed approach is divided into three phases: pre-processing, feature selection, and classification. The Elephant Herd Algorithm (EHA) is used to select the most crucial features after pre-processing the raw data to increase the effectiveness of the model. To decrease overfitting and increase detection accuracy, a MobileNet is used to construct the model for the classification phase using the select features of BHPs. The performance of the experimental outcomes was assessed using evaluation metrics like accuracy, specificity, recall, and f-measure. The EHA-DL approach method yielded a 99.27% accuracy rate, which was comparatively high when compared to other approaches. In optical burst switching networks, the method effectively and highly efficiently detects flooding assaults and maintains network stability.
  • Prediction of Temperature in Indian Metropolitan Cities Using Linear Regression and Long Short Term Memory Models
    Sindhu P. Menon, Venkat Ganesh R, Basavaraj M, Tharun A, Ramkumar V
    2023 International Conference on Network Multimedia and Information Technology Nmitcon 2023, 2023
    UHI is the process whereby human activity and urban infrastructure cause urban regions to suffer from warmer temperatures than rural ones. This study explores the use of machine and deep learning models for temperature prediction based on the Urban Heat Island (UHI) phenomenon. The study used historical data on UHI and temperature for a specific urban area. Preprocessing techniques were applied on the data and the model was trained and tested using MLR and LSTM. A comparative analysis of the models performance was done wherein it was observed that MLR outperforms LSTM in prediction of temperature. The MLR model is a classical linear regression model that assumes a linear relationship between temperature and relevant environmental variables such as humidity, pressure, wind speed, and direction. The LSTM model, is an algorithm that uses a recurrent neural network architecture to capture temporal dependencies and long-term patterns in the temperature data. The study also analyzes the feature importance of the environmental variables used in the MLR algorithm and the importance of the time-series data in the LSTM model. The results show that temperature and humidity are the prominent features in the MLR model, while the LSTM algorithm heavily relies on time-series data.
  • An In-Depth Analysis of Electric Vehicle Charging Station Based on LSTM and SVM Hybrid Model
    V. Ramkumar, Akabarsaheb B Nadaf, Manasi Vyankatesh Ghamande, Amar Prakash Dabral, Priti Mangesh Bharambe, Davinder Kumar
    7th International Conference on Electronics Communication and Aerospace Technology Iceca 2023 Proceedings, 2023
    As part of their future smart city ambitions, many countries hope to increase environmental sustainability by electrifying their transportation networks. This means that the percentage of electric vehicles in any particular city's total vehicle population will rise rapidly. Electric vehicle (EV) batteries can be recharged in a number of ways, but charging stations will be given top priority. Charging stations should be dispersed across a city in such a way that all EVs may reach one within a reasonable period of time and then use that charge to travel the entire city. This data preprocessing phase makes use of normalized processing, time interval processing, and outlier processing. The features are derived using principal component analysis. The LSTM method entails a set of four gates (an input, a forget, a learn, and a remember), All of which contribute to the model's training. The models are tested using an LSTM-SVM method. When compared to LSTM and SVM, the proposed method produces higher-quality results.
  • Space cloud in cubesat - Consigning expert system to space
    I. Aravindaguru, D. Arulselvam, N. Kanagavalli, V. Ramkumar, R. Karthick
    Aip Conference Proceedings, 2022
    The world gets incalculably benefitted from Space Technology in terms of Communication, Positioning, Observation, Detection. The advancement of technology and the commencement of very small satellites starting from Microsatellites, Nanosatellites, Picosatellites, Femtosatellites have meant that startle large Multinational companies and emerging countries that could reach space in an accessible way with a short span of time in a position to compete the targeted destination. The most innovative and interesting sector in space is “CubeSat” that are being used in several applications such as Remote Sensing, Earth Observation, Asset Tracking, Security, defence, IoT & Communications, Humanitarian aid, etc., Exploration of the Universe has been one of the fundamental human instincts. Though Space Explorations began with man's quest for knowledge, the technologies that were developed in the process have found applications that are of direct relevance to the development of society. Today Space-based telecommunications, TV Broadcasting, Metrology, Resource Monitoring have become much more pivotal and seminal in everyday life. This demographical statistic proves and shows the reason and their consideration for the rapid accretion towards Minisatellites especially CubeSats. The Collection, Procession, and the distribution of the meaningful data and information, wherein bringing up the Cloud Computing Service allied with Artificial Intelligence in CubeSats.
  • An efficient iot based healthcare data management and transfer using blockchain technology
    P. Veeramani, P. Rajasekar, V. Ramkumar, R. Azhagumurugan, Shaik Althaf Hussain Basha, A. Santham Bharathy
    Aip Conference Proceedings, 2022
    In recent times, technological advancements have resulted in dramatic change in the health sector. The Internet of Things, Cloud Computing, Block chain, lab-on-a-chip, non-invasive and percutaneous operations, and other innovations have made treating a variety of ailments much easier. Both research and the healthcare business have benefited greatly from these emerging innovations. Miniaturized healthcare sensors driven by IoT can be used for clinical tests and self-health tracking. They assist professionals in remote regions who weren't in direct communication with clients with immediate diagnostic and treatment recommendations. Controlling access mechanisms and uneven security policies were a hurdle in meeting the security standards of these data. A blockchain-based intelligent contract and an enterprise-distributed record architecture can be used to track the patient's condition. This permits patients' medical information, and an irreversible and lengthy history log, to be retrieved worldwide at whatever time. The suggested system gives greater monitoring, increased connectivity, and higher data security if compared to standard patient monitoring devices.
  • UTILISATION OF THE DLBM APPROACH FOR EFFECTIVE ROUTING OPTIMISATION IN AN OPTICAL BURST SWITCHING NETWORK ON ECOLOGICAL ENVIRONMENT
    Journal of Environmental Protection and Ecology, 2022
  • Design and Simulation of UWB Antenna with Multiple Notched Bands on the Feed Line
    V. Ramkumar, R. Vijay Ravindran, R. Bhavani, C. Vennila, M. Gunavathi
    Iet Conference Proceedings, 2022
  • An Efficient SAR Image Detection Based on Deep Dense-Mobile net Method
    R. Bhavani, V. Ramkumar, V. Ravindran, R. Sindhuja, K. Swaminathan
    Iet Conference Proceedings, 2022
  • Design and Implementation of PV Powered Air Cooler System Using Thermoelectric Cooler
    Paranthagan B, Vijay Ravindran, M. Marimuthu, Satheesh Ragunathan, Swaminathan K, Ramkumar V
    3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies I Pact 2021, 2021
  • IoT-Based Smart Transformer Monitoring System with Raspberry Pi
    Vijay Ravindran, Ramprakash Ponraj, C. Krishnakumar, Satheesh Ragunathan, V Ramkumar, K Swaminathan
    3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies I Pact 2021, 2021
  • Implementation of business process re-engineering using lean and green strategy in manufacturing industry
    R. Vinayagasundaram, V. Ramkumar, K. Kavi Arasu, S. A. Sriram Anax
    Aip Conference Proceedings, 2020

RECENT SCHOLAR PUBLICATIONS

  • Surgeon’s mental health: an overlooked crisis in the post-pandemic surgical landscape
    G Gulothungan, R Vahalingam, YP Ragini, H Chopra, TB Emran
    International Journal of Surgery Open 64 (2), 153-154 , 2026
    2026
  • Next-gen surgical telementoring: real-time collaboration for safer patient care and smarter training
    S Gulothungan, R Vahalingam, YP Ragini, H Chopra, TB Emran
    International Journal of Surgery Open, 10.1097 , 2025
    2025
  • Enhancing Teachers' Performance in Higher Education Through Human Resource Management Using a Hybrid SVM-Reinforcement Learning Model
    S Kumar, PV Kashid, VA Gaidhani, RM Kani, R Vahalingam
    2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025
    2025
  • A Hybrid Random Forest and Neural Network Model for Enhanced Credit Card Fraud Detection in E-Commerce
    IAK Shaikh, YB Reddy, A Shankar, K Rajasekhar, R Vahalingam
    2025 International Conference on Computing Technologies & Data Communication … , 2025
    2025
  • Optimizing Smart Irrigation in Agriculture with a Fuzzy Logic and Genetic Algorithm Hybrid Model for Water Resource Management
    ACMV Srinivas, CL Monica, U Manjulamma, BP Gajbhare, R Vahalingam, ...
    2025 5th International Conference on Intelligent Technologies (CONIT), 1-6 , 2025
    2025
  • Cost-effective surgical innovations for low-resource settings: advancing healthcare in underdeveloped regions
    J Palanivelu, R Vahalingam, H Chopra, T Malik
    International Journal of Surgery Open 63 (1), 62-63 , 2025
    2025
  • Detection of Burst Header Packet Flooding Attacks via Optimization based Deep Learning Framework in Optical Burst Switching Network
    R Vahalingam, B Rajagopal, S Arumugam
    Informacije MIDEM 53 (3), 167-176 , 2023
    2023
    Citations: 1
  • An In-Depth Analysis of Electric Vehicle Charging Station based on LSTM and SVM Hybrid Model
    DV Ramkumar
    ICECA 2023 , 2023
    2023
    Citations: 4
  • An efficient iot based healthcare data management and transfer using blockchain technology
    P Veeramani, P Rajasekar, V Ramkumar, R Azhagumurugan, SAH Basha, ...
    AIP Conference Proceedings 2518 (1), 030001 , 2022
    2022
    Citations: 3
  • Space cloud in cubesat-Consigning expert system to space
    I Aravindaguru, D Arulselvam, N Kanagavalli, V Ramkumar, R Karthick
    AIP Conference Proceedings 2518 (1), 100001 , 2022
    2022
    Citations: 21
  • OPTICAL BURST SWITCH NETWORK WITH BRIDGED MULTIPLE SUBNETWORKS FOR DEFLECTION REDUCTION AND ENERGY SAVING
    VC Ramkumar V
    NeuroQuantology 20 (6), 4686-4705 , 2022
    2022
  • Design and simulation of UWB antenna with multiple notched bands on the feed line
    V Ramkumar, R Vijay Ravindran, R Bhavani, C Vennila, M Gunavathi
    IET Conference Proceedings CP797 2022 (1), 288-292 , 2022
    2022
  • An efficient SAR image detection based on deep dense-mobile net method
    R Bhavani, V Ramkumar, V Ravindran, R Sindhuja, K Swaminathan
    7th International Conference on Computing in Engineering & Technology (ICCET … , 2022
    2022
    Citations: 9
  • AN IOT BASED SYSTEM TO MONITOR THE WARDS TRAVELLING THROUGH SCHOOL BUSES
    R V
    US Patent INPA 3,797 , 2022
    2022
  • a machine learning based approach to analyze the multi channel queries of E-commerce sites
    R V
    US Patent App. 202,241/005,805 , 2022
    2022
  • Optical Communication Essentials
    R V
    2022
  • Utilisation of the DLBM approach for effective routing optimisation in an optical burst switching network on ecological environment
    V Ramkumar, C Vennila
    JOURNAL OF ENVIRONMENTAL PROTECTION AND ECOLOGY 23 (4), 1653-1662 , 2022
    2022
    Citations: 1
  • Design and implementation of PV powered air cooler system using thermoelectric cooler
    B Paranthagan, V Ravindran, M Marimuthu, S Ragunathan, ...
    2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-6 , 2021
    2021
    Citations: 12
  • IoT-based smart transformer monitoring system with raspberry Pi
    V Ravindran, R Ponraj, C Krishnakumar, S Ragunathan, V Ramkumar, ...
    2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-7 , 2021
    2021
    Citations: 54
  • Implementation of business process re-engineering using lean and green strategy in manufacturing industry
    R Vinayagasundaram, V Ramkumar, KK Arasu, SAS Anax
    AIP Conference Proceedings 2207 (1), 020010 , 2020
    2020
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • IoT-based smart transformer monitoring system with raspberry Pi
    V Ravindran, R Ponraj, C Krishnakumar, S Ragunathan, V Ramkumar, ...
    2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-7 , 2021
    2021
    Citations: 54
  • Space cloud in cubesat-Consigning expert system to space
    I Aravindaguru, D Arulselvam, N Kanagavalli, V Ramkumar, R Karthick
    AIP Conference Proceedings 2518 (1), 100001 , 2022
    2022
    Citations: 21
  • Design and implementation of PV powered air cooler system using thermoelectric cooler
    B Paranthagan, V Ravindran, M Marimuthu, S Ragunathan, ...
    2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-6 , 2021
    2021
    Citations: 12
  • An efficient SAR image detection based on deep dense-mobile net method
    R Bhavani, V Ramkumar, V Ravindran, R Sindhuja, K Swaminathan
    7th International Conference on Computing in Engineering & Technology (ICCET … , 2022
    2022
    Citations: 9
  • An In-Depth Analysis of Electric Vehicle Charging Station based on LSTM and SVM Hybrid Model
    DV Ramkumar
    ICECA 2023 , 2023
    2023
    Citations: 4
  • Implementation of business process re-engineering using lean and green strategy in manufacturing industry
    R Vinayagasundaram, V Ramkumar, KK Arasu, SAS Anax
    AIP Conference Proceedings 2207 (1), 020010 , 2020
    2020
    Citations: 4
  • An efficient iot based healthcare data management and transfer using blockchain technology
    P Veeramani, P Rajasekar, V Ramkumar, R Azhagumurugan, SAH Basha, ...
    AIP Conference Proceedings 2518 (1), 030001 , 2022
    2022
    Citations: 3
  • Detection of Burst Header Packet Flooding Attacks via Optimization based Deep Learning Framework in Optical Burst Switching Network
    R Vahalingam, B Rajagopal, S Arumugam
    Informacije MIDEM 53 (3), 167-176 , 2023
    2023
    Citations: 1
  • Utilisation of the DLBM approach for effective routing optimisation in an optical burst switching network on ecological environment
    V Ramkumar, C Vennila
    JOURNAL OF ENVIRONMENTAL PROTECTION AND ECOLOGY 23 (4), 1653-1662 , 2022
    2022
    Citations: 1
  • Surgeon’s mental health: an overlooked crisis in the post-pandemic surgical landscape
    G Gulothungan, R Vahalingam, YP Ragini, H Chopra, TB Emran
    International Journal of Surgery Open 64 (2), 153-154 , 2026
    2026
  • Next-gen surgical telementoring: real-time collaboration for safer patient care and smarter training
    S Gulothungan, R Vahalingam, YP Ragini, H Chopra, TB Emran
    International Journal of Surgery Open, 10.1097 , 2025
    2025
  • Enhancing Teachers' Performance in Higher Education Through Human Resource Management Using a Hybrid SVM-Reinforcement Learning Model
    S Kumar, PV Kashid, VA Gaidhani, RM Kani, R Vahalingam
    2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025
    2025
  • A Hybrid Random Forest and Neural Network Model for Enhanced Credit Card Fraud Detection in E-Commerce
    IAK Shaikh, YB Reddy, A Shankar, K Rajasekhar, R Vahalingam
    2025 International Conference on Computing Technologies & Data Communication … , 2025
    2025
  • Optimizing Smart Irrigation in Agriculture with a Fuzzy Logic and Genetic Algorithm Hybrid Model for Water Resource Management
    ACMV Srinivas, CL Monica, U Manjulamma, BP Gajbhare, R Vahalingam, ...
    2025 5th International Conference on Intelligent Technologies (CONIT), 1-6 , 2025
    2025
  • Cost-effective surgical innovations for low-resource settings: advancing healthcare in underdeveloped regions
    J Palanivelu, R Vahalingam, H Chopra, T Malik
    International Journal of Surgery Open 63 (1), 62-63 , 2025
    2025
  • OPTICAL BURST SWITCH NETWORK WITH BRIDGED MULTIPLE SUBNETWORKS FOR DEFLECTION REDUCTION AND ENERGY SAVING
    VC Ramkumar V
    NeuroQuantology 20 (6), 4686-4705 , 2022
    2022
  • Design and simulation of UWB antenna with multiple notched bands on the feed line
    V Ramkumar, R Vijay Ravindran, R Bhavani, C Vennila, M Gunavathi
    IET Conference Proceedings CP797 2022 (1), 288-292 , 2022
    2022
  • AN IOT BASED SYSTEM TO MONITOR THE WARDS TRAVELLING THROUGH SCHOOL BUSES
    R V
    US Patent INPA 3,797 , 2022
    2022
  • a machine learning based approach to analyze the multi channel queries of E-commerce sites
    R V
    US Patent App. 202,241/005,805 , 2022
    2022
  • Optical Communication Essentials
    R V
    2022