Venkataramanan

Scopus Publications

A Quantum-Enhanced Deep Learning Framework for Precise Leaf Disease Detection in Tomato and Cotton Crops
T. Nivethitha, C. Venkataramanan
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2026
Approximated Multiple Constant Multiplication Using Hamming Boolean Merging Based Compatible Graph Synthesis for Video Super Resolution
V. Parthipan, C. Venkataramanan
Circuits Systems and Signal Processing, 2026
Digital Rights Management System with RC4-2S Encryption Technique
C. Kanmani Pappa, N. Ashok Kumar, Kabilamani, C. Venkataramanan, K. P. Porkodi, P. Nagaraja
De Gruyter Proceedings in Mathematics, 2026
A novel mobile sink placement in wireless sensor network using deep maxout network based energy prediction with adjacent cell score
U. Nilabar Nisha, A. Manikandan, C. Venkataramanan, J. Ashok
Wireless Networks, 2025
COA-SSD: A novel chaotic optimization algorithm for enhancement of real-time video surveillance images using single shot detector with MobileNetV2
Vivek Pandiya Raj, K. Radha, S. Harihara Gopalan, C. Venkataramanan, R. Dhanapal, A. Manikandan
Systems and Soft Computing, 2025
Video surveillance involves the deployment of cameras to observe and record activities for security and monitoring purposes. This is vital for crime prevention, public safety, and improving operational efficiency across various environments. The rising demand for real-time security and threat detection has increased interest in sophisticated video surveillance systems. However, challenges persist in achieving an accurate automated analysis under diverse environmental and situational conditions. This paper presents an optimization strategy for video surveillance system deployment using a deep-learning algorithm. This strategy combines the base image with information about the behavioral events depicted in the frame sequence and then uses a Sobel filter to detect boundaries. The present study employs a rapid feature point identification algorithm known as the local-peak scale-invariant feature transform (LP-SIFT), which is based on multi-scale local peak features that are invariant to scale and represent multi-scale fluid turbulence. Traditional segmentation methods in video surveillance often lack contextual understanding and temporal consistency, which Modulated Memory Networks aim to address using adaptive memory-driven feature modulation. Next, we used an (SSD) with MobileNet V2 to classify fragments. SSDs can bypass the region proposal network and reduce latency. SSDs incorporate several optimizations such as multiple cooperative functions and base boxes to compensate for the loss of accuracy. To optimize and enhance the accuracy and efficiency of the video surveillance classification, the model parameters were fine-tuned. The Coati Optimization Algorithm (COA) is a metaheuristic algorithm inspired by coati behaviors: their cooperative strategy when attacking iguanas, and their anti-predator and avoidance behavior strategies. To evaluate the LP-SIFT algorithm, we considered datasets with varying scenes, pixel sizes, and distortion levels, across different lighting conditions and environments.
Intelligent Classification System for Thyroid Disease Diagnosis using Medical Imaging Data with Extreme Learning Machine
Dency Flora G, C Venkataramanan
Proceedings of 8th International Conference on Computing Methodologies and Communication Iccmc 2025, 2025
Thyroid disease, encompassing conditions such as hyperthyroidism and hypothyroidism, it demands an prompt diagnosis to ensure proper detection and treatment. The research develops a deep learning-based framework for detecting thyroid diseases using image datasets. The evaluation of the model was conducted using benchmark datasets from Kaggle and newly curated thyroid ultrasound image datasets from the UCI repository, specifically targeting hyperthyroid and hypothyroid conditions. To enhance image quality and reduce noise, Wiener filtering was applied during the preprocessing stage. For classification, because of its high generalizability and lightning-fast learning speed, the Extreme Learning Machine (ELM) method was chosen. Furthermore, the model’s hyper parameters were fine-tuned using a Hybrid Dragonfly Optimization Algorithm (HDFOA), combining exploration and exploitation capabilities to boost detection accuracy. Showing promise for rapid and dependable thyroid illness detection in clinical settings. The proposed model outperformed the current leading models and achieved a higher accuracy of 97.2% based on evaluation metrics such as accuracy, precision, recall, and F1-score.
Enhanced Energy Harvesting in Wireless Sensor Networks with Diverse Power Converters and ADRC
A. Shanmugapriya, C. Venkataramanan
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2025
Design of a M-shaped microstrip patch antenna for ISM band of applications
Loganayaki K, Mohana Priya J, Naveen E, Prathaksana S, Venkataramanan C
2025 IEEE International Students Conference on Electrical Electronics and Computer Science Sceecs 2025, 2025
A micro-strip patch antenna (MPA) is widely applied in the field of wireless communication, due to its smaller size and frequency of operation. An M-shaped MPA is proposed in this paper which operates in the band of 2.4GHz. The rectangular MPA has many slot shapes or strips, such as M-Strip, Zigzag pattern, and multiple circles, to enhance properties like VSWR, return loss(RL), gain, and frequency bandwidth. Microstrip patch antennas are becoming more and more popular because of their small, flat shape. These antennas can be readily applied in spacecraft, airplanes or portable communication devices. This antenna design's VSWR and return loss at 2.4GHz are measured to be 1.06 and -42.463 dB, respectively. The suggested antenna accomplishes downsizing without sacrificing return loss, VSWR, or resonant frequency by using microstrip line feeding.
Graphene Based Solar Photonic Battery for Aircraft-A Finite Element Based 2D Analysis
Geetha P, R Sudarmani, Venkataramanan c, Satyam Satyam, Sudarson Nagarajan
SAE Technical Papers, 2025
<div class="section abstract"><div class="htmlview paragraph">Over the past decade, significant progress in nano science and nanotechnology has opened new avenues for the development of high-performance photovoltaic cells. At present, a variety of nanostructure-based designs—comprising metals, polymers, and semiconductors—are being explored for photovoltaic applications. Advancements in the understanding of optical and electrical mechanisms governing photovoltaic conversion have been supported by theoretical analyses and modeling studies. Nevertheless, the high fabrication cost and relatively low efficiency of conventional solar photovoltaic cells remain major barriers to their large-scale deployment. One-dimensional (1D) nano materials, in particular, have introduced promising prospects for enhancing photovoltaic performance owing to their unique structural and electronic characteristics. Nanowires, nano rods, and nanotubes exemplify such 1D nanostructures, offering substantial potential to improve photon absorption, electron transport, and charge collection within photovoltaic devices. Graphene, a two-dimensional (2D) atomically thin lattice of carbon arranged in a hexagonal configuration, has emerged as a material of exceptional scientific interest. Its superior mechanical properties are attributed to the sp<sup>2</sup>-hybridized covalent bonds formed by three of the four valence electrons of each carbon atom with neighboring atoms. The remaining delocalized electron contributes to the remarkable optoelectronic properties of graphene, including its exceptionally high carrier mobility, which surpasses that of many conventional conductive materials. Furthermore, graphene thin films can be fabricated through a range of solution-based processing techniques, such as spin-coating, thereby enabling cost-effective, scalable, and versatile production. In the present study, a graphene-based two-dimensional solar cell is modeled and analyzed using the finite element method (FEM) to investigate its photovoltaic behavior and performance characteristics. It is found that the cell potential is 3.85V, VoC is 4.05V, Load cycle current is 4.25V with the surface temperature as 319K. The battery gets saturated at 1500s with graphene. Meanwhile, lithium battery produces cell potential as 3.05V, VoC is 3.05V, Load cycle current is 3.25V. Thus, grapene shows an improvement of 8% in cell potential, 25% in load current value. Lithium battery used for cell phones has the Qn=3500mAh capacity. In graphene, it is 3958mAh with an improvement of 13%.</div></div>
Wireless Multi-Factor Wearable Authentication System using Breath and Head-Tilt Signatures for Secure Access Control
C Venkataramanan, S Mohammed Shameem, S Prithikshan, V Rahul, A M Rohith
3rd International Conference on Emerging Applications of Material Science and Technology Iceamst 2025, 2025
Development of Capacitive Pressure Sensor for Automotives
Geetha P, Neelima K, R Sudarmani, Venkataramanan C, Satyam Satyam, Sudarson Nagarajan
SAE Technical Papers, 2025
AI-Infused Blockchain Technology for Thrust Applications
C. Venkataramanan
Blockchain and Cryptocurrency Management Systems and Technology Challenges, 2024
AI-Infused Blockchain Technology for Thrust Applications
Debesh Bhowmik
Blockchain and Cryptocurrency Management Systems and Technology Challenges, 2024
Design of Microstrip Patch Antenna with S-Slits for Wireless Applications
C Venkataramanan, P Nagarajan, N Ashok Kumar, K.P Porkodi, C Kanmani Pappa, A Kabilamani
Proceedings of the 5th International Conference on Smart Electronics and Communication Icosec 2024, 2024
Energy Efficient Clustering and Dynamic Slot Allocation for Wireless Sensor Networks
C Venkataramanan, Udhayakumar Pasupathi, A. Anbarasi, B. Karthikeyan, C. Agilan, A. Manikandan
2024 Asian Conference on Intelligent Technologies Acoit 2024, 2024
Novel Framework Design of MIMO Antenna for 5G Applications
P. Kabilamani, K. P. Porkodi, C Kanmani Pappa, P. Nagarajan, N. Ashokkumar, C Venkataramanan
Proceedings of the 5th International Conference on Smart Electronics and Communication Icosec 2024, 2024
Particle Swarm Optimization Based Intelligent Smart City Parking Guidance System
N Ashokkumar, C Venkataramanan, Nagarajan. P, C. Kanmani Pappa, P. Kabilamani, K.P. Porkodi
2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
A score based link delay aware routing protocol to improve energy optimization in wireless sensor network
Nilabar Nisha U, Manikandan A, Venkataramanan C, Dhanapal R
Journal of Engineering Research Kuwait, 2023
An energy efficient clustering with enhanced chicken swarm optimization algorithm with adaptive position routing protocol in mobile adhoc network
R. Reka, A. Manikandan, C. Venkataramanan, R. Madanachitran
Telecommunication Systems, 2023
Finite Element Analysis of Graphene Based Solar Photonic Battery for Electric Vehicle
Geetha P, R. Sudarmani, C. Venkataraman, S. Shubha
SAE Technical Papers, 2023
Modeling and Verification of 1D Array Methyl Ammonium Lead Halide Perovskite Solar Cells for Electric Vehicles
Geetha P, R. Sudarmani, C. Venkataraman, S. Shubha
SAE Technical Papers, 2023
Design and Performance Enhancement of DGS Based Planar Antenna for UWB Wireless Communication
Satyam, N. Gireesh, D. Damodaram, C. Venkataramanan
IEEE 1st International Conference on Ambient Intelligence Knowledge Informatics and Industrial Electronics Aikiie 2023, 2023
Experimental Analysis on SVM-based Image Classifiers for Medical Applications
C. Venkataramanan, M. Mohankumar, K. Mohanapriya, K.G. Kamalisri, M. Karunya, L. Suganya
2023 2nd International Conference on Advances in Computational Intelligence and Communication Icacic 2023, 2023
Design of Microstrip Patch Antenna [MPA] for ISM Band of Applications
N Sathyaraj, C. Venkataramanan, D.Sathish Kumar, S.Saravana Kumar, K. Saravanan, M. Vignesh
7th International Conference on Electronics Communication and Aerospace Technology Iceca 2023 Proceedings, 2023
Fuzzy based local agent routing protocol for delay conscious MANETs
B. Senthil Kumar, C. Venkataramanan
International Journal of Vehicle Information and Communication Systems, 2022
Design of Intelligent Socket Module for Smart Home Application using Internet of Things
R. Sarojini, C. Venkataramanan, R. Sudha, S. Ramalingam
3rd International Conference on Smart Electronics and Communication Icosec 2022 Proceedings, 2022
Dual-band Micro-Strip Antenna using Split Ring Resonators for ISM Bands
Venkataramanan C, Sarojini R, Porchelvi N, Pavan Kumar VMSN, Ramalingam S
Proceedings International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2022, 2022
Diamond Shaped Micro-strip Fractal Antenna for Ultra Wideband
Venkataramanan C, Porchelvi N, J. Martin Sahayaraj, Subramanian P, Jaya Pratha S
International Conference on Edge Computing and Applications Icecaa 2022 Proceedings, 2022
DCTP Architecture for Data-Centric Applications of Wireless Sensor Networks
Venkataramanan Chakrapani, Senthil Kumar Babu
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2021
LWBA: Levy-walk bat algorithm based data prediction for precision agriculture in wireless sensor networks
C. Venkataramanan, S. Ramalingam, A. Manikandan
Journal of Intelligent and Fuzzy Systems, 2021
BLSBA-ED-SSO: Bivariate Lévy-stable bat algorithm-based energy detection for spectrum sensing optimization in cognitive radio networks (CRNs)
Senthil Kumar Babu, C. Venkataramanan
International Journal of Communication Systems, 2020
Hierarchical MAC protocol with adaptive duty-cycle adjustment algorithm for wireless sensor network
C. Venkataramanan, S.M. Girirajkumar
International Journal of Operational Research, 2020
A hybrid solution for efficient utilization of energy in wireless sensor networks
International Journal of Scientific and Technology Research, 2019
Constructive relay based architecture for energy aware mobile AD-HOC networks
Journal of Advanced Research in Dynamical and Control Systems, 2017
Hierarchical adaptive mac protocol for collision avoidance and improving channel utilization in wireless sensor network
C Venkataramanan, S. M Girirajkumar
Journal of Computational and Theoretical Nanoscience, 2016
Soft set matrix optimization based node selection in wireless sensor networks
Asian Journal of Information Technology, 2016
ReRMAC congestion control protocol for wireless sensor networks
Chakrapani Venkataramanan, S. M. Girirajkumar
Indian Journal of Science and Technology, 2015
EARMP: A unified application specific MAC protocol for wireless sensor networks
C. Venkataramanan, S. M. Girirajkumar
2014 International Conference on Information Communication and Embedded Systems Icices 2014, 2015
Markov fuzzy based mac protocol for life time maximization of wireless sensor network
Chakrapani Venkataramanan, Selvaraj M. Girirajkumar
International Journal of Computers and Applications, 2014
Hierarchical energy and delay aware MAC protocol for wireless sensor networks
International Review on Computers and Software, 2013
TP-MAC: Trustable pass medium access control protocol design for energy aware wireless sensor networks
European Journal of Scientific Research, 2012

Venkataramanan

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Scopus Publications