Transformation Optics and Transformation Electromagnetics: Comprehensive Review with Experimental Validation, Performance Analysis and Commercial Viability Assessment Khasim K.N.V, Rajasekar B Ssrg International Journal of Electronics and Communication Engineering, 2026 The article presented here gives a detailed overview of Transformation Optics and Transformation Electromagnetics, and highlights the crucial gaps identified through a fine literature review. It includes proper experimental validation data that shows antenna gains of 15.7 to 16.1 dBi, beam steering capabilities up to ±50°, and cloaking performance with Radar Cross Section (RCS) decreasing from -9.4 dB to -9.2 dB. The article also provides quantitative standards, detailed case studies of successful implementations, a thorough analysis of limitations, as well as an economic forecast projecting a $20.9B market by 2035. The article also proposes an organized research roadmap that addresses manufacturing challenges, standardization requirements, and regulatory-related issues. This research work links theoretical concepts with real-world applications that offer the required essential guidance to researchers, engineers, and industry stakeholders in the Electromagnetics area.
Energy Harvesting Antennas for Sustainable IoT Solutions National Journal of Antennas and Propagation, 2025 Energy harvesting antennas represent a pivotal technology for enabling sustainable solutions in the Internet of Things (IoT).By harnessing ambient energy sources such as radio frequency (RF) waves, these antennas provide a pathway toward self-sustaining IoT devices with reduced reliance on traditional batteries.Existing IoT systems heavily depend on battery-powered devices, which face challenges such as limited energy capacity, frequent maintenance, and environmental concerns from battery disposal.These issues hinder the scalability and longevity of IoT networks, especially in remote or hard-to-access locations.The proposed framework leverages IoT-based energy harvesting [IoT-EH] using highly efficient antennas that collect RF energy from ambient sources like cellular networks, Wi-Fi signals, and broadcast systems.This harvested energy powers low-energy IoT devices, ensuring uninterrupted operation.The framework integrates energy harvesting antennas with energy management systems to optimize power allocation and usage dynamically.The proposed method facilitates sustainable IoT deployments by eliminating the need for frequent battery replacements and minimizing environmental impact.It is particularly beneficial in applications such as smart agriculture, environmental monitoring, and industrial automation, where continuous device operation and minimal maintenance are critical.The findings demonstrate that the proposed approach significantly extends the device lifecycle, reduces maintenance costs, and enhances system reliability.Moreover, experimental results reveal an efficient conversion of ambient RF energy, ensuring that IoT devices achieve energy autonomy.This method presents a scalable and eco-friendly solution to the growing energy demands of IoT ecosystems.
A Comprehensive Analysis of FPGA Based Image Processing Technique in Machine Learning Approaches Mattagunja Varaprasad, B. Rajasekar 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems Iacis 2025, 2025 A low-power Very Large-Scale Integration (VLSI) design using a Field-Programmable Gate Array (FPGA) technology enables real-time image processing through highspeed data transfer and the execution of multiple parallel operations on a same clock signal. Integrated nanomaterials are employed to reduce overall power consumption. Carbon Nanotube Field-Effect Transistor (CNTEFT) technology facilitates high-speed operation, while VLSI reduces transistor count and power consumption, making the model suitable for low-power applications. However, increased power consumption and additional chip area can arise due to inefficient circuit design and the integration of low-power VLSI circuits within FPGA technology. This analysis focuses on image processing, edge detection approach and object detection approach, implemented as combinational circuits and analyzed for low-power VLSI using CNTFET and Gate Diffusion Input (GDI) technology. The arithmetic circuit includes a full adderbased dynamic threshold, 6 transistor full adder, signal processing unit, 4-bit unary decoder, and multiplexer implemented in a combinational circuit. Power consumption, latency, power-delay product (PDP), and energy consumption are considered as the performance metrics of the methods.
AI-Powered Classification of Bone Marrow Cancer: A Deep Learning Approach for Leukemia and Myeloma Diagnosis Sravanthi P, Shaik Jahirunnisa, Adarsh Naik S, K N V Khasim, B Rajasekar 2025 6th International Conference on Data Intelligence and Cognitive Informatics Icdici 2025, 2025 The Bone Marrow Cancer Classification system is an Artificial Intelligence powered platform designed to help users to classify the blood cancer reports. This cancer generally originates in the stem cells of the bone marrow. It is primarily classified into Leukemia and Myeloma. Diagnosing these conditions requires morphological examination by trained human examiners, making the process tedious and time-consuming. The project aims to provide an in-depth analysis for the examination of blood cells, with a significant focus on classifying leukemia and myeloma cells in blood smears. The project primarily uses Convolutional Neural Networks employed to classify the blood cell images for that purpose Residual Network (ResNet) and AlexNet architecture are used, the work of the Project involves several key steps, including data Augmentation and Pre-processing, Dataset division, Model training and Ensemble the results of both Architectures to improve the overall accuracy of the model.
Serverless Cloud Computing for Scalable E-Commerce Applications Utilizing Load Balancing Algorithms and Docker Swarm K. Priya, P. Jyothi, B. Premkumar, Rajasekar, A L. Chidambaram 2025 International Conference on Networks and Cryptology Netcrypt 2025, 2025 Remote computing has completely transformed the deployment and management of scalable e-Commerce applications, by providing an optimal solution to address varying traffic conditions economically and efficiently. The present study investigates how serverless computing can be integrated in e-commerce applications with emphasis on load balancing and Docker Swarm. E-commerce applications are used in web sites that have fluctuations in the traffic rates and hence resource management is important so as to ensure the quality is not compromised. Load balancing is still used in the context of serverless computing to empower the dynamic load distribution of the arriving requests to multiple serverless instances with relatively low response times and the efficient usage of resources. Container orchestration service Docker Swarm is utilized to create and manage microservices in a serverless manner with the support of quick scaling and efficient workload balancing. The research assesses the effect of different load balancing techniques, including round-robin or least-connections, in application performance under varying traffic conditions. Furthermore, this paper also discusses how Docker Swarm's automation of the scale-up and scale-down modes and failure recovery keep the environment available and reliable. The current study indicates that serverless, load balancing algorithms and Docker Swarm provide the much-needed boost to the scalability, performance and cost of the e-commerce application making serverless the best solution for online retail market.
Hybrid Optical-Electrical Transceiver Architecture for High-Speed Data Communications Suryakanta Panda, Nitish Vashisht, Srinivasa Rao K S, Rajasekar. B, Kalyan Acharjya, Nitish Vashisht 2025 International Conference on Automation and Computation Autocom 2025, 2025 Evaluating Design Tradeoffs in MMW Wave Arrays for High-Speed Wireless Data Communication and its Optimization over Fiber If you tear open your cloud, you will find a stream of is and Os at the heart of all this, with shrill screams from demanding applications like video, virtual reality, etc. pushing I believe close to their limits bandwidth comments here up purely optical links. We are reporting on highresolution computational imaging optimized for 3D surface reconstruction with tight constraints on operational uncertainty. Traditional electronic-only transceiver architecture is approaching its physical limits regarding data speed and power efficiency spurring the critical demand for more advanced approaches. Novel hybrid optical-electrical transceiver architecture has been discussed to overcome these limitations. It blends the fast speeds and broad bandwidths made possible by optical communication with the flexibility and scale of electrical circuits. The heart of this architecture is an electro-optic interface that converts electrical signals to optical. Enabling this interface is advanced materials like silicon photonics that permit optical and electronic components to be integrated into a single chip. This hybrid architecture combines optical communication for high-speed data transmission and enables data rates that are multiple orders of magnitude faster than traditional electronic-only architectures. Moreover, optical interconnects directly benefit the transceiver by lowering its power consumption, reducing total energy use and improving system performance.
Malware Classification Using Artificial Neural Network Charan R K, Chavan Chandu Nayak, K N V Khasim, Ashwini Kodipalli, Ushasree. A, B Rajasekar 2025 International Conference on Computing Technologies Icoct 2025, 2025 The rapid increase of malware poses a significant cybersecurity threat, necessitating effective detection and classification techniques. Traditional signature-based methods often fall short due to their inability to recognize novel and evolving malware strains. This paper explores the application of Artificial Neural Networks (ANN) for malware classification, leveraging their capability to learn complex patterns and generalize from training data. We developed and fine-tuned a machine learning algorithm based on neural networks. We utilized a diverse and extensive collection of data, which included samples of both harmful malware and legitimate software applications. The proposed ANN model achieved a high classification accuracy, demonstrating its efficacy in distinguishing between malicious and non-malicious executables. Comparative analysis of different optimizer techniques highlights the superior performance of our ANN based approach. The results suggest that ANNs can significantly enhance malware detection systems, offering a robust solution for cybersecurity defenses. Future work will focus on optimizing the model and expanding the dataset to further improve classification accuracy and adaptability to emerging threats.
Optimizing Image-based Vehicle Damage Estimation through Artificial Intelligence Anuja Nanda, Rajasekar.B, Vivek Saraswat, Asif Mohamed H B, Naresh Kaushik, Raghu N Aistemedu 2025 2025 International Conference on AI Driven Stem Education and Learning Technologies Proceedings, 2025 Image-based vehicle damage estimation has emerged as a crucial application of artificial intelligence, enabling faster and more reliable assessments compared to manual inspection. It offers significant potential in the insurance and automotive industries by reducing human error and improving decision-making efficiency. However, existing approaches often face challenges such as limited accuracy in detecting subtle damage patterns, high dependency on large labeled datasets, and poor adaptability across diverse vehicle models and environmental conditions. These limitations hinder practical deployment in real-world scenarios. To address these issues, we propose an Image Damage Estimation Framework (IDEF) that integrates Convolutional Neural Networks (CNNs) with Transfer Learning using ResNet architecture for severity classification. This framework enhances feature extraction, reduces training complexity, and improves generalization by leveraging pretrained knowledge from large-scale image datasets. The proposed method can be applied in insurance claim processing, automated vehicle inspection, and fleet management systems, ensuring timely and precise evaluation of damage severity. Experimental findings demonstrate that IDEF significantly improves classification accuracy, reduces computational overhead, and delivers robust performance across varying conditions. This establishes it as a reliable AI-based solution for accurately estimating vehicle damage. The evaluation considered accuracy (93.5%), precision (91.6%), recall (92.7%), and F1-score (92.1%), proving the proposed IDEF framework significantly outperforms existing vehicle damage estimation methods.
Optimizing Image-Based Vehicle Damage Estimation Through Artificial Intelligence Anuja Nanda, Rajasekar. B, Vivek Saraswat, Asif Mohamed H B, Naresh Kaushik, Raghu N 2025 International Conference on Metaverse and Current Trends in Computing Icmctc 2025, 2025 Vehicle damage is any physical injury or degradation that affects the design, functionality, or appearance of a vehicle. Numerous factors, such as accidents, injuries, degradation over time, vandalism, and natural failures, might cause damage. It can struggle with accurately assessing complicated damage types, various lighting conditions, and diverse vehicle models. To address these issues, this study introduces a unique approach, the Adaptive Sea Lion Optimized Intelligent Random Forest (ASLO-IRF)to estimate vehicle damage. The damaged vehicle image dataset was collected in Kaggle, that was pre-processed by histogram equalization. The experiment is done using the Python platform and the results demonstrate that the suggested strategy outperformed the conventional approaches with recall (96.5%), precision (98.3%), and f1-score (95.7%). The integration of AI into vehicle damage estimation is a step in the direction of modernizing the insurance industry, using innovation and fostering the adoption of the latest technology.
Exoskeleton Pysiotherapy and Assistive Robotic Arm Pradeep Surya Dadi, Geetha Rani K, Sathish Kumar P. J, Rajasekar B, Surendran R 2nd International Conference on Sustainable Computing and Smart Systems Icscss 2024 Proceedings, 2024
Role of IOT in Healthcare using Smart Textiles S. Karthikeyan, T. Sankar, M. Vijayakarthick, T Ravi, B. Rajasekar Icpects 2020 IEEE 2nd International Conference on Power Energy Control and Transmission Systems Proceedings, 2020
Computationally simpler and fast convergence algorithm for neural network based Ldpc encoder/ decoder International Journal of Scientific and Technology Research, 2019
Insilico analysis of docking studies CGSP strain of streptococcus pneumoniae International Journal of Scientific and Technology Research, 2019
Comparative analysis on supervised machine learning models for future wireless communication networks International Journal of Innovative Technology and Exploring Engineering, 2019
Front design and implementation of high speed front design and implementation of high speed hybrid dual d-fifo -ff (Flip ff (flip-flop) synchronizer flop) using verilog International Journal of Engineering and Advanced Technology, 2019
Low power CMOS design technique for power switches gating Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
Content based image retrieval using multi-view alignment hashing Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
FPGA implementation of ASK, BPSK and QPSK modulator using hardware co-simulation Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
Based on artificial neural network reconstructing fast X-Ray and CT images Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
Data logging of boiler temperature using Real time operating system Arpn Journal of Engineering and Applied Sciences, 2016
A survey on data acquisition for boiler temperature using RTOS Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
Feasibility of log-domain technique for high performance LDPC decoding concatenated with STBC Arpn Journal of Engineering and Applied Sciences, 2015
Design of enhanced multi-bit threshold bit flipping algorithm for low complex LDPC decoders Arpn Journal of Engineering and Applied Sciences, 2015
Performance analysis of an efficient D flip-flop based linear feedback shift register using CMOS technology Research Journal of Pharmaceutical Biological and Chemical Sciences, 2015
Concentric Square Slotted Four-Port MIMO Antenna Using EBG Decoupling Structure for 5G Applications BMS Sreenivasa Rao, B Rajasekar, N Prasad, BTP Madhav, ... Millimeter Wave and Terahertz Devices for 5G and 6G systems: Modern Design … , 2025 2025 Citations: 1
AI-Powered Classification of Bone Marrow Cancer: A Deep Learning Approach for Leukemia and Myeloma Diagnosis P Sravanthi, S Jahirunnisa, A Naik, KNV Khasim, B Rajasekar 2025 6th International Conference on Data Intelligence and Cognitive … , 2025 2025
Malware Classification Using Artificial Neural Network RK Charan, CC Nayak, KNV Khasim, A Kodipalli, B Rajasekar 2025 International Conference on Computing Technologies (ICOCT), 1-6 , 2025 2025
Machine Learning in Oncology: SVM-Based Classification of Lung, Breast and Liver Cancer from MRI Scans R Surendran, SR Navaneethakrishnan, B Rajasekar, KS Balamurugan, ... 2024 IEEE 9th International Conference on Engineering Technologies and … , 2024 2024 Citations: 6
Exoskeleton Pysiotherapy and Assistive Robotic Arm PS Dadi, B Rajasekar, R Surendran 2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024 2024 Citations: 3
Design of Four Element Multiband MIMO Antenna for 5G Devices V Shivani, KNV Khasim, PPSN Murthy, B Rajasekar, SNV Sujithbabu 2024 5th International Conference on Image Processing and Capsule Networks … , 2024 2024 Citations: 1
Empowering Independence: Raspberry Pi OCR for Visually Impaired User RS Sree, K Vikas, GSB Datta, KNV Khasim, B Rajasekar 2024 3rd International Conference on Applied Artificial Intelligence and … , 2024 2024
An intelligent weather prediction model using optimized 1D CNN with attention GRU S Hemamalini, KG Rani, B Rajasekar, SM Sendil GLOBAL NEST JOURNAL 26 (2) , 2024 2024 Citations: 1
Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks. Y Alotaibi, B Rajasekar, R Jayalakshmi, S Rajendran Computers, Materials & Continua 78 (3) , 2024 2024 Citations: 21
A Modified study on Genetic Algorithm in sensing orientations among the multi-directional Wireless Sensor Networks B Rajasekar, RAG Soundari, SM Basha, R Dhanalakshmi, V CB 2023 International Conference on Innovative Computing, Intelligent … , 2023 2023
An efficient allocation of resources in wireless communications iot network for numerous users SM Basha, R Dhanalakshmi, AG Soundari, V CB, B Rajasekar 2023 International Conference on Innovative Computing, Intelligent … , 2023 2023 Citations: 1
A success of bulk queueing service of expected waiting time with regular service, repair, idle and single server vacation in real-life data analysis GTS Devi, KG Rani, B Rajasekar, PJS Kumar, R Surendran IET Conference Proceedings CP859 2023 (44), 562-565 , 2023 2023
Design of phase measurement system using hybrid dual D-FIFO-FF synchronizer and PWM based duty cycle computation SKGK Pedapudi, B Rajasekar Measurement: Sensors 26, 100708 , 2023 2023 Citations: 5
Identification of Fatigue Drivers Based on Multiple Convolutional Neural Networks in Accelerometry Data CB Venkatramanan, B Rajasekar, SM Basha, AG Soundari, ... 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023
Expression of Concern for: Identification of Fatigue Drivers Based on Multiple Convolutional Neural Networks in Accelerometry Data CB Venkatramanan, B Rajasekar, SM Basha, AG Soundari, ... 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023
ANND: Identification and Prediction of Tooth Decay based on Artificial Neural Network and DenseNet Model AG Soundari, R Dhanalakshmi, B Rajasekar, SM Basha 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023 Citations: 2
Exploring the Role of Mining Wireless Framework in Identifying Human Privacy Vulnerabilities in Internet of Things Networks R Dhanalakshmi, CB Venkatramanan, B Rajasekar, SM Basha, ... 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023
Miniaturized coplanar waveguide‐fed metamaterial inspired antenna for radio frequency identification applications R Subbaiyan, BR Rajasekar Microwave and Optical Technology Letters 65 (1), 328-333 , 2023 2023 Citations: 3
A Compact Microstrip Bandpass Filter for Ultra-Wide Band Harmonic Suppression M Sugadev, C Pavan, B Rajasekar, M Kaushik 2022 International Conference on Computer Communication and Informatics … , 2022 2022 Citations: 2
Mid-Band Frequencies BMSS Rao, B Rajasekar Proceedings of International Conference on Wireless Communication: ICWiCom … , 2022 2022
MOST CITED SCHOLAR PUBLICATIONS
Image processing technique for automatic detection of plant diseases and alerting system in agricultural farms PK Mugithe, RV Mudunuri, B Rajasekar, S Karthikeyan 2020 International Conference on Communication and Signal Processing (ICCSP … , 2020 2020 Citations: 37
An efficient resource allocation strategies in cloud computing B Rajasekar, SK Manigandan International Journal of Innovative Research in Computer and Communication … , 2015 2015 Citations: 22
Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks. Y Alotaibi, B Rajasekar, R Jayalakshmi, S Rajendran Computers, Materials & Continua 78 (3) , 2024 2024 Citations: 21
Machine Learning in Oncology: SVM-Based Classification of Lung, Breast and Liver Cancer from MRI Scans R Surendran, SR Navaneethakrishnan, B Rajasekar, KS Balamurugan, ... 2024 IEEE 9th International Conference on Engineering Technologies and … , 2024 2024 Citations: 6
[Retracted] A Feasible Multimodal Photoacoustic Imaging Approach for Evaluating the Clinical Symptoms of Inflammatory Arthritis B Rajasekar, P Nirmala, P Bhuvaneswari, R Radhika, S Asha, KR Kavitha, ... BioMed Research International 2022 (1), 7358575 , 2022 2022 Citations: 6
Design of phase measurement system using hybrid dual D-FIFO-FF synchronizer and PWM based duty cycle computation SKGK Pedapudi, B Rajasekar Measurement: Sensors 26, 100708 , 2023 2023 Citations: 5
Low power 4× 4 bit multiplier design using DADDA, WALLACE algorithm and gate diffusion input technology KVK Reddy, K Abhinav, B Rajasekar, K Ashokkumar Journal of Computational and Theoretical Nanoscience 16 (8), 3359-3366 , 2019 2019 Citations: 5
Brain tumour segmentation using CNN and WT B Rajasekar Research Journal of Pharmacy and Technology 12 (10), 4613-4617 , 2019 2019 Citations: 4
Exoskeleton Pysiotherapy and Assistive Robotic Arm PS Dadi, B Rajasekar, R Surendran 2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024 2024 Citations: 3
Miniaturized coplanar waveguide‐fed metamaterial inspired antenna for radio frequency identification applications R Subbaiyan, BR Rajasekar Microwave and Optical Technology Letters 65 (1), 328-333 , 2023 2023 Citations: 3
Automatic number plate recognition using convolution neural network B Rajasekar, BMSK Roshan, BC Naidu, VV Kumar Sixth International Conference on Intelligent Computing and Applications … , 2021 2021 Citations: 3
Modified greedy permutation algorithm for low complexity encoding in LDPC codes B Rajasekar, E Logashanmugam 2014 International Conference on Control, Instrumentation, Communication and … , 2014 2014 Citations: 3
ANND: Identification and Prediction of Tooth Decay based on Artificial Neural Network and DenseNet Model AG Soundari, R Dhanalakshmi, B Rajasekar, SM Basha 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023 Citations: 2
A Compact Microstrip Bandpass Filter for Ultra-Wide Band Harmonic Suppression M Sugadev, C Pavan, B Rajasekar, M Kaushik 2022 International Conference on Computer Communication and Informatics … , 2022 2022 Citations: 2
Coplanar wave guide fed circular fractal antenna using wireless applications B Rajasekar, GS Reddy, G Naveen, M Sugadev World Review of Science, Technology and Sustainable Development 18 (1), 1-6 , 2022 2022 Citations: 2
Role of IOT in Healthcare Using Smart Textiles S Karthikeyan, T Sankar, M Vijayakarthick, T Ravi, B Rajasekar 2020 International Conference on Power, Energy, Control and Transmission … , 2020 2020 Citations: 2
Based on artificial neural network reconstructing fast X-Ray and CT images M Murali, K Singh, M Varun, B Rajasekar RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES 7 (4 … , 2016 2016 Citations: 2
Concentric Square Slotted Four-Port MIMO Antenna Using EBG Decoupling Structure for 5G Applications BMS Sreenivasa Rao, B Rajasekar, N Prasad, BTP Madhav, ... Millimeter Wave and Terahertz Devices for 5G and 6G systems: Modern Design … , 2025 2025 Citations: 1
Design of Four Element Multiband MIMO Antenna for 5G Devices V Shivani, KNV Khasim, PPSN Murthy, B Rajasekar, SNV Sujithbabu 2024 5th International Conference on Image Processing and Capsule Networks … , 2024 2024 Citations: 1
An intelligent weather prediction model using optimized 1D CNN with attention GRU S Hemamalini, KG Rani, B Rajasekar, SM Sendil GLOBAL NEST JOURNAL 26 (2) , 2024 2024 Citations: 1
