Dr.M Narender

@tkrcet.ac.in

Professor and Computer Science and Engineering
TKR College of engineering and technology

Dr.M Narender


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https://researchid.co/machhanarender

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications
4

Scopus Publications

154

Scholar Citations

7

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • Machine Learning for Genomic Expression Classification-Based Phenotype Prediction in Topological Data Analysis
    Narender M, Karrar S. Mohsin, Ragunthar T, Anusha Papasani, Firas Tayseer Ayasrah, Anjaneyulu Naik R
    Journal of Machine and Computing, 2024
    Genomic data has become more prevalent due to sequencing and Machine Learning (ML) innovations, which have increased the biological genomics study. The multidimensional nature of this data provides challenges to phenotype prediction, which is required for individualized health care and the research investigation of genetic problems; nevertheless, it holds tremendous potential for understanding the association between genes and physical features. The authors of this paper introduce a new technique for symptom prediction from data from genomes, which combines Topological Data Analysis (TDA), Graph Convolutional Networks (GCN), and Support Vector Machines (SVM). The proposed method aims to address these challenges. By using TDA for multifaceted feature extraction, GCN to analyze gene interaction networks, and SVM for reliable classification in high-dimensional spaces, the above technique overcomes the drawbacks of conventional approaches. This TDA-GCN-SVM model has been demonstrated to be implemented in a method that is superior to conventional methods on distinct tumor datasets in terms of accuracy and additional measures. A novel method for genomic study and a more significant comprehension of genomic data analysis are both caused by this innovation, which is an enormous achievement in precision healthcare.
  • Comparative Analysis of Video Transmission in Vehicular Networks using IEEE 802.11g and IEEE 802.11p Standards
    H.M. Moyeenudin, S. Hari Kumar, M. Narender, Jose Anand A., J. Amutharaj
    2023 1st International Conference on Advances in Electrical Electronics and Computational Intelligence Icaeeci 2023, 2023
    There is a difficulty in the implementation of vehicular networks due to the high cost of equipment and the limitations that current technology imposes for the implementation of VANET networks. According to the literature that emphasizes that despite present a good solution for connectivity in vehicular networks, their architecture is unfeasible due to the high cost involved, mainly in the installation and implementation of adequate infrastructure. The main objective of this work is to present a comparative analysis between the performance of the IEEE 802.11g and IEEE 802.11p standards, using the Ad Hoc on Demand Distance Vector Routing (AODV) routing protocol and through the Network Simulator (NS-2), find out which of the standards demonstrates a better performance in video transmission. In this context, network scenarios are simulated, in different situations applying movement of nodes, the performance results of the standards in the proposed network scenarios are compared and evaluated, obtained through data collection through simulations. The quality of the video transmitted by both standards are compared and evaluated, using QoE (Quality of Experience) metrics.
  • An Analysis on the Power Consumption of Nodes in Ad hoc IEEE 802.11 Networks
    H.M. Moyeenudin, M. Narender, M. A. Mukunthan, Kanimozhi Raman, D. Balasubramanian
    Proceedings 2023 3rd International Conference on Pervasive Computing and Social Networking Icpcsn 2023, 2023
    This article analyzes the power consumption of nodes in ad hoc IEEE 802.11 networks. The main objective of this analysis is to discover theoretic restrictions for the gains obtained in node lifetime through different energy conservation techniques found in the literature. The evaluation of energy consumption considers the characteristics of the medium access method and the interaction of the nodes in the packet forwarding process. The basic idea is to regulate the lifetime of a node based on its average consumption. Consumption is estimated based on the amount of time the node remnants transmitting, receiving or idle. The potential gains obtained by different techniques for saving or balancing energy consumption are then analysed. It is shown that the flow balancing technique can achieve a maximum gain for the node lifetime between 11% and 30%, depending on the network configuration.
  • Evaluation of a Wireless Sensor Network for the Detection of Forest Fires
    Anuradha. T, A. Suganya, R. Muthalagu, M. Narender, Jose Anand A.
    Proceedings of the 2nd International Conference on Edge Computing and Applications Icecaa 2023, 2023
    The objective of the study is to assess the effectiveness and reliability of the WSN in detecting forest fires accurately and providing timely alerts to the authorities. Field experiments in a forested area are conducted with controlled fire scenarios to simulate real-world fire conditions. The WSN sensors were deployed, and data from the sensors were collected and analyzed. Proposed result demonstrate that the WSN is capable of detecting forest fires with high accuracy and providing timely alerts. The sensors effectively captured changes in environmental parameters associated with fire events. Through data fusion and intelligent algorithms, the WSN system accurately differentiated between normal environmental variations and fire-related anomalies. The wireless communication capability of the network enabled real-time transmission of data to a central monitoring station, allowing for immediate analysis and decision-making. Additionally, the WSN system demonstrated robustness and fault tolerance, as it could continue functioning even if individual sensors were damaged or lost. The evaluation of the WSN for forest fire detection showed promising results, highlighting its potential as an effective tool for early fire detection and prevention. The use of such a wireless sensor network can enhance the efficiency of fire management strategies, enabling timely responses, reducing response times, and minimizing the impact of forest fires on ecosystems and communities.

RECENT SCHOLAR PUBLICATIONS

  • High-Precision Brain Tumor Segmentation with Switchable Normalization in Faster R-CNN Architecture
    AM 6. D.Ramana Kumar, P.Vamsheedhar Reddy, Hafeena Mohammad, Guda Madhu ...
    Scientific Reports , 2026
    2026
  • High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture
    DR Kumar, PV Reddy, H Mohammad, G Madhu, SB K, M Narender, ...
    Scientific Reports , 2026
    2026
  • A Conversational Healthcare Companion in Kannada
    J Raju, K Rohitaksha, KS Rekha, BG Jairam, M Narender, S Dhananjaya, ...
    Engineering, Technology & Applied Science Research 16 (1), 32377-32383 , 2026
    2026
  • A data-driven approach to predicting breast cancer recurrence with hybrid machine learning models
    BG Deepa, R Velmurugan, M Narender, KP Suhaas
    1 11 (1), 79 , 2026
    2026
  • QoS-Aware Task Offloading in Fog-IoT Environment Using Hybrid Deep Q-Learning with Actor-Critic Framework.
    AK Gowda, A Zareen
    Journal Européen des Systèmes Automatisés 58 (10) , 2025
    2025
    Citations: 1
  • A Hybrid Framework for Smart Educational Governance Using AI, Blockchain, and Data-Driven Management Systems.
    NT Gurram, M Narender, S Bhardwaj, JP Kalita
    Advances in Consumer Research 2 (5) , 2025
    2025
    Citations: 25
  • A Framework for the Video Surveillance Suspicious Activity Detection
    K Rohitaksha, AL Pujari, S Dhananjaya, M Narender
    Engineering, Technology & Applied Science Research 15 (4), 25402-25406 , 2025
    2025
    Citations: 1
  • Efficient Resource Management in Edge Computing for Autonomous Systems with An Energy-aware Approach
    M Narender
    2025
  • Artificial Intelligence in Financial Fraud Detection
    M Narender, AJ Anand
    Handbook of AI-Driven Threat Detection and Prevention, 193-207 , 2025
    2025
    Citations: 12
  • Hybrid framework for privacy and integrity in the IoT environment using the network topology measures and deep learning techniques
    HC Pavithra, J Rajeshwari, KS Rekha, M Narender, BG Jairam, R Sunitha
    Int. J. Comput. Methods Exp. Meas 13 (4), 868-881 , 2025
    2025
  • AI in Financial Fraud Detection in “Handbook of AI-Driven Threat Detection and Prevention A Holistic Approach to Security
    DJA Dr.M.Narender
    Handbook of AI-Driven Threat Detection and Prevention, 15 , 2025
    2025
  • Polycystic Ovary Syndrome Detection Using Contextual Ensemble Network and ELMAN Neural Network with Green Anaconda Optimization
    R Kalshetty, N Vedavathi, M Narender, CI Johnpaul, T Mathew
    Journal of Multiscale Modelling 15 (04), 2450007 , 2024
    2024
    Citations: 4
  • Millets Industry Dynamics: Leveraging Sales Projection and Customer Segmentation
    KP Suhaas, BG Deepa, D Shashank, M Narender
    SN Computer Science 5 (8), 1063 , 2024
    2024
    Citations: 4
  • End to End Model to Reduce the Inference, Jamming, and to Increase the Trust from the Compromised Secondary Nodes in Cognitive Radio Networks
    S Dhananjaya, M Narender, R Sunitha
    2024 International Conference on Intelligent and Innovative Technologies in … , 2024
    2024
  • Deep reinforcement learning based channel allocation (DRLCA) in cognitive radio networks
    MN Pavan, S Kumar, G Nayak, M Narender
    J. Electr. Syst. 20 (6), 914-926 , 2024
    2024
    Citations: 2
  • Deep learning-powered segmentation and classification of diabetic retinopathy for enhanced diagnostic precision
    M Harisha, A Bhosale, M Narender
    Artificial Intelligence in Health 1, 2783 , 2024
    2024
    Citations: 8
  • Comparative analysis of video transmission in vehicular networks using IEEE 802.11 g and IEEE 802.11 p Standards
    HM Moyeenudin, SH Kumar, M Narender, J Amutharaj
    2023 First International Conference on Advances in Electrical, Electronics … , 2023
    2023
    Citations: 25
  • An Analysis on the Power Consumption of Nodes in Ad hoc IEEE 802.11 Networks
    HM Moyeenudin, M Narender, MA Mukunthan, K Raman, ...
    https://ieeexplore.ieee.org/xpl/conhome/10265860/proceeding 3 (3), 1185-1195 , 2023
    2023
  • Evaluation of a wireless sensor network for the detection of forest fires
    A Suganya, R Muthalagu, M Narender
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023
    Citations: 22
  • Deep regularization mechanism for combating class imbalance problem in intrusion detection system for defending DDoS attack in SDN
    M Narender, BN Yuvaraju
    J. Comput. Sci 19 (3), 334-344 , 2023
    2023
    Citations: 8

MOST CITED SCHOLAR PUBLICATIONS

  • A Hybrid Framework for Smart Educational Governance Using AI, Blockchain, and Data-Driven Management Systems.
    NT Gurram, M Narender, S Bhardwaj, JP Kalita
    Advances in Consumer Research 2 (5) , 2025
    2025.0
    Citations: 25
  • Comparative analysis of video transmission in vehicular networks using IEEE 802.11 g and IEEE 802.11 p Standards
    HM Moyeenudin, SH Kumar, M Narender, J Amutharaj
    2023 First International Conference on Advances in Electrical, Electronics … , 2023
    2023.0
    Citations: 25
  • Evaluation of a wireless sensor network for the detection of forest fires
    A Suganya, R Muthalagu, M Narender
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023.0
    Citations: 22
  • Artificial Intelligence in Financial Fraud Detection
    M Narender, AJ Anand
    Handbook of AI-Driven Threat Detection and Prevention, 193-207 , 2025
    2025.0
    Citations: 12
  • Preemptive modelling towards classifying vulnerability of DDoS attack in SDN environment
    M Narender, BN Yuvaraju
    International Journal of Electrical and Computer Engineering 10 (2), 1599-1611 , 2020
    2020.0
    Citations: 11
  • Deep learning-powered segmentation and classification of diabetic retinopathy for enhanced diagnostic precision
    M Harisha, A Bhosale, M Narender
    Artificial Intelligence in Health 1, 2783 , 2024
    2024.0
    Citations: 8
  • Deep regularization mechanism for combating class imbalance problem in intrusion detection system for defending DDoS attack in SDN
    M Narender, BN Yuvaraju
    J. Comput. Sci 19 (3), 334-344 , 2023
    2023.0
    Citations: 8
  • An Empirical Study on the Relationship Between Institutional Ownership and Capital Structure
    AS Kiran, M Narender
    IUP Journal of Corporate Governance 20 (1), 28-42 , 2021
    2021.0
    Citations: 7
  • Communication b/w Mobile-Robots and PC controller Based On ZigBee Network
    HV Laxmi, M Narender
    International Journal of Engineering Research and Applications (IJERA) 1 (4 … , 0
    Citations: 7
  • Machha. Narender, and GN Ramesh,―Security Provision for Mobile Ad-Hoc Networks Using Ntp & Fuzzy Logic Techniques‖
    S Kumar
    Global Journal of Computer Science and Technology, 62 , 2010
    2010.0
    Citations: 6
  • Multi-Layer person authentication approach for electronic business using biometrics
    M Narendar, M Mohan Rao, MY Babu
    Glob J Comput Sci Technol 10, 63-67 , 2010
    2010.0
    Citations: 5
  • Polycystic Ovary Syndrome Detection Using Contextual Ensemble Network and ELMAN Neural Network with Green Anaconda Optimization
    R Kalshetty, N Vedavathi, M Narender, CI Johnpaul, T Mathew
    Journal of Multiscale Modelling 15 (04), 2450007 , 2024
    2024.0
    Citations: 4
  • Millets Industry Dynamics: Leveraging Sales Projection and Customer Segmentation
    KP Suhaas, BG Deepa, D Shashank, M Narender
    SN Computer Science 5 (8), 1063 , 2024
    2024.0
    Citations: 4
  • Exploitation of second generation superporous hydrogel composites as matrix retardants, in gel coating of pregabalin formulation and in-vivo characterization
    R Chandrakala, D Varun, M Narender, R Sunitha
    INTERNATIONAL JOURNAL OF PHARMACEUTICAL SCIENCES AND RESEARCH 9 (12), 5131-5144 , 2018
    2018.0
    Citations: 3
  • Deep reinforcement learning based channel allocation (DRLCA) in cognitive radio networks
    MN Pavan, S Kumar, G Nayak, M Narender
    J. Electr. Syst. 20 (6), 914-926 , 2024
    2024.0
    Citations: 2
  • QoS-Aware Task Offloading in Fog-IoT Environment Using Hybrid Deep Q-Learning with Actor-Critic Framework.
    AK Gowda, A Zareen
    Journal Européen des Systèmes Automatisés 58 (10) , 2025
    2025.0
    Citations: 1
  • A Framework for the Video Surveillance Suspicious Activity Detection
    K Rohitaksha, AL Pujari, S Dhananjaya, M Narender
    Engineering, Technology & Applied Science Research 15 (4), 25402-25406 , 2025
    2025.0
    Citations: 1
  • To Defeat DDoS Attacks in Cloud Computing Environment Using Software Defined Networking (SDN)
    BN Yuvaraju, M Narender
    Computer Science On-line Conference, 73-93 , 2020
    2020.0
    Citations: 1
  • Effect of the organic manures and inorganic fertilizers on growth and yield of garlic (Allium sativum L.)
    J Prakash, S Kumar, VK Pandey, S Verma, S Maji
    2017.0
    Citations: 1
  • Wireless Sensor Network Optimization Using Multiple Movable Sensors for Data Gathering
    M Narender, K Anjana Devi
    Australian Journal of Basic and Applied Sciences 10 (1), 95-99 , 2016
    2016.0
    Citations: 1