USHA BHANU NAGESWARAN

@srmvalliammai.ac.in

Professor , Department of ECE
SRM Valliammai Engineering College

USHA BHANU NAGESWARAN


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https://researchid.co/ushabhanu123

EDUCATION

B.E ECE
M.E VLSI Design
Ph. D in VLSI Signal Processing

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Hardware and Architecture, Signal Processing, Computer Vision and Pattern Recognition
19

Scopus Publications

86

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS
    N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi
    International Journal of Advances in Signal and Image Sciences, 2025
    Mobile Wireless Sensor Networks (MWSNs) are highly vulnerable to various security threats due to their open communication channels and deployment in unattended or hostile environments. Although clustered MWSNs offer improved energy efficiency, their dynamic and open nature makes them particularly susceptible to attacks. Among these, the Selective Forwarding Attack (SFA) poses a serious threat by selectively dropping packets, thereby disrupting cooperative data transmission and reducing network reliability. This paper proposes a Random Forest (RF)-based SFA detection framework designed for the dynamic nature of clustered MWSNs. The proposed RF-SFAD system integrates Gini Importance (GI) and Recursive Feature Elimination (RFE) for effective feature selection, eliminating irrelevant or redundant data to improve classification performance. It monitors next-hop node behavior using key parameters such as packet loss rate, forwarding rate, packet size, and energy consumption to identify malicious activities indicative of SFA. Experimental evaluations conducted in a simulated MWSN environment demonstrate that the proposed RF-SFAD system achieves a detection accuracy of 98.5%, confirming its effectiveness and robustness in identifying selective forwarding attacks in MWSNs.
  • Investigations of Deep Learning Algorithms for Identification of Brain Tumors
    Selvaraj Margasagayan, Usha Bhanu N
    1st International Conference on Communication Computing Smart Materials and Devices Icccsmd 2024, 2024
    The objective of this paper is to understand the technological advancement in the medical image segmentation and classification of Magnetic Resonance (MR) Images using Deep Learning (DL) approaches. The existing DL algorithms explores to detect meningioma, glioma and pituitary tumor kind of Brain Tumor (BT). Convolution Neural Network (CNN) architecture remains most popular to solve medical image classification problems. The modification in existing CNN yields new techniques like Inception architecture, Efficient Net architecture, You Only Look Once (YOLO) structure and Gaussian CNN (GCNN) architecture. The performance metrics of the existing modified CNN algorithms are analyzed for various datasets, algorithms, and for achieved accuracy. These investigations are useful for designing new DL algorithms for early detection of brain tumors.
  • Applications of the internet of things and big data in automated healthcare
    S. Benila, N. Usha Bhanu
    System Design Using the Internet of Things with Deep Learning Applications, 2023
    A connected automatic healthcare system can play a major role in enabling patients to access and track their health data and permit for flawless communication with the providers of healthcare. The applications of IoT devices in the healthcare business facilitate doctors in observing patient activities and advanced treatment and give suggestions regarding patient’s health with the decision tools and automation technologies. With the employment of this automatic technology, there are incomparable benefits that may improve the standard and potency of treatments and consequently improve the health of the patients with reduced cost. As the range of patients is increasing day by day, the healthcare business plays a crucial part in the generation of massive amounts of data. The amount of data is continually growing, and that comes from numerous sources; managing this information is extremely critical. Moreover, it is very challenging to retrieve this information and for further investigation. Big data analytics (BDA) is an alternative approach to healthcare systems that must estimate the affordable time for making sensible discretions organizing 2future views, and maximizing value. The analyzed information helps physicians to create choices for patients. In fact, healthcare BDA has the ability to lower treatment costs, predict epidemic outbreaks, avert preventable diseases, and improve people’s overall quality of life. This chapter examines the need for IoT in the healthcare business, data analysis, and BDA. Investigations into various sorts of existing big IoT data analytics, as well as the relationship between IoT and data analytics in the healthcare industry, are also explained. The chapter also focuses on open challenges faced in the real-time implementation of connected healthcare and BDA.
  • Dingo algorithm-based forwarder selection and huffman coding to improve authentication
    Nageswaran Usha Bhanu, Prathaban Banu Priya, Tiruveedhula Sajana, Shanmugasundaram Shanthi, Murugan Mageshbabu, Erram Swarnalatha, Kuntiyellannagari Bhagya Laxmi, Kannabiran Saravanan
    Indonesian Journal of Electrical Engineering and Computer Science, 2023
    <span>In wireless sensor network (WSN), the high volume of observe and transmitted data among sensor nodes make it requires to maintain the security. Even though numerous secure data transmission approaches designed over a network, an inadequate resource and the complex environment cause not able to used in WSNs. Moreover, secure data communication is a big challenging problem in WSNs especially for the military application. This paper proposes a dingo algorithm-based forwarder selection and huffman coding (DAHC) to improve authentication in internet of things (IoT) WSN. Initially, it detects the anomalous nodes by applying support vector machine (SVM) algorithm based on sensor node energy, node selfishness, and signal to noise ratio (SNR). Next, we using the dingo algorithm to select the forwarder node. This dingo algorithm computes the fitness function based on node degreee, node distance and node energy. Finally, the huffman coding to provide end to end authentication established on node energy from sender to receiver. During data transmission, the huffman coding to build the binary hop count value, it improves the authentication in the WSN. Performance results specify that this approach enhances the detection ratio and throughput.</span>
  • A mutated addition–subtraction unit to reduce the complexity of FFT
    Saravanakumar Chandrasekaran, Usha Bhanu Nageswaran
    Applied Nanoscience Switzerland, 2023
  • Investigations of Machine Learning Algorithms for High Efficiency Video Coding (HEVC)
    N Usha Bhanu, C Saravanakumar
    Proceedings of 2023 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2023, 2023
    The growing demand of high-resolution video on portable devices, the applications require higher coding efficiency, high throughput and low power for handling heterogenous types of video signals. This paper presents a survey on possibility of applying Machine Learning (ML) models in H.265/ HEVC video encoder unit. Higher computational complexity with respect to motion estimation, coding, and parallel processing architectures are required for HEVC. The existing HEVC algorithms are based on spatial temporal relationship which requires dynamic video sequences handling for fast changes in scenes. This paper focuses on the possible realization of machine learning algorithms for Rate Control (RC) in video sequences, Coding Unit (CU) depth decision, Neural network-based Motion Estimation and Compensation, adaptive de-blocking filter for reducing blocking artifacts and task driven semantic coding for real time video applications. The algorithms are surveyed with respect to the learning process used in various units of HEVC encoders and summarized in terms of parameters achieved and datasets used in the existing literature.
  • Validation of Adder blocks with Shared Resource Methodology for Precise Cell Boundary Identification in Biotechnology Applications
    Saravanakumar C, Usha Bhanu N, Subhashini N, Sureshkumar V, Marirajan S, Sandhya V P
    Proceedings 2023 3rd International Conference on Innovative Sustainable Computational Technologies Cisct 2023, 2023
    For quantitative single-cell biology using optical microscopy, locating cells in a microscopic image is critical. Although there are several segmentation methods available, successful segmentation is difficult and typically necessitates problem-specific algorithm tweaking. Furthermore, recent algorithms are dependent on a few fundamental methodologies that detect cell borders using the image's gradient field. Many microscopy procedures, on the other hand, can provide pictures with distinct intensity patterns at the cell membrane. This has yet to be leveraged algorithmically to develop more generic segmentation approaches. In the proposed work, a simple algorithm is employed to identify the boundary of a cell in a microscopic image and it is deployed in a hardware chip to experiment with it. The results show the isolation of boundaries of the cell with improvement in the area occupied by the hardware. The resource-sharing technique is employed to reduce the area by 50 - 60% without compromising the identification of the boundary of the cell in the microscopic image.
  • A Constructive approach to Numerical Mapping scheme of Nucleotides for Preprocessing in Machine Learning
    C Saravanakumar, N Usha Bhanu
    Proceedings of the Confluence 2022 12th International Conference on Cloud Computing Data Science and Engineering, 2022
    One of the major issues in the Bioinformatics discipline is to construct a method by which the precise protein-coding region can be identified in the intended nucleotide series. The exact spotting of protein coding regions in a nucleotide is valuable in numerous entities. For an instance, it aids in describing unique proteins, develop drugs, and furthermore in uncovering the developmental foundation of a specific living being. Digital Signal Processing (DSP) rooted technique is quite popular for identifying protein coding regions. The main fundamental stage of the DSP oriented prediction of exon, is to direct the nucleotide base to the numeric values. Choosing a numerical mapping configuration influences the characteristics of the DNA sequence, helping them to pinpoint the precise area of the exon. Over the most recent twenty years, a number of methods to map the nucleotides have been effectively utilized as a preprocessing stage for exon prediction. The proposed method of mapping a sequence outerforms other schemes in predicting the region of exons.
  • Fog Managed Data Model for IoT based Healthcare Systems
    Benila S Benila S, Usha Bhanu N. Benila S
    Journal of Internet Technology, 2022
    <p>In Internet of things enabled healthcare system, sensors create vast volumes of data that are analyzed in the cloud. Transferring data from the cloud to the application takes a long time. An effective infrastructure can reduce latency and costs by processing data in real-time and close to the user devices. Fog computing can solve this issue by reducing latency by storing, processing, and analyzing patient data at the network edge. Placing the resources at fog layer and scheduling tasks is quite challenging in Fog computing. This paper proposes a Fog Managed Data Model (FMDM) with three layers namely Sensor, Fog and cloud to solve the aforementioned issue. Sensors generate patient data and that are managed and processed by Fog and cloud layers. Tasks are scheduled using a Weighted Fog Priority Job Scheduling algorithm (WFPJS) and fog nodes are allocated based on Priority based Virtual Machine Classification Algorithm (PVCA). The performance of this model is validated with static scheduling techniques with variable patient counts and network configurations. The proposed FMDM with WFPJS reduces response time, total execution cost, network usage, network latency, computational latency and energy consumption.</p> <p> </p>
  • Service level agreement based secured data analytics framework for healthcare systems
    S. Benila, N. Usha Bhanu
    Intelligent Automation and Soft Computing, 2022
    Many physical objects are connected to the internet in this modern day to make things easier to work based on the convenience of the user, which reduces human involvement with the help of Internet of Things (IoT) technology.This aids in the capture of large amounts of data, the interchange of information via the internet, and the remote operation of machines. IoT health data is typically in the form of big data and is frequently coupled with the cloud for secure storage. Cloud technology provides a wide range of technological services via the internet, and it is a highly interoperable and on-demand network for a wide range of computing resources. The Service Level Agreement (SLA) is made between the cloud and the patient, and it outlines the services supplied as well as the level of security provided to the user. For fulfilling service, the deployed external cloud has challenges with load balancing and work scheduling. Furthermore, the gathered health data must be effectively processed by medical practitioners. To solve this issue, a Secure Cluster Naive Bayes (CNB) framework is proposed, both with and without Dimensionality Reduction. To preserve its anonymity, the obtained data is hashed and stored in the cloud using the blockchain technology. SLA sessions are organized to prioritize patient data for decryption and prediction. At the doctor’s end, the decrypted data is first filtered and dimensionally reduced before being clustered using a dual K-means clustering technique and classified using the Naive Bayes algorithm. The web-based graphical user interface server is responsible for connecting the IoT device, the cloud, and the doctor. The security performance of the DRCNB and CNB frameworks is evaluated using block chain characteristics, the frequency of SLA violations, and processing and execution time. The DRCNB framework is 91.1% accurate, while the CNB model is 80.73% accurate, making it more accurate than previous models. The new models exceed the prior ones in terms of both security and prediction performance.
  • Fault diagnosis of Gate Level 2 - To - 1 Multiplexer in FinFET Technology
    Saravanakumar C, Usha Bhanu N
    2021 International Conference on System Computation Automation and Networking Icscan 2021, 2021
  • Implementation of class based priority tunneling in multi protocol label switching networks
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • Fast motion estimation algorithm using hybrid search patterns for video streaming application
    Vani Rajamanickam, Ushabhanu Nageswaran, Sangeetha Marikkannan
    International Journal of Computers Communications and Control, 2017
  • Investigation of algorithms for reducing delay in cognitive radio networks
    W. L. Nancy Priyanka, N. Usha Bhanu
    2016 International Conference on Information Communication and Embedded Systems Icices 2016, 2016
  • VLSI architectures for high speed and low power implementation of 5/3 lifting discrete wavelet transform
    N. Usha Bhanu, A. Chilambuchelvan
    International Journal of Computational Science and Engineering, 2016
  • High speed VLSI architecture for non separable block based lifting wavelet transform
    Journal of Theoretical and Applied Information Technology, 2014
  • High-Speed Systolic VLSI Architecture for 2-D Forward Lifting-Based DWT
    N. Usha Bhanu, A. Chilambuchelvan
    Arabian Journal for Science and Engineering, 2014
  • VLSI architectures for lifting based DWT: A detailed survey
    Usha Bhanu Nageswaran, A. Chilambuchelvan
    ACM International Conference Proceeding Series, 2012
  • High speed VLSI implementation of lifting based DWT
    Usha Bhanu Nageswaran, A. Chilambuchelvan
    ACM International Conference Proceeding Series, 2012

RECENT SCHOLAR PUBLICATIONS

  • RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS
    KS Usha Bhanu N, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi
    International Journal of Advances in Signal and Image Sciences (IJASIS) 11 … , 2025
    2025
    Citations: 2
  • Applications of the Internet of Things and Big Data in Automated Healthcare
    S Benila, NU Bhanu
    System Design Using the Internet of Things with Deep Learning Applications, 1-19 , 2023
    2023
  • Investigations of machine learning algorithms for high efficiency video coding (hevc)
    NU Bhanu, C Saravanakumar
    2023 International Conference on Signal Processing, Computation, Electronics … , 2023
    2023
    Citations: 3
  • A mutated addition–subtraction unit to reduce the complexity of FFT
    S Chandrasekaran, UB Nageswaran
    Applied Nanoscience 13 (4), 2935-2944 , 2023
    2023
    Citations: 11
  • Dingo algorithm-based forwarder selection and huffman coding to improve authentication
    BP Usha Bhanu.N
    Indonesian Journal of Electrical Engineering and Computer Science 32 , 2023
    2023
    Citations: 18
  • Validation of Adder blocks with Shared Resource Methodology for Precise Cell Boundary Identification in Biotechnology Applications
    UBN Saravanakumar.C
    3rd International Conference on Innovative Sustainable Computational … , 2023
    2023
  • A Constructive approach to Numerical Mapping scheme of Nucleotides for Preprocessing in Machine Learning
    C Saravanakumar, NU Bhanu
    2022 12th International Conference on Cloud Computing, Data Science … , 2022
    2022
    Citations: 3
  • Speed Efficient Fast Fourier Transform for Signal Processing of Nucleotides to Detect Diabetic Retinopathy Using Machine Learning
    C Saravanakumar, N Usha Bhanu
    Journal of Medical Imaging and Health Informatics 12 (1), 27-34 , 2022
    2022
    Citations: 1
  • Service Level Agreement Based Secured Data Analytics Framework for Healthcare Systems
    S Benila, NU Bhanu
    Intelligent Automation & Soft Computing 32 (2), 1277-1291 , 2022
    2022
    Citations: 5
  • Fog Managed Data Model for IoT Based Health Care system
    UBN S.Benila
    Journal of Internet Technology 23 (No: 2), 217- 226 , 2022
    2022
  • Fault diagnosis of Gate Level 2–to–1 Multiplexer in FinFET Technology
    C Saravanakumar
    2021 International Conference on System, Computation, Automation and … , 2021
    2021
    Citations: 3
  • Building Cyber Physical Systems–Design Challenges, Techniques
    UB Nageswaran, M Murali, S Meiyalagan
    Smart Cyber Physical Systems, 3-22 , 2020
    2020
  • Women safety thread
    R Sharmila, AN Ravindhar, M Saravanan, NU Bhanu
    International Journal of Engineering Research & Technology (IJERT) 9 (05) , 2020
    2020
    Citations: 8
  • A competent multiplier architecture with reduced transistor count for Radix-2 butterfly computation of fast Fourier transform
    S Chandrasekaran, U Bhanu
    TEST Engineering and Management, Page , 2020
    2020
    Citations: 3
  • Exploration of De Blocking Filter and Sample Adaptive Offset for HEVC Standard
    S Chandrasekaran, U Bhanu
    International Journal of Future Generation Communication and Networking 13 … , 2020
    2020
  • Real Time Video Surveillance Architecture for Secured City Automation
    M Ramesh, NMA Khan, NU Bhanu
    2019
  • Implementation of traffic engineering technique in MPLS network using RSVP
    R Nisha, NU Bhanu
    i-Manager's Journal on Wireless Communication Networks 7 (1), 12 , 2018
    2018
    Citations: 1
  • Investigation of Open Short Path First for Implementing Hub and Spoke Topologies in Virtual Private Networks
    TRS Vidya, U Bhanu
    i-manager's Journal on Wireless Communication Networks 6 (2), 1 , 2017
    2017
    Citations: 1
  • Investigation of algorithms for reducing delay in cognitive radio networks
    WLN Priyanka, NU Bhanu
    2016 International Conference on Information Communication and Embedded … , 2016
    2016
  • VLSI architectures for high speed and low power implementation of 5/3 lifting discrete wavelet transform
    NU Bhanu, A Chilambuchelvan
    International Journal of Computational Science and Engineering 12 (2-3), 254-263 , 2016
    2016
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • Dingo algorithm-based forwarder selection and huffman coding to improve authentication
    BP Usha Bhanu.N
    Indonesian Journal of Electrical Engineering and Computer Science 32 , 2023
    2023
    Citations: 18
  • A detailed survey on VLSI architectures for lifting based DWT for efficient hardware implementation
    UN Bhanu, A Chilambuchelvan
    International Journal of VLSI design & Communication Systems 3 (2), 143 , 2012
    2012
    Citations: 17
  • A mutated addition–subtraction unit to reduce the complexity of FFT
    S Chandrasekaran, UB Nageswaran
    Applied Nanoscience 13 (4), 2935-2944 , 2023
    2023
    Citations: 11
  • Women safety thread
    R Sharmila, AN Ravindhar, M Saravanan, NU Bhanu
    International Journal of Engineering Research & Technology (IJERT) 9 (05) , 2020
    2020
    Citations: 8
  • High-speed systolic VLSI architecture for 2-D forward lifting-based DWT
    N Usha Bhanu, A Chilambuchelvan
    Arabian Journal for Science and Engineering 39 (8), 6125-6135 , 2014
    2014
    Citations: 6
  • Service Level Agreement Based Secured Data Analytics Framework for Healthcare Systems
    S Benila, NU Bhanu
    Intelligent Automation & Soft Computing 32 (2), 1277-1291 , 2022
    2022
    Citations: 5
  • Investigations of machine learning algorithms for high efficiency video coding (hevc)
    NU Bhanu, C Saravanakumar
    2023 International Conference on Signal Processing, Computation, Electronics … , 2023
    2023
    Citations: 3
  • A Constructive approach to Numerical Mapping scheme of Nucleotides for Preprocessing in Machine Learning
    C Saravanakumar, NU Bhanu
    2022 12th International Conference on Cloud Computing, Data Science … , 2022
    2022
    Citations: 3
  • Fault diagnosis of Gate Level 2–to–1 Multiplexer in FinFET Technology
    C Saravanakumar
    2021 International Conference on System, Computation, Automation and … , 2021
    2021
    Citations: 3
  • A competent multiplier architecture with reduced transistor count for Radix-2 butterfly computation of fast Fourier transform
    S Chandrasekaran, U Bhanu
    TEST Engineering and Management, Page , 2020
    2020
    Citations: 3
  • RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS
    KS Usha Bhanu N, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi
    International Journal of Advances in Signal and Image Sciences (IJASIS) 11 … , 2025
    2025
    Citations: 2
  • High speed vlsi implementation of lifting based dwt
    UB Nageswaran, A Chilambuchelvan
    Proceedings of the International Conference on Advances in Computing … , 2012
    2012
    Citations: 2
  • Speed Efficient Fast Fourier Transform for Signal Processing of Nucleotides to Detect Diabetic Retinopathy Using Machine Learning
    C Saravanakumar, N Usha Bhanu
    Journal of Medical Imaging and Health Informatics 12 (1), 27-34 , 2022
    2022
    Citations: 1
  • Implementation of traffic engineering technique in MPLS network using RSVP
    R Nisha, NU Bhanu
    i-Manager's Journal on Wireless Communication Networks 7 (1), 12 , 2018
    2018
    Citations: 1
  • Investigation of Open Short Path First for Implementing Hub and Spoke Topologies in Virtual Private Networks
    TRS Vidya, U Bhanu
    i-manager's Journal on Wireless Communication Networks 6 (2), 1 , 2017
    2017
    Citations: 1
  • VLSI architectures for high speed and low power implementation of 5/3 lifting discrete wavelet transform
    NU Bhanu, A Chilambuchelvan
    International Journal of Computational Science and Engineering 12 (2-3), 254-263 , 2016
    2016
    Citations: 1
  • VLSI architectures for lifting based DWT: A detailed survey
    UB Nageswaran, A Chilambuchelvan
    Proceedings of the International Conference on Advances in Computing … , 2012
    2012
    Citations: 1
  • Applications of the Internet of Things and Big Data in Automated Healthcare
    S Benila, NU Bhanu
    System Design Using the Internet of Things with Deep Learning Applications, 1-19 , 2023
    2023
  • Validation of Adder blocks with Shared Resource Methodology for Precise Cell Boundary Identification in Biotechnology Applications
    UBN Saravanakumar.C
    3rd International Conference on Innovative Sustainable Computational … , 2023
    2023
  • Fog Managed Data Model for IoT Based Health Care system
    UBN S.Benila
    Journal of Internet Technology 23 (No: 2), 217- 226 , 2022
    2022