Dr.P.HEMA

@rmkcet.ac.in

Assistant Professor, Science &Humanities , Mathematics
R.M.K. College of Engineering and Technology

Dr.P.HEMA


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https://researchid.co/ambahema

EDUCATION

B.Sc .,M.Sc., M..

RESEARCH INTERESTS

Operations Research
7

Scopus Publications

73

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • RETRACTED: Distributed data analytics for wireless sensor networks (WSNs) using fuzzy logic-based machine learning
    Amit Sharma, M. Naga Raju, P. Hema, Morsa Chaitanuya, M.V. Jagannatha Reddy, et al.
    Journal of Intelligent and Fuzzy Systems, 2025
  • Analysis of Graph Inverses and Algebraic Connectivity in a Systematic Way
    R. Stella Maragatham
    Communications on Applied Nonlinear Analysis, 2025
    an exhaustive and methodical study of algebraic connectedness and graph inverses. In many contexts, graph theory plays a crucial role, particularly when understanding intricate systems. This paper delves into the fundamental concepts of graph inverses and explains their significance for network analysis and connectivity evaluation. The Laplacian lattice's second-smallest eigenvalue, or algebraic connectivity µN−1, plays a crucial role in some features like network heartiness, synchronisation security, and diffusion processes. In this study, we focus on the algebraic connectedness in the network-of-networks (NoN), which is the general context of linked networks. A key component of science is the graph hypothesis. Algebraic graph hypothesis refers to the use of algebraic techniques to graph problems. This article concludes a focus on algebraic graph hypothesis and presents and examines a different algebraic and mathematical variety idea to regard as the greatest matching of an undirected graph.
  • Advanced Statistical and Nonlinear Analysis Techniques for Deep Learning in MBA Education
    S. Cynthiya Margaret Indrani
    Communications on Applied Nonlinear Analysis, 2024
    Integration of sophisticated statistical and nonlinear analysis techniques by deep learning has become a main strategy for enhancing MBA program educational outcomes. Our work provides the DRAN, which combines residual learning with attention processes, thereby focusing on the most relevant aspects of educational datasets. Nonlinear regression and clustering are among advanced statistical techniques that assist the DRAN model to effectively capture complex relationships in the data, hence improving knowledge of student behavior and performance. The approach trains the DRAN model to estimate academic achievements and offer tailored learning interventions after preprocessing of student data including grades, attendance, and engagement measurements. The DRAN model outperforms traditional machine learning methods with an accuracy of 92.7% in assessing student performance and an improvement of 15% in the precision of tailored learning recommendations. These findings show how deep learning might transform MBA education by arming educators with useful insights that drive student success. Together, deep residual learning and nonlinear dynamics increase forecast accuracy and enable flexible learning environments fit for particular requirements. This research contributes to the growing corpus of information on the application of artificial intelligence in education and paves the basis for next breakthroughs in individualized learning systems.
  • Complexity and Monitoring of Economic Operations Using a Game-Theoretic Model for Cloud Computing
    P Hema, N R Rejin Paul, Lenka Čepová, Bhola Khan, Kailash Kumar, et al.
    Systems, 2023
    In this study, a model is presented for allocating cloud computing resources based on economic considerations using tools from game theory. The model, called the Non-Cooperative Game Resource Allocation Algorithm (NCGRAA), is designed to achieve the optimum stage in cloud computing. In addition, the Bargaining Game Resource Allocation Algorithm (BGRAA) is introduced to the existing system to develop the billing process within the constraints of availability and fairness. This system-based algorithm implements methods for converging on and improving the Nash Equilibrium and Nash Bargaining solutions. While the Nash equilibrium helps to develop decision-making concepts with game theory, one of its main goals is to achieve the desired outcome and avoid deviation from the working stage. Nash Bargaining is a unique solution that occurs between two parties and takes into account the process of bargaining to provide a fair solution that is scale invariant and independent. In recent years, cloud computing has become a popular way to manage computing services and enable producers and consumers to interact. This process allows users to obtain goods at an affordable cost from sellers according to their expectations. This research investigates the economic operation monitoring of cloud computing using the gaming theory model. A Static Negotiation Analysis Method with a Bargaining Process (SNAM-BP) for a dynamic conceptual framework is presented to display the weighted relationship between primary issues and keywords used to evaluate the potential partnership of each country.
  • An Effective Approach for Image Denoising Using Wavelet Transform Involving Deep Learning Techniques
    Abhay Shukla, K. Seethalakshmi, P Hema, Jitendra Chandrakant Musale
    Proceedings of the 4th International Conference on Smart Electronics and Communication Icosec 2023, 2023
    In contemporary years, image denoising has developed as an important investigation topic in the arena of image processing due to the increasing demand for high-quality images. Deep learning approaches have recently demonstrated outstanding results in a variety of image processing applications. In this research, a wavelet transform and deep learning-based method is suggested for image denoising. To successfully remove noise from an image, the suggested method is based on a hybrid network that combines wavelet transform with convolutional neural networks (CNNs). The suggested method is divided into two steps, one based on wavelet transforms and the other on deep learning. The input image is divided into wavelet coefficients at various scales and orientations in the wavelet transform-based stage. The noise is subsequently filtered out of the wavelet coefficients using a thresholding method. A CNN is taught to acquire the plotting among the noisy image and the denoised image during the deep learning-based step. The experimental results show that, in terms of both quantitative metrics and visual quality of the denoised images, the suggested strategy outperforms a number of state-of-the-art image denoising methods. The suggested method is also independent of the prior knowledge of the noise statistics and resilient to various types of noise. Overall, the suggested method successfully tackles image denoising by fusing the compensations of deep learning and wavelet transform. The suggested method could be used for a variety of computer vision applications that call for high-quality image denoising.
  • Empirical Analysis of Rainfall Prediction System using an DGRNN-SAM Approach
    P HEMA, Uppara Raghu Babu, E. Manigandan, A Rajesh Kumar, Nagamalleswari Devireddy, et al.
    Proceedings of the 5th International Conference on Inventive Research in Computing Applications Icirca 2023, 2023
    Precipitation forecasting, especially for shorter timescales, is a critical issue in meteorological service. Most current research aims to improve prediction methods by using radar or satellite imagery. On the other hand, there is a situation in which numerous sensors at different observation sites acquire the same set of weather features. There is room for improvement in existing work due to the fact that imperfect site observations might still yield useful information for weather prediction at neighboring locations. This study proposes a multitask neural network model to automatically extract characteristics from time series gathered at observation sites and to utilize the correlation between different sites for weather forecasting, thus resolving the aforementioned problem. As far as currently aware, this is the first attempt to use multi-task learning and deep learning approaches to predict the amount of short-term rainfall based on characteristics from many places. In particular, it recast the task as an end-to-end multi-site neural network model, which allows to mimic inter-site correlations and transfer learning from one site to another. The method that has been suggested begins with the preprocessing step of cleaning and normalizing the data. When training the model with DGRNN-SAM, the process of feature selection and evaluation is carried out utilizing differential evaluation. When contrasted with other two models, such as LSTM and GRU, the suggested method fares quite well in terms of its performance.
  • Robust soft sensor systems for industry: Evaluated through real-time case study
    P. Hema, E. Sathish, M. Maheswari, Anita Khosla, Bhaskar Pant, et al.
    Measurement Sensors, 2022

RECENT SCHOLAR PUBLICATIONS

  • Optimized Seizure Detection in EEG Using Dual‐Branch Feature Fusion and Machine Learning Technique
    P Hema, V R
    Developmental Neurobiology 86 (2), e70014 , 2026
    2026
  • Coronally advanced flap for treatment of multiple gingival recession in maxillary teeth–A Evaluative study
    P Hema, S Mageshkumar, M Ebenezer
    European Journal of Dental Research 3 (1), 1-1 , 2026
    2026
  • Alzheimer's Care Assistant: A Machine Learning-Based Wearable Solution for Cognitive Support and Monitoring
    CS Kumar, P Hema, B Amitha, V Chandana, KK Nandini, AK Pandey, ...
    Intelligent and Sustainable Power and Energy Systems, 230-237 , 2026
    2026
  • Performance Analysis and Fabrication of a Flexible Piezoresistive Strain Sensor by utilizing CNT-Based Nanocomposites
    P Hema, AK Pandey, KK Nandini, S Kumar
    2025 IEEE 2nd International Conference on Green Industrial Electronics and … , 2025
    2025
  • Tunnel Technique with Connective Tissue Graft for Root Coverage of Teeth with Restored Cervical Lesions: Case Report
    KN Dharsana, P Hema, SM Kumar, SA Kumar
    Asian Journal of Dental Sciences 8 (1), 374-378 , 2025
    2025
  • Design of smart pest detector and harvest insight rover
    P Hema, SA Kumar, R Devanand, R Dhanush, M Dharani
    AIP Conference Proceedings 3300 (1), 020182 , 2025
    2025
  • Predicting home appliance electricity usage in low energy consumption houses with high accuracy using SVR and BP-ANN machine learn
    M Aruna, N Ashwini, P Hema, VJ Kolla, KU Singh, SS Kumar
    Challenges in Information, Communication and Computing Technology, 587-591 , 2024
    2024
    Citations: 1
  • Analysis of Graph Inverses and Algebraic Connectivity in a Systematic Way
    DNV Dr. R. Stella Maragatham1* , Dr. B. Pardha Saradhi2 , Dr. P. Aparna3 ...
    Communications on Applied Nonlinear Analysis 32, 525-538 , 2024
    2024
  • Effectiveness of Oral Health Education Among Visually Challenged Children using Oral and Braille-A Comparative Study
    P Hema, S Ganesan, E Ahila, S Thirumalai, SM Kumar
    Indian Journal of Dental Research 35 (4), 399-402 , 2024
    2024
    Citations: 1
  • 20 Epileptic Seizure
    P Hema, R Vanithamani
    Industry 5.0 for Smart Healthcare Technologies: Utilizing Artificial … , 2024
    2024
  • A Comprehensive Review of Epileptic Seizure Prediction using Medical Internet of Things
    P Hema, R Vanithamani
    2022 International Conference on Power, Energy, Control and Transmission … , 2022
    2022
    Citations: 1
  • Robust soft sensor systems for industry: Evaluated through real-time case study
    P Hema, E Sathish, M Maheswari, A Khosla, B Pant, MR Ambethkar
    Measurement: Sensors 24, 100542 , 2022
    2022
    Citations: 5
  • Semilunar Vestibular Incision Technique for Treatment of Multiple Gingival Recession in Maxillary Teeth-An Evaluative Study
    P Hema, P Balu, S Kumar, G Haritheertham, S Thirumalai, E Ahila
    Indian Journal of Dental Research 33 (4), 363-366 , 2022
    2022
  • A comprehensive review on wireless body area network-technologies, challenges, application and energy saving techniques
    S Menaga, R Vanithamani, P Hema
    2022 3rd International Conference on Electronics and Sustainable … , 2022
    2022
    Citations: 17
  • Application of RAM in Dual-Hesitant Fuzzy Transportation Problem.
    H Fathima, S Devi, SK Prabha, P Hema, S Sangeetha
    Journal of Algebraic Statistics 13 (2) , 2022
    2022
    Citations: 2
  • Measurement: Sensors
    P Hema, E Sathish, M Maheswari, A Khosla, B Pant, MR Ambethkar
    Measurement 24, 100542 , 2022
    2022
  • COEFFICIENT BOUNDS ALONGWITH THEIR EXTREMAL FUNCTIONS MAKING RESULTS SHARP FOR CERTAIN SUBCLASSES OF ANALYTIC FUNCTIONS USING SUBORDINATION METHOD
    DPHDG Singh
    Advances in Mechanics 10 (1), 1478-1486 , 2022
    2022
  • WITHDRAWN: Fuzzy graph theory in coloring graph
    S Sangeetha, P Hema, N Selvarani, P Geetha, P Karthikeyan, SG Kumar
    Materials Today: Proceedings , 2021
    2021
    Citations: 11
  • Geometric mean with Pythagorean fuzzy transportation problem
    SK Prabha, S Sangeetha, P Hema, M Basheer, G Veeramala
    Turkish journal of computer and mathematics education 12 (7), 1171-1176 , 2021
    2021
    Citations: 18
  • Unbalanced ftp with circumcenter of centroids and heuristic method
    SK Prabha, P Hema, S Sangeetha, S Sreedevi, T Guhan, VJ Pillai
    Annals of the Romanian Society for Cell Biology 25 (1), 5672-5684 , 2021
    2021
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • Geometric mean with Pythagorean fuzzy transportation problem
    SK Prabha, S Sangeetha, P Hema, M Basheer, G Veeramala
    Turkish journal of computer and mathematics education 12 (7), 1171-1176 , 2021
    2021
    Citations: 18
  • A comprehensive review on wireless body area network-technologies, challenges, application and energy saving techniques
    S Menaga, R Vanithamani, P Hema
    2022 3rd International Conference on Electronics and Sustainable … , 2022
    2022
    Citations: 17
  • WITHDRAWN: Fuzzy graph theory in coloring graph
    S Sangeetha, P Hema, N Selvarani, P Geetha, P Karthikeyan, SG Kumar
    Materials Today: Proceedings , 2021
    2021
    Citations: 11
  • Contra nI∗ µ-continuity
    S Ganesan, P Hema, S Jeyashri, C Alexander
    Asia Mathematika 4 (2), 127-133 , 2020
    2020
    Citations: 6
  • Robust soft sensor systems for industry: Evaluated through real-time case study
    P Hema, E Sathish, M Maheswari, A Khosla, B Pant, MR Ambethkar
    Measurement: Sensors 24, 100542 , 2022
    2022
    Citations: 5
  • Role of immunology in periodontal disease: a brief review
    V Kumar, R Arvina, KS Sivaranjani, P Hema, A Varghese
    Journal of Scientific Dentistry 8 (2), 25-28 , 2020
    2020
    Citations: 4
  • Application of RAM in Dual-Hesitant Fuzzy Transportation Problem.
    H Fathima, S Devi, SK Prabha, P Hema, S Sangeetha
    Journal of Algebraic Statistics 13 (2) , 2022
    2022
    Citations: 2
  • Unbalanced ftp with circumcenter of centroids and heuristic method
    SK Prabha, P Hema, S Sangeetha, S Sreedevi, T Guhan, VJ Pillai
    Annals of the Romanian Society for Cell Biology 25 (1), 5672-5684 , 2021
    2021
    Citations: 2
  • Genetic Aspects of Chronic and Aggressive Periodontitis
    KS Sivaranjani, VKB Na, R Arvina, P Hema
    Journal of Scientific Dentistry 8 (2), 61-68 , 2020
    2020
    Citations: 2
  • Fixed coefficients for a subclass of spirallike functions
    G Balachandar, P Hema
    International Journal of Mathematics Trends and Technology-IJMTT 58 , 2018
    2018
    Citations: 2
  • Predicting home appliance electricity usage in low energy consumption houses with high accuracy using SVR and BP-ANN machine learn
    M Aruna, N Ashwini, P Hema, VJ Kolla, KU Singh, SS Kumar
    Challenges in Information, Communication and Computing Technology, 587-591 , 2024
    2024
    Citations: 1
  • Effectiveness of Oral Health Education Among Visually Challenged Children using Oral and Braille-A Comparative Study
    P Hema, S Ganesan, E Ahila, S Thirumalai, SM Kumar
    Indian Journal of Dental Research 35 (4), 399-402 , 2024
    2024
    Citations: 1
  • A Comprehensive Review of Epileptic Seizure Prediction using Medical Internet of Things
    P Hema, R Vanithamani
    2022 International Conference on Power, Energy, Control and Transmission … , 2022
    2022
    Citations: 1
  • The Study of Strategic form of Repeated Game Theory
    V Vinoba, P Hema
    International Journal of Emerging Technology and Advanced Engineering 6 (4) , 2016
    2016
    Citations: 1
  • Optimized Seizure Detection in EEG Using Dual‐Branch Feature Fusion and Machine Learning Technique
    P Hema, V R
    Developmental Neurobiology 86 (2), e70014 , 2026
    2026
  • Coronally advanced flap for treatment of multiple gingival recession in maxillary teeth–A Evaluative study
    P Hema, S Mageshkumar, M Ebenezer
    European Journal of Dental Research 3 (1), 1-1 , 2026
    2026
  • Alzheimer's Care Assistant: A Machine Learning-Based Wearable Solution for Cognitive Support and Monitoring
    CS Kumar, P Hema, B Amitha, V Chandana, KK Nandini, AK Pandey, ...
    Intelligent and Sustainable Power and Energy Systems, 230-237 , 2026
    2026
  • Performance Analysis and Fabrication of a Flexible Piezoresistive Strain Sensor by utilizing CNT-Based Nanocomposites
    P Hema, AK Pandey, KK Nandini, S Kumar
    2025 IEEE 2nd International Conference on Green Industrial Electronics and … , 2025
    2025
  • Tunnel Technique with Connective Tissue Graft for Root Coverage of Teeth with Restored Cervical Lesions: Case Report
    KN Dharsana, P Hema, SM Kumar, SA Kumar
    Asian Journal of Dental Sciences 8 (1), 374-378 , 2025
    2025
  • Design of smart pest detector and harvest insight rover
    P Hema, SA Kumar, R Devanand, R Dhanush, M Dharani
    AIP Conference Proceedings 3300 (1), 020182 , 2025
    2025