Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications
7
Scopus Publications
89
Scholar Citations
5
Scholar h-index
3
Scholar i10-index
Scopus Publications
Cat swarm optimized tumor segmentation and an ensemble model for glioblastoma patient survival prediction Bhagyalaxmi K Sigma Journal of Engineering and Natural Sciences, 2025 Glioblastoma is characterized as the most common and lethal primary brain tumor among adults, glioblastoma is associated with enormous clinical management challenges due to its high rate of recurrence, poor prognosis and underlying complexity.Here we propose a study to improve the prediction of overall survival in GBM patients treated with stereotactic radiosurgery using advanced image segmentation and machine learning techniques.In this paper, we propose a novel fusion of Cat Swarm Optimization based hybrid ResNet and U-Net models to achieve an accurate segmentation of the tumor as well as an ensemble of machine learning algorithms for survival prediction enabling us to overcome limitations of conventional techniques.We demonstrate that on the BraTS2020 related regions we are able to produce almost perfect segmentations with metrics, like 99.2% segmentation accuracy,loss of 0.023, recall of0.986, a mean intersection over union (IOU) of 0.991, a dice coefficient of 0.96, a precision of 0.991, a sensitivity of 0.991, and a specificity of 0.997.For in the field of survival prediction we looked at many machine learning models which we found out that the Random Forest did an outstanding job at handling the complex issues presented by the segmented images.Also we saw that the Ensemble method did very well in this area which we report to have achieved 60.01%accuracy.We present that which is the use of in depth image segmentation in combination with machine learning greatly improves results in Glioblastoma survival prediction.Also this approach does not only improve the prognostic accuracy but also brings to the table what may be game changing elements in clinical management and personalized treatment.
IoT-Based Humidity Sensing and Control in Smart Hospitals k-Nearest Neighbors for Infection Control and Patient Comfort K. Bhagya Laxmi, John Benito Jesudasan Peter, P. Rajalakshmi, K. Dhivya, Nilamadhab Mishra, S. Srinivasan 2024 1st International Conference on Innovations in Communications Electrical and Computer Engineering Icicec 2024, 2024 A novel method for monitoring and controlling humidity levels in smart hospital settings by means of the Internet of Things (IoT). To maximize patient comfort and infection control measures, IoT device connection allows for real-time humidity level monitoring and modification. Improving the system's responsiveness to humidity data is possible with the use of the k-Nearest Neighbors (KNN) algorithm. Machine learning (ML) method, the system can forecast the ideal relative humidity from past data and present weather. A major factor in preventing the spread of infectious diseases in healthcare facilities is keeping the relative humidity at an optimal level. The general health and success of the healing process depend on the patient's level of comfort. The proposed IoT system for smart hospital humidity management considers medical and patient needs. The system's capacity to dynamically adjust humidity levels based on data improves infection control and patient satisfaction.
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>
Mobile cloud computing using unpredictable queriable cryptography K. Bhagya Laxmi, B. J. Praveena, M. Priyanka Aip Conference Proceedings, 2022 This study looks at the safety issue of outsourcing user resources from the cloud. There is a specific combination encryption system to search for authenticated user information in the cloud. The framework facilitates parallel fused keyword searches besides matched performance, two essential considerations for realistic searchable encryption. A disorderly transformation approach is proposed to help stable indexing, preservation, and query fudge our keyword. A safe sharing list is also generated to identify the corresponding outcomes while protecting user data protection and privacy, saving user mobile device energy. Our strategy means that even the cloud vendor who is semi-trustful in our situation is privately protected for the customer. The suggested approach is intended to effectively recover the encrypted data stored remotely for mobile cloud scenarios using cryptography. Extensive tests are carried out, and test findings indicate that the proposed solution is reliable and ideal for a stable cloud server.
A secure incentive based waste monitoring system using IoT B. J. Praveena, K. Bhagyalaxmi, M. Priyanka Aip Conference Proceedings, 2022 The increase of waste generation has been considered a significant challenge to large urban centers worldwide and represents critical issues for countries with accelerated population growth like India. Many initiations have been taken by the government to maintain cleanliness but problem remains the same. Taking the problem into consideration, we propose a Secure Incentive based Waste monitoring system to encourage garbage segregation at the initial level. This waste segregation at initial level will make the recycling process easy and addresses major environmental issues. In this system, a weight detector is placed that checks the weight of the separated garbage thrown and displays the weight. If the weight exceeds the lower-limit then a QR code is being displayed which can be scanned with the Incentive application which can be stored as the rewards to the public. The government should consider these rewards at any government e-payments. This system mainly focuses on encouraging the public to utilize the dustbins than littering on the roadways. Privacy and Security of the public rewards can be maintained using Blockchain Technology.
RECENT SCHOLAR PUBLICATIONS
Cloud-Integrated XGBoost Model for Accurate Prediction of Pulmonary Fibrosis Progression V Vivekanandan, D Suriyakala, RJ Kannan, VG Sivakumar, ... 2025 10th International Conference on Communication and Electronics Systems … , 2025 2025
Cat swarm optimized tumor segmentation and an ensemble model for glioblastoma patient survival prediction K Bhagyalaxmi, B Dwarakanath Sigma 43 (5), 1592-1606 , 2025 2025
Glioma segmentation using hybrid filter and modified African vulture optimization B Kuntiyellannagari, B Dwarakanath Bulletin of Electrical Engineering and Informatics 14 (2), 1447-1455 , 2025 2025 Citations: 5
Detection Using CNN and Transfer Learning K Bhagyalaxmi, V Vennela, NT Reddy Advances in Machine Learning and Big Data Analytics I: ICMLBDA 2023, NIT … , 2025 2025
CDCG-UNet: Chaotic optimization assisted brain tumor segmentation based on dilated channel gate attention U-Net model K Bhagyalaxmi, B Dwarakanath Neuroinformatics 23 (2), 12 , 2025 2025 Citations: 10
Ensemble Model for Detection and Classification of Brain Tumors K Bhagyalaxmi, B Dwarakanath 2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024 2024
IoT-Based Humidity Sensing and Control in Smart Hospitals k-Nearest Neighbors for Infection Control and Patient Comfort KB Laxmi, JBJ Peter, P Rajalakshmi, K Dhivya, N Mishra, S Srinivasan 2024 First International Conference on Innovations in Communications … , 2024 2024 Citations: 1
Deep learning for multi-grade brain tumor detection and classification: a prospective survey K Bhagyalaxmi, B Dwarakanath, PVP Reddy Multimedia Tools and Applications 83 (25), 65889-65911 , 2024 2024 Citations: 33
Hybrid model for detection of brain tumor using convolution neural networks K Bhagyalaxmi, B Dwarakanath Computer Science and Information Technologies 5 (1), 84-90 , 2024 2024 Citations: 7
Hybrid model for brain tumor detection using convolution neural networks PVPR Bhagyalaxmi K , Bhoopalan Dwarakanath The Indonesian Journal of Electrical Engineering and Computer Science … , 2024 2024 Citations: 2
Ensemble of deep learning models and machine learning classifiers for the classification of brain tumors K Bhagyalaxmi, B Dwarakanath, PVP Reddy 2024 2nd International Conference on Computer, Communication and Control … , 2024 2024 Citations: 5
Dingo algorithm-based forwarder selection and huffman coding to improve authentication NU Bhanu, PB Priya, T Sajana, S Shanthi, M Mageshbabu, ... Indonesian Journal of Electrical Engineering and Computer Science 32 (1 … , 2023 2023 Citations: 18
Convolution Neural Networks K Bhagyalaxmi, B Dwarakanath International Conference on Machine Learning and Big Data Analytics, 131-139 , 2023 2023
Mobile cloud computing using unpredictable queriable cryptography KB Laxmi, BJ Praveena, M Priyanka AIP Conference Proceedings 2519 (1), 030078 , 2022 2022
A secure incentive based waste monitoring system using IoT BJ Praveena, K Bhagyalaxmi, M Priyanka AIP Conference Proceedings 2424 (1), 060002 , 2022 2022 Citations: 3
Security Enhancement with Smart Door Unlocking using Machine Learning KB Lakshmi, A Maddela, A Palvai, L Muppana i-manager's Journal on Image Processing 8 (1), 7 , 2021 2021
Face Detection and Recognition for Automatic Attendance System using Artificial Intelligence JSK Bhagyalaxmi Journal of Engineering Computing Architecture 10 (6), 43-56 , 2020 2020
Twitter Sentiment Analysis using Vader on Python CR D.Keerthi K.Bhagyalaxmi ,B.Yamini Journal of Engineering Technologies and Innovative Research 7 (5), 1025-1031 , 2020 2020 Citations: 5
Home Automation using MQTT server AM Neeraj P K.Bhagyalaxmi,D.Sai teja Reddy International journal of creative research thoughts 6 (1), 82-84 , 2018 2018
MOST CITED SCHOLAR PUBLICATIONS
Deep learning for multi-grade brain tumor detection and classification: a prospective survey K Bhagyalaxmi, B Dwarakanath, PVP Reddy Multimedia Tools and Applications 83 (25), 65889-65911 , 2024 2024 Citations: 33
Dingo algorithm-based forwarder selection and huffman coding to improve authentication NU Bhanu, PB Priya, T Sajana, S Shanthi, M Mageshbabu, ... Indonesian Journal of Electrical Engineering and Computer Science 32 (1 … , 2023 2023 Citations: 18
CDCG-UNet: Chaotic optimization assisted brain tumor segmentation based on dilated channel gate attention U-Net model K Bhagyalaxmi, B Dwarakanath Neuroinformatics 23 (2), 12 , 2025 2025 Citations: 10
Hybrid model for detection of brain tumor using convolution neural networks K Bhagyalaxmi, B Dwarakanath Computer Science and Information Technologies 5 (1), 84-90 , 2024 2024 Citations: 7
Glioma segmentation using hybrid filter and modified African vulture optimization B Kuntiyellannagari, B Dwarakanath Bulletin of Electrical Engineering and Informatics 14 (2), 1447-1455 , 2025 2025 Citations: 5
Ensemble of deep learning models and machine learning classifiers for the classification of brain tumors K Bhagyalaxmi, B Dwarakanath, PVP Reddy 2024 2nd International Conference on Computer, Communication and Control … , 2024 2024 Citations: 5
Twitter Sentiment Analysis using Vader on Python CR D.Keerthi K.Bhagyalaxmi ,B.Yamini Journal of Engineering Technologies and Innovative Research 7 (5), 1025-1031 , 2020 2020 Citations: 5
A secure incentive based waste monitoring system using IoT BJ Praveena, K Bhagyalaxmi, M Priyanka AIP Conference Proceedings 2424 (1), 060002 , 2022 2022 Citations: 3
Hybrid model for brain tumor detection using convolution neural networks PVPR Bhagyalaxmi K , Bhoopalan Dwarakanath The Indonesian Journal of Electrical Engineering and Computer Science … , 2024 2024 Citations: 2
IoT-Based Humidity Sensing and Control in Smart Hospitals k-Nearest Neighbors for Infection Control and Patient Comfort KB Laxmi, JBJ Peter, P Rajalakshmi, K Dhivya, N Mishra, S Srinivasan 2024 First International Conference on Innovations in Communications … , 2024 2024 Citations: 1
Cloud-Integrated XGBoost Model for Accurate Prediction of Pulmonary Fibrosis Progression V Vivekanandan, D Suriyakala, RJ Kannan, VG Sivakumar, ... 2025 10th International Conference on Communication and Electronics Systems … , 2025 2025
Cat swarm optimized tumor segmentation and an ensemble model for glioblastoma patient survival prediction K Bhagyalaxmi, B Dwarakanath Sigma 43 (5), 1592-1606 , 2025 2025
Detection Using CNN and Transfer Learning K Bhagyalaxmi, V Vennela, NT Reddy Advances in Machine Learning and Big Data Analytics I: ICMLBDA 2023, NIT … , 2025 2025
Ensemble Model for Detection and Classification of Brain Tumors K Bhagyalaxmi, B Dwarakanath 2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024 2024
Convolution Neural Networks K Bhagyalaxmi, B Dwarakanath International Conference on Machine Learning and Big Data Analytics, 131-139 , 2023 2023
Mobile cloud computing using unpredictable queriable cryptography KB Laxmi, BJ Praveena, M Priyanka AIP Conference Proceedings 2519 (1), 030078 , 2022 2022
Security Enhancement with Smart Door Unlocking using Machine Learning KB Lakshmi, A Maddela, A Palvai, L Muppana i-manager's Journal on Image Processing 8 (1), 7 , 2021 2021
Face Detection and Recognition for Automatic Attendance System using Artificial Intelligence JSK Bhagyalaxmi Journal of Engineering Computing Architecture 10 (6), 43-56 , 2020 2020
Home Automation using MQTT server AM Neeraj P K.Bhagyalaxmi,D.Sai teja Reddy International journal of creative research thoughts 6 (1), 82-84 , 2018 2018
