Engineering, Electrical and Electronic Engineering, Sensory Systems, Biomedical Engineering
10
Scopus Publications
151
Scholar Citations
4
Scholar h-index
3
Scholar i10-index
Scopus Publications
An efficient model for diabetic detection using heuristic approach based serial cascaded convolutional ensemble network Santosh Kumar Bejugam, Jyothi Vankara Artificial Intelligence Review, 2025 Diabetes is a chronic pathology that poses significant risks to people. If diabetes is not properly diagnosed and treated, it may contribute to serious health problems. Delayed diagnosis causes many health issues and leads to numerous deaths every year. So, researchers have developed efficient diabetes detection systems for the early detection of this pathology. However, the existing model raises serious issues about the security and privacy of private medical information, and it requires rigorous safety precautions to prevent intrusions and unapproved access. In addition, the unclear characteristics of existing models cause difficulty in healthcare facilities. Thus, the advanced deep learning-based diabetic detection model was designed in this work to overcome these challenges. Also, it aims to detect diabetics and helps to prevent the progression of diabetes in patients. At first, the required data is gathered from the online data source and then fed to the optimal feature selection phase. Here, the features and weight are optimally selected using the Fitness-based Billiards-Inspired Optimization (FBIO) algorithm. This process helps the model to focus on the most impactful information within the data. Further, the obtained optimal weighted feature is passed to the Serial Cascaded Convolutional Ensemble Network (SCCEN) for detection. Here, the SCCEN model serially cascades techniques such as Convolutional Autoencoder (CAE), “1-dimensional Convolutional Neural Network” (1DCNN), and “Convolutional Long Short-Term Memory” (ConvLSTM). This process helps to improve the detection accuracy. Finally, the designed approach’s effectiveness is analyzed by comparing its performance with existing techniques. The suggested approach’s accuracy for dataset-1 is 97.4%, dataset-2 is 97.31%, and dataset-3 is 96.69%, which is higher than the conventional techniques and optimization algorithms. Thus, the result proved that the introduced framework can detect diabetics in premature stages and help the patient to take suitable treatment.
Development of a MEMS-based Piezoresistive Cantilever Sensor for Lead (Pb(II)) Detection in Drinking Water Jyothi Vankara, Rajesh Kumar Burra Engineering Technology and Applied Science Research, 2024 One of the most hazardous pollutants of natural water resources is lead -Pb (II)- which poses a significant threat to human health and environmental safety. The accumulation of this heavy metal in an organism affects a number of systems and is particularly dangerous for children. At low levels of intake over short periods, it induces diarrhea, abdominal pain, and renal damage, with the potential for fatal outcomes in extreme cases. The principal sources of lead pollution are industries, coal-fired power plants and motor vehicles. In response to the critical demand for effective lead detection, researchers have developed advanced Micro-Electromechanical Systems (MEMS) piezoresistive cantilever sensors that make use of the chelating properties of Ethylenediaminetetraacetic Acid (EDTA) and the superior electrical properties of reduced Graphene Oxide (rGO). It has been proven that this composite can be effectively immobilized on a MEMS cantilever surface, enabling the selective removal of Pb (II) ions from wastewater. This adsorption process exerts stress on the surface of the cantilever, resulting in variations in resistance that can subsequently be measured. A sensitive and selective MEMS piezoresistive cantilever sensor for Pb (II) has been developed, offering significant potential as a lead monitoring tool in water samples. The sensor demonstrated high sensitivity and selectivity, with a detection limit of 1 ppb and a linear response range of 10-100 ppb. This novel approach has the potential to significantly enhance pollution monitoring and provide substantial benefits for public health by enabling real-time, on-site mapping of lead contamination across aqueous environments. This technological advancement in the environmental surveillance domain offers a new perspective on the safety of water and the reduction of potential health hazards associated with lead consumption.
Diabetes Prediction using Deep Ensemble Network Santosh Kumar Bejugam, Jyothi Vankara 2024 International Conference on Decision Aid Sciences and Applications Dasa 2024, 2024 Timely diabetes detection is crucial for effective management and minimizing complications. This research presents a novel framework for early diabetes diagnosis, combining DeepEnsembleNet's capabilities with a hybrid optimization strategy. The methodology begins with robust data preprocessing, addressing missing values and outliers through advanced statistical techniques. A comprehensive feature extraction process uncoveres key insights, leveraging statistical measures and correlation analysis. Feature selection is optimized using Hybrid Immunity League Championship Algorithm (HILCA), a tailored approach integrating bio-inspired optimization techniques. The DeepEnsembleNet architecture seamlessly integrates multiple neural network types to accommodate diverse data modalities. Extensive experimentation and hyperparameter tuning have yielded promising results, demonstrating the model's potential for accurate early diabetes detection. By concurrently optimizing feature selection and hyperparameters, this hybrid approach enhances overall performance. This innovation holds significant promise for improving diabetes treatment outcomes and enhancing patient quality of life.
Diabetic prediction framework using optimisation strategy via optimal weighted score-based deep ensemble network to support diabetic patients Santosh Kumar Bejugam, Jyothi Vankara International Journal of Bioinformatics Research and Applications, 2023 Diabetes is one of the dangerous diseases that increase blood glucose levels, and it affects the patient's life. Next, in the deep feature extraction stage, the collected data is employed as the input. Here, the deep features are extracted using one-dimensional convolutional neural network (1DCNN). Then, the acquired optimal features are offered as the input to intelligent deep ensemble network (IDENet) that holds the networks such as long short-term memory (LSTM), 1DCNN, deep temporal context networks (DTCN) and extreme learning (EL). The parameters of IDENet are tuned by enhanced light spectrum with horse herd optimisation (ELS-HHO). Further, the attained predicted values from the IDENet are fed as the input to the weighted fusion of predicted values. Then, their weights are tuned by ELS-HHO to attain the effective glucose prediction outcome. Finally, the suggested glucose prediction model secured a better prediction rate than the classical glucose prediction models in experimental observation.
A survey of MEMS cantilever applications in determining volatile organic compounds Suresh Vasagiri, Rajesh Kumar Burra, Jyothi Vankara, M.S. Pradeep Kumar Patnaik Aip Advances, 2022 Recently, microelectromechanical system (MEMS) cantilevers have received significant interest in the domain of Volatile Organic Compounds (VOCs). An analysis of MEMS cantilevers in VOCs is presented in this Review. It examines the different forms of sensors used to detect VOCs. It goes into the conditions that influence MEMS and the strategies used for VOC sensing. It examines research on MEMS cantilevers and other VOC sensing and detection techniques. It shows how MEMS can be used to detect VOCs. Moreover, it presents a comparative study based on the objectives, types of sensors employed, merits, and shortcomings of existing works. This Review intends to explore MEMS cantilevers in VOCs for supporting further research and applications.
Parameter Extraction for Tremor Signals Santosh Kumar Bejugam, Jyothi V 2020 5th IEEE International Conference on Emerging Electronics Icee 2020, 2020 Tremor is an involuntary movement of limbs that occurs with certain neurological disorders. The neurological disorders include Parkinson's disease, Huntington disease, spino cerebellar degenerations, etc., In all these diseases the limbs of the patient move involuntarily and rhythmically. It can affect any part of the body either one side or both the sides symmetrically. The neuro physician during the assessment of the patient depends on video-grapy or Electromyography or both. Even then the physician does not get the complete information, as these techniques are very primitive, apart from being uneconomical. Also they require lot of time for recording and analysis. Even the information preservation also becomes difficult. In certain cases, the physician mainly depends on the feedback from the patient. In order to overcome these difficulties and also to reduce the time and even cost, a technique has been proposed and implemented. The technique involves recording the tremor using a tri-axial accelerometer, which can be fastened to the limb, where the measurements need to be recorded. The analog output from the accelerometer is amplified and fed to a microcontroller for onward transmission of the sampled values to PC. In PC a Matlab program acquires these samples and processes the same for amplitude and frequency related information. The data was obtained from 15 patients having various neurological disorders and a set of 10 controlled groups is also considered. Both the group's data have been analyzed and the results are reported.
Effect of added mass using resonant peak shifting technique Rajesh Kumar Burra, Jyothi Vankara, D. V. Rama Kota Reddy Journal of Micro Nanolithography MEMS and Moems, 2012 Microcantilever is the fundamental structure for the realization of a microelectromechanical systems sensor with higher sensitivity and selectivity in a number of fields like biomedical, defense, and environmental. Present research is also focusing on the applications of microcantilever in the field of food industry. Among the two fundamental techniques for microcantilever, deflection and resonant peak shift, it was proven that the latter one is the best suited for added mass detection. In our study, we derive an analytical expression for δm based on the shift in frequency (δf') that accounts for the elasticity of the added mass and the location of the mass on the beam. In particular, we create a finite element methods model of our system in a commercial package, COMSOL (Bangalore, India), and carry out modal analysis for the cantilever beam resonator with and without the added mass, varying the relative stiffness and mass of the two components (the cantilever beam and the added mass), to compare the results of shift in resonant frequency with those obtained from rigid mass models. The results show the effect of elasticity clearly in certain ranges of relative stiffness and mass.
RECENT SCHOLAR PUBLICATIONS
An efficient model for diabetic detection using heuristic approach based serial cascaded convolutional ensemble network SK Bejugam, J Vankara Artificial Intelligence Review 58 (10), 333 , 2025 2025 Citations: 3
Diabetes Prediction using Deep Ensemble Network SK Bejugam, J Vankara 2024 International Conference on Decision Aid Sciences and Applications … , 2024 2024 Citations: 2
Development of a MEMS-based piezoresistive cantilever sensor for lead (Pb (II)) detection in drinking water J Vankara, RK Burra Engineering, Technology & Applied Science Research 14 (5), 17330-17336 , 2024 2024 Citations: 2
Diabetic prediction framework using optimisation strategy via optimal weighted score-based deep ensemble network to support diabetic patients SK Bejugam, J Vankara International Journal of Bioinformatics Research and Applications 19 (5-6 … , 2023 2023
A survey of MEMS cantilever applications in determining volatile organic compounds S Vasagiri, RK Burra, J Vankara, MS Kumar Patnaik AIP Advances 12 (3) , 2022 2022 Citations: 63
Design a T-Shape Cantilever Beam Using by Scilab and COMSOL V Suresh, B Rajesh Kumar, V Jyothi Proceedings of International Conference on Communication, Circuits, and … , 2021 2021
Effect of insertion force for successful penetration of a conical shaped microneedle into the skin G Aswani Kumar, B Rajesh Kumar, V Jyothi, S Injeti Trends in Mechanical and Biomedical Design: Select Proceedings of ICMechD … , 2020 2020 Citations: 3
Design of MEMS cantilever sensors for identification of VOCs using IntelliSuite SSS Srikanth, BR Kumar, V Suresh, V Jyothi, IS Rao, GA Kumar Materials Today: Proceedings 22, 3162-3170 , 2020 2020 Citations: 7
Design and Simulation of Platinum Micro Heater for VOC sensing Applications S Srikanth, BR Kumar, V Suresh, V Jyothi International Journal of Innovative Technology and Exploring Engineering … , 2019 2019 Citations: 2
Analysis of Mass Based Micro Cantilever Using Comsol J Gayathri¹, BR Kumar, V Jyothi 2015
Design & Simulation of MEMS Accelerometer Using COMSOL Multiphysics Software N Divya, V Jyothi, B Rajesh Kumar 2015 Citations: 3
Design of power generation unit using roller mechanism BS Sarma, V Jyothi, D Sudhir IOSR J. Electr. Electron. Eng 9 (3), 55-60 , 2014 2014 Citations: 40
Extraction of information from PCG signal using LabVIEW M Urekha, BR Kumar, V Jyothi International Journal of Engineering Science and Technology 6 (4), 111 , 2014 2014
Effect of added mass using resonant peak shifting technique RK Burra, J Vankara, DVRK Reddy Journal of Micro/Nanolithography, MEMS, and MOEMS 11 (2), 021203-021203 , 2012 2012 Citations: 4
Image fusion using evolutionary algorithm (GA) V Jyothi, BR Kumar, PK Rao, DVRK Reddy Int. J. Comp. Tech. Appl. 2 (2), 322-326 , 2011 2011 Citations: 22
MOST CITED SCHOLAR PUBLICATIONS
A survey of MEMS cantilever applications in determining volatile organic compounds S Vasagiri, RK Burra, J Vankara, MS Kumar Patnaik AIP Advances 12 (3) , 2022 2022 Citations: 63
Design of power generation unit using roller mechanism BS Sarma, V Jyothi, D Sudhir IOSR J. Electr. Electron. Eng 9 (3), 55-60 , 2014 2014 Citations: 40
Image fusion using evolutionary algorithm (GA) V Jyothi, BR Kumar, PK Rao, DVRK Reddy Int. J. Comp. Tech. Appl. 2 (2), 322-326 , 2011 2011 Citations: 22
Design of MEMS cantilever sensors for identification of VOCs using IntelliSuite SSS Srikanth, BR Kumar, V Suresh, V Jyothi, IS Rao, GA Kumar Materials Today: Proceedings 22, 3162-3170 , 2020 2020 Citations: 7
Effect of added mass using resonant peak shifting technique RK Burra, J Vankara, DVRK Reddy Journal of Micro/Nanolithography, MEMS, and MOEMS 11 (2), 021203-021203 , 2012 2012 Citations: 4
An efficient model for diabetic detection using heuristic approach based serial cascaded convolutional ensemble network SK Bejugam, J Vankara Artificial Intelligence Review 58 (10), 333 , 2025 2025 Citations: 3
Effect of insertion force for successful penetration of a conical shaped microneedle into the skin G Aswani Kumar, B Rajesh Kumar, V Jyothi, S Injeti Trends in Mechanical and Biomedical Design: Select Proceedings of ICMechD … , 2020 2020 Citations: 3
Design & Simulation of MEMS Accelerometer Using COMSOL Multiphysics Software N Divya, V Jyothi, B Rajesh Kumar 2015 Citations: 3
Diabetes Prediction using Deep Ensemble Network SK Bejugam, J Vankara 2024 International Conference on Decision Aid Sciences and Applications … , 2024 2024 Citations: 2
Development of a MEMS-based piezoresistive cantilever sensor for lead (Pb (II)) detection in drinking water J Vankara, RK Burra Engineering, Technology & Applied Science Research 14 (5), 17330-17336 , 2024 2024 Citations: 2
Design and Simulation of Platinum Micro Heater for VOC sensing Applications S Srikanth, BR Kumar, V Suresh, V Jyothi International Journal of Innovative Technology and Exploring Engineering … , 2019 2019 Citations: 2
Diabetic prediction framework using optimisation strategy via optimal weighted score-based deep ensemble network to support diabetic patients SK Bejugam, J Vankara International Journal of Bioinformatics Research and Applications 19 (5-6 … , 2023 2023
Design a T-Shape Cantilever Beam Using by Scilab and COMSOL V Suresh, B Rajesh Kumar, V Jyothi Proceedings of International Conference on Communication, Circuits, and … , 2021 2021
Analysis of Mass Based Micro Cantilever Using Comsol J Gayathri¹, BR Kumar, V Jyothi 2015
Extraction of information from PCG signal using LabVIEW M Urekha, BR Kumar, V Jyothi International Journal of Engineering Science and Technology 6 (4), 111 , 2014 2014
