J SRIDHAR

@sietk.org

ASSOCIATE PROFESSOR AND CSE DEPARTMENT
SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY

J SRIDHAR


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https://researchid.co/sridharcse
9 yearsTeaching experience

EDUCATION

Ph.D in Computer science and engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science, Information Systems, Computer Science Applications
22

Scopus Publications

244

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Repairable Resilient Data Search: Forward Secure Attribute Encryption for IoT cloud security
    J. Sridhar, M. Giri, K. Gayathri, K. Yamini, K. Yaswanth, et al.
    Conference Proceedings 2025 4th International Conference on Advances in Computing Communication Embedded and Secure Systems Access 2025, 2025
  • Enhance the Context-Based Online Recommendation System using Deep Reccurrent Neural Network with Enhaned Pigeon Search Optimization
    A Suresh, J Sridhar, R M Mallika, D Nagaraju, G Indiravathi
    IEEE International Conference on Recent Advances in Science and Engineering Technology Icraset 2024, 2024
    Most research in the area of Recommendation Systems (RS) seeks to improve quality by applying multiple methodologies. The main objective is to improve predictive performance while disregarding other design objectives, including the environment of a patient’s article. As a result, at numerous levels, a learning-based RS was proposed in this research. It is an efficient RS to improve the smallest amount of error during suggestion. The information started with the Python framework. Following preprocessing, the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm was used to present the extracted and contextual information from each preprocessing evaluation. The resulting characteristics were used as an entry for density-based clustering, which groups client evaluations into negative, neutral and favourable attitudes. Each item had an uncertain chance of being appreciated by a customer. The effectiveness of the recommendation system was measured according to its regrets, using an Oracle method that would know the probability of a benchmark. The hybrid Deep Recurring Neural Network- Enhanced Pigeon Search Optimization (DRNN-EPSO) method has been used to initialize the Recurrent Neural Network (RNN) modeling input variables. Also, the article used RNN, logistic regression, Multi-Layer Perceptron (MLP) and other supervised learning methods. Our study indicates the weighting factor of the various components of disappointment (i) the element emerging from the restriction of not trying to present the very same product to the very same consumer 2 times, (ii) the element emerging from having to learn the opportunities consumers like goods, & lastly the element emerging from having to learn the internal structure. The proposed model’s performance was measured using correctness, specificity, & recall measures, and it is contrasted latest systems. The proposed model has an average accuracy of $99.6 \\%$, which would be more accurate than previous machine learning techniques.
  • A Stock Price Prediction Model Based On Investor Sentiment and Lexical Data Analysis (Lda)
    J. Sridhar, M. P. Kumar, Madhuranthakam Anusha, Rupuneni Charitha, Karjala Chirudeep, et al.
    Proceeding of 2024 International Conference on Communication Computing and Energy Efficient Technologies I3ceet 2024, 2024
    Internet finance’s growth has sparked interest in investing, especially in the stock market, which is complex due to its data volume and volatility. Accurate stock price prediction is crucial to manage risks and enhance returns, leading scholars to use statistical methods to create linear models for stock price trends. The methodology integrates sentiment analysis, lexical data analysis, and intelligent algorithms.
  • InterOperative Biopsy Site Relocalization in Endoscope for Gastrointestinal tract using Deep Learning
    J. Sridhar, B. Pavan Kumar, G Soumya, A V Saravanan, A Surendra, et al.
    2024 5th IEEE Global Conference for Advancement in Technology Gcat 2024, 2024
    Gastric cancer (GC) is a common and deadly tumor with poor prognosis. Early detection uses endoscopy, and further treatment requires pathological confirmation and CT scanning. AI systems can help due to a lack of pathologists globally. Most GCs have genetic instability, an early gastric cancer sign. A new classification system based on histology, genotype, and molecular phenotype aids early diagnosis, prevention, and treatment. The project uses deep learning, especially Gastronet, to assist in GC diagnosis, offering high accuracy without extra tests.
  • Enhancing Dental X-Ray Segmentation Using Deep Learning
    B. Sarvesan, J. Sridhar, S Soumya, Vaddi Tejaswini, Gopi Yamini, et al.
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
    Dental X-ray image analysis plays a crucial role in diagnosing periodontal diseases, which significantly impact oral health. In this approach, we propose a hybrid deep learning Model for classifying dental X-ray images into periodontal and non-periodontal categories. Our method combines the strengths of VGG16 and MobileNet architectures, leveraging VGG's robust feature extraction capabilities and MobileNet's efficiency. The hybrid model is trained end-to-end, fine-tuning the convolutional base of VGG while preserving its early layers. We evaluate the model's performance on a dataset comprising periodontal and non-periodontal images, achieving competitive results in terms of accuracy and generalization. Our approach demonstrates promising potential for assisting dental professionals in early detection and classification of periodontal diseases, contributing to improved patient care and treatment planning in dental healthcare.
  • Gastric Disease Determination Using Advanced Deep Learning
    K. Sangeetha, D Gokulakrishnan, J. Sridhar, N. Shanthi, C. Vijayalakshmi, et al.
    2022 1st International Conference on Computer Power and Communications Iccpc 2022 Proceedings, 2022
    Gastric cancer is perhaps the most widely recognized harmful cancers with unfortunate prognostic outcome. Endoscopic assessment is primarily used for early recognition, while obsessive affirmation and computed tomography scanning are proposed for additional treatment. Gastric cancer growth stays as one of the dangerous cancers with unfortunate forecast. The overall lack of pathologists offers a one kind of chance for the utilization of artificial intelligence assistance system to help frameworks to ease the responsibility and increment diagnostic accuracy. Most gastric cancer shows hereditary instability, either micro satellite precariousness or chromosomal precariousness, which is viewed as an early stage in gastric carcinogenesis. Contemporary classification of gastric cancer in view of histological highlights, genotypes and subatomic phenotypes assists better with understanding the qualities of each subtype, and work on early analysis, anticipation and treatment. This task fosters a strategy utilizing deep learning algorithms to anticipate the health issues like ulcer, heartburn, indigestion and nausea which includes various tests to show up the end. Progressed algorithm, MIFNET is utilized to precisely analyze the presence of illness efficiently. MIFNET is a aggregation of three distinct algorithm, called as multi task net, fusion net and global net, the aggregation of which gives precise expectation of gastric cancer without any further diagnosis. A web application utilizes React.js will be produced for getting the contribution from the client and then showing the anticipated outcome. Hence, this proposed system helps in powerful determination of gastric cancer with greater accuracy than the existing system. Subsequently, this proposed work helps in successful analysis of Gastric Cancer in various parts of the stomach with greater accuracy than the existing system.
  • Implementing encounter level hierarchy for chronic disease
    International Journal of Scientific and Technology Research, 2019
  • Predicts chronic diseases using a patient's previous history
    J. Sridhar, Dr.K.P. Thooyamani, Dr.V. Khanaa, and
    International Journal of Engineering and Advanced Technology, 2019
    Early vicinity of preventable illnesses is crucial for better illness the administrators, progressed interventions, and logically gainful restorative administrations aid dispersion. Unique AI approachs were made to make use of statistics in digital health report for this errand. A variety of beyond undertakings, regardless, base on composed fields and loses the wonderful share of facts inside the unstructured notes. In this work we propose a trendy play out various undertakings framework for disorder beginning choice that joins both loose substance therapeutic notes and sorted out statistics. We take a gander at execution of modified sizeable mastering systems along with CNN, LSTM and unique leveled fashions. Rather than general substance based choice fashions, our gadget does not require sickness unequivocal factor fabricating, and might manage negations and numerical traits that exist in the substance. Our consequences on a buddy of around 1 million sufferers showcase that models the use of substance outmaneuver models the usage of simply composed statistics, and that fashions match for the usage of numerical characteristics and nullifications inside the substance, in spite of the hard substance, similarly improve execution. Furthermore, we take a gander at changed popularity strategies for therapeutic experts to decipher version conjectures.
  • Effective monitoring of systems in LAN using virtual server network computing
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Novel approach for identifying bugs using text classification and information retrieval
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Disintegration and collection of stirring entity route based on choice gesture
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Mobile large data storage security in cloud computing environment-a new approach
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Vehicular cloud computing security issues and solutions
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • A class based knowledge rule system for measuring climate change
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • A novel economic framework for cloud and grid computing
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Thick client web application prototype
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • A novel approach for load balancing in diverse distributed computing environment
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Ecommerce transaction security challenges and prevention methods-new approach
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Secured study using efficient data storage techniques with digital forensics and decoy technology for multi owner, dynamic groups in the cloud
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • A retina support validation method by eye localization
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Various schemes for database encryption-a survey
    Journal of Chemical and Pharmaceutical Sciences, 2016
  • Secure mobile agents communication on intranet
    Journal of Chemical and Pharmaceutical Sciences, 2016

RECENT SCHOLAR PUBLICATIONS

  • Enhancing Cardiovascular Disease Prediction Through Deep Learning: Leveraging Retinal Images with CNN and MobileNet Architecture
    J Sridhar, AS Rishika, M Teja, JMA Dass, N Sreya, ST Kumar
    2026 International Conference on Data Science, Agents and Artificial … , 2026
    2026
  • SASF-ML: Scalable Adaptive Security Framework for Machine Learning
    J Sridhar, M Giri, ES Harshitha, MK Raja, N Govardhan, TD Sree
    2026 International Conference on Intelligent and Innovative Technologies in … , 2026
    2026
  • Repairable Resilient Data Search: Forward Secure Attribute Encryption for IoT cloud security
    J Sridhar, M Giri, K Gayathri, K Yamini, K Yaswanth, B Syam
    2025 4th International Conference on Advances in Computing, Communication … , 2025
    2025
    Citations: 7
  • InterOperative Biopsy Site Relocalization in Endoscope for Gastrointestinal tract using Deep Learning
    J Sridhar, BP Kumar, G Soumya, AV Saravanan, A Surendra, P Shruthi
    2024 5th IEEE Global Conference for Advancement in Technology (GCAT), 1-5 , 2024
    2024
  • Retracted: Gastric Disease Determination Using Advanced Deep Learning
    K Sangeetha, D Gokulakrishnan, J Sridhar, N Shanthi, C Vijayalakshmi, ...
    2022 International Conference on Computer, Power and Communications (ICCPC … , 2022
    2022
    Citations: 1
  • Retraction Notice: Gastric Disease Determination Using Advanced Deep Learning
    K Sangeetha, D Gokulakrishnan, J Sridhar, N Shanthi, C Vijayalakshmi, ...
    2022 International Conference on Computer, Power and Communications (ICCPC), 1-1 , 2022
    2022
  • Cloud privacy preserving for dynamic groups
    J Sridhar, M Sriram
    International Journal of Pure and Applied Mathematics 116 (8), 117-21 , 2017
    2017
    Citations: 7
  • Various Schemes for Database Encryption - A Survey
    S Pothumani, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 103-106 , 2016
    2016
    Citations: 2
  • A retina support validation method by eye localization
    J Sridhar, M Sriram, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 90-92 , 2016
    2016
  • Secured study Using Efficient Data Storage Techniques with Digital Forensics and Decoy Technology for Multi Owner, Dynamic Groups in the Cloud
    J Sridhar, M Sriram, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 85-89 , 2016
    2016
  • A novel approach for load balancing in diverse distributed computing environment
    SS Gowthem, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 73-76 , 2016
    2016
  • Thick client web application prototype
    SS Gowthem, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 69-72 , 2016
    2016
  • Ecommerce Transaction Security Challenges and Prevention Methods- New Approach
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 65-68 , 2016
    2016
    Citations: 49
  • Implementing dynamic query ordering in MPEG-4 for identifying forged video clip
    J Sridhar, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 64-65 , 2016
    2016
  • Effective monitoring of systems in LAN using virtual server network computing
    J Sridhar, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 181-183 , 2016
    2016
  • Secure mobile agents communication on intranet
    S Pothumani, M Sriram, J Sridhar, A Selvan G
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 32-35 , 2016
    2016
    Citations: 69
  • A novel economic framework for cloud and grid computing
    S Pothumani, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 29-31 , 2016
    2016
  • Novel approach for identifying bugs using text classification and information retrieval
    SS Gowthem, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 428-432 , 2016
    2016
  • Vehicular cloud computing security issues and solutions
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 424-427 , 2016
    2016
    Citations: 52
  • Mobile large data storage security in cloud computing environment-a new approach
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 420-423 , 2016
    2016
    Citations: 53

MOST CITED SCHOLAR PUBLICATIONS

  • Secure mobile agents communication on intranet
    S Pothumani, M Sriram, J Sridhar, A Selvan G
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 32-35 , 2016
    2016
    Citations: 69
  • Mobile large data storage security in cloud computing environment-a new approach
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 420-423 , 2016
    2016
    Citations: 53
  • Vehicular cloud computing security issues and solutions
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 424-427 , 2016
    2016
    Citations: 52
  • Ecommerce Transaction Security Challenges and Prevention Methods- New Approach
    N Priya, J Sridhar, M Sriram
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 65-68 , 2016
    2016
    Citations: 49
  • Repairable Resilient Data Search: Forward Secure Attribute Encryption for IoT cloud security
    J Sridhar, M Giri, K Gayathri, K Yamini, K Yaswanth, B Syam
    2025 4th International Conference on Advances in Computing, Communication … , 2025
    2025
    Citations: 7
  • Cloud privacy preserving for dynamic groups
    J Sridhar, M Sriram
    International Journal of Pure and Applied Mathematics 116 (8), 117-21 , 2017
    2017
    Citations: 7
  • Various Schemes for Database Encryption - A Survey
    S Pothumani, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 103-106 , 2016
    2016
    Citations: 2
  • Solving Problems of Library Management System
    S Pothumani, J Sridhar
    International Journal of Innovative Research in Computer and Communication … , 2015
    2015
    Citations: 2
  • A Survey on Applications of IWD Algorithm
    S Pothumani, J Sridhar
    International Journal of Innovative Research in Computer and Communication … , 2015
    2015
    Citations: 2
  • Retracted: Gastric Disease Determination Using Advanced Deep Learning
    K Sangeetha, D Gokulakrishnan, J Sridhar, N Shanthi, C Vijayalakshmi, ...
    2022 International Conference on Computer, Power and Communications (ICCPC … , 2022
    2022
    Citations: 1
  • Enhancing Cardiovascular Disease Prediction Through Deep Learning: Leveraging Retinal Images with CNN and MobileNet Architecture
    J Sridhar, AS Rishika, M Teja, JMA Dass, N Sreya, ST Kumar
    2026 International Conference on Data Science, Agents and Artificial … , 2026
    2026
  • SASF-ML: Scalable Adaptive Security Framework for Machine Learning
    J Sridhar, M Giri, ES Harshitha, MK Raja, N Govardhan, TD Sree
    2026 International Conference on Intelligent and Innovative Technologies in … , 2026
    2026
  • InterOperative Biopsy Site Relocalization in Endoscope for Gastrointestinal tract using Deep Learning
    J Sridhar, BP Kumar, G Soumya, AV Saravanan, A Surendra, P Shruthi
    2024 5th IEEE Global Conference for Advancement in Technology (GCAT), 1-5 , 2024
    2024
  • Retraction Notice: Gastric Disease Determination Using Advanced Deep Learning
    K Sangeetha, D Gokulakrishnan, J Sridhar, N Shanthi, C Vijayalakshmi, ...
    2022 International Conference on Computer, Power and Communications (ICCPC), 1-1 , 2022
    2022
  • A retina support validation method by eye localization
    J Sridhar, M Sriram, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 90-92 , 2016
    2016
  • Secured study Using Efficient Data Storage Techniques with Digital Forensics and Decoy Technology for Multi Owner, Dynamic Groups in the Cloud
    J Sridhar, M Sriram, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 85-89 , 2016
    2016
  • A novel approach for load balancing in diverse distributed computing environment
    SS Gowthem, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 73-76 , 2016
    2016
  • Thick client web application prototype
    SS Gowthem, M Sriram, J Sridhar
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 69-72 , 2016
    2016
  • Implementing dynamic query ordering in MPEG-4 for identifying forged video clip
    J Sridhar, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (3), 64-65 , 2016
    2016
  • Effective monitoring of systems in LAN using virtual server network computing
    J Sridhar, KP Thooyamani
    Journal of Chemical and Pharmaceutical Sciences 9 (2), 181-183 , 2016
    2016

Publications

17 publication in scopus

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

3 patents