Application of SRF-PI Current Control in the Design of a Single-Phase Asymmetrical Inverter for Use in Weak Grid Environments
Keywords:
Single-Phase, Weak Grid Condition, Synchronous Reference Frame, Asymmetrical Inverter, PLL bandwidth
Abstract
The power stage circuit and control system of the ACHMI uses a dual-loop current control mechanism in the hybrid reference frame (HRF), a synchronous reference frame phase-locked loop (PLL), and a hybrid modulation technique to generate a multilevel output voltage. The complete ACHMI system's small-signal model is derived using a simple, step-by-step derivation approach. Small-signal analysis is used to linearize the ACHMI system, which yields a model of its impedance. In addition, a refined impedance stability criterion is developed and used to analyse the robustness of the system under investigation. By adjusting the PLL bandwidth, output power factor angle, and grid current reference signal amplitude in the presence of poor grid conditions, the ACHMI's stability can be evaluated. This research suggests a methodical design procedure for choosing the PLL proportional-integral (PI) controller to guarantee steady-state performance and dynamic response in an ACHMI system. Finally, the theoretical theory is verified by modelling and real findings from a scaled-down grid-connected ACHMI prototype system.
References
1. F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, “Overview of control and grid synchronisation for distributed power generation systems,” IEEE Transactions on Industrial Electronics., vol. 53, no. 5, pp. 1398-1409, Oct. 2006.
2. L. Harnefors, X. Wang, A. G. Yepes, and F. Blaabjerg, “Passivity-based stability assessment of grid-connected VSCs – an overview,” IEEE Journal of Emerging and Selected Topics in Power Electronics. vol. 4, no. 1, pp. 116-125, Mar. 2016.
3. M.Malinowski, K. Gopakumar, J. Rodriguez, andM. A. Perez, “A survey on cascaded multilevel inverters,” IEEE Transactions on Industrial Electronics., vol. 57, no. 7, pp. 2197–2206, Jul. 2010.
4. A. Ajami, M. R. J. Oskuee, M. T. Khosroshahi, and A. Mokhberdoran,“ Cascade-multi-cell multilevel converter with reduced number of switches,” IET Power Electronics, vol. 7, no. 3, pp. 552–558, Mar. 2014.
5. C. D. Townsend, T. J. Summers and R. E. Betz, “Multigoal Heuristic Model Predictive Control Technique Applied to a Cascaded H-bridge StatCom,” IEEE Transactions on Power Electronics., vol. 27, no. 3, pp. 1191-1200, March 2012.
6. Alarood, A. A., Faheem, M., Al‐Khasawneh, M. A., Alzahrani, A. I., & Alshdadi, A. A. (2023). Secure medical image transmission using deep neural network in e‐health applications. Healthcare Technology Letters, 10(4), 87-98.
7. Markkandeyan, S., Gupta, S., Narayanan, G. V., Reddy, M. J., Al-Khasawneh, M. A., Ishrat, M., & Kiran, A. (2023). Deep learning based semantic segmentation approach for automatic detection of brain tumor. International Journal of Computers Communications & Control, 18(4).
8. Al-Khasawneh, M. A., Alzahrani, A., & Alarood, A. (2023). Alzheimer’s Disease Diagnosis Using MRI Images. In Data Analysis for Neurodegenerative Disorders (pp. 195-212). Singapore: Springer Nature Singapore.
9. Al-Khasawneh, M. A., Alzahrani, A., & Alarood, A. (2023). An Artificial Intelligence Based Effective Diagnosis of Parkinson Disease Using EEG Signal. In Data Analysis for Neurodegenerative Disorders (pp. 239-251). Singapore: Springer Nature Singapore.
10. Al-Khasawneh, M. A., Faheem, M., Aldhahri, E. A., Alzahrani, A., & Alarood, A. A. (2023). A MapReduce Based Approach for Secure Batch Satellite Image Encryption. IEEE Access.
11. K. Peddireddy, "Streamlining Enterprise Data Processing, Reporting and Realtime Alerting using Apache Kafka," 2023 11th International Symposium on Digital Forensics and Security (ISDFS), Chattanooga, TN, USA, 2023, pp. 1-4.
12. Kiran Peddireddy. Kafka-based Architecture in Building Data Lakes for Real-time Data Streams. International Journal of Computer Applications 185(9):1-3, May 2023.
13. Anitha Peddireddy, Kiran Peddireddy, "Next-Gen CRM Sales and Lead Generation with AI," International Journal of Computer Trends and Technology, vol. 71, no. 3, pp. 21-26, 2023.
14. Peddireddy, K., and D. Banga. "Enhancing Customer Experience through Kafka Data Steams for Driven Machine Learning for Complaint Management." International Journal of Computer Trends and Technology 71.3 (2023): 7-13.
15. S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Empowering Maxillofacial Diagnosis Through Transfer Learning Models,” in 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), 2023, pp. 728–732.
16. S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Enhancing Alzheimer Stage Classification of MRI Images through Transfer Learning,” in 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), 2023, pp. 733–737.
17. S. Degadwala, D. Vyas, K. N. Patel, M. Soni, P. P. Singh, and R. Maranan, “Optimizing Hindi Paragraph Summarization through PageRank Method,” in 2023 2nd International Conference on Edge Computing and Applications (ICECAA), 2023, pp. 504–509.
18. V. N. D. Krishnamurthy, S. Degadwala, and D. Vyas, “Forecasting Future Sea Level Rise: A Data-driven Approach using Climate Analysis,” in 2023 2nd International Conference on Edge Computing and Applications (ICECAA), 2023, pp. 646–651.
19. S. Degadwala, D. Vyas, A. Kothari, and U. Khunt, “Cancer Death Cases Forecasting using Supervised Machine Learning,” in 2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC), 2023, pp. 903–907.
20. M. Shah, K. Gandhi, B. M. Pandhi, P. Padhiyar, and S. Degadwala, “Computer Vision & Deep Learning based Realtime and Pre-Recorded Human Pose Estimation,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 313–319.
21. N. K. Pareek, D. Soni, and S. Degadwala, “Early Stage Chronic Kidney Disease Prediction using Convolution Neural Network,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 16–20.
22. P. Padhiyar, K. Parmar, N. Parmar, and S. Degadwala, “Visual Distance Fraudulent Detection in Exam Hall using YOLO Detector,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1–7.
23. M. Manwal, A. M. Alvi, N. K. Turaga, A. Mittal, R. Rivera, and S. Degadwala, “Node based Label Propagation for Bitcoin Transaction Pattern Identification Over Similar Community,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1147–1153.
24. D. Agrawal, H. Makwana, S. S. Dave, S. Degadwala, and V. Desai, “Error Level Analysis and Deep Learning For Detecting Image Forgeries,” in 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), 2023, pp. 114–117.
25. S. Pareek, A. Kumar, and S. Degadwala, “Machine Learning & Internet of Things in Plant Disease Detection: A comprehensive Review,” in 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), 2023, pp. 1354–1359.
26. P. K. Purohit, A. Kumar, and S. Degadwala, “Design and Development of Protected Services in Cloud Computing Environment,” in 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2023, pp. 985–988.
27. H. Lakhani, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “PET-MRI Sequence Fusion using Convolution Neural Network,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 317–321.
28. F. Ahamad, D. K. Lobiyal, S. Degadwala, and D. Vyas, “Inspecting and Finding Faults in Railway Tracks Using Wireless Sensor Networks,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1241–1245.
29. D. Rathod, K. Patel, A. J. Goswami, S. Degadwala, and D. Vyas, “Exploring Drug Sentiment Analysis with Machine Learning Techniques,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 9–12.
30. C. H. Patel, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “EfficientNetB0 for Brain Stroke Classification on Computed Tomography Scan,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 713–718.
31. V. Desai, S. Degadwala, and D. Vyas, “Multi-Categories Vehicle Detection For Urban Traffic Management,” in 2023 Second International Conference on Electronics and Renewable Systems (ICEARS), 2023, pp. 1486–1490.
32. D. D. Pandya, S. K. Patel, A. H. Qureshi, A. J. Goswami, S. Degadwala, and D. Vyas, “Multi-Class Classification of Vector Borne Diseases using Convolution Neural Network,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 1–8.
33. D. D. Pandya, A. K. Patel, J. M. Purohit, M. N. Bhuptani, S. Degadwala, and D. Vyas, “Forecasting Number of Indian Startups using Supervised Learning Regression Models,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 948–952.
34. S. Degadwala, D. Vyas, D. D. Pandya, and H. Dave, “Multi-Class Pneumonia Classification Using Transfer Deep Learning Methods,” in 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2023, pp. 559–563.
35. D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Diagnostic Criteria for Depression based on Both Static and Dynamic Visual Features,” in 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2023, pp. 635–639.
36. R. Shah, V. Shah, A. R. Nair, T. Vyas, S. Desai, and S. Degadwala, “Software Effort Estimation using Machine Learning Algorithms,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 1–8.
37. M. Prajapati, M. Nakrani, T. Vyas, L. Gohil, S. Desai, and S. Degadwala, “Automatic Question Tagging using Machine Learning and Deep learning Algorithms,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 932–938.
38. Shashi, V. Srikanth, P. Biswas, V. Chinnammal, S. A. Bhosale, and S. Degadwala, “Usage of ML and IoT in Healthcare Diagnose During Pandemic,” in 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), 2022, pp. 624–631.
39. Y. J. Prajapati, P. P. Gandhi, and S. Degadwala, “A Review - ML and DL Classifiers for Emotion Detection in Audio and Speech Data,” in 2022 International Conference on Inventive Computation Technologies (ICICT), 2022, pp. 63–69.
40. S. Singh, V. Srikanth, S. Kumar, L. Saravanan, S. Degadwala, and S. Gupta, “IOT Based Deep Learning framework to Diagnose Breast Cancer over Pathological Clinical Data,” in 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM), 2022, vol. 2, pp. 731–735.
41. M. Shah, N. Pujara, K. Mangaroliya, L. Gohil, T. Vyas, and S. Degadwala, “Music Genre Classification using Deep Learning,” in 2022 6th International Conference on Computing Methodologies and Communication (ICCMC), 2022, pp. 974–978.
42. S. Dave, S. Degadwala, and D. Vyas, “DDoS Detection at Fog Layer in Internet of Things,” in 2022 International Conference on Edge Computing and Applications (ICECAA), 2022, pp. 610–617.
43. D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Ensemble Learning based Enzyme Family Classification using n-gram Feature,” in 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS), 2022, pp. 1386–1392.
44. V. B. Gadhavi, S. Degadwala, and D. Vyas, “Transfer Learning Approach For Recognizing Natural Disasters Video,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 793–798.
45. J. Mahale, S. Degadwala, and D. Vyas, “Crop Prediction System based on Soil and Weather Characteristics,” in 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2022, pp. 340–345.
46. M. Shah, S. Degadwala, and D. Vyas, “Diet Recommendation System based on Different Machine Learners: A Review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 290–295.
47. B. Trivedi, S. Degadwala, and D. Vyas, “Parallel data stream anonymization methods: A review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 887–891.
48. D. D. Pandya, N. S. Gupta, A. Jadeja, R. D. Patel, S. Degadwala, and D. Vyas, “Bias Protected Attributes Data Balancing using Map Reduce,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 1540–1544.
49. R. Baria, S. Degadwala, R. Upadhyay, and D. Vyas, “Theoretical Evaluation of Machine And Deep Learning For Detecting Fake News,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 325–329.
50. P. Bam, S. Degadwala, R. Upadhyay, and D. Vyas, “Spoken Language Recognization Based on Features and Classification Methods: A Review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 868–873.
51. A. Patel, S. Degadwala, and D. Vyas, “Lung Respiratory Audio Prediction using Transfer Learning Models,” in 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2022, pp. 1107–1114.
52. V. K. Singh, S. Pandey, S. Degadwala, and D. Vyas, “DNA and KAMLA Approaches in Metamorphic Cryptography: An Evaluation,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 1173–1178.
53. D. D. Pandya, G. Amarawat, A. Jadeja, S. Degadwala, and D. Vyas, “Analysis and Prediction of Location based Criminal Behaviors Through Machine Learning,” in 2022 International Conference on Edge Computing and Applications (ICECAA), 2022, pp. 1324–1332.
54. R. Modi, K. Naik, T. Vyas, S. Desai, and S. Degadwala, “E-mail autocomplete function using RNN Encoder-decoder sequence-to-sequence model,” in 2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2021, pp. 710–714.
55. S. Rangineni and D. Marupaka, “Data Mining Techniques Appropriate for the Evaluation of Procedure Information,” International Journal of Management, IT & Engineering, vol. 13, no. 9, pp. 12–25, Sep. 2023.
56. S. Rangineni, “An Analysis of Data Quality Requirements for Machine Learning Development Pipelines Frameworks,” International Journal of Computer Trends and Technology, vol. 71, no. 9, pp. 16–27, 2023.
57. S. Agarwal, “Unleashing the Power of Data: Enhancing Physician Outreach through Machine Learning,” International Research Journal of Engineering and Technology, vol. 10, no. 8, pp. 717–725, Aug. 2023.
58. S. Agarwal, “An Intelligent Machine Learning Approach for Fraud Detection in Medical Claim Insurance: A Comprehensive Study,” Scholars Journal of Engineering and Technology, vol. 11, no. 9, pp. 191–200, Sep. 2023.
59. Bhanushali, K. Sivagnanam, K. Singh, B. K. Mittapally, L. T. Reddi, and P. Bhanushali, “Analysis of Breast Cancer Prediction Using Multiple Machine Learning Methodologies”, Int J Intell Syst Appl Eng, vol. 11, no. 3, pp. 1077–1084, Jul. 2023.
60. S. Parate, H. P. Josyula, and L. T. Reddi, “Digital Identity Verification: Transforming Kyc Processes In Banking Through Advanced Technology And Enhanced Security Measures,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 9, pp. 128–137, Sep. 2023.
61. K. Peddireddy and D. Banga, “Enhancing Customer Experience through Kafka Data Steams for Driven Machine Learning for Complaint Management,” International Journal of Computer Trends and Technology, vol. 71, no. 3, pp. 7-13, 2023.
62. K. Peddireddy, “Kafka-based Architecture in Building Data Lakes for Real-time Data Streams,” International Journal of Computer Applications, vol. 185, no. 9, pp. 1-3, May 2023.
63. R. Kandepu, “IBM FileNet P8: Evolving Traditional ECM Workflows with AI and Intelligent Automation,” International Journal of Innovative Analyses and Emerging Technology, vol. 3, no. 9, pp. 23–30, Sep. 2023.
64. R. Kandepu, “Leveraging FileNet Technology for Enhanced Efficiency and Security in Banking and Insurance Applications and its future with Artificial Intelligence (AI) and Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 8, pp. 20–26, Aug. 2023.
65. Rina Bora, Deepa Parasar, Shrikant Charhate , A detection of tomato plant diseases using deep learning MNDLNN classifier, , Signal, Image and Video Processing, April 2023.
66. Deepa Parasar, Vijay R. Rathod, Particle swarm optimization K-means clustering segmentation of foetus Ultrasound Image, Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, 2017.
67. Parvatikar, S., Parasar, D. (2021). Categorization of Plant Leaf Using CNN. (eds) Intelligent Computing and Networking. Lecture Notes in Networks and Systems, vol 146. Springer, Singapore.
68. Naufil Kazi, Deepa Parasar, Yogesh Jadhav, Predictive Risk Analysis by using Machine Learning during Covid-19, in Application of Artificial Intelligence in COVID-19 book by Springer Singapore. ISBN:978-981-15-7317-0.
69. Naufil Kazi, Deepa Parasar, Human Identification Using Thermal Sensing Inside Mines, 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2021, pp. 608-615.
70. Yogesh Jadhav, Deepa Parasar, Fake Review Detection System through Analytics of Sales Data in Proceeding of First Doctoral Symposium on Natural Computing Research by Springer Singapore. Lecture Notes in Networks and Systems book series (LNNS, volume 169), ISBN 978-981-334-072-5.
71. Parasar, D., Jadhav, Y.H. (2021). An Automated System to Detect Phishing URL by Using Machine Learning Algorithm. In: Raj, J.S. (eds) International Conference on Mobile Computing and Sustainable Informatics. ICMCSI 2020. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
72. Parasar, D., Jadhav, Y.H. (2021). An Automated System to Detect Phishing URL by Using Machine Learning Algorithm. In: Raj, J.S. (eds) International Conference on Mobile Computing and Sustainable Informatics. ICMCSI 2020. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
73. Deepa Parasar, Preet V. Smit B., Vivek K., Varun I., Aryaa S., Blockchain Based Smart Integrated Healthcare System, Frontiers of ICT in Healthcare, April 2023 Lecture Notes in Networks and Systems, vol 519. Springer, Singapore, EAIT 2022.
74. Deepa Parasar., Sahi, I., Jain, S., Thampuran, A. (2022). Music Recommendation System Based on Emotion Detection. Artificial Intelligence and Sustainable Computing. Algorithms for Intelligent Systems. Springer, Singapore.
75. Mishra, S., & Samal, S. K. (2023). An Efficient Model for Mitigating Power Transmission Congestion Using Novel Rescheduling Approach. Journal of Circuits, Systems and Computers, 2350237.
76. Samal, S. K., & Khadanga, R. K. (2023). A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid. Journal of Electrical and Computer Engineering, 2023.
77. A. B. Naeem, B. Senapati, M. S. Islam Sudman, K. Bashir, and A. E. M. Ahmed, “Intelligent road management system for autonomous, non-autonomous, and VIP vehicles,” World Electric Veh. J., vol. 14, no. 9, p. 238, 2023.
78. A. M. Soomro et al., “Constructor development: Predicting object communication errors,” in 2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology (ICES&T), 2023.
79. A. M. Soomro et al., “In MANET: An improved hybrid routing approach for disaster management,” in 2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology (ICES&T), 2023.
80. B. Senapati, J. R. Talburt, A. Bin Naeem, and V. J. R. Batthula, “Transfer learning based models for food detection using ResNet-50,” in 2023 IEEE International Conference on Electro Information Technology (eIT), 2023.
81. B. Senapati and B. S. Rawal, “Quantum communication with RLP quantum resistant cryptography in industrial manufacturing,” Cyber Security and Applications, vol. 1, no. 100019, p. 100019, 2023.
82. B. Senapati and B. S. Rawal, “Adopting a deep learning split-protocol based predictive maintenance management system for industrial manufacturing operations,” in Lecture Notes in Computer Science, Singapore: Springer Nature Singapore, 2023, pp. 22–39.
83. S. Venkatasubramanian, D. A. Suhasini, and D. C.Vennila, “An Energy Efficient Clustering Algorithm in Mobile Adhoc Network Using Ticket Id Based Clustering Manager,” International Journal of Computer Science and Network Security, vol. 21, no. 7, pp. 341–349, Jul. 2021.
84. Venkatasubramanian, S., Suhasini, A. and Vennila, C., “An Efficient Route Optimization Using Ticket-ID Based Routing Management System (T-ID BRM)”. Wireless Personal Communications, pp.1-20, 2021.
85. S. Venkatasubramanian, A. Suhasini, C. Vennila, “Efficient Multipath Zone-Based Routing in MANET Using (TID-ZMGR) Ticked-ID Based Zone Manager”, International Journal of Computer Networks and Applications (IJCNA), 8(4), PP: 435- 443, 2021.
86. Veena, A., Gowrishankar, S. An automated pre-term prediction system using EHG signal with the aid of deep learning technique. Multimed Tools Appl (2023).
87. A. Veena and S. Gowrishankar, "Context based healthcare informatics system to detect gallstones using deep learning methods," International Journal of Advanced Technology and Engineering Exploration, vol. 9, (96), pp. 1661-1677, 2022.
88. Veena, A., Gowrishankar, S. (2021). Healthcare Analytics: Overcoming the Barriers to Health Information Using Machine Learning Algorithms. In: Chen, J.IZ., Tavares, J.M.R.S., Shakya, S., Iliyasu, A.M. (eds) Image Processing and Capsule Networks. ICIPCN 2020. Advances in Intelligent Systems and Computing, vol 1200. Springer, Cham.
89. A. Veena and S. Gowrishankar, "Processing of Healthcare Data to Investigate the Correlations and the Anomalies," 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 2020, pp. 611-617,
90. A. Veena and S. Gowrishankar, "Applications, Opportunities, and Current Challenges in the Healthcare Industry", 2022 Healthcare 4.0: Health Informatics and Precision Data Management, 2022, pp. 27–50.
91. K. Bhardwaj, S. Rangineni, L. Thamma Reddi, M. Suryadevara, and K. Sivagnanam, “Pipeline-Generated Continuous Integration and Deployment Method For Agile Software Development,” European Chemical Bulletin, vol. 12, no. Special Issue 7, pp. 5590–5603, 2023.
92. S. Rangineni, D. Marupaka, and A. K. Bhardwaj, “An examination of machine learning in the process of data integration,” International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 79–85, Jun. 2023.
93. T. K. Behera, D. Marupaka, L. Thamma Reddi, and P. Gouda, “Enhancing Customer Support Efficiency through Seamless Issue Management Integration: Issue Sync Integration System,” European Chemical Bulletin, vol. 12, no. 10, pp. 1157–1178.
94. S. Rangineni and D. Marupaka, “Analysis Of Data Engineering For Fraud Detection Using Machine Learning And Artificial Intelligence Technologies,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 7, pp. 2137–2146, Jul. 2023.
95. L. Thamma Reddi, “Transforming Management Accounting: Analyzing The Impacts Of Integrated Sap Implementation,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 8, pp. 1786–1793, Aug. 2023.
96. M. Suryadevera, S. Rangineni, and S. Venkata, “Optimizing Efficiency and Performance: Investigating Data Pipelines for Artificial Intelligence Model Development and Practical Applications,” International Journal of Science and Research, vol. 12, no. 7, pp. 1330–1340, Jul. 2023.
97. D. Marupaka, S. Rangineni, and A. K. Bhardwaj, “Data Pipeline Engineering in The Insurance Industry: A Critical Analysis Of Etl Frameworks, Integration Strategies, And Scalability,” International Journal Of Creative Research Thoughts, vol. 11, no. 6, pp. c530–c539, Jun. 2023.
98. S. Rangineni, A. K. Bhardwaj, and D. Marupaka, “An Overview and Critical Analysis of Recent Advances in Challenges Faced in Building Data Engineering Pipelines for Streaming Media,” The Review of Contemporary Scientific and Academic Studies, vol. 3, no. 6, Jun. 2023.
99. B. Nemade and D. Shah, “An IoT based efficient Air pollution prediction system using DLMNN classifier,” Phys. Chem. Earth (2002), vol. 128, no. 103242, p. 103242, 2022.
100. B. Nemade and D. Shah, “An efficient IoT based prediction system for classification of water using novel adaptive incremental learning framework,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5121–5131, 2022.
101. B. Nemade, “Automatic traffic surveillance using video tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016.
102. Venkatasubramanian, S.. “Optimized Gaming based Multipath Routing Protocol with QoS Support for High-Speed MANET”, International Journal of Advanced Research in Science, Communication and Technology. vol. 9, No. 1, ,pp.62-73, September , 2021.
103. Venkatasubramanian.S., “A Chaotic Salp Swarm Feature Selection Algorithm for Apple and Tomato Plant Leaf Disease Detection”, International Journal of Advanced Trends in Computer Science and Engineering, 10(5), pp.3037–3045,2021.
104. K. Gaurav, A. S. Ray, and A. Pradhan, “Investment Behavior of Corporate Professionals Towards Mutual Funds in India,” International Journal of Accounting & Finance Review, vol. 14, no. 1, pp. 30–39, 2023.
105. M. Rajanikanth and K. Gaurav, “Influence of Reference Group on Tractor Purchasing Decision of Farmers In Telangana,” Academy of Marketing Studies Journal, vol. 27, no. 5, pp. 1–12, 2023.
106. K. Gaurav, A. S. Ray, and N. K. Sahu, “Factors Determining the Role of Brand in Purchase Decision of Sportswear,” PalArch’s Journal of Archaeology of Egypt / Egyptology, vol. 17, no. 7, pp. 2168–2186, 2020.
107. K. Gaurav and V. Raju, “Factors influencing Highway Retailer Satisfaction in FMCG industry,” Mukt Shabd Journal, vol. 9, no. 4, pp. 1297–1316, 2020.
108. K. Gaurav and A. Suraj Ray, “Impact of Social Media Advertising on Consumer Buying Behavior in Indian E-commerce Industry,” Sumedha Journal of Management, vol. 9, no. 1, pp. 41–51, Jun. 2020.
109. Khan, S. (2021). Data Visualization to Explore the Countries Dataset for Pattern Creation. International Journal of Online Biomedical Engineering, 17(13), 4-19.
110. Khan, S. (2021). Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model. International Journal of Online Biomedical Engineering, 17(8).
111. Khan, S. (2022). Business Intelligence Aspect for Emotions and Sentiments Analysis. Paper presented at the 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT).
112. Khan, S. (2021). Study Factors for Student Performance Applying Data Mining Regression Model Approach. International Journal of Computer Science Network Security, 21(2), 188-192.
113. A. Patel, S. Samal, S. Ghosh and B. Subudhi, "A study on wide-area controller design for inter-area oscillation damping," 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC), Kolkata, India, 2016, pp. 245-249.
114. B. Subudhi, S. K. Sarnal and S. Ghosh, "A new low-frequency oscillatory modes estimation using TLS-ESPRIT and least mean squares sign-data (LMSSD) adaptive filtering," TENCON 2017 - 2017 IEEE Region 10 Conference, Penang, Malaysia, 2017, pp. 751-756.
115. Chaudhary, J. K., Sharma, H., Tadiboina, S. N., Singh, R., Khan, M. S., & Garg, A. (2023). Applications of Machine Learning in Viral Disease Diagnosis. In 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1167-1172). IEEE.
116. D. K. Sharma, B. Singh, M. Raja, R. Regin, and S. S. Rajest, “An Efficient Python Approach for Simulation of Poisson Distribution,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
117. D. K. Sharma, B. Singh, R. Regin, R. Steffi, and M. K. Chakravarthi, “Efficient Classification for Neural Machines Interpretations based on Mathematical models,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
118. D. K. Sharma, N. A. Jalil, R. Regin, S. S. Rajest, R. K. Tummala, and Thangadurai, “Predicting network congestion with machine learning,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), 2021
119. F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi, and S. Suman Rajest, “Optimization technique approach to resolve food sustainability problems,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
120. Fazil, M., Khan, S., Albahlal, B. M., Alotaibi, R. M., Siddiqui, T., & Shah, M. A. (2023). Attentional Multi-Channel Convolution With Bidirectional LSTM Cell Toward Hate Speech Prediction. IEEE Access, 11, 16801-16811.
121. G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest, and N. Singh, “Involvement of distance measure in assessing and resolving efficiency environmental obstacles,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
122. Gupta, G., Khan, S., Guleria, V., Almjally, A., Alabduallah, B. I., Siddiqui, T., Albahlal, B. M., et al. (2023). DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms. Diagnostics, 13(6), 1093.
123. Jain, A., Krishna, M. M., Tadiboina, S. N., Joshi, K., Chanti, Y., & Krishna, K. S. (2023). An analysis of medical images using deep learning. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1440-1445). IEEE.
124. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest, and V. P. Mishra, “Maximum information measure policies in reinforcement learning with deep energy-based model,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
125. Khan, S., & Alshara, M. (2019). Development of Arabic evaluations in information retrieval. International Journal of Advanced Applied Sciences, 6(12), 92-98.
126. Khan, S., & AlSuwaidan, L. (2022). Agricultural monitoring system in video surveillance object detection using feature extraction and classification by deep learning techniques. Computers and Electrical Engineering, 102, 108201.
127. Khan, S., Siddiqui, T., Mourade, A. et al. Manufacturing industry based on dynamic soft sensors in integrated with feature representation and classification using fuzzy logic and deep learning architecture. Int J Adv Manuf Technol (2023).
128. Kumar, J. (2016). Evaluating Superiority of Modern Vis-A-Vis Traditional Financial Performance Measures: Evidences from Indian Pharmaceutical Industry. JIMS8M: The Journal of Indian Management & Strategy, 21(1), 21-30.
129. Kumar, J. (2016). Synoptic View on Economic Value Added (EVA)-Literature Review Summary. Wealth: International Journal of Money, Banking & Finance, 5(2), 34-57.
130. M. Mahato, “Organizational change: An action oriented toolkit,” South Asian Journal of Management, vol. 22, no. 4, pp. 197. 2015.
131. M. Modekurti, and R. Chattopadhyay, “The relationship between organizational role stress and life satisfaction levels among women employees: an empirical study,” The Icfaian Journal of Management Research. vol. 7, no. 5, pp. 25-34. 2008.
132. M. Modekurti-Mahato, P. Kumar, and P. G. Raju, “Impact of Emotional Labor on Organizational Role Stress – A Study in the Services Sector in India,” Procedia Economics and Finance, vol. 11, pp. 110–121, 2014.
133. Mahendran, R., Tadiboina, S. N., Thrinath, B. S., Gadgil, A., Madem, S., & Srivastava, Y. (2022). Application of Machine Learning and Internet of Things for Identification of Nutrient Deficiencies in Oil Palm. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 2024-2028). IEEE.
134. Manikandan, N., Tadiboina, S. N., Khan, M. S., Singh, R., & Gupta, K. K. (2023). Automation of Smart Home for the Wellbeing of Elders Using Empirical Big Data Analysis. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1164-1168). IEEE.
135. Mishra, S., & Kumar Samal, S. (2023). Mitigation of transmission line jamming by price intrusion technique in competitive electricity market. International Journal of Ambient Energy, 44(1), 171-176.
136. Mishra, S., & Samal, S. K. (2023). Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector. Energy Systems, 1-13.
137. P. G. Raju and M. M. Mahato, “Impact of longer usage of lean manufacturing system (Toyotism) on employment outcomes - a study in garment manufacturing industries in India,” International Journal of Services and Operations Management, vol. 18, no. 3, p. 305, 2014.
138. P. K. Sahu, S. Maity, R. K. Mahakhuda and S. K. Samal, "A fixed switching frequency sliding mode control for single-phase voltage source inverter," 2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014], Nagercoil, India, 2014, pp. 1006-1010.
139. P. Paramasivan, “A Novel Approach: Hydrothermal Method of Fine Stabilized Superparamagnetics of Cobalt Ferrite (CoFe2O4) Nanoparticles,” Journal of Superconductivity and Novel Magnetism, vol. 29, pp. 2805–2811, 2016.
140. P. Paramasivan, “Comparative investigation of NiFe2O4 nano and microstructures for structural, optical, magnetic and catalytic properties,” Advanced Science, Engineering and Medicine, vol. 8, pp. 392–397, 2016.
141. P. Paramasivan, “Controllable synthesis of CuFe2O4 nanostructures through simple hydrothermal method in the presence of thioglycolic acid,” Physica E: Low-dimensional Systems and Nanostructures, vol. 84, pp. 258–262, 2016.
142. P. Paramasivan, S. Narayanan, and N. M. Faizee, “Enhancing Catalytic Activity of Mn3O4 by Selective Liquid Phase Oxidation of Benzyl Alcohol,” Advanced Science, Engineering and Medicine, vol. 10, pp. 1–5, 2018.
143. S Silvia Priscila, M Hemalatha, “ Diagnosisof heart disease with particle bee-neural network” Biomedical Research, Special Issue, pp. S40-S46, 2018.
144. S Silvia Priscila, M Hemalatha, “ Heart Disease Prediction Using Integer-Coded Genetic Algorithm (ICGA) Based Particle Clonal Neural Network (ICGA-PCNN)”, Bonfring International Journal of Industrial Engineering and Management Science 8 (2), 15-19, 2018.
145. S. Ambika, T. A. Sivakumar, and P. Sukantha, “Preparation and characterization of nanocopper ferrite and its green catalytic activity in alcohol oxidation reaction,” Journal of Superconductivity and Novel Magnetism, vol. 32, pp. 903–910, 2019.
146. S. Khan, V. Ch, K. Sekaran, K. Joshi, C. K. Roy and M. Tiwari, "Incorporating Deep Learning Methodologies into the Creation of Healthcare Systems," 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, 2023, pp. 994-998.
147. Sahoo, A. K., & Samal, S. K. (2023). Online fault detection and classification of 3-phase long transmission line using machine learning model. Multiscale and Multidisciplinary Modeling, Experiments and Design, 6(1), 135-146.
148. SS Priscila, M Hemalatha, “Improving the performance of entropy ensembles of neural networks (EENNS) on classification of heart disease prediction”, Int J Pure Appl Math 117 (7), 371-386, 2017.
149. Tadiboina, S. N., & Chase, G. C. (2022). The importance and leverage of modern information technology infrastructure in the healthcare industry. Int J Res Trends Innov, 7(11), 340-344.
2. L. Harnefors, X. Wang, A. G. Yepes, and F. Blaabjerg, “Passivity-based stability assessment of grid-connected VSCs – an overview,” IEEE Journal of Emerging and Selected Topics in Power Electronics. vol. 4, no. 1, pp. 116-125, Mar. 2016.
3. M.Malinowski, K. Gopakumar, J. Rodriguez, andM. A. Perez, “A survey on cascaded multilevel inverters,” IEEE Transactions on Industrial Electronics., vol. 57, no. 7, pp. 2197–2206, Jul. 2010.
4. A. Ajami, M. R. J. Oskuee, M. T. Khosroshahi, and A. Mokhberdoran,“ Cascade-multi-cell multilevel converter with reduced number of switches,” IET Power Electronics, vol. 7, no. 3, pp. 552–558, Mar. 2014.
5. C. D. Townsend, T. J. Summers and R. E. Betz, “Multigoal Heuristic Model Predictive Control Technique Applied to a Cascaded H-bridge StatCom,” IEEE Transactions on Power Electronics., vol. 27, no. 3, pp. 1191-1200, March 2012.
6. Alarood, A. A., Faheem, M., Al‐Khasawneh, M. A., Alzahrani, A. I., & Alshdadi, A. A. (2023). Secure medical image transmission using deep neural network in e‐health applications. Healthcare Technology Letters, 10(4), 87-98.
7. Markkandeyan, S., Gupta, S., Narayanan, G. V., Reddy, M. J., Al-Khasawneh, M. A., Ishrat, M., & Kiran, A. (2023). Deep learning based semantic segmentation approach for automatic detection of brain tumor. International Journal of Computers Communications & Control, 18(4).
8. Al-Khasawneh, M. A., Alzahrani, A., & Alarood, A. (2023). Alzheimer’s Disease Diagnosis Using MRI Images. In Data Analysis for Neurodegenerative Disorders (pp. 195-212). Singapore: Springer Nature Singapore.
9. Al-Khasawneh, M. A., Alzahrani, A., & Alarood, A. (2023). An Artificial Intelligence Based Effective Diagnosis of Parkinson Disease Using EEG Signal. In Data Analysis for Neurodegenerative Disorders (pp. 239-251). Singapore: Springer Nature Singapore.
10. Al-Khasawneh, M. A., Faheem, M., Aldhahri, E. A., Alzahrani, A., & Alarood, A. A. (2023). A MapReduce Based Approach for Secure Batch Satellite Image Encryption. IEEE Access.
11. K. Peddireddy, "Streamlining Enterprise Data Processing, Reporting and Realtime Alerting using Apache Kafka," 2023 11th International Symposium on Digital Forensics and Security (ISDFS), Chattanooga, TN, USA, 2023, pp. 1-4.
12. Kiran Peddireddy. Kafka-based Architecture in Building Data Lakes for Real-time Data Streams. International Journal of Computer Applications 185(9):1-3, May 2023.
13. Anitha Peddireddy, Kiran Peddireddy, "Next-Gen CRM Sales and Lead Generation with AI," International Journal of Computer Trends and Technology, vol. 71, no. 3, pp. 21-26, 2023.
14. Peddireddy, K., and D. Banga. "Enhancing Customer Experience through Kafka Data Steams for Driven Machine Learning for Complaint Management." International Journal of Computer Trends and Technology 71.3 (2023): 7-13.
15. S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Empowering Maxillofacial Diagnosis Through Transfer Learning Models,” in 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), 2023, pp. 728–732.
16. S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Enhancing Alzheimer Stage Classification of MRI Images through Transfer Learning,” in 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), 2023, pp. 733–737.
17. S. Degadwala, D. Vyas, K. N. Patel, M. Soni, P. P. Singh, and R. Maranan, “Optimizing Hindi Paragraph Summarization through PageRank Method,” in 2023 2nd International Conference on Edge Computing and Applications (ICECAA), 2023, pp. 504–509.
18. V. N. D. Krishnamurthy, S. Degadwala, and D. Vyas, “Forecasting Future Sea Level Rise: A Data-driven Approach using Climate Analysis,” in 2023 2nd International Conference on Edge Computing and Applications (ICECAA), 2023, pp. 646–651.
19. S. Degadwala, D. Vyas, A. Kothari, and U. Khunt, “Cancer Death Cases Forecasting using Supervised Machine Learning,” in 2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC), 2023, pp. 903–907.
20. M. Shah, K. Gandhi, B. M. Pandhi, P. Padhiyar, and S. Degadwala, “Computer Vision & Deep Learning based Realtime and Pre-Recorded Human Pose Estimation,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 313–319.
21. N. K. Pareek, D. Soni, and S. Degadwala, “Early Stage Chronic Kidney Disease Prediction using Convolution Neural Network,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 16–20.
22. P. Padhiyar, K. Parmar, N. Parmar, and S. Degadwala, “Visual Distance Fraudulent Detection in Exam Hall using YOLO Detector,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1–7.
23. M. Manwal, A. M. Alvi, N. K. Turaga, A. Mittal, R. Rivera, and S. Degadwala, “Node based Label Propagation for Bitcoin Transaction Pattern Identification Over Similar Community,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1147–1153.
24. D. Agrawal, H. Makwana, S. S. Dave, S. Degadwala, and V. Desai, “Error Level Analysis and Deep Learning For Detecting Image Forgeries,” in 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), 2023, pp. 114–117.
25. S. Pareek, A. Kumar, and S. Degadwala, “Machine Learning & Internet of Things in Plant Disease Detection: A comprehensive Review,” in 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), 2023, pp. 1354–1359.
26. P. K. Purohit, A. Kumar, and S. Degadwala, “Design and Development of Protected Services in Cloud Computing Environment,” in 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2023, pp. 985–988.
27. H. Lakhani, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “PET-MRI Sequence Fusion using Convolution Neural Network,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 317–321.
28. F. Ahamad, D. K. Lobiyal, S. Degadwala, and D. Vyas, “Inspecting and Finding Faults in Railway Tracks Using Wireless Sensor Networks,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 1241–1245.
29. D. Rathod, K. Patel, A. J. Goswami, S. Degadwala, and D. Vyas, “Exploring Drug Sentiment Analysis with Machine Learning Techniques,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 9–12.
30. C. H. Patel, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “EfficientNetB0 for Brain Stroke Classification on Computed Tomography Scan,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 713–718.
31. V. Desai, S. Degadwala, and D. Vyas, “Multi-Categories Vehicle Detection For Urban Traffic Management,” in 2023 Second International Conference on Electronics and Renewable Systems (ICEARS), 2023, pp. 1486–1490.
32. D. D. Pandya, S. K. Patel, A. H. Qureshi, A. J. Goswami, S. Degadwala, and D. Vyas, “Multi-Class Classification of Vector Borne Diseases using Convolution Neural Network,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023, pp. 1–8.
33. D. D. Pandya, A. K. Patel, J. M. Purohit, M. N. Bhuptani, S. Degadwala, and D. Vyas, “Forecasting Number of Indian Startups using Supervised Learning Regression Models,” in 2023 International Conference on Inventive Computation Technologies (ICICT), 2023, pp. 948–952.
34. S. Degadwala, D. Vyas, D. D. Pandya, and H. Dave, “Multi-Class Pneumonia Classification Using Transfer Deep Learning Methods,” in 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2023, pp. 559–563.
35. D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Diagnostic Criteria for Depression based on Both Static and Dynamic Visual Features,” in 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2023, pp. 635–639.
36. R. Shah, V. Shah, A. R. Nair, T. Vyas, S. Desai, and S. Degadwala, “Software Effort Estimation using Machine Learning Algorithms,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 1–8.
37. M. Prajapati, M. Nakrani, T. Vyas, L. Gohil, S. Desai, and S. Degadwala, “Automatic Question Tagging using Machine Learning and Deep learning Algorithms,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 932–938.
38. Shashi, V. Srikanth, P. Biswas, V. Chinnammal, S. A. Bhosale, and S. Degadwala, “Usage of ML and IoT in Healthcare Diagnose During Pandemic,” in 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), 2022, pp. 624–631.
39. Y. J. Prajapati, P. P. Gandhi, and S. Degadwala, “A Review - ML and DL Classifiers for Emotion Detection in Audio and Speech Data,” in 2022 International Conference on Inventive Computation Technologies (ICICT), 2022, pp. 63–69.
40. S. Singh, V. Srikanth, S. Kumar, L. Saravanan, S. Degadwala, and S. Gupta, “IOT Based Deep Learning framework to Diagnose Breast Cancer over Pathological Clinical Data,” in 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM), 2022, vol. 2, pp. 731–735.
41. M. Shah, N. Pujara, K. Mangaroliya, L. Gohil, T. Vyas, and S. Degadwala, “Music Genre Classification using Deep Learning,” in 2022 6th International Conference on Computing Methodologies and Communication (ICCMC), 2022, pp. 974–978.
42. S. Dave, S. Degadwala, and D. Vyas, “DDoS Detection at Fog Layer in Internet of Things,” in 2022 International Conference on Edge Computing and Applications (ICECAA), 2022, pp. 610–617.
43. D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Ensemble Learning based Enzyme Family Classification using n-gram Feature,” in 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS), 2022, pp. 1386–1392.
44. V. B. Gadhavi, S. Degadwala, and D. Vyas, “Transfer Learning Approach For Recognizing Natural Disasters Video,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 793–798.
45. J. Mahale, S. Degadwala, and D. Vyas, “Crop Prediction System based on Soil and Weather Characteristics,” in 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2022, pp. 340–345.
46. M. Shah, S. Degadwala, and D. Vyas, “Diet Recommendation System based on Different Machine Learners: A Review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 290–295.
47. B. Trivedi, S. Degadwala, and D. Vyas, “Parallel data stream anonymization methods: A review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 887–891.
48. D. D. Pandya, N. S. Gupta, A. Jadeja, R. D. Patel, S. Degadwala, and D. Vyas, “Bias Protected Attributes Data Balancing using Map Reduce,” in 2022 6th International Conference on Electronics, Communication and Aerospace Technology, 2022, pp. 1540–1544.
49. R. Baria, S. Degadwala, R. Upadhyay, and D. Vyas, “Theoretical Evaluation of Machine And Deep Learning For Detecting Fake News,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 325–329.
50. P. Bam, S. Degadwala, R. Upadhyay, and D. Vyas, “Spoken Language Recognization Based on Features and Classification Methods: A Review,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 868–873.
51. A. Patel, S. Degadwala, and D. Vyas, “Lung Respiratory Audio Prediction using Transfer Learning Models,” in 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), 2022, pp. 1107–1114.
52. V. K. Singh, S. Pandey, S. Degadwala, and D. Vyas, “DNA and KAMLA Approaches in Metamorphic Cryptography: An Evaluation,” in 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 2022, pp. 1173–1178.
53. D. D. Pandya, G. Amarawat, A. Jadeja, S. Degadwala, and D. Vyas, “Analysis and Prediction of Location based Criminal Behaviors Through Machine Learning,” in 2022 International Conference on Edge Computing and Applications (ICECAA), 2022, pp. 1324–1332.
54. R. Modi, K. Naik, T. Vyas, S. Desai, and S. Degadwala, “E-mail autocomplete function using RNN Encoder-decoder sequence-to-sequence model,” in 2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2021, pp. 710–714.
55. S. Rangineni and D. Marupaka, “Data Mining Techniques Appropriate for the Evaluation of Procedure Information,” International Journal of Management, IT & Engineering, vol. 13, no. 9, pp. 12–25, Sep. 2023.
56. S. Rangineni, “An Analysis of Data Quality Requirements for Machine Learning Development Pipelines Frameworks,” International Journal of Computer Trends and Technology, vol. 71, no. 9, pp. 16–27, 2023.
57. S. Agarwal, “Unleashing the Power of Data: Enhancing Physician Outreach through Machine Learning,” International Research Journal of Engineering and Technology, vol. 10, no. 8, pp. 717–725, Aug. 2023.
58. S. Agarwal, “An Intelligent Machine Learning Approach for Fraud Detection in Medical Claim Insurance: A Comprehensive Study,” Scholars Journal of Engineering and Technology, vol. 11, no. 9, pp. 191–200, Sep. 2023.
59. Bhanushali, K. Sivagnanam, K. Singh, B. K. Mittapally, L. T. Reddi, and P. Bhanushali, “Analysis of Breast Cancer Prediction Using Multiple Machine Learning Methodologies”, Int J Intell Syst Appl Eng, vol. 11, no. 3, pp. 1077–1084, Jul. 2023.
60. S. Parate, H. P. Josyula, and L. T. Reddi, “Digital Identity Verification: Transforming Kyc Processes In Banking Through Advanced Technology And Enhanced Security Measures,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 9, pp. 128–137, Sep. 2023.
61. K. Peddireddy and D. Banga, “Enhancing Customer Experience through Kafka Data Steams for Driven Machine Learning for Complaint Management,” International Journal of Computer Trends and Technology, vol. 71, no. 3, pp. 7-13, 2023.
62. K. Peddireddy, “Kafka-based Architecture in Building Data Lakes for Real-time Data Streams,” International Journal of Computer Applications, vol. 185, no. 9, pp. 1-3, May 2023.
63. R. Kandepu, “IBM FileNet P8: Evolving Traditional ECM Workflows with AI and Intelligent Automation,” International Journal of Innovative Analyses and Emerging Technology, vol. 3, no. 9, pp. 23–30, Sep. 2023.
64. R. Kandepu, “Leveraging FileNet Technology for Enhanced Efficiency and Security in Banking and Insurance Applications and its future with Artificial Intelligence (AI) and Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 8, pp. 20–26, Aug. 2023.
65. Rina Bora, Deepa Parasar, Shrikant Charhate , A detection of tomato plant diseases using deep learning MNDLNN classifier, , Signal, Image and Video Processing, April 2023.
66. Deepa Parasar, Vijay R. Rathod, Particle swarm optimization K-means clustering segmentation of foetus Ultrasound Image, Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, 2017.
67. Parvatikar, S., Parasar, D. (2021). Categorization of Plant Leaf Using CNN. (eds) Intelligent Computing and Networking. Lecture Notes in Networks and Systems, vol 146. Springer, Singapore.
68. Naufil Kazi, Deepa Parasar, Yogesh Jadhav, Predictive Risk Analysis by using Machine Learning during Covid-19, in Application of Artificial Intelligence in COVID-19 book by Springer Singapore. ISBN:978-981-15-7317-0.
69. Naufil Kazi, Deepa Parasar, Human Identification Using Thermal Sensing Inside Mines, 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2021, pp. 608-615.
70. Yogesh Jadhav, Deepa Parasar, Fake Review Detection System through Analytics of Sales Data in Proceeding of First Doctoral Symposium on Natural Computing Research by Springer Singapore. Lecture Notes in Networks and Systems book series (LNNS, volume 169), ISBN 978-981-334-072-5.
71. Parasar, D., Jadhav, Y.H. (2021). An Automated System to Detect Phishing URL by Using Machine Learning Algorithm. In: Raj, J.S. (eds) International Conference on Mobile Computing and Sustainable Informatics. ICMCSI 2020. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
72. Parasar, D., Jadhav, Y.H. (2021). An Automated System to Detect Phishing URL by Using Machine Learning Algorithm. In: Raj, J.S. (eds) International Conference on Mobile Computing and Sustainable Informatics. ICMCSI 2020. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
73. Deepa Parasar, Preet V. Smit B., Vivek K., Varun I., Aryaa S., Blockchain Based Smart Integrated Healthcare System, Frontiers of ICT in Healthcare, April 2023 Lecture Notes in Networks and Systems, vol 519. Springer, Singapore, EAIT 2022.
74. Deepa Parasar., Sahi, I., Jain, S., Thampuran, A. (2022). Music Recommendation System Based on Emotion Detection. Artificial Intelligence and Sustainable Computing. Algorithms for Intelligent Systems. Springer, Singapore.
75. Mishra, S., & Samal, S. K. (2023). An Efficient Model for Mitigating Power Transmission Congestion Using Novel Rescheduling Approach. Journal of Circuits, Systems and Computers, 2350237.
76. Samal, S. K., & Khadanga, R. K. (2023). A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid. Journal of Electrical and Computer Engineering, 2023.
77. A. B. Naeem, B. Senapati, M. S. Islam Sudman, K. Bashir, and A. E. M. Ahmed, “Intelligent road management system for autonomous, non-autonomous, and VIP vehicles,” World Electric Veh. J., vol. 14, no. 9, p. 238, 2023.
78. A. M. Soomro et al., “Constructor development: Predicting object communication errors,” in 2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology (ICES&T), 2023.
79. A. M. Soomro et al., “In MANET: An improved hybrid routing approach for disaster management,” in 2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology (ICES&T), 2023.
80. B. Senapati, J. R. Talburt, A. Bin Naeem, and V. J. R. Batthula, “Transfer learning based models for food detection using ResNet-50,” in 2023 IEEE International Conference on Electro Information Technology (eIT), 2023.
81. B. Senapati and B. S. Rawal, “Quantum communication with RLP quantum resistant cryptography in industrial manufacturing,” Cyber Security and Applications, vol. 1, no. 100019, p. 100019, 2023.
82. B. Senapati and B. S. Rawal, “Adopting a deep learning split-protocol based predictive maintenance management system for industrial manufacturing operations,” in Lecture Notes in Computer Science, Singapore: Springer Nature Singapore, 2023, pp. 22–39.
83. S. Venkatasubramanian, D. A. Suhasini, and D. C.Vennila, “An Energy Efficient Clustering Algorithm in Mobile Adhoc Network Using Ticket Id Based Clustering Manager,” International Journal of Computer Science and Network Security, vol. 21, no. 7, pp. 341–349, Jul. 2021.
84. Venkatasubramanian, S., Suhasini, A. and Vennila, C., “An Efficient Route Optimization Using Ticket-ID Based Routing Management System (T-ID BRM)”. Wireless Personal Communications, pp.1-20, 2021.
85. S. Venkatasubramanian, A. Suhasini, C. Vennila, “Efficient Multipath Zone-Based Routing in MANET Using (TID-ZMGR) Ticked-ID Based Zone Manager”, International Journal of Computer Networks and Applications (IJCNA), 8(4), PP: 435- 443, 2021.
86. Veena, A., Gowrishankar, S. An automated pre-term prediction system using EHG signal with the aid of deep learning technique. Multimed Tools Appl (2023).
87. A. Veena and S. Gowrishankar, "Context based healthcare informatics system to detect gallstones using deep learning methods," International Journal of Advanced Technology and Engineering Exploration, vol. 9, (96), pp. 1661-1677, 2022.
88. Veena, A., Gowrishankar, S. (2021). Healthcare Analytics: Overcoming the Barriers to Health Information Using Machine Learning Algorithms. In: Chen, J.IZ., Tavares, J.M.R.S., Shakya, S., Iliyasu, A.M. (eds) Image Processing and Capsule Networks. ICIPCN 2020. Advances in Intelligent Systems and Computing, vol 1200. Springer, Cham.
89. A. Veena and S. Gowrishankar, "Processing of Healthcare Data to Investigate the Correlations and the Anomalies," 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 2020, pp. 611-617,
90. A. Veena and S. Gowrishankar, "Applications, Opportunities, and Current Challenges in the Healthcare Industry", 2022 Healthcare 4.0: Health Informatics and Precision Data Management, 2022, pp. 27–50.
91. K. Bhardwaj, S. Rangineni, L. Thamma Reddi, M. Suryadevara, and K. Sivagnanam, “Pipeline-Generated Continuous Integration and Deployment Method For Agile Software Development,” European Chemical Bulletin, vol. 12, no. Special Issue 7, pp. 5590–5603, 2023.
92. S. Rangineni, D. Marupaka, and A. K. Bhardwaj, “An examination of machine learning in the process of data integration,” International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 79–85, Jun. 2023.
93. T. K. Behera, D. Marupaka, L. Thamma Reddi, and P. Gouda, “Enhancing Customer Support Efficiency through Seamless Issue Management Integration: Issue Sync Integration System,” European Chemical Bulletin, vol. 12, no. 10, pp. 1157–1178.
94. S. Rangineni and D. Marupaka, “Analysis Of Data Engineering For Fraud Detection Using Machine Learning And Artificial Intelligence Technologies,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 7, pp. 2137–2146, Jul. 2023.
95. L. Thamma Reddi, “Transforming Management Accounting: Analyzing The Impacts Of Integrated Sap Implementation,” International Research Journal of Modernization in Engineering Technology and Science, vol. 5, no. 8, pp. 1786–1793, Aug. 2023.
96. M. Suryadevera, S. Rangineni, and S. Venkata, “Optimizing Efficiency and Performance: Investigating Data Pipelines for Artificial Intelligence Model Development and Practical Applications,” International Journal of Science and Research, vol. 12, no. 7, pp. 1330–1340, Jul. 2023.
97. D. Marupaka, S. Rangineni, and A. K. Bhardwaj, “Data Pipeline Engineering in The Insurance Industry: A Critical Analysis Of Etl Frameworks, Integration Strategies, And Scalability,” International Journal Of Creative Research Thoughts, vol. 11, no. 6, pp. c530–c539, Jun. 2023.
98. S. Rangineni, A. K. Bhardwaj, and D. Marupaka, “An Overview and Critical Analysis of Recent Advances in Challenges Faced in Building Data Engineering Pipelines for Streaming Media,” The Review of Contemporary Scientific and Academic Studies, vol. 3, no. 6, Jun. 2023.
99. B. Nemade and D. Shah, “An IoT based efficient Air pollution prediction system using DLMNN classifier,” Phys. Chem. Earth (2002), vol. 128, no. 103242, p. 103242, 2022.
100. B. Nemade and D. Shah, “An efficient IoT based prediction system for classification of water using novel adaptive incremental learning framework,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5121–5131, 2022.
101. B. Nemade, “Automatic traffic surveillance using video tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016.
102. Venkatasubramanian, S.. “Optimized Gaming based Multipath Routing Protocol with QoS Support for High-Speed MANET”, International Journal of Advanced Research in Science, Communication and Technology. vol. 9, No. 1, ,pp.62-73, September , 2021.
103. Venkatasubramanian.S., “A Chaotic Salp Swarm Feature Selection Algorithm for Apple and Tomato Plant Leaf Disease Detection”, International Journal of Advanced Trends in Computer Science and Engineering, 10(5), pp.3037–3045,2021.
104. K. Gaurav, A. S. Ray, and A. Pradhan, “Investment Behavior of Corporate Professionals Towards Mutual Funds in India,” International Journal of Accounting & Finance Review, vol. 14, no. 1, pp. 30–39, 2023.
105. M. Rajanikanth and K. Gaurav, “Influence of Reference Group on Tractor Purchasing Decision of Farmers In Telangana,” Academy of Marketing Studies Journal, vol. 27, no. 5, pp. 1–12, 2023.
106. K. Gaurav, A. S. Ray, and N. K. Sahu, “Factors Determining the Role of Brand in Purchase Decision of Sportswear,” PalArch’s Journal of Archaeology of Egypt / Egyptology, vol. 17, no. 7, pp. 2168–2186, 2020.
107. K. Gaurav and V. Raju, “Factors influencing Highway Retailer Satisfaction in FMCG industry,” Mukt Shabd Journal, vol. 9, no. 4, pp. 1297–1316, 2020.
108. K. Gaurav and A. Suraj Ray, “Impact of Social Media Advertising on Consumer Buying Behavior in Indian E-commerce Industry,” Sumedha Journal of Management, vol. 9, no. 1, pp. 41–51, Jun. 2020.
109. Khan, S. (2021). Data Visualization to Explore the Countries Dataset for Pattern Creation. International Journal of Online Biomedical Engineering, 17(13), 4-19.
110. Khan, S. (2021). Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model. International Journal of Online Biomedical Engineering, 17(8).
111. Khan, S. (2022). Business Intelligence Aspect for Emotions and Sentiments Analysis. Paper presented at the 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT).
112. Khan, S. (2021). Study Factors for Student Performance Applying Data Mining Regression Model Approach. International Journal of Computer Science Network Security, 21(2), 188-192.
113. A. Patel, S. Samal, S. Ghosh and B. Subudhi, "A study on wide-area controller design for inter-area oscillation damping," 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC), Kolkata, India, 2016, pp. 245-249.
114. B. Subudhi, S. K. Sarnal and S. Ghosh, "A new low-frequency oscillatory modes estimation using TLS-ESPRIT and least mean squares sign-data (LMSSD) adaptive filtering," TENCON 2017 - 2017 IEEE Region 10 Conference, Penang, Malaysia, 2017, pp. 751-756.
115. Chaudhary, J. K., Sharma, H., Tadiboina, S. N., Singh, R., Khan, M. S., & Garg, A. (2023). Applications of Machine Learning in Viral Disease Diagnosis. In 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1167-1172). IEEE.
116. D. K. Sharma, B. Singh, M. Raja, R. Regin, and S. S. Rajest, “An Efficient Python Approach for Simulation of Poisson Distribution,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
117. D. K. Sharma, B. Singh, R. Regin, R. Steffi, and M. K. Chakravarthi, “Efficient Classification for Neural Machines Interpretations based on Mathematical models,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021.
118. D. K. Sharma, N. A. Jalil, R. Regin, S. S. Rajest, R. K. Tummala, and Thangadurai, “Predicting network congestion with machine learning,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), 2021
119. F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi, and S. Suman Rajest, “Optimization technique approach to resolve food sustainability problems,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
120. Fazil, M., Khan, S., Albahlal, B. M., Alotaibi, R. M., Siddiqui, T., & Shah, M. A. (2023). Attentional Multi-Channel Convolution With Bidirectional LSTM Cell Toward Hate Speech Prediction. IEEE Access, 11, 16801-16811.
121. G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest, and N. Singh, “Involvement of distance measure in assessing and resolving efficiency environmental obstacles,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
122. Gupta, G., Khan, S., Guleria, V., Almjally, A., Alabduallah, B. I., Siddiqui, T., Albahlal, B. M., et al. (2023). DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms. Diagnostics, 13(6), 1093.
123. Jain, A., Krishna, M. M., Tadiboina, S. N., Joshi, K., Chanti, Y., & Krishna, K. S. (2023). An analysis of medical images using deep learning. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1440-1445). IEEE.
124. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest, and V. P. Mishra, “Maximum information measure policies in reinforcement learning with deep energy-based model,” in 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2021.
125. Khan, S., & Alshara, M. (2019). Development of Arabic evaluations in information retrieval. International Journal of Advanced Applied Sciences, 6(12), 92-98.
126. Khan, S., & AlSuwaidan, L. (2022). Agricultural monitoring system in video surveillance object detection using feature extraction and classification by deep learning techniques. Computers and Electrical Engineering, 102, 108201.
127. Khan, S., Siddiqui, T., Mourade, A. et al. Manufacturing industry based on dynamic soft sensors in integrated with feature representation and classification using fuzzy logic and deep learning architecture. Int J Adv Manuf Technol (2023).
128. Kumar, J. (2016). Evaluating Superiority of Modern Vis-A-Vis Traditional Financial Performance Measures: Evidences from Indian Pharmaceutical Industry. JIMS8M: The Journal of Indian Management & Strategy, 21(1), 21-30.
129. Kumar, J. (2016). Synoptic View on Economic Value Added (EVA)-Literature Review Summary. Wealth: International Journal of Money, Banking & Finance, 5(2), 34-57.
130. M. Mahato, “Organizational change: An action oriented toolkit,” South Asian Journal of Management, vol. 22, no. 4, pp. 197. 2015.
131. M. Modekurti, and R. Chattopadhyay, “The relationship between organizational role stress and life satisfaction levels among women employees: an empirical study,” The Icfaian Journal of Management Research. vol. 7, no. 5, pp. 25-34. 2008.
132. M. Modekurti-Mahato, P. Kumar, and P. G. Raju, “Impact of Emotional Labor on Organizational Role Stress – A Study in the Services Sector in India,” Procedia Economics and Finance, vol. 11, pp. 110–121, 2014.
133. Mahendran, R., Tadiboina, S. N., Thrinath, B. S., Gadgil, A., Madem, S., & Srivastava, Y. (2022). Application of Machine Learning and Internet of Things for Identification of Nutrient Deficiencies in Oil Palm. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 2024-2028). IEEE.
134. Manikandan, N., Tadiboina, S. N., Khan, M. S., Singh, R., & Gupta, K. K. (2023). Automation of Smart Home for the Wellbeing of Elders Using Empirical Big Data Analysis. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1164-1168). IEEE.
135. Mishra, S., & Kumar Samal, S. (2023). Mitigation of transmission line jamming by price intrusion technique in competitive electricity market. International Journal of Ambient Energy, 44(1), 171-176.
136. Mishra, S., & Samal, S. K. (2023). Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector. Energy Systems, 1-13.
137. P. G. Raju and M. M. Mahato, “Impact of longer usage of lean manufacturing system (Toyotism) on employment outcomes - a study in garment manufacturing industries in India,” International Journal of Services and Operations Management, vol. 18, no. 3, p. 305, 2014.
138. P. K. Sahu, S. Maity, R. K. Mahakhuda and S. K. Samal, "A fixed switching frequency sliding mode control for single-phase voltage source inverter," 2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014], Nagercoil, India, 2014, pp. 1006-1010.
139. P. Paramasivan, “A Novel Approach: Hydrothermal Method of Fine Stabilized Superparamagnetics of Cobalt Ferrite (CoFe2O4) Nanoparticles,” Journal of Superconductivity and Novel Magnetism, vol. 29, pp. 2805–2811, 2016.
140. P. Paramasivan, “Comparative investigation of NiFe2O4 nano and microstructures for structural, optical, magnetic and catalytic properties,” Advanced Science, Engineering and Medicine, vol. 8, pp. 392–397, 2016.
141. P. Paramasivan, “Controllable synthesis of CuFe2O4 nanostructures through simple hydrothermal method in the presence of thioglycolic acid,” Physica E: Low-dimensional Systems and Nanostructures, vol. 84, pp. 258–262, 2016.
142. P. Paramasivan, S. Narayanan, and N. M. Faizee, “Enhancing Catalytic Activity of Mn3O4 by Selective Liquid Phase Oxidation of Benzyl Alcohol,” Advanced Science, Engineering and Medicine, vol. 10, pp. 1–5, 2018.
143. S Silvia Priscila, M Hemalatha, “ Diagnosisof heart disease with particle bee-neural network” Biomedical Research, Special Issue, pp. S40-S46, 2018.
144. S Silvia Priscila, M Hemalatha, “ Heart Disease Prediction Using Integer-Coded Genetic Algorithm (ICGA) Based Particle Clonal Neural Network (ICGA-PCNN)”, Bonfring International Journal of Industrial Engineering and Management Science 8 (2), 15-19, 2018.
145. S. Ambika, T. A. Sivakumar, and P. Sukantha, “Preparation and characterization of nanocopper ferrite and its green catalytic activity in alcohol oxidation reaction,” Journal of Superconductivity and Novel Magnetism, vol. 32, pp. 903–910, 2019.
146. S. Khan, V. Ch, K. Sekaran, K. Joshi, C. K. Roy and M. Tiwari, "Incorporating Deep Learning Methodologies into the Creation of Healthcare Systems," 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, 2023, pp. 994-998.
147. Sahoo, A. K., & Samal, S. K. (2023). Online fault detection and classification of 3-phase long transmission line using machine learning model. Multiscale and Multidisciplinary Modeling, Experiments and Design, 6(1), 135-146.
148. SS Priscila, M Hemalatha, “Improving the performance of entropy ensembles of neural networks (EENNS) on classification of heart disease prediction”, Int J Pure Appl Math 117 (7), 371-386, 2017.
149. Tadiboina, S. N., & Chase, G. C. (2022). The importance and leverage of modern information technology infrastructure in the healthcare industry. Int J Res Trends Innov, 7(11), 340-344.
Published
2023-10-11
How to Cite
Almas Begum M.A.A, Gandhi Geerthana M, Siva Sakthiya M, P. Anand, & Shagar Banu. M. (2023). Application of SRF-PI Current Control in the Design of a Single-Phase Asymmetrical Inverter for Use in Weak Grid Environments. International Journal of Human Computing Studies, 5(10), 24-40. https://doi.org/10.31149/ijhcs.v5i10.4854
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