Single Switch DC-DC Converter for Battery Feed Electrical Vehicle
Keywords:
Single Switch, DC-DC Converter, Battery, Feed Electrical Vehicle
Abstract
A new single-switch transformer less lift DC-DC converter has been suggested that energy component cars could benefit from a new single-switch transformer reduced lift DC-DC converter. The newly developed topology makes use of a different capacitor multiplier and an integrated LC2D yield organise in order to improve the voltage addition of the converter and reduce the voltage load that is placed on the force switch. In addition, the suggested converter features a broad voltage gain range, which allows it to accommodate a broad variety of voltage swings produced by the energy component. The operating standards of the suggested converter as well as its consistent state examinations are presented below. Recreation was utilised in the production of a scaled-down, exploratory model that had 800 V and 1 kW. The outcomes of the re-enactment demonstrate that the framework is sufficient.
References
1. Rina Bora, Deepa Parasar, Shrikant Charhate, A detection of tomato plant diseases using deep learning MNDLNN classifier, Signal, Image and Video Processing, April 2023.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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.
17. 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.
18. 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.
19. S. Degadwala, D. Vyas, H. Biswas, U. Chakraborty, and S. Saha, “Image captioning using inception V3 transfer learning model,” in 2021 6th International Conference on Communication and Electronics Systems (ICCES), 2021, pp. 1103–1108.
20. H. Dave, V. Patel, J. N. Mehta, S. Degadwala, and D. Vyas, “Regional Kidney Stone Detection and Classification In Ultrasound Images,” in 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), 2021, pp. 1108–1112.
21. S. Degadwala, D. Vyas, M. R. Hossain, A. R. DIder, M. N. Ali, and P. Kuri, “Location-Based Modelling and Analysis of Threats by Using Text Mining,” Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, pp. 1940–1944, 2021.
22. A. Mahajan, J. Patel, M. Parmar, G. L. A. Joao, K. Shekokar, and S. Degadwala, “3-Layer LSTM Model for Detection of Epileptic Seizures,” in 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), 2020, pp. 447–450.
23. Mahajan, S. Degadwala, P. Talukder, B. Meetei, and M. Rameshkumar, “A Novel Approach on Epileptic Seizures Detection Using Convolutional Neural Network,” in 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2020, pp. 1541–1545.
24. S. D. Patel, S. Degadwala, and A. Mahajan, “A Review on Acute Lymphoblastic Leukemia Classification Based on Hybrid Low Level Features,” in 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), 2020, pp. 1–5.
25. M. Kulkarni, S. Degadwala, and A. Mahajan, “A Review on Digital Image Watermarking Based on Dual Noise and Geometric Attacks,” in 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), 2020, pp. 778–781.
26. S. Degadwala, D. Vyas, H. Dave, and A. Mahajan, “Visual social distance alert system using computer vision & deep learning,” in 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2020, pp. 1512–1516.
27. S. Degadwala, U. Chakraborty, S. Saha, H. Biswas, and D. Vyas, “EPNet: Efficient Patch-based Deep Network for Real-Time Semantic Segmentation,” in 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), 2020, pp. 611–615.
28. K. S. Varma, A. Mahajan, and S. D. Degadwala, “Product Reviews based on Location using N-gram model,” in 2018 3rd International Conference on Inventive Computation Technologies (ICICT), 2018, pp. 100–104.
29. S. J. Patel, S. D. Degadwala, and K. S. Shekokar, “A survey on multi light source shadow detection techniques,” in 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017, pp. 1–4.
30. S. D. Degadwala and S. Gaur, “Two way privacy preserving system using combine approach: QR-code & VCS,” in 2017 Innovations in Power and Advanced Computing Technologies (i-PACT), 2017, pp. 1–5.
31. S. D. Degadwala and S. Gaur, “An efficient privacy preserving system using VCS, block DWT-SVD and modified zernike moment on RST attacks,” in 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–4.
32. S. Degadwala, S. Pandya, V. Patel, S. Shah, and U. Doshi, “A review on real time face tracking and identification for surveillance system,” in International Conference on Recent Trends in Engineering, Science & Technology - (ICRTEST 2016), 2016, pp. 1–5.
33. S. D. Degadwala and S. Gaur, “A study of privacy preserving system based on progressive VCS and RST attacks,” in 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016, pp. 138–142.
34. J. Samajpati and S. D. Degadwala, “Hybrid approach for apple fruit diseases detection and classification using random forest classifier,” in 2016 International Conference on Communication and Signal Processing (ICCSP), 2016, pp. 1015–1019.
35. P. A. Parmar and S. D. Degadwala, “A feature level fusion fingerprint indexing approach based on MV and MCC using SVM classifier,” in 2016 International Conference on Communication and Signal Processing (ICCSP), 2016, pp. 1024–1028.
36. Venkatasubramanian.S, et al. “A Cross Layer Supported Non-Reservation Based Approach For Qos Provisioning In Mobile Ad Hoc Networks”, International Journal of Innovative Research in Science and Engineering, vol.3, No.2, 184-189. 2017
37. Venkatasubramanian, S., Suhasini, A., Vennila, C. “QoS Provisioning in MANET Using Fuzzy-Based Multifactor Multipath Routing Metric”. In proceedings of Sustainable Communication Networks and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 93. Springer, Singapore.
38. R. Harini, R. Janani, S. Keerthana, S. Madhubala and S. Venkatasubramanian, "Sign Language Translation," 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020, pp. 883-886.
39. S.Venkatasubramanian, A. Suhasini, C.Vennila, "Cluster Head Selection and Optimal Multipath detection using Coral Reef Optimization in MANET Environment", International Journal of Computer Network and Information Security(IJCNIS), Vol.14, No.3, pp.88-99, 2022.
40. Venkatasubramanian, S., Suhasini, A., Lakshmi Kanthan, “Sparrow Search Algorithm for Detecting the Cross-layer Packet Drop Attack in Mobile Ad Hoc Network (MANET) Environment”, Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117, 2022, Springer, Singapore.
41. Veena, A., Gowrishankar, S. An automated pre-term prediction system using EHG signal with the aid of deep learning technique. Multimed Tools Appl (2023).
42. 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.
43. 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.
44. 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,
45. 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.
46. 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.
47. 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.
48. 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.
49. 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.
50. 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.
51. 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.
52. 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.
53. 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.
54. A. Bodepudi, M. Reddy, S. S. Gutlapalli, and M. Mandapuram, “Voice recognition systems in the Cloud Networks,” Asian Journal of Applied Science and Engineering, vol. 8, no. 1, pp. 51–60, 2019.
55. Bodepudi, M. Reddy, S. S. Gutlapalli, and M. Mandapuram, “Algorithm policy for the authentication of indirect fingerprints used in cloud computing,” American Journal of Trade and Policy, vol. 8, no. 3, pp. 231–238, 2021.
56. S. S. Gutlapalli, M. Mandapuram, M. Reddy, and A. Bodepudi, “Evaluation of Hospital Information Systems (his) in terms of their suitability for tasks,” Malaysian Journal of Medical and Biological Research, vol. 6, no. 2, pp. 143–150, 2019.
57. M. Mandapuram, “Applications of Blockchain and Distributed Ledger Technology (DLT) in Commercial Settings”, Asian Accounting and Auditing Advancement (4A Journal), vol. 7, no. 1, pp. 50–57, Dec. 2016.
58. M. Mandapuram, “Application of artificial intelligence in contemporary business: An analysis for content management system optimization,” Asian Business Review, vol. 7, no. 3, pp. 117–122, 2017a.
59. M. Mandapuram, “Security risk analysis of the internet of things,” ABC Research Alert, vol. 5, no. 3, pp. 49–55, 2017b.
60. 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.
61. 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.
62. Nemade, “Automatic traffic surveillance using video tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016.
63. M. Mandapuram, S. R. Thodupunori, A. Bodepudi, and M. Reddy, “Investigating the prospects of Generative Artificial Intelligence,” Asian Journal of Humanity, Art and Literature, vol. 5, no. 2, pp. 167–174, 2018.
64. M. Mandapuram, S. S. Gutlapalli, M. Reddy, and A. Bodepudi, “Application of artificial intelligence (AI) technologies to accelerate market segmentation,” Global Disclosure of Economics and Business, vol. 9, no. 2, pp. 141–150, 2020.
65. M. Mandapuram and Md. F. Hosen, “The object-oriented database management system versus the Relational Database Management System: A comparison,” Global Disclosure of Economics and Business, vol. 7, no. 2, pp. 89–96, 2018.
66. M. Reddy, A. Bodepudi, M. Mandapuram, and S. S. Gutlapalli, “Face detection and recognition techniques through the Cloud Network: An Exploratory Study,” ABC Journal of Advanced Research, vol. 9, no. 2, pp. 103–114, 2020.
67. G. P. Shukla, P. Chaudhary, P. Ghosh, M. Mandapuram, S. S. Gutlapalli, M Lourens, “Human resource management: a conceptual framework for comprehending the Internet of Things (IoT) and Machine Learning,” Official Journal of the Patent Office (IN), no. 26/2023 (30/06/2023), 2023. Patent number 202321036845 A.
68. A. R. Kunduru, "Security Concerns and Solutions for Enterprise Cloud Computing Applications," Asian Journal of Research in Computer Science, vol. 15, no. 4, pp. 24-33, 2023.
69. R. Kunduru, "Industry Best Practices on Implementing Oracle Cloud ERP Security," International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 1-8, 2023.
70. R. Kunduru, "Cloud Appian BPM (Business Process Management) Usage In health care Industry," IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 6, pp. 339-343, 2023.
71. R. Kunduru, "Effective Usage of Artificial Intelligence in Enterprise Resource Planning Applications," International Journal of Computer Trends and Technology, vol. 71, no. 4, pp. 73-80, 2023.
72. R. Kunduru, "Recommendations to Advance the Cloud Data Analytics and Chatbots by Using Machine Learning Technology," International Journal of Engineering and Scientific Research, vol. 11, no. 3, pp. 8-20, 2023.
73. R. Kunduru and R. Kandepu, "Data Archival Methodology in Enterprise Resource Planning Applications (Oracle ERP, Peoplesoft)," Journal of Advances in Mathematics and Computer Science, vol. 38, no. 9, pp. 115-127, 2023.
74. R. Kunduru, "Artificial Intelligence Usage in Cloud Application Performance Improvement," Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 8, pp. 42-47, 2023.
75. R. Kunduru, "Artificial Intelligence Advantages in Cloud Fintech Application Security," Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 8, pp. 48-53, 2023.
76. R. Kunduru, "Cloud BPM Application (Appian) Robotic Process Automation Capabilities," Asian Journal of Research in Computer Science, vol. 16, no. 3, pp. 267-280, Aug. 2023.
77. R. Kunduru, “Machine Learning in Drug Discovery: A Comprehensive Analysis of Applications, Challenges, and Future Directions”, IJOT, vol. 5, no. 8, pp. 29-37, Aug. 2023.
78. Khan, S. (2021). Data Visualization to Explore the Countries Dataset for Pattern Creation. International Journal of Online Biomedical Engineering, 17(13), 4-19.
79. 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).
80. 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).
81. 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.
82. Khan, S., & Alshara, M. (2019). Development of Arabic evaluations in information retrieval. International Journal of Advanced Applied Sciences, 6(12), 92-98.
83. 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.
84. 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).
85. 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.
86. 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.
87. 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.
88. 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.
89. 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.
90. 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.
91. 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, (pp. 1164-1168). IEEE.
92. 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.
93. S. S. Banait, S. S. Sane, D. D. Bage and A. R. Ugale, “Reinforcement mSVM: An Efficient Clustering and Classification Approach using reinforcement and supervised Technique, ”International Journal of Intelligent Systems and Applications in Engineering (IJISAE), Vol.35, no.1S, p .78-89. 2022.
94. S. S. Banait, S. S. Sane and S. A. Talekar, “An efficient Clustering Technique for Big Data Mining”, International Journal of Next Generation Computing (IJNGC), Vol.13, no.3, pp.702-717. 2022.
95. S. A. Talekar, S. S. Banait and M. Patil. “Improved Q- Reinforcement Learning Based Optimal Channel Selection in CognitiveRadio Networks,” International Journal of Computer Networks & Communications (IJCNC), Vol.15, no.3, pp.1-14, 2023.
96. S. S. Banait and S. S. Sane, “Novel Data Dimensionality Reduction Approach Using Static Threshold, Minimum Projection Error and Minimum Redundancy, “Asian Journal of Organic & Medicinal Chemistry (AJOMC), Vol.17, no.2, pp.696-705, 2022.
97. S. S. Banait and S. S. Sane, “Result Analysis for Instance and Feature Selection in Big Data Environment, “International Journal for Research in Engineering Application & Management (IJREAM), Vol.8, no.2, pp.210-215, 2022.
98. A, V. V.., T, S.., S, S. N.., & Rajest, D. S. S.. (2022). IoT-Based Automated Oxygen Pumping System for Acute Asthma Patients. European Journal of Life Safety and Stability (2660-9630), 19 (7), 8-34.
99. 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.
100. Ali Y., Shreemali J., Chakrabarti T., Chakrabarti P., Poddar S., “Prediction of Reaction Parameters on Reaction Kinetics for Treatment of Industrial Wastewater: A Machine Learning Perspective”, Materials Today: Proceedings, 2020.
101. Ashish Kumar Sinha, Ananda Shankar Hati, Mohamed Benbouzid, Prasun Chakrabarti, “ANN-based Pattern Recognition for Induction Motor Broken Rotor Bar Monitoring under Supply Frequency Regulation”, Machines, 9(5):87, 2021.
102. 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.
103. Chakrabarti P., Basu J.K., Kim T.H., “Business Planning in the light of Neuro-fuzzy and Predictive Forecasting”, Communications in Computer and Information Science, 123, pp.283-290, 2010.
104. Chakrabarti P., Goswami P.S., “Approach towards realizing resource mining and secured information transfer”, International Journal of Computer Science and Network Security, 8(7), pp.345-350, 2008.
105. Chakrabarti P., Chakrabarti T., Sharma M., Atre D, Pai K.B., “Quantification of Thought Analysis of Alcohol-addicted persons and memory loss of patients suffering from stage-4 liver cancer”, Advances in Intelligent Systems and Computing, 1053, pp.1099-1105, 2020.
106. Chakrabarti P., Bane S., Satpathy B., Goh M, Datta B N, Chakrabarti T., “Compound Poisson Process and its Applications in Business”, Lecture Notes in Electrical Engineering, 601, pp.678-685,2020.
107. Chakrabarti P., Bhuyan B., Chaudhuri A. and Bhunia C.T., “A novel approach towards realizing optimum data transfer and Automatic Variable Key(AVK)”, International Journal of Computer Science and Network Security, 8(5), pp.241-250, 2008.
108. Chakrabarti P., Chakrabarti T., Satpathy B., SenGupta I. Ware J A., “Analysis of strategic market management in the light of stochastic processes, recurrence relation, Abelian group and expectation”, Advances in Artificial Intelligence and Data Engineering, 1133, pp.701-710, 2020.
109. Chakrabarti P., Choudhury A., Naik N., Bhunia C.T., “Key generation in the light of mining and fuzzy rule”, International Journal of Computer Science and Network Security, 8(9), pp.332-337, 2008.
110. Chakrabarti P., De S.K., Sikdar S.C., “Statistical Quantification of Gain Analysis in Strategic Management”, International Journal of Computer Science and Network Security,9(11), pp.315-318, 2009.
111. Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Poddar S., “Business gain forecasting in Materials Industry - A linear dependency, exponential growth, moving average, neuro-associator and compound Poisson process perspective”, Materials Today: Proceedings, 2020.
112. Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Chaudhuri N.S., Siano P., “Business forecasting in the light of statistical approaches and machine learning classifiers”, Communications in Computer and Information Science, 1045, pp.13-21, 2019.
113. G. K. Bhamre and S. S. Banait, “Parallelization of Multipattern Matching on GPU, “International Journal of Electronics, Communication & Soft Computing Science and Engineering, Vol.3, no.3, pp.24-28, 2014.
114. Gupta, I.K., Choubey, A. and Choubey, S., 2022. Artifical intelligence with optimal deep learning enabled automated retinal fundus image classification model. Expert Systems, 39(10), p.e13028.
115. Gupta, I.K., Choubey, A. and Choubey, S., 2022. Mayfly optimization with deep learning enabled retinal fundus image classification model. Computers and Electrical Engineering, 102, p.108176.
116. Gupta, I.K., Mishra, A.K., Diwan, T.D. and Srivastava, S., 2023. Unequal clustering scheme for hotspot mitigation in IoT-enabled wireless sensor networks based on fire hawk optimization. Computers and Electrical Engineering, 107, p.108615.
117. K. Gupta, A. Choubey, and S. Choubey, “Salp swarm optimisation with deep transfer learning enabled retinal fundus image classification model,” Int. J. Netw. Virtual Organ., vol. 27, no. 2, p. 163–180, 2022.
118. Jerusha Angelene Christabel G, Shynu T, S. Suman Rajest, R. Regin, & Steffi. R. (2022). The use of Internet of Things (Iot) Technology in the Context of “Smart Gardens” is Becoming Increasingly Popular. International Journal of Biological Engineering and Agriculture, 1(2), 1–13.
119. Kothi N., Laxkar P. Jain A., Chakrabarti P., “Ledger based sorting algorithm”, Advances in Intelligent Systems and Computing, 989, pp. 37-46, 2020.
120. Magare A., Lamin M., Chakrabarti P., “Inherent Mapping Analysis of Agile Development Methodology through Design Thinking”, Lecture Notes on Data Engineering and Communications Engineering, 52, pp.527-534,2020.
121. Meng, F. (2023) Transformers: Statistical Interpretation, Architectures and Applications.
122. Meng, F., Jagadeesan, L., & Thottan, M. (2021). Model-based reinforcement learning for service mesh fault resiliency in a web application-level. arXiv preprint arXiv:2110.13621.
123. Meng, F., Zhang, L., & Chen, Y. (2023) FEDEMB: An Efficient Vertical and Hybrid Federated Learning Algorithm Using Partial Network Embedding.
124. Meng, F., Zhang, L., & Chen, Y. (2023) Sample-Based Dynamic Hierarchical Trans-Former with Layer and Head Flexibility Via Contextual Bandit.
125. Mishra, A.K., Gupta, I.K., Diwan, T.D. and Srivastava, S., 2023. Cervical precancerous lesion classification using quantum invasive weed optimization with deep learning on biomedical pap smear images. Expert Systems, p.e13308.
126. 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.
127. Mishra, S., & Samal, S. K. (2023). Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector. Energy Systems, 1-13.
128. 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.
129. Patidar H., Chakrabarti P., “A Novel Edge Cover based Graph Coloring Algorithm”, International Journal of Advanced Computer Science and Applications, 8(5), pp.279-286,2017.
130. Patidar H., Chakrabarti P., “A Tree-based Graphs Coloring Algorithm Using Independent Set”, Advances in Intelligent Systems and Computing, 714, pp. 537-546, 2019.
131. Patidar H., Chakrabarti P., Ghosh A., “Parallel Computing Aspects in Improved Edge Cover based Graph Coloring Algorithm”, Indian Journal of Science and Technology ,10(25), pp.1-9,2017.
132. Prasad A., Chakrabarti P., “Extending Access Management to maintain audit logs in cloud computing", International Journal of Advanced Computer Science and Applications, 5(3), pp.144-147, 2014.
133. Priyadarshi N., Bhoi A.K., Sahana S.K., Mallick P.K., Chakrabarti P., Performance enhancement using novel soft computing AFLC approach for PV power system”, Advances in Intelligent Systems and Computing, 1040, pp.439-448,2020.
134. Priyadarshi N., Bhoi A.K., Sharma A.K., Mallick P.K., Chakrabarti P., “An efficient fuzzy logic control-based soft computing technique for grid-tied photovoltaic system”, Advances in Intelligent Systems and Computing, 1040,pp.131-140,2020.
135. R. Regin, Steffi. R, Jerusha Angelene Christabel G, Shynu T, S. Suman Rajest (2022), “Internet of Things (IoT) System Using Interrelated Computing Devices in Billing System”, Journal of Advanced Research in Dynamical and Control Systems, Vol.14, no.1, pp. 24-40.
136. R. Steffi, G. Jerusha Angelene Christabel, T. Shynu, S. Suman Rajest, R. Regin (2022), “ A Method for the Administration of the Work Performed by Employees”, Journal of Advanced Research in Dynamical and Control Systems, Vol.14, no.1, pp. 7-23.
137. Rajest, S. S.., Regin, R.., T, S.., G, J. A. C.., & R, S. (2022). Production of Blockchains as Well as their Implementation. Vital Annex: International Journal of Novel Research in Advanced Sciences, 1(2), 21–44.
138. Regin, D. R., Rajest, D. S. S., T, S., G, J. A. C., & R, S. (2022). An Automated Conversation System Using Natural Language Processing (NLP) Chatbot in Python. Central Asian Journal Of Medical And Natural Sciences, 3(4), 314-336.
139. S. S. Rajest, R. Regin, S. T, J. A. C. G, and S. R, “Improving Infrastructure and Transportation Systems Using Internet of Things Based Smart City”, CAJOTAS, vol. 3, no. 9, pp. 125-141, Sep. 2022.
140. 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.
141. Shah K., Laxkar P., Chakrabarti P., “A hypothesis on ideal Artificial Intelligence and associated wrong implications”, Advances in Intelligent Systems and Computing, 989, pp.283-294, 2020.
142. Sharma A.K., Panwar A., Chakrabarti P. Viswakarma S., “Categorization of ICMR Using Feature Extraction Strategy and MIR with Ensemble Learning”, Procedia Computer Science, 57, pp.686-694,2015.
143. T, S., Rajest, S. S., Regin, R., Christabel G, J. A., & R, S. (2022). Automation And Control Of Industrial Operations Using Android Mobile Devices Based On The Internet Of Things. Central Asian Journal of Mathematical Theory and Computer Sciences, 3(9), 1-33.
144. Tiwari M., Chakrabarti P, Chakrabarti T., “Performance analysis and error evaluation towards the liver cancer diagnosis using lazy classifiers for ILPD”, Communications in Computer and Information Science, 837, pp.161-168,2018.
145. Tiwari M., Chakrabarti P, Chakrabarti T., “Novel work of diagnosis in liver cancer using Tree classifier on liver cancer dataset (BUPA liver disorder)”, Communications in Computer and Information Science, 837, pp.155-160, 2018.
Verma K., Srivastava P., Chakrabarti P., “Exploring structure oriented feature tag weighting algorithm for web documents identification”, Communications in Computer and Information Science, 837, pp.169-180, 2018.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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.
17. 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.
18. 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.
19. S. Degadwala, D. Vyas, H. Biswas, U. Chakraborty, and S. Saha, “Image captioning using inception V3 transfer learning model,” in 2021 6th International Conference on Communication and Electronics Systems (ICCES), 2021, pp. 1103–1108.
20. H. Dave, V. Patel, J. N. Mehta, S. Degadwala, and D. Vyas, “Regional Kidney Stone Detection and Classification In Ultrasound Images,” in 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), 2021, pp. 1108–1112.
21. S. Degadwala, D. Vyas, M. R. Hossain, A. R. DIder, M. N. Ali, and P. Kuri, “Location-Based Modelling and Analysis of Threats by Using Text Mining,” Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, pp. 1940–1944, 2021.
22. A. Mahajan, J. Patel, M. Parmar, G. L. A. Joao, K. Shekokar, and S. Degadwala, “3-Layer LSTM Model for Detection of Epileptic Seizures,” in 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), 2020, pp. 447–450.
23. Mahajan, S. Degadwala, P. Talukder, B. Meetei, and M. Rameshkumar, “A Novel Approach on Epileptic Seizures Detection Using Convolutional Neural Network,” in 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2020, pp. 1541–1545.
24. S. D. Patel, S. Degadwala, and A. Mahajan, “A Review on Acute Lymphoblastic Leukemia Classification Based on Hybrid Low Level Features,” in 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), 2020, pp. 1–5.
25. M. Kulkarni, S. Degadwala, and A. Mahajan, “A Review on Digital Image Watermarking Based on Dual Noise and Geometric Attacks,” in 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), 2020, pp. 778–781.
26. S. Degadwala, D. Vyas, H. Dave, and A. Mahajan, “Visual social distance alert system using computer vision & deep learning,” in 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2020, pp. 1512–1516.
27. S. Degadwala, U. Chakraborty, S. Saha, H. Biswas, and D. Vyas, “EPNet: Efficient Patch-based Deep Network for Real-Time Semantic Segmentation,” in 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), 2020, pp. 611–615.
28. K. S. Varma, A. Mahajan, and S. D. Degadwala, “Product Reviews based on Location using N-gram model,” in 2018 3rd International Conference on Inventive Computation Technologies (ICICT), 2018, pp. 100–104.
29. S. J. Patel, S. D. Degadwala, and K. S. Shekokar, “A survey on multi light source shadow detection techniques,” in 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017, pp. 1–4.
30. S. D. Degadwala and S. Gaur, “Two way privacy preserving system using combine approach: QR-code & VCS,” in 2017 Innovations in Power and Advanced Computing Technologies (i-PACT), 2017, pp. 1–5.
31. S. D. Degadwala and S. Gaur, “An efficient privacy preserving system using VCS, block DWT-SVD and modified zernike moment on RST attacks,” in 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), 2017, pp. 1–4.
32. S. Degadwala, S. Pandya, V. Patel, S. Shah, and U. Doshi, “A review on real time face tracking and identification for surveillance system,” in International Conference on Recent Trends in Engineering, Science & Technology - (ICRTEST 2016), 2016, pp. 1–5.
33. S. D. Degadwala and S. Gaur, “A study of privacy preserving system based on progressive VCS and RST attacks,” in 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016, pp. 138–142.
34. J. Samajpati and S. D. Degadwala, “Hybrid approach for apple fruit diseases detection and classification using random forest classifier,” in 2016 International Conference on Communication and Signal Processing (ICCSP), 2016, pp. 1015–1019.
35. P. A. Parmar and S. D. Degadwala, “A feature level fusion fingerprint indexing approach based on MV and MCC using SVM classifier,” in 2016 International Conference on Communication and Signal Processing (ICCSP), 2016, pp. 1024–1028.
36. Venkatasubramanian.S, et al. “A Cross Layer Supported Non-Reservation Based Approach For Qos Provisioning In Mobile Ad Hoc Networks”, International Journal of Innovative Research in Science and Engineering, vol.3, No.2, 184-189. 2017
37. Venkatasubramanian, S., Suhasini, A., Vennila, C. “QoS Provisioning in MANET Using Fuzzy-Based Multifactor Multipath Routing Metric”. In proceedings of Sustainable Communication Networks and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 93. Springer, Singapore.
38. R. Harini, R. Janani, S. Keerthana, S. Madhubala and S. Venkatasubramanian, "Sign Language Translation," 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020, pp. 883-886.
39. S.Venkatasubramanian, A. Suhasini, C.Vennila, "Cluster Head Selection and Optimal Multipath detection using Coral Reef Optimization in MANET Environment", International Journal of Computer Network and Information Security(IJCNIS), Vol.14, No.3, pp.88-99, 2022.
40. Venkatasubramanian, S., Suhasini, A., Lakshmi Kanthan, “Sparrow Search Algorithm for Detecting the Cross-layer Packet Drop Attack in Mobile Ad Hoc Network (MANET) Environment”, Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117, 2022, Springer, Singapore.
41. Veena, A., Gowrishankar, S. An automated pre-term prediction system using EHG signal with the aid of deep learning technique. Multimed Tools Appl (2023).
42. 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.
43. 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.
44. 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,
45. 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.
46. 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.
47. 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.
48. 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.
49. 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.
50. 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.
51. 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.
52. 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.
53. 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.
54. A. Bodepudi, M. Reddy, S. S. Gutlapalli, and M. Mandapuram, “Voice recognition systems in the Cloud Networks,” Asian Journal of Applied Science and Engineering, vol. 8, no. 1, pp. 51–60, 2019.
55. Bodepudi, M. Reddy, S. S. Gutlapalli, and M. Mandapuram, “Algorithm policy for the authentication of indirect fingerprints used in cloud computing,” American Journal of Trade and Policy, vol. 8, no. 3, pp. 231–238, 2021.
56. S. S. Gutlapalli, M. Mandapuram, M. Reddy, and A. Bodepudi, “Evaluation of Hospital Information Systems (his) in terms of their suitability for tasks,” Malaysian Journal of Medical and Biological Research, vol. 6, no. 2, pp. 143–150, 2019.
57. M. Mandapuram, “Applications of Blockchain and Distributed Ledger Technology (DLT) in Commercial Settings”, Asian Accounting and Auditing Advancement (4A Journal), vol. 7, no. 1, pp. 50–57, Dec. 2016.
58. M. Mandapuram, “Application of artificial intelligence in contemporary business: An analysis for content management system optimization,” Asian Business Review, vol. 7, no. 3, pp. 117–122, 2017a.
59. M. Mandapuram, “Security risk analysis of the internet of things,” ABC Research Alert, vol. 5, no. 3, pp. 49–55, 2017b.
60. 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.
61. 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.
62. Nemade, “Automatic traffic surveillance using video tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016.
63. M. Mandapuram, S. R. Thodupunori, A. Bodepudi, and M. Reddy, “Investigating the prospects of Generative Artificial Intelligence,” Asian Journal of Humanity, Art and Literature, vol. 5, no. 2, pp. 167–174, 2018.
64. M. Mandapuram, S. S. Gutlapalli, M. Reddy, and A. Bodepudi, “Application of artificial intelligence (AI) technologies to accelerate market segmentation,” Global Disclosure of Economics and Business, vol. 9, no. 2, pp. 141–150, 2020.
65. M. Mandapuram and Md. F. Hosen, “The object-oriented database management system versus the Relational Database Management System: A comparison,” Global Disclosure of Economics and Business, vol. 7, no. 2, pp. 89–96, 2018.
66. M. Reddy, A. Bodepudi, M. Mandapuram, and S. S. Gutlapalli, “Face detection and recognition techniques through the Cloud Network: An Exploratory Study,” ABC Journal of Advanced Research, vol. 9, no. 2, pp. 103–114, 2020.
67. G. P. Shukla, P. Chaudhary, P. Ghosh, M. Mandapuram, S. S. Gutlapalli, M Lourens, “Human resource management: a conceptual framework for comprehending the Internet of Things (IoT) and Machine Learning,” Official Journal of the Patent Office (IN), no. 26/2023 (30/06/2023), 2023. Patent number 202321036845 A.
68. A. R. Kunduru, "Security Concerns and Solutions for Enterprise Cloud Computing Applications," Asian Journal of Research in Computer Science, vol. 15, no. 4, pp. 24-33, 2023.
69. R. Kunduru, "Industry Best Practices on Implementing Oracle Cloud ERP Security," International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 1-8, 2023.
70. R. Kunduru, "Cloud Appian BPM (Business Process Management) Usage In health care Industry," IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 6, pp. 339-343, 2023.
71. R. Kunduru, "Effective Usage of Artificial Intelligence in Enterprise Resource Planning Applications," International Journal of Computer Trends and Technology, vol. 71, no. 4, pp. 73-80, 2023.
72. R. Kunduru, "Recommendations to Advance the Cloud Data Analytics and Chatbots by Using Machine Learning Technology," International Journal of Engineering and Scientific Research, vol. 11, no. 3, pp. 8-20, 2023.
73. R. Kunduru and R. Kandepu, "Data Archival Methodology in Enterprise Resource Planning Applications (Oracle ERP, Peoplesoft)," Journal of Advances in Mathematics and Computer Science, vol. 38, no. 9, pp. 115-127, 2023.
74. R. Kunduru, "Artificial Intelligence Usage in Cloud Application Performance Improvement," Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 8, pp. 42-47, 2023.
75. R. Kunduru, "Artificial Intelligence Advantages in Cloud Fintech Application Security," Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 8, pp. 48-53, 2023.
76. R. Kunduru, "Cloud BPM Application (Appian) Robotic Process Automation Capabilities," Asian Journal of Research in Computer Science, vol. 16, no. 3, pp. 267-280, Aug. 2023.
77. R. Kunduru, “Machine Learning in Drug Discovery: A Comprehensive Analysis of Applications, Challenges, and Future Directions”, IJOT, vol. 5, no. 8, pp. 29-37, Aug. 2023.
78. Khan, S. (2021). Data Visualization to Explore the Countries Dataset for Pattern Creation. International Journal of Online Biomedical Engineering, 17(13), 4-19.
79. 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).
80. 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).
81. 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.
82. Khan, S., & Alshara, M. (2019). Development of Arabic evaluations in information retrieval. International Journal of Advanced Applied Sciences, 6(12), 92-98.
83. 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.
84. 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).
85. 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.
86. 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.
87. 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.
88. 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.
89. 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.
90. 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.
91. 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, (pp. 1164-1168). IEEE.
92. 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.
93. S. S. Banait, S. S. Sane, D. D. Bage and A. R. Ugale, “Reinforcement mSVM: An Efficient Clustering and Classification Approach using reinforcement and supervised Technique, ”International Journal of Intelligent Systems and Applications in Engineering (IJISAE), Vol.35, no.1S, p .78-89. 2022.
94. S. S. Banait, S. S. Sane and S. A. Talekar, “An efficient Clustering Technique for Big Data Mining”, International Journal of Next Generation Computing (IJNGC), Vol.13, no.3, pp.702-717. 2022.
95. S. A. Talekar, S. S. Banait and M. Patil. “Improved Q- Reinforcement Learning Based Optimal Channel Selection in CognitiveRadio Networks,” International Journal of Computer Networks & Communications (IJCNC), Vol.15, no.3, pp.1-14, 2023.
96. S. S. Banait and S. S. Sane, “Novel Data Dimensionality Reduction Approach Using Static Threshold, Minimum Projection Error and Minimum Redundancy, “Asian Journal of Organic & Medicinal Chemistry (AJOMC), Vol.17, no.2, pp.696-705, 2022.
97. S. S. Banait and S. S. Sane, “Result Analysis for Instance and Feature Selection in Big Data Environment, “International Journal for Research in Engineering Application & Management (IJREAM), Vol.8, no.2, pp.210-215, 2022.
98. A, V. V.., T, S.., S, S. N.., & Rajest, D. S. S.. (2022). IoT-Based Automated Oxygen Pumping System for Acute Asthma Patients. European Journal of Life Safety and Stability (2660-9630), 19 (7), 8-34.
99. 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.
100. Ali Y., Shreemali J., Chakrabarti T., Chakrabarti P., Poddar S., “Prediction of Reaction Parameters on Reaction Kinetics for Treatment of Industrial Wastewater: A Machine Learning Perspective”, Materials Today: Proceedings, 2020.
101. Ashish Kumar Sinha, Ananda Shankar Hati, Mohamed Benbouzid, Prasun Chakrabarti, “ANN-based Pattern Recognition for Induction Motor Broken Rotor Bar Monitoring under Supply Frequency Regulation”, Machines, 9(5):87, 2021.
102. 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.
103. Chakrabarti P., Basu J.K., Kim T.H., “Business Planning in the light of Neuro-fuzzy and Predictive Forecasting”, Communications in Computer and Information Science, 123, pp.283-290, 2010.
104. Chakrabarti P., Goswami P.S., “Approach towards realizing resource mining and secured information transfer”, International Journal of Computer Science and Network Security, 8(7), pp.345-350, 2008.
105. Chakrabarti P., Chakrabarti T., Sharma M., Atre D, Pai K.B., “Quantification of Thought Analysis of Alcohol-addicted persons and memory loss of patients suffering from stage-4 liver cancer”, Advances in Intelligent Systems and Computing, 1053, pp.1099-1105, 2020.
106. Chakrabarti P., Bane S., Satpathy B., Goh M, Datta B N, Chakrabarti T., “Compound Poisson Process and its Applications in Business”, Lecture Notes in Electrical Engineering, 601, pp.678-685,2020.
107. Chakrabarti P., Bhuyan B., Chaudhuri A. and Bhunia C.T., “A novel approach towards realizing optimum data transfer and Automatic Variable Key(AVK)”, International Journal of Computer Science and Network Security, 8(5), pp.241-250, 2008.
108. Chakrabarti P., Chakrabarti T., Satpathy B., SenGupta I. Ware J A., “Analysis of strategic market management in the light of stochastic processes, recurrence relation, Abelian group and expectation”, Advances in Artificial Intelligence and Data Engineering, 1133, pp.701-710, 2020.
109. Chakrabarti P., Choudhury A., Naik N., Bhunia C.T., “Key generation in the light of mining and fuzzy rule”, International Journal of Computer Science and Network Security, 8(9), pp.332-337, 2008.
110. Chakrabarti P., De S.K., Sikdar S.C., “Statistical Quantification of Gain Analysis in Strategic Management”, International Journal of Computer Science and Network Security,9(11), pp.315-318, 2009.
111. Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Poddar S., “Business gain forecasting in Materials Industry - A linear dependency, exponential growth, moving average, neuro-associator and compound Poisson process perspective”, Materials Today: Proceedings, 2020.
112. Chakrabarti P., Satpathy B., Bane S., Chakrabarti T., Chaudhuri N.S., Siano P., “Business forecasting in the light of statistical approaches and machine learning classifiers”, Communications in Computer and Information Science, 1045, pp.13-21, 2019.
113. G. K. Bhamre and S. S. Banait, “Parallelization of Multipattern Matching on GPU, “International Journal of Electronics, Communication & Soft Computing Science and Engineering, Vol.3, no.3, pp.24-28, 2014.
114. Gupta, I.K., Choubey, A. and Choubey, S., 2022. Artifical intelligence with optimal deep learning enabled automated retinal fundus image classification model. Expert Systems, 39(10), p.e13028.
115. Gupta, I.K., Choubey, A. and Choubey, S., 2022. Mayfly optimization with deep learning enabled retinal fundus image classification model. Computers and Electrical Engineering, 102, p.108176.
116. Gupta, I.K., Mishra, A.K., Diwan, T.D. and Srivastava, S., 2023. Unequal clustering scheme for hotspot mitigation in IoT-enabled wireless sensor networks based on fire hawk optimization. Computers and Electrical Engineering, 107, p.108615.
117. K. Gupta, A. Choubey, and S. Choubey, “Salp swarm optimisation with deep transfer learning enabled retinal fundus image classification model,” Int. J. Netw. Virtual Organ., vol. 27, no. 2, p. 163–180, 2022.
118. Jerusha Angelene Christabel G, Shynu T, S. Suman Rajest, R. Regin, & Steffi. R. (2022). The use of Internet of Things (Iot) Technology in the Context of “Smart Gardens” is Becoming Increasingly Popular. International Journal of Biological Engineering and Agriculture, 1(2), 1–13.
119. Kothi N., Laxkar P. Jain A., Chakrabarti P., “Ledger based sorting algorithm”, Advances in Intelligent Systems and Computing, 989, pp. 37-46, 2020.
120. Magare A., Lamin M., Chakrabarti P., “Inherent Mapping Analysis of Agile Development Methodology through Design Thinking”, Lecture Notes on Data Engineering and Communications Engineering, 52, pp.527-534,2020.
121. Meng, F. (2023) Transformers: Statistical Interpretation, Architectures and Applications.
122. Meng, F., Jagadeesan, L., & Thottan, M. (2021). Model-based reinforcement learning for service mesh fault resiliency in a web application-level. arXiv preprint arXiv:2110.13621.
123. Meng, F., Zhang, L., & Chen, Y. (2023) FEDEMB: An Efficient Vertical and Hybrid Federated Learning Algorithm Using Partial Network Embedding.
124. Meng, F., Zhang, L., & Chen, Y. (2023) Sample-Based Dynamic Hierarchical Trans-Former with Layer and Head Flexibility Via Contextual Bandit.
125. Mishra, A.K., Gupta, I.K., Diwan, T.D. and Srivastava, S., 2023. Cervical precancerous lesion classification using quantum invasive weed optimization with deep learning on biomedical pap smear images. Expert Systems, p.e13308.
126. 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.
127. Mishra, S., & Samal, S. K. (2023). Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector. Energy Systems, 1-13.
128. 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.
129. Patidar H., Chakrabarti P., “A Novel Edge Cover based Graph Coloring Algorithm”, International Journal of Advanced Computer Science and Applications, 8(5), pp.279-286,2017.
130. Patidar H., Chakrabarti P., “A Tree-based Graphs Coloring Algorithm Using Independent Set”, Advances in Intelligent Systems and Computing, 714, pp. 537-546, 2019.
131. Patidar H., Chakrabarti P., Ghosh A., “Parallel Computing Aspects in Improved Edge Cover based Graph Coloring Algorithm”, Indian Journal of Science and Technology ,10(25), pp.1-9,2017.
132. Prasad A., Chakrabarti P., “Extending Access Management to maintain audit logs in cloud computing", International Journal of Advanced Computer Science and Applications, 5(3), pp.144-147, 2014.
133. Priyadarshi N., Bhoi A.K., Sahana S.K., Mallick P.K., Chakrabarti P., Performance enhancement using novel soft computing AFLC approach for PV power system”, Advances in Intelligent Systems and Computing, 1040, pp.439-448,2020.
134. Priyadarshi N., Bhoi A.K., Sharma A.K., Mallick P.K., Chakrabarti P., “An efficient fuzzy logic control-based soft computing technique for grid-tied photovoltaic system”, Advances in Intelligent Systems and Computing, 1040,pp.131-140,2020.
135. R. Regin, Steffi. R, Jerusha Angelene Christabel G, Shynu T, S. Suman Rajest (2022), “Internet of Things (IoT) System Using Interrelated Computing Devices in Billing System”, Journal of Advanced Research in Dynamical and Control Systems, Vol.14, no.1, pp. 24-40.
136. R. Steffi, G. Jerusha Angelene Christabel, T. Shynu, S. Suman Rajest, R. Regin (2022), “ A Method for the Administration of the Work Performed by Employees”, Journal of Advanced Research in Dynamical and Control Systems, Vol.14, no.1, pp. 7-23.
137. Rajest, S. S.., Regin, R.., T, S.., G, J. A. C.., & R, S. (2022). Production of Blockchains as Well as their Implementation. Vital Annex: International Journal of Novel Research in Advanced Sciences, 1(2), 21–44.
138. Regin, D. R., Rajest, D. S. S., T, S., G, J. A. C., & R, S. (2022). An Automated Conversation System Using Natural Language Processing (NLP) Chatbot in Python. Central Asian Journal Of Medical And Natural Sciences, 3(4), 314-336.
139. S. S. Rajest, R. Regin, S. T, J. A. C. G, and S. R, “Improving Infrastructure and Transportation Systems Using Internet of Things Based Smart City”, CAJOTAS, vol. 3, no. 9, pp. 125-141, Sep. 2022.
140. 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.
141. Shah K., Laxkar P., Chakrabarti P., “A hypothesis on ideal Artificial Intelligence and associated wrong implications”, Advances in Intelligent Systems and Computing, 989, pp.283-294, 2020.
142. Sharma A.K., Panwar A., Chakrabarti P. Viswakarma S., “Categorization of ICMR Using Feature Extraction Strategy and MIR with Ensemble Learning”, Procedia Computer Science, 57, pp.686-694,2015.
143. T, S., Rajest, S. S., Regin, R., Christabel G, J. A., & R, S. (2022). Automation And Control Of Industrial Operations Using Android Mobile Devices Based On The Internet Of Things. Central Asian Journal of Mathematical Theory and Computer Sciences, 3(9), 1-33.
144. Tiwari M., Chakrabarti P, Chakrabarti T., “Performance analysis and error evaluation towards the liver cancer diagnosis using lazy classifiers for ILPD”, Communications in Computer and Information Science, 837, pp.161-168,2018.
145. Tiwari M., Chakrabarti P, Chakrabarti T., “Novel work of diagnosis in liver cancer using Tree classifier on liver cancer dataset (BUPA liver disorder)”, Communications in Computer and Information Science, 837, pp.155-160, 2018.
Verma K., Srivastava P., Chakrabarti P., “Exploring structure oriented feature tag weighting algorithm for web documents identification”, Communications in Computer and Information Science, 837, pp.169-180, 2018.
Published
2023-09-26
How to Cite
S, K., B, M. I., R, R., & M, S. B. (2023). Single Switch DC-DC Converter for Battery Feed Electrical Vehicle. International Journal on Orange Technologies, 5(9), 31-49. Retrieved from https://journals.researchparks.org/index.php/IJOT/article/view/4802
Section
Articles
