Environmental Neurochemistry and Neurodevelopmental Disorders in Pediatrics
DOI:
https://doi.org/10.55544/jrasb.2.5.32Keywords:
neurodevelopmental disorders, Environmental neurochemistry, neurotoxins, intervention strategies, children's healthAbstract
Neurochemistry about environment and neurodevelopmental disorders in children is the interesting part of the analysis of the research paper. This paper focuses on the effects brought on by toxins in the environment such as heavy metals and pesticides to a developing brain and common disorder relating to ADHD as well as autism spectrum disorders. Placing the focus on policy and community intervention, as well as to determine the effective step for intervention, this study examines the biochemical pathways to neurotoxic exposures. Therefore, the aim of this current study is to enhance knowledge on risks to the environment in order to afford optimal neurodevelopment to children.
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Antonelli, M. C., Pallarés, M. E., Ceccatelli, S., & Spulber, S. (2017). Long-term consequences of prenatal stress and neurotoxicants exposure on neurodevelopment. Progress in neurobiology, 155, 21-35. https://doi.org/10.1016/j.pneurobio.2016.05.005
Arima, Y., & Fukuoka, H. (2020). Developmental origins of health and disease theory in cardiology. Journal of cardiology, 76(1), 14-17. https://doi.org/10.1016/j.jjcc.2020.02.003
Bellinger, D. C. (2018). An overview of environmental chemical exposures and neurodevelopmental impairments in children. Pediatric Medicine, 1. https://pm.amegroups.org/article/view/4617/html
Dórea, J. G. (2021). Exposure to environmental neurotoxic substances and neurodevelopment in children from Latin America and the Caribbean. Environmental research, 192, 110199. https://doi.org/10.1016/j.envres.2020.110199
Elliott, S., & Davis, J. M. (2020). Challenging taken-for-granted ideas in early childhood education: A critique of Bronfenbrenner’s ecological systems theory in the age of post-humanism. Research handbook on childhoodnature: Assemblages of childhood and nature research, 1119-1154. https://doi.org/10.1007/978-3-319-67286-1_60
Freire, C., Amaya, E., Gil, F., Fernández, M. F., Murcia, M., Llop, S., ... & INMA Project. (2018). Prenatal co-exposure to neurotoxic metals and neurodevelopment in preschool children: The Environment and Childhood (INMA) Project. Science of the Total Environment, 621, 340-351. https://doi.org/10.1016/j.scitotenv.2017.11.273
McCann, M. E., & Soriano, S. G. (2019). Does general anesthesia affect neurodevelopment in infants and children?. Bmj, 367. https://doi.org/10.1136/bmj.l6459
Rauh, V. A., & Margolis, A. E. (2016). Research review: environmental exposures, neurodevelopment, and child mental health–new paradigms for the study of brain and behavioral effects. Journal of Child Psychology and Psychiatry, 57(7), 775-793. https://doi.org/10.1111/jcpp.12537
Rock, K. D., & Patisaul, H. B. (2018). Environmental mechanisms of neurodevelopmental toxicity. Current environmental health reports, 5, 145-157. https://doi.org/10.1007/s40572-018-0185-0
Tran, N. Q. V., & Miyake, K. (2017). Neurodevelopmental disorders and environmental toxicants: epigenetics as an underlying mechanism. International journal of genomics, 2017(1), 7526592. https://doi.org/10.1155/2017/7526592
Santhosh Palavesh. (2019). The Role of Open Innovation and Crowdsourcing in Generating New Business Ideas and Concepts. International Journal for Research Publication and Seminar, 10(4), 137–147. https://doi.org/10.36676/jrps.v10.i4.1456
Santosh Palavesh. (2021). Developing Business Concepts for Underserved Markets: Identifying and Addressing Unmet Needs in Niche or Emerging Markets. Innovative Research Thoughts, 7(3), 76–89. https://doi.org/10.36676/irt.v7.i3.1437
Palavesh, S. (2021). Co-Creating Business Concepts with Customers: Approaches to the Use of Customers in New Product/Service Development. Integrated Journal for Research in Arts and Humanities, 1(1), 54–66. https://doi.org/10.55544/ijrah.1.1.9
Santhosh Palavesh. (2022). Entrepreneurial Opportunities in the Circular Economy: Defining Business Concepts for Closed-Loop Systems and Resource Efficiency. European Economic Letters (EEL), 12(2), 189–204. https://doi.org/10.52783/eel.v12i2.1785
Santhosh Palavesh. (2022). The Impact of Emerging Technologies (e.g., AI, Blockchain, IoT) On Conceptualizing and Delivering new Business Offerings. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 160–173. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10955
Santhosh Palavesh. (2021). Business Model Innovation: Strategies for Creating and Capturing Value Through Novel Business Concepts. European Economic Letters (EEL), 11(1). https://doi.org/10.52783/eel.v11i1.1784
Santhosh Palavesh. (2023). Leveraging Lean Startup Principles: Developing And Testing Minimum Viable Products (Mvps) In New Business Ventures. Educational Administration: Theory and Practice, 29(4), 2418–2424. https://doi.org/10.53555/kuey.v29i4.7141
Palavesh, S. (2023). The role of design thinking in conceptualizing and validating new business ideas. Journal of Informatics Education and Research, 3(2), 3057.
Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810
Sri Sai Subramanyam Challa. (2023). Regulatory Intelligence: Leveraging Data Analytics for Regulatory Decision-Making. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11), 1426–1434. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10893
Challa, S. S. S. (2020). Assessing the regulatory implications of personalized medicine and the use of biomarkers in drug development and approval. European Chemical Bulletin, 9(4), 134-146.
D.O.I10.53555/ecb.v9:i4.17671
EVALUATING THE EFFECTIVENESS OF RISK-BASED APPROACHES IN STREAMLINING THE REGULATORY APPROVAL PROCESS FOR NOVEL THERAPIES. (2021). Journal of Population Therapeutics and Clinical Pharmacology, 28(2), 436-448. https://doi.org/10.53555/jptcp.v28i2.7421
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5), 380-387.
Ashok Choppadandi. (2022). Exploring the Potential of Blockchain Technology in Enhancing Supply Chain Transparency and Compliance with Good Distribution Practices (GDP). International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 336–343. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10981
Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2020). Evaluating the use of machine learning algorithms in predicting drug-drug interactions and adverse events during the drug development process. NeuroQuantology, 18(12), 176-186. https://doi.org/10.48047/nq.2020.18.12.NQ20252
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Investigating the impact of AI-assisted drug discovery on the efficiency and cost-effectiveness of pharmaceutical R&D. Journal of Cardiovascular Disease Research, 14(10), 2244.
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality Management Systems in Regulatory Affairs: Implementation Challenges and Solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3), 278–284. https://doi.org/10.55544/jrasb.1.3.36
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, & Sneha Aravind. (2022). Strategies for Effective Product Roadmap Development and Execution in Data Analytics Platforms. International Journal for Research Publication and Seminar, 13(1), 328–342. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1515
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, & Sneha Aravind. (2022). Leveraging Data Analytics to Improve User Satisfaction for Key Personas: The Impact of Feedback Loops. International Journal for Research Publication and Seminar, 11(4), 242–252. https://doi.org/10.36676/jrps.v11.i4.1489
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, 2021. "Utilizing Splunk for Proactive Issue Resolution in Full Stack Development Projects" ESP Journal of Engineering & Technology Advancements 1(1): 57-64.
Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, Ranjit Kumar Gupta, Santosh Palavesh. (2023). Monetizing API Suites: Best Practices for Establishing Data Partnerships and Iterating on Customer Feedback. European Economic Letters (EEL), 13(5), 2040–2053. https://doi.org/10.52783/eel.v13i5.1798
Sagar Shukla. (2021). Integrating Data Analytics Platforms with Machine Learning Workflows: Enhancing Predictive Capability and Revenue Growth. International Journal on Recent and Innovation Trends in Computing and Communication, 9(12), 63–74. Retrieved from https://ijritcc.org/index.php/ijritcc/article/view/11119
Shukla, S., Thekkan Rajan, A., Aravind, S., & Gupta, R. K. (2023). Implementing scalable big-data tech stacks in pre-seed start-ups: Challenges and strategies for realizing strategic vision. International Journal of Communication Networks and Information Security, 15(1).
Sneha Aravind. (2021). Integrating REST APIs in Single Page Applications using Angular and TypeScript. International Journal of Intelligent Systems and Applications in Engineering, 9(2), 81 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6829
Aravind, S., Cherukuri, H., Gupta, R. K., Shukla, S., & Rajan, A. T. (2022). The role of HTML5 and CSS3 in creating optimized graphic prototype websites and application interfaces. NeuroQuantology, 20(12), 4522-4536. https://doi.org/10.48047/NQ.2022.20.12.NQ77775
Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730
Rishabh Rajesh Shanbhag, Rajkumar Balasubramanian, Ugandhar Dasi, Nikhil Singla, & Siddhant Benadikar. (2022). Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control. International Journal for Research Publication and Seminar, 13(5), 292–311. https://doi.org/10.36676/jrps.v13.i5.1462
Siddhant Benadikar. (2021). Developing a Scalable and Efficient Cloud-Based Framework for Distributed Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761
Siddhant Benadikar. (2021). Evaluating the Effectiveness of Cloud-Based AI and ML Techniques for Personalized Healthcare and Remote Patient Monitoring. International Journal on Recent and Innovation Trends in Computing and Communication, 9(10), 03–16. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11036
Rishabh Rajesh Shanbhag. (2023). Exploring the Use of Cloud-Based AI and ML for Real-Time Anomaly Detection and Predictive Maintenance in Industrial IoT Systems. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 925 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6762
Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/673
Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730
Challa, S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of PharmaResearch, 7(5), 380-387.
Ritesh Chaturvedi. (2023). Robotic Process Automation (RPA) in Healthcare: Transforming Revenue Cycle Operations. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 652–658. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11045
Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25
Chaturvedi, R., & Sharma, S. (2022). Enhancing healthcare staffing efficiency with AI-powered demand management tools. Eurasian Chemical Bulletin, 11(Regular Issue 1), 675-681. https://doi.org/10.5281/zenodo.13268360
Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475
Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475
Saloni Sharma. (2020). AI-Driven Predictive Modelling for Early Disease Detection and Prevention. International Journal on Recent and Innovation Trends in Computing and Communication, 8(12), 27–36. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11046
Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25
Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, Uday Krishna Padyana, Hitesh Premshankar Rai. (2022). Blockchain Technology for Secure and Transparent Financial Transactions. European Economic Letters (EEL), 12(2), 180–188. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1283
Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2023). Edge computing vs. cloud computing: A comparative analysis of their roles and benefits. Volume 20, No. 3, 214-226.
Fadnavis, N. S., Patil, G. B., Padyana, U. K., Rai, H. P., & Ogeti, P. (2020). Machine learning applications in climate modeling and weather forecasting. NeuroQuantology, 18(6), 135-145. https://doi.org/10.48047/nq.2020.18.6.NQ20194
Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889
Gireesh Bhaulal Patil. (2022). AI-Driven Cloud Services: Enhancing Efficiency and Scalability in Modern Enterprises. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 153–162. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6728
Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20
Patil, G. B., Padyana, U. K., Rai, H. P., Ogeti, P., & Fadnavis, N. S. (2021). Personalized marketing strategies through machine learning: Enhancing customer engagement. Journal of Informatics Education and Research, 1(1), 9. http://jier.org
Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20
Krishnateja Shiva. (2022). Leveraging Cloud Resource for Hyperparameter Tuning in Deep Learning Models. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2), 30–35. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10980
Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., & Dave, A. (2022). The rise of robo-advisors: AI-powered investment management for everyone. Journal of Namibian Studies, 31, 201-214.
Etikani, P., Bhaskar, V. V. S. R., Nuguri, S., Saoji, R., & Shiva, K. (2023). Automating machine learning workflows with cloud-based pipelines. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 375–382. https://doi.org/10.48047/ijisae.2023.11.1.375
Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., Saoji, R., & Shiva, K. (2023). AI-powered algorithmic trading strategies in the stock market. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 264–277. https://doi.org/10.1234/ijsdip.org_2023-Volume-11-Issue-1_Page_264-277
Bhaskar, V. V. S. R., Etikani, P., Shiva, K., Choppadandi, A., & Dave, A. (2019). Building explainable AI systems with federated learning on the cloud. Journal of Cloud Computing and Artificial Intelligence, 16(1), 1–14.
Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2022). Blockchain technology for secure and transparent financial transactions. European Economic Letters, 12(2), 180-192. http://eelet.org.uk
Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810
Dave, A., Shiva, K., Etikani, P., Bhaskar, V. V. S. R., & Choppadandi, A. (2022). Serverless AI: Democratizing machine learning with cloud functions. Journal of Informatics Education and Research, 2(1), 22-35. http://jier.org
Dave, A., Etikani, P., Bhaskar, V. V. S. R., & Shiva, K. (2020). Biometric authentication for secure mobile payments. Journal of Mobile Technology and Security, 41(3), 245-259.
Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2021). Adaptive AI-based deep learning models for dynamic control in software-defined networks. International Journal of Electrical and Electronics Engineering (IJEEE), 10(1), 89–100. ISSN (P): 2278–9944; ISSN (E): 2278–9952
Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889
Joel lopes, Arth Dave, Hemanth Swamy, Varun Nakra, & Akshay Agarwal. (2023). Machine Learning Techniques And Predictive Modeling For Retail Inventory Management Systems. Educational Administration: Theory and Practice, 29(4), 698–706. https://doi.org/10.53555/kuey.v29i4.5645
Nitin Prasad. (2022). Security Challenges and Solutions in Cloud-Based Artificial Intelligence and Machine Learning Systems. International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 286–292. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10750
Prasad, N., Narukulla, N., Hajari, V. R., Paripati, L., & Shah, J. (2020). AI-driven data governance framework for cloud-based data analytics. Volume 17, (2), 1551-1561.
Jigar Shah , Joel lopes , Nitin Prasad , Narendra Narukulla , Venudhar Rao Hajari , Lohith Paripati. (2023). Optimizing Resource Allocation And Scalability In Cloud-Based Machine Learning Models. Migration Letters, 20(S12), 1823–1832. Retrieved from https://migrationletters.com/index.php/ml/article/view/10652
Big Data Analytics using Machine Learning Techniques on Cloud Platforms. (2019). International Journal of Business Management and Visuals, ISSN: 3006-2705, 2(2), 54-58. https://ijbmv.com/index.php/home/article/view/76
Shah, J., Narukulla, N., Hajari, V. R., Paripati, L., & Prasad, N. (2021). Scalable machine learning infrastructure on cloud for large-scale data processing. Tuijin Jishu/Journal of Propulsion Technology, 42(2), 45-53.
Narukulla, N., Lopes, J., Hajari, V. R., Prasad, N., & Swamy, H. (2021). Real-time data processing and predictive analytics using cloud-based machine learning. Tuijin Jishu/Journal of Propulsion Technology, 42(4), 91-102
Secure Federated Learning Framework for Distributed Ai Model Training in Cloud Environments. (2019). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 7(1), 31-39. https://ijope.com/index.php/home/article/view/145
Paripati, L., Prasad, N., Shah, J., Narukulla, N., & Hajari, V. R. (2021). Blockchain-enabled data analytics for ensuring data integrity and trust in AI systems. International Journal of Computer Science and Engineering (IJCSE), 10(2), 27–38. ISSN (P): 2278–9960; ISSN (E): 2278–9979.
Hajari, V. R., Prasad, N., Narukulla, N., Chaturvedi, R., & Sharma, S. (2023). Validation techniques for AI/ML components in medical diagnostic devices. NeuroQuantology, 21(4), 306-312. https://doi.org/10.48047/NQ.2023.21.4.NQ23029
Hajari, V. R., Chaturvedi, R., Sharma, S., Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Interoperability testing strategies for medical IoT devices. Tuijin Jishu/Journal of Propulsion Technology, 44(1), 258.
DOI: 10.36227/techrxiv.171340711.17793838/v1
P. V., V. R., & Chidambaranathan, S. (2023). Polyp segmentation using UNet and ENet. In Proceedings of the 6th International Conference on Recent Trends in Advance Computing (ICRTAC) (pp. 516-522). Chennai, India. https://doi.org/10.1109/ICRTAC59277.2023.10480851
Athisayaraj, A. A., Sathiyanarayanan, M., Khan, S., Selvi, A. S., Briskilla, M. I., Jemima, P. P., Chidambaranathan, S., Sithik, A. S., Sivasankari, K., & Duraipandian, K. (2023). Smart thermal-cooler umbrella (UK Design No. 6329357).
Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2023). Regulatory intelligence: Leveraging data analytics for regulatory decision-making. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 10.
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5),
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2021). Navigating regulatory requirements for complex dosage forms: Insights from topical, parenteral, and ophthalmic products. NeuroQuantology, 19(12), 15.
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality management systems in regulatory affairs: Implementation challenges and solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3),
Tilala, M. (2023). Real-time data processing in healthcare: Architectures and applications for immediate clinical insights. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 20.
Tilala, M., & Chawda, A. D. (2020). Evaluation of compliance requirements for annual reports in pharmaceutical industries. NeuroQuantology, 18(11), 27.
Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Enhancing regulatory compliance through training and development programs: Case studies and recommendations. Journal of Cardiovascular Research, 14(11),
Ghavate, N. (2018). An Computer Adaptive Testing Using Rule Based. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 4(I). Retrieved from http://asianssr.org/index.php/ajct/article/view/443
Shanbhag, R. R., Dasi, U., Singla, N., Balasubramanian, R., & Benadikar, S. (2020). Overview of cloud computing in the process control industry. International Journal of Computer Science and Mobile Computing, 9(10), 121-146. https://www.ijcsmc.com
Benadikar, S. (2021). Developing a scalable and efficient cloud-based framework for distributed machine learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761
Shanbhag, R. R., Benadikar, S., Dasi, U., Singla, N., & Balasubramanian, R. (2022). Security and privacy considerations in cloud-based big data analytics. Journal of Propulsion Technology, 41(4), 62-81.
Shanbhag, R. R., Balasubramanian, R., Benadikar, S., Dasi, U., & Singla, N. (2021). Developing scalable and efficient cloud-based solutions for ecommerce platforms. International Journal of Computer Science and Engineering (IJCSE), 10(2), 39-58.
Shanbhag, R. R. (2023). Accountability frameworks for autonomous AI decision-making systems. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 565-569.
Tripathi, A. (2020). AWS serverless messaging using SQS. IJIRAE: International Journal of Innovative Research in Advanced Engineering, 7(11), 391-393.
Tripathi, A. (2019). Serverless architecture patterns: Deep dive into event-driven, microservices, and serverless APIs. International Journal of Creative Research Thoughts (IJCRT), 7(3), 234-239. Retrieved from http://www.ijcrt.org
Tripathi, A. (2023). Low-code/no-code development platforms. International Journal of Computer Applications (IJCA), 4(1), 27–35. Retrieved from https://iaeme.com/Home/issue/IJCA?Volume=4&Issue=1
Tripathi, A. (2022). Serverless deployment methodologies: Smooth transitions and improved reliability. IJIRAE: International Journal of Innovative Research in Advanced Engineering, 9(12), 510-514.
Tripathi, A. (2022). Deep dive into Java tiered compilation: Performance optimization. International Journal of Creative Research Thoughts (IJCRT), 10(10), 479-483. Retrieved from https://www.ijcrt.org
22-4*5-20 23--5*5-25 24-7*5-35 - 80
Thakkar, D. (2021). Leveraging AI to transform talent acquisition. International Journal of Artificial Intelligence and Machine Learning, 3(3), 7. https://www.ijaiml.com/volume-3-issue-3-paper-1/
Thakkar, D. (2020, December). Reimagining curriculum delivery for personalized learning experiences. International Journal of Education, 2(2), 7. Retrieved from https://iaeme.com/Home/article_id/IJE_02_02_003
Kanchetti, D., Munirathnam, R., & Thakkar, D. (2019). Innovations in workers compensation: XML shredding for external data integration. Journal of Contemporary Scientific Research, 3(8). ISSN (Online) 2209-0142.
Thakkar, D., Kanchetti, D., & Munirathnam, R. (2022). The transformative power of personalized customer onboarding: Driving customer success through data-driven strategies. Journal for Research on Business and Social Science, 5(2). ISSN (Online) 2209-7880. Retrieved from https://www.jrbssonline.com
Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, Harsh Vaidya. (2023). Online Bank Management System in Eclipse IDE: A Comprehensive Technical Study. European Economic Letters (EEL), 13(3), 2095–2113. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1874
Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, & Harsh Vaidya. (2019). Search and Recommendation Procedure with the Help of Artificial Intelligence. International Journal for Research Publication and Seminar, 10(4), 148–166. https://doi.org/10.36676/jrps.v10.i4.1503
Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, & Ravi Kumar Singh. (2023). Using OOP Concepts for the Development of a Web-Based Online Bookstore System with a Real-Time Database. International Journal for Research Publication and Seminar, 14(5), 253–274. https://doi.org/10.36676/jrps.v14.i5.1502
Vaidya, H., Nayani, A. R., Gupta, A., Selvaraj, P., & Singh, R. K. (2020). Effectiveness and future trends of cloud computing platforms. Tuijin Jishu/Journal of Propulsion Technology, 41(3). Retrieved from https://www.journal-propulsiontech.com
Prassanna Selvaraj, Ravi Kumar Singh, Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta. (2023). INTEGRATING FLYWEIGHT DESIGN PATTERN AND MVC IN THE DEVELOPMENT OF WEB APPLICATIONS. International Journal of Communication Networks and Information Security (IJCNIS), 15(1), 245–249. Retrieved from https://ijcnis.org/index.php/ijcnis/article/view/7068
Selvaraj, P. . (2022). Library Management System Integrating Servlets and Applets Using SQL Library Management System Integrating Servlets and Applets Using SQL database. International Journal on Recent and Innovation Trends in Computing and Communication, 10(4), 82–89. https://doi.org/10.17762/ijritcc.v10i4.11109
Gupta, A., Selvaraj, P., Singh, R. K., Vaidya, H., & Nayani, A. R. (2022). The Role of Managed ETL Platforms in Reducing Data Integration Time and Improving User Satisfaction. Journal for Research in Applied Sciences and Biotechnology, 1(1), 83–92. https://doi.org/10.55544/jrasb.1.1.12
Alok Gupta. (2021). Reducing Bias in Predictive Models Serving Analytics Users: Novel Approaches and their Implications. International Journal on Recent and Innovation Trends in Computing and Communication, 9(11), 23–30. Retrieved from https://ijritcc.org/index.php/ijritcc/article/view/11108
Rinkesh Gajera , "Leveraging Procore for Improved Collaboration and Communication in Multi-Stakeholder Construction Projects", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 3, Issue 3, pp.47-51, May-June.2019
Rinkesh Gajera , "Integrating Power Bi with Project Control Systems: Enhancing Real-Time Cost Tracking and Visualization in Construction", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 7, Issue 5, pp.154-160, September-October.2023
URL : https://ijsrce.com/IJSRCE123761
Voddi, V. K. R., & Konda, K. R. (2021). Spatial distribution and dynamics of retail stores in New York City. Webology, 18(6). Retrieved from https://www.webology.org/issue.php?volume=18&issue=60
R. Kar, V. K. Reddy Voddi, B. G. Patra and J. Pathak, "CoRL: A Cost-Responsive Learning Optimizer for Neural Networks," 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Oahu, HI, USA, 2023, pp. 1828-1833, doi: 10.1109/SMC53992.2023.10394113.
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