https://isjr.co.in/index.php/ITAI <p><strong>International Transactions in Artificial Intelligence</strong></p> <p><strong>Journal Scope:</strong></p> <p><em>International Transactions in Artificial Intelligence</em> is a premier peer-reviewed journal dedicated to advancing the field of artificial intelligence (AI) through high-quality research and contributions from scientists, researchers, and practitioners across the globe. The journal aims to provide a platform for the dissemination of cutting-edge research, innovation, and knowledge in the diverse and rapidly evolving field of AI.</p> <p><strong>Key Focus Areas:</strong></p> <p><em>International Transactions in Artificial Intelligence</em> covers a wide range of topics and research areas within the field of AI. The journal's scope includes, but is not limited to, the following key focus areas:</p> <ol> <li> <p><strong>Machine Learning</strong>: Theoretical foundations, algorithms, and applications of machine learning, including deep learning, reinforcement learning, and other related methodologies.</p> </li> <li> <p><strong>Natural Language Processing</strong>: Research on understanding, generating, and processing human language, including sentiment analysis, language modeling, and machine translation.</p> </li> <li> <p><strong>Computer Vision</strong>: Advancements in computer vision, image and video analysis, object recognition, and scene understanding.</p> </li> <li> <p><strong>AI Ethics and Governance</strong>: Exploration of ethical, legal, and societal implications of AI, as well as strategies for responsible AI development and deployment.</p> </li> <li> <p><strong>AI Applications</strong>: Practical applications of AI in various domains, including healthcare, finance, education, and industry, highlighting real-world use cases and case studies.</p> </li> <li> <p><strong>Reinforcement Learning</strong>: Research on reinforcement learning algorithms and their applications in robotics, game playing, and autonomous systems.</p> </li> <li> <p><strong>AI in Robotics</strong>: Integration of AI techniques with robotics, including robot perception, motion planning, and human-robot interaction.</p> </li> <li> <p><strong>AI for Problem Solving</strong>: Techniques for problem-solving, reasoning, and decision-making using AI, including knowledge representation and expert systems.</p> </li> <li> <p><strong>AI and Healthcare</strong>: Innovative AI solutions for healthcare, including medical imaging, disease diagnosis, and patient care improvement.</p> </li> <li> <p><strong>AI and Education</strong>: Utilization of AI in educational technology, personalized learning, and intelligent tutoring systems.</p> </li> </ol> <p><strong>Publication Formats:</strong></p> <p>The journal publishes a wide range of article types, including:</p> <ul> <li>Original Research Papers</li> <li>Review Articles</li> <li>Short Communications</li> <li>Case Studies</li> <li>Survey Papers</li> <li>Technical Notes</li> </ul> <p><strong>Editorial Board:</strong></p> <p><em>International Transactions in Artificial Intelligence</em> boasts a distinguished editorial board comprising experts and researchers from diverse subfields of AI. The editorial board ensures the highest standards of quality and rigor in the review process.</p> <p><strong>Audience:</strong></p> <p>This journal is a valuable resource for researchers, academics, industry professionals, policymakers, and students interested in the latest developments and breakthroughs in artificial intelligence. It serves as a platform for exchanging ideas, fostering collaboration, and shaping the future of AI.</p> <p><em>International Transactions in Artificial Intelligence</em> is committed to fostering excellence and innovation in AI research and welcomes contributions that advance the understanding and application of AI across various domains. Researchers and practitioners are invited to submit their work to be considered for publication in this esteemed journal.</p> <p><strong>Impact Factor:</strong> 7.565</p> en-US Fri, 06 Dec 2024 06:18:24 +0000 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 https://isjr.co.in/index.php/ITAI/article/view/283 <p>This paper explores the optimization of SAP data processing through the integration of machine learning algorithms in cloud environments. As enterprises increasingly adopt SAP systems for enterprise resource planning (ERP), the complexity and volume of data generated have grown significantly, demanding more efficient processing methods. Traditional SAP data processing methods often struggle with scalability, speed, and real-time analytics. This research presents a solution that leverages cloud computing and machine learning techniques to enhance data integration, accelerate processing times, and improve decision-making. By applying machine learning models, such as regression, classification, and clustering algorithms, to SAP data, organizations can derive deeper insights, predict trends, and automate processes. The paper discusses various cloud platforms, such as AWS and Microsoft Azure, and evaluates their capabilities for supporting SAP data processing in conjunction with machine learning. The findings highlight the potential for significant improvements in data efficiency, business analytics, and operational performance.</p> Vedaprada Raghunath, Mohan Kunkulagunta, Geeta Sandeep Nadella Copyright (c) 2024 https://isjr.co.in/index.php/ITAI/article/view/283 Fri, 06 Dec 2024 00:00:00 +0000