Suvarna Patil

This book explores the field of polymer science and engineering with coverage from foundational principles to cutting-edge advancements. It provides ample coverage of polymer characterization techniques, including spectroscopy, chromatography, microscopy, and thermal analysis. The book also delves into practical aspects of polymer processing and manufacturing, exploring techniques such as extrusion, injection molding, and 3D printing. Examples and case studies illustrate the practical relevance of polymer science, from biomedical implants to sustainable packaging solutions are included. Key features- -Combines foundational aspects of polymers with contemporary advancements, especially in areas like living polymerizations -Covers a wide range of industries, including automotive, aerospace, healthcare, electronics, packaging, and construction, with specific examples and applications in each sector. -Discusses computational techniques, including AI and machine learning applications, for optimizing polymer design and performance -Illustrates sustainable polymer production, recycling strategies, and the development of biodegradable polymers -Includes case studies and real-world applications from globally recognized companies such as BASF, Dow Chemical, and Toray Industries This book is aimed at researchers and graduate students in polymer and materials engineering.

With a specific focus on energy efficiency, Optimizing IoT Networks examines the application of machine learning to enhance resource allocations in IoT networks. It discusses various algorithms, including neural networks and reinforcement learning, to optimise resource use and improve network performance. It addresses challenges such as the dynamic behaviour of IoT devices and the need for real-time decision-making. It discusses optimisation methods used alongside machine learning to enhance resource allocation efficiency.• Provides a foundational understanding of IoT network architecture and the importance of efficient resource allocation• Discusses complexities in resource allocation due to dynamic device behaviour and varying data traffic patterns• Covers key machine learning concepts and algorithms relevant to optimising resource allocation in IoT networks• Emphasises the significance of energy efficiency in IoT networks and its impact on resource allocation strategies• Explores algorithms such as clustering, regression, and reinforcement learning for effective resource allocationThe book is designed for researchers, practitioners, and scholars in computer science and technology who are interested in or actively working on optimising IoT networks.

Le livre intitul "Database Management Systems for Business Organizations", crit par le professeur Anil Gaikwad, le docteur Hindurao Sankpal et le docteur Suvarna Patil, est une contribution d cente au monde des affaires, dans lequel sont pr sent es les principales applications des syst mes de gestion de bases de donn es (SGBD). Ce livre est important pour tous les tudiants qui apprennent l'ing nierie informatique, l'informatique, les dipl mes de gestion et les PG en applications informatiques et tudes de gestion, les fonctionnaires de l'informatique et de la gestion et les tudiants en g n ral. Il explique galement la n cessit d'utiliser des technologies avanc es dans le domaine des SGBDR. Ce livre apportera une contribution d cente dans le domaine de la gestion et des applications informatiques et profitera galement aux parties prenantes du monde universitaire et des affaires. Organisations.