Artificial Intelligence and Responsive Optimization PDF Download

Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Author: Panos M. Pardalos
Publisher: Springer Nature
ISBN: 3030844595
Category : Mathematics
Languages : en
Pages : 239

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Book Description
This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities. Special features include: New research on the design of city elements and smart systems with respect to new technologies and scientific thinking Discussions on the theoretical background that lead to smart cities for the future New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

Author: Seyed Navid Mashhadi Moghaddam
Publisher: Springer Nature
ISBN: 9819751160
Category :
Languages : en
Pages : 455

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Book Description

Author: Chandra P. Sharma
Publisher: Elsevier
ISBN: 0443184992
Category : Science
Languages : en
Pages : 344

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Book Description
Artificial Intelligence in Tissue and Organ Regeneration discusses the role of artificial intelligence as a highly sought-after technology in the area of organ and tissue regeneration. Certain groups have made significant progress in mass producing mini organs and organoids from stem cells utilizing such techniques. As time goes on, there will be a need to improve these procedures, protocols, regulatory guidelines, and their clinical implications. - Integrates existing literature in a highly interdisciplinary area - Presents comprehensive current and future perspectives, combining artificial intelligence and machine learning with organ and tissue regeneration - Provides new and emerging technology that is useful in healthcare and the medical field

Author: Amit Kumar Tyagi
Publisher: CRC Press
ISBN: 1040151396
Category : Computers
Languages : en
Pages : 419

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Book Description
Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.

Author: Silja Voeneky
Publisher: Cambridge University Press
ISBN: 1009207881
Category : Law
Languages : en
Pages : 1440

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Book Description
In the past decade, artificial intelligence (AI) has become a disruptive force around the world, offering enormous potential for innovation but also creating hazards and risks for individuals and the societies in which they live. This volume addresses the most pressing philosophical, ethical, legal, and societal challenges posed by AI. Contributors from different disciplines and sectors explore the foundational and normative aspects of responsible AI and provide a basis for a transdisciplinary approach to responsible AI. This work, which is designed to foster future discussions to develop proportional approaches to AI governance, will enable scholars, scientists, and other actors to identify normative frameworks for AI to allow societies, states, and the international community to unlock the potential for responsible innovation in this critical field. This book is also available as Open Access on Cambridge Core.

Author: Zhang Wenpeng
Publisher: Infinite Study
ISBN: 1599730219
Category :
Languages : en
Pages : 123

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Book Description
Papers on Smarandache inversion sequence, global attractivity of a recursive sequence, Smarandache fantastic ideals of Smarandache BCI-algebras, translational hull of superabundant semigroups with semilattice of idempotents, the Universality of some Smarandache loops of Bol-Moufang type, and other similar topics. Contributors: M. Karama, P. Zhang, W. Kandasamy, M. Khoshnevisan, K. Ilanthenral, M. Bencze, H. Ibstedt, W. Zhu, J. Earls, and many others.

Author: Rajest, S. Suman
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 618

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Book Description
The numerous developments in wireless communications and artificial intelligence (AI) have recently transformed the Internet of Things (IoT) networks to a level of connectivity and intelligence beyond any prior design. This topology is sharply exemplified in mobile edge computing, smart cities, smart homes, smart grids, and the IoT, among many other intelligent applications. Intelligent networks are founded on integrating caching and multi-agent systems that optimize data storage and the entire device’s learning process. However, a central node through which all agents transmit status messages and reward information is a major drawback of this design pattern. This central node condition instigates more communication overhead, potential data leakage, and the birth of data islands. To reverse this trend, using distributed optimization techniques and methodologies in cache-enabled multi-agent learning environments is increasingly beneficial. Advancing Intelligent Networks Through Distributed Optimization explains the current race for sophisticated and accurate distributed optimization in cache-enabled intelligent IoT networks given the need to make multi-agent learning converge faster and reduce communication overhead. These techniques will require innovative resource allocation strategies stretching from system training to caching, communication, and processing amongst millions of agents. This book combines the key recent research in these races into a single binder that can serve all the interested theoretical and practical scholars. The book focuses broadly on intelligent systems’ optimization trends. It identifies the various applications of advanced distributed optimization from manufacturing to medicine, agriculture and smart cities.

Author: Larry Cao
Publisher: CFA Institute Research Foundation
ISBN: 195292734X
Category : Business & Economics
Languages : en
Pages : 258

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Book Description
Artificial intelligence (AI) and big data have their thumbprints all over the modern asset management firm. Like detectives investigating a crime, the practitioner contributors to this book put the latest data science techniques under the microscope. And like any good detective story, much of what is unveiled is at the same time surprising and hiding in plain sight. Each chapter takes you on a well-guided tour of the development and application of specific AI and big data techniques and brings you up to the minute on how they are being used by asset managers. Given the diverse backgrounds and affiliations of our authors, this book is the perfect companion to start, refine, or plan the next phase of your data science journey.

Author: M. Khoshnevisan
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 20

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Book Description
Each individual investor is different, with different financial goals, different levels of risk tolerance and different personal preferences. From the point of view of investment management, these characteristics are often defined as objectives and constraints.