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The rapid advancement of technology in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and generative AI, presents a challenge for academic scholars to remain informed with the most current information and with the latest techniques and applications. The lack of comprehensive resources also hinders researchers'ability to gain a deep understanding of these subjects and effectively implement these technologies. Advanced Applications of Generative AI and Natural Language Processing Models is a comprehensive resource which offers an effective solution by investigating cutting-edge developments in NLP and generative AI. It provides insights into how these technologies function, their benefits, and the associated challenges. This book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI for students, researchers, and professionals in AI, NLP, and computer science. It uses real-world examples and practical applications to empower scholars to apply their knowledge and solve complex problems. Advanced Applications of Generative AI and Natural Language Processing Models is a complete guide that equips researchers with the knowledge needed to utilize NLP and generative AI, including deep learning for NLP, generative models for text generation, language modeling and sentiment analysis, machine translation and multilingual models, ethical considerations in NLP, conversational AI applications, and case studies and real-world applications.

This book provides information on interdependencies of medicine and telecommunications engineering and how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear-cut views on medical technologies. The authors provide chapters on communication essentiality in healthcare, processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field.

'For a long time, researchers in the fields of psychology and neuroscience have been interested in discovering ways to boost productivity in traditionally'healthy,''clinical,'and'military'populations. However, one of the biggest challenges in reaching this objective is developing personalised performance phenotypes that can be used to build interventions that are specifically catered to each individual's needs. Impact: Thanks to AI's recent advancements, we can now create individualised training, preparation, and recovery plans that are tailored to each person's unique cognitive and biological profile. Concurrent AI advancements, especially in the psychological and neurological sciences, have demonstrated the importance of incorporating domain expertise and stakeholder inputs into the development of trustworthy AI. Value: This Patterns themed issue seeks original empirical work, literature reviews, and methodological papers that establish and validate precision artificial intelligence methods for human performance optimization, with a focus on modelling individual differences via state-of-the-art computational methods'--

In the fields of psychological and brain sciences, there is a pressing need to enhance individual performance through tailored interventions, considering the unique cognitive and biological traits of humans. However, discovering such precision approaches has proven to be a challenging task. Traditional methods often fall short in providing personalized solutions; the lack of a comprehensive integration of domain expertise and human judgment inevitably limits the effectiveness of artificial intelligence (AI) in optimizing human performance. As the demand for individualized training, health monitoring, and cognitive improvement rises, it becomes imperative to bridge the gap between AI capabilities and the specific needs of human subjects. Advances in Artificial and Human Intelligence in the Modern Era offers a groundbreaking solution to address the existing challenges in the intersection of AI and human performance optimization. This book delves into the latest empirical research, literature reviews, and methodological papers to present precision AI methods for personalized interventions. By exploring how domain expertise and human insights can improve AI's performance, the book establishes a comprehensive framework to model individual differences and develop effective, tailored AI strategies. Designed with care to be useful to academic scholars and researchers in psychological and brain sciences, computer science, and related disciplines, this book offers a multifaceted exploration of innovative advancements in artificial and human intelligence convergence. Through its diverse chapters covering topics such as detecting mental health issues, incorporating human intelligence into AI tools, improving trustworthiness, and exploring data standards, the book provides a definitive resource for harnessing the full potential of AI to optimize human performance. By merging expertise from both fields, the book sets the stage for a new era of individualized interventions that can revolutionize how we approach human cognitive enhancement, training, and overall well-being.

Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science.Features• Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place • Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0 • Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security • Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.