Bøger af Alex Khang

In recent years, the advent of biosensors and bioelectronics has facilitated the swift and precise detection of numerous biomolecules or pathogens in animal samples, aquatic habitats, and plants. These technologies have emerged as potent assets for the agriculture and aquaculture industries. Many experts have raised the question; how might the integration of biosensors into portable devices or automated monitoring systems enable on-site and real-time detection of diverse biomolecules or pathogens? Agriculture and Aquaculture Applications of Biosensors and Bioelectronics presents the recent developments in biological recognition elements, transducer materials, and signal processing techniques for biosensors and bioelectronics used in agriculture and aquaculture applications. Sophisticated biosensors and bioelectronics operate through the immobilization of biological recognition components-such as enzymes or antibodies-on a transducer surface. This immobilization process allows for the targeted recognition and binding of biomolecules or pathogens. The resulting electrical, optical, or chemical changes triggered by the recognition event are quantifiable through various methods and are often enhanced by applications utilizing artificial intelligence (AI). The necessity for high sensitivity and selectivity, the optimization of biocompatibility and stability, and the integration of biosensors with AI-aided solutions are just some of the challenges and opportunities in developing biosensors for high-tech agriculture and aquaculture. This book targets a mixed audience of biotechnology engineers, biosensors scientists, bioelectronics researchers, high-tech agriculture analysts, Ph.D. scholars, researchers, academics, professionals, engineers, and students.

The book offers a comprehensive exploration of the fusion between quantum technology, AI, and robotics, providing readers with a deep understanding of the interplay between these fields and the transformative potential they hold.The Quantum Evolution: Application of AI and Robotics in the Future of Quantum Technology uncovers the potential of quantum algorithms to tackle complex computational problems exponentially faster than classical counterparts. Readers are introduced to quantum machine learning and its potential to revolutionize AI by enabling more efficient data analysis, pattern recognition, and decision-making. The book explores the potential applications of quantum-inspired neural networks and how they can enhance the capabilities of AI systems, ushering in a new era of intelligent machines. It also delves into the potential risks and challenges associated with quantum technology integration, such as quantum security and privacy concerns. The book showcases numerous real-world applications and examples of how quantum technology, AI, and robotics are being utilized today, giving readers concrete insights into how these advancements are shaping industries, healthcare, communication, and more.This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, professionals, and students from different communities to share and contribute new ideas, methodologies, technologies, models, frameworks, theories and practices in quantum technology.

In a world driven by technology and data, classical computing faces limitations in tackling complex challenges like climate modeling and financial risk assessment. These barriers impede our aspirations to revolutionize industries and solve intricate real-world problems. To bridge this gap, we must embrace quantum computing. Edited by Alex Khang PH, Principles and Applications of Quantum Computing is a transformative solution to this challenge. It delves into the interdisciplinary realms of computer science, physics, and mathematics, unveiling the incredible potential of quantum computing, which outperforms supercomputers by 158 million times. This technology, rooted in quantum mechanics, offers solutions to global problems and opens new frontiers in AI, cybersecurity, finance, drug development, and more. By engaging with this book, you become a pioneer in the quantum revolution, contributing to reshaping the limits of what's achievable in our digital age.

Academic scholars face the daunting challenge of keeping pace with the rapid evolution of innovative technologies. The emergence of AI-driven solutions, deep learning frameworks, and medical robotics introduces a complex terrain, demanding in-depth understanding and analysis. As scholars navigate the intricacies of patient hate speech detection, cardiovascular diseases AI-CDSS, and the revolution in medical diagnostics, a pressing need arises for comprehensive insights that bridge the gap between theoretical knowledge and practical applications. Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications serves as a solution in this era of transformative healthcare and addresses these challenges head-on. It unravels the complexities surrounding the implementation of AI in healthcare, offering in-depth discussions on the latest breakthroughs. From unraveling the mysteries of AI-driven cataract detection to exploring the implications of decentralized mammography classification, the book is a valuable resource that equips scholars with the knowledge to navigate this innovative landscape.

This book covers the basics of machine vision and robotics in the manufacturing industry. Major applicability of intelligent machines and robotics in the manufacturing sector are explored in three major areas of product traceability, remote product-monitoring, supply chain, logistics, and product record management.Machine Vision and Industrial Robotics in Manufacturing: Approaches, Technologies, and Applications explains advanced technologies based on AI and Industrial Internet of Things related to smart manufacturing applications.The book introduces the emerging machines and robotics applications that are enabling smart factories initiatives worldwide. The chapters examine labor productivity, factory device installation, and defective product detection. The authors share with readers the modern models, emerging technologies, designs, frameworks, theories, practices, and sustainable approaches to design and implement machine vision with industrial robotics. They also examine the challenging issues associated with the leveraging of technologies related to machine vision, computer vision, robotics, Internet of Things, Industrial IoT technologies, AI-equipped machines, applications, and automatic techniques for intelligent manufacturing systems and smart factory infrastructure in the era of industry 4.0 manufacturing. The authors also examine topics such as the role of existing management and production solutions, their limitations, and future directions in manufacturing industry.This book targets a mixed audience of students, engineers, scholars, researchers, academics and professionals who are learning, researching, and working in the field of machine vision, AI, IIoT, MV, CV, and robotic technologies from different industries and economics.

Within the healthcare sector, a pressing need for transformative changes is growing. From chronic diseases to complex diagnostic procedures, the industry stands at the crossroads of technological innovation and a burgeoning demand for more efficient, precise interventions. Patient expectations are soaring, and the deluge of medical data is overwhelming traditional healthcare systems. It is within this challenging environment that AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications emerges as a beacon of insight and practical solutions. The traditional healthcare framework is struggling to keep pace with the diverse demands of patients and the ever-expanding volume of medical data. As diseases become more intricate, attempts to provide timely identification and precise treatment of ailments become increasingly elusive. The urgency for a paradigm shift in healthcare delivery is emphasized by the critical need for early interventions, particularly in disease prediction. This challenge necessitates a holistic approach that harnesses the power of artificial intelligence (AI) and innovative technologies to steer healthcare toward a more responsive and patient-centric future.

In the post-COVID-19 healthcare landscape, the demand for smart healthcare solutions and precision medicine systems has grown significantly. To address these challenges, the book AI and IoT-Based Technologies for Precision Medicine provides a comprehensive resource for doctors, researchers, engineers, and students. By leveraging AI and IoT technologies, the book equips healthcare professionals with advanced tools and methodologies for predictive disease analysis, informed decision-making, and other aspects of precision medicine. This resource bridges the gap between theory and practice, exploring concepts like machine learning, deep learning, computer vision, AI-integrated applications, IoT-based technologies, healthcare data analytics, and biotechnology applications. Through this, the book empowers healthcare practitioners to pioneer innovative solutions that enhance efficiency, accuracy, and security in medical practices. AI and IoT-Based Technologies for Precision Medicine not only offer insights into the potential of AI-powered applications and IoT-equipped techniques in smart healthcare but also foster collaboration among healthcare scholars and professionals. This authoritative guide encourages knowledge sharing and collaboration to harness the transformative potential of AI and IoT, leading to revolutionary advancements in medical practices and healthcare services. With this book as a guide, readers can navigate the evolving landscape of high-tech medicine, taking confident steps toward a cutting-edge and precise medical ecosystem.

This book covers the need for IoT technologies and AI-aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. The last part focuses on AI-aided IoT techniques, Data analytics and visualization tools.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, ML-aided models, IoT-driven applications, and cybersecurity techniques in the era of the Industrial Revolution 4.0.

The recent advancements in the field of the internet of things (IoT), AI, big data, blockchain, augmented reality (AR)/virtual reality (VR), cloud platforms, quantum computing, cybersecurity, and telecommunication technology enabled the promotion of conventional computer-aided industry to the metaverse ecosystem that is powered by AR/VR-driven technologies. In this paradigm shift, the integrated technologies of IoT and AI play a vital role to connect the cyberspace of computing systems and virtual environments. AR/VR supports a huge range of industrial applications such as logistics, the food industry, and manufacturing utilities. AI-Based Technologies and Applications in the Era of the Metaverse discusses essential components of the metaverse ecosystem such as concepts, methodologies, technologies, modeling, designs, statistics, implementation, and maintenance. Covering key topics such as machine learning, deep learning, quantum computing, and blockchain, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.