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This book presents the proceedings of the 8th International Conference on Engineering, Project, and Product Management (EPPM 2017), highlighting the importance of engineering, project and product management in a region of the world that is in need of transformation and rebuilding. The aim of the conference was to bring together the greatest minds in engineering and management and offer them a platform to share their innovative, and potentially transformational, findings. The proceedings are comprehensive, multidisciplinary, and advanced in their approach with an appeal not only for academicians and university students but also for professionals in various engineering fields, especially construction, manufacturing and production.
This book gathers high-quality papers presented at the International Conference on Artificial Intelligence and Applications (ICAIA 2020), held at Maharaja Surajmal Institute of Technology, New Delhi, India, on 6–7 February 2020. The book covers areas such as artificial neural networks, fuzzy systems, computational optimization technologies and machine learning.
This book critically examines the global diffusion and local reception of resilience through the implementation of Disaster Risk Reduction (DRR) programmes in Pacific and Caribbean island states. Global efforts to strengthen local disaster resilience capacities have become a staple of international development activity in recent decades, yet the successful implementation of DRR projects designed to strengthen local resilience remains elusive. While there are pockets of success, a gap remains between global expectations and local realities. Through a critical realist study of global and local worldviews of resilience in the Pacific and Caribbean islands, this book argues that the global advocacy of DRR remains inadequate because of a failure to prioritise a person-orientated ethics in its conceptualization of disaster resilience. This regional comparison provides a valuable lens to understand the underlying social structures that makes resilience possible and the extent to which local governments, communities and persons interpret and modify their behaviour on risk when faced with the global message on resilience. This book will be of much interest to students of resilience, risk management, development studies, and area studies.
This book explores the latest advances in the field of building management. Several chapters use new technologies such as the BIM methodology for collecting life cycle information and managing the maintenance of existing buildings, sharing valid historical and architectural heritage data, energy analysis of building envelopes, and planning new buildings or sustainable building practices. In addition, other tools are presented that focus on improving access to BIM information, open-source governance, mobile applications to accelerate information transfer, the use of blockchain, lean design methods, and open-source software to solve critical path problems. Some contributions feature the assessment of occupational risks in construction, as it is necessary to plan preventive measures based on risk assessments integrated throughout the construction process, which is another important element for the management of this sector.
Providing readers with a unique guide of how businesses can achieve resilience to digital conflict, Conflict Management in Digital Business helps prepare for unexpected situations such as pandemics, to maintain competitive advantage, and illuminating pathways to turn conflicts caused by extraordinary situations into opportunities.
Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.
The development of the Digital Economy has been a landmark breakthrough for economic systems in the 21st century, as it opens up opportunities for the full-scale implementation of new digital technologies and the optimization of economic activities. While the conceptual essence and specific features of the digital economy are described in detail in the existing literature, the practical foundations of its formation are poorly studied. In this book, the digital economy is studied from the perspective of neo-institutional economic theory. This allows for the tracking of the process of formation (institutionalization) of the digital economy, determining the basic institutions that are necessary for its formation and that exist in modern economic practice, and analyzing scenarios for the future development of the digital economy in the 21st century.
In today's rapidly evolving world, the exponential growth of data poses a significant challenge. As data volumes increase, traditional methods of analysis and decision-making become inadequate. This surge in data complexity calls for innovative solutions that efficiently extract meaningful insights. Machine learning has emerged as a powerful tool to address this challenge, offering algorithms and techniques to analyze large datasets and uncover hidden patterns, trends, and correlations. Machine Learning Techniques and Industry Applications demystifies machine learning through detailed explanations, examples, and case studies, making it accessible to a broad audience. Whether you're a student, researcher, or practitioner, this book equips you with the knowledge and skills needed to harness the power of machine learning to address diverse challenges. From e-government to healthcare, cyber-physical systems to agriculture, this book explores how machine learning can drive innovation and sustainable development.
As Industry 4.0 brings on a new bout of transformation and fundamental changes in various industries, the traditional manufacturing and production methods are falling to the wayside. Industrial processes must embrace modern technology and the most recent trends to keep up with the times. With “smart factories”; the automation of information and data; and the inclusion of IoT, AI technologies, robotics, and cloud computing comes new challenges to tackle. These changes are creating new threats in security, reliability, the regulations around legislation and standardization of technologies, malfunctioning devices or operational disruptions, and more. These effects span a variety of industries and need to be discussed. Research Anthology on Cross-Industry Challenges of Industry 4.0 explores the challenges that have risen as multidisciplinary industries adapt to the Fourth Industrial Revolution. With a shifting change in technology, operations, management, and business models, the impacts of Industry 4.0 and digital transformation will be long-lasting and will forever change the face of manufacturing and production. This book highlights a cross-industry view of these challenges, the impacts they have, potential solutions, and the technological advances that have brought about these new issues. It is ideal for mechanical engineers, electrical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians, and students looking for cross-industry research on the challenges associated with Industry 4.0.
Advances in technological innovations, automation, and the latest developments in artificial intelligence (AI) have revolutionized the nature of work and created a demand for a new set of skills to navigate the Fourth Industrial Revolution (Industry 4.0). Therefore, it is necessary to equip displaced workers with a new set of skills that are essential for conversion into technical or other functional areas of business. Human Capital Formation for the Fourth Industrial Revolution is an essential research publication that recognizes the need to revitalize human capital formation for graduate employability in Industry 4.0 and discusses new skills and competencies needed to cope with the challenges present within this industrial revolution. The book seeks to provide a basis for curriculum design in line with the advances in technological innovations, automation, and artificial intelligence to enhance current and future employment. Featuring an array of topics such as curriculum design, emotional intelligence, and healthcare, this book is ideal for human resource managers, development specialists, training officers, teachers, universities, practitioners, academicians, researchers, managers, policymakers, and students.