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| Author | : Shi Yin |
| Publisher | : Frontiers Media SA |
| Total Pages | : 195 |
| Release | : 2023-09-06 |
| Genre | : Science |
| ISBN | : 2832532985 |
| Author | : Samsul Ariffin Abdul Karim |
| Publisher | : Springer Nature |
| Total Pages | : 81 |
| Release | : 2020-02-27 |
| Genre | : Technology & Engineering |
| ISBN | : 9811526559 |
This book explores key examples concerning the implementation of information technology and mathematical modeling to solve issues concerning environmental sustainability. The examples include using fuzzy weighted multivariate regression to predict the water quality index at Perak River in Malaysia; using wireless sensor networks (WSNs) for a remote river water pollution monitoring system; deriving biomass activated carbon from oil palm shell; and assessing the performance of a PV/T air solar collector. The book offers a valuable resource for all graduate students and researchers who are working in this rapidly growing area.
| Author | : |
| Publisher | : |
| Total Pages | : 88 |
| Release | : 2020 |
| Genre | : Fuzzy statistics |
| ISBN | : 9789811526565 |
This book explores key examples concerning the implementation of information technology and mathematical modeling to solve issues concerning environmental sustainability. The examples include using fuzzy weighted multivariate regression to predict the water quality index at Perak River in Malaysia; using wireless sensor networks (WSNs) for a remote river water pollution monitoring system; deriving biomass activated carbon from oil palm shell; and assessing the performance of a PV/T air solar collector. The book offers a valuable resource for all graduate students and researchers who are working in this rapidly growing area.
| Author | : Biswadip Basu Mallik |
| Publisher | : Bentham Science Publishers |
| Total Pages | : 263 |
| Release | : 2024-07-22 |
| Genre | : Computers |
| ISBN | : 9815223267 |
This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions. Key themes AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains. This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.
| Author | : Mangey Ram |
| Publisher | : Academic Press |
| Total Pages | : 420 |
| Release | : 2020-10-02 |
| Genre | : Mathematics |
| ISBN | : 012818907X |
Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods. Focuses on recent research in mathematics applications for Industry 4.0 Provides insights on international and transnational scales Identifies mathematics knowledge gaps for Industry 4.0 Describes fruitful areas for further research in industrial mathematics, including forthcoming international studies and research
| Author | : Turan Paksoy |
| Publisher | : CRC Press |
| Total Pages | : 369 |
| Release | : 2020-12-17 |
| Genre | : Technology & Engineering |
| ISBN | : 1000245101 |
Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.
| Author | : J. Paulo Davim |
| Publisher | : Woodhead Publishing |
| Total Pages | : 244 |
| Release | : 2017-05-25 |
| Genre | : Business & Economics |
| ISBN | : 0857094823 |
Computational Methods and Production Engineering: Research and Development is an original book publishing refereed, high quality articles with a special emphasis on research and development in production engineering and production organization for modern industry. Innovation and the relationship between computational methods and production engineering are presented. Contents include: Finite Element method (FEM) modeling/simulation; Artificial neural networks (ANNs); Genetic algorithms; Evolutionary computation; Fuzzy logic; neuro-fuzzy systems; Particle swarm optimization (PSO); Tabu search and simulation annealing; and optimization techniques for complex systems. As computational methods currently have several applications, including modeling manufacturing processes, monitoring and control, parameters optimization and computer-aided process planning, this book is an ideal resource for practitioners. Presents cutting-edge computational methods for production engineering Explores the relationship between applied computational methods and production engineering Presents new innovations in the field Edited by a key researcher in the field
| Author | : Daniel Alejandro Rossit |
| Publisher | : Elsevier |
| Total Pages | : 286 |
| Release | : 2024-06-12 |
| Genre | : Science |
| ISBN | : 0443216509 |
Evolution and Trends of Sustainable Approaches: Latest Development and Innovations in Science and Technology Applications provides different trends and approaches within the sustainability framework to assess their impact and offer possible solutions to problems facing the global sustainability paradigm. This book evaluates sustainability assessment approaches which support different levels of both decision-making and policy processes, thereby improving the management of natural and human systems. This book explores sustainable firm solutions, the upward trend of sustainability, and its variants. At the same time, different existing approaches are analyzed. These sustainable assessment approaches can be applied to products, services and technologies as well as business models, such as the Product-Service-System (PSS), Circular Economy (CE), Industrial Symbiosis (IS), and Supply Chain (SC). Finally, the book explores Sustainability Indicators (SIs), which are widely used to measure and communicate progress towards sustainable development, along with Life Cycle Sustainability Assessment (LCSA), balancing the three dimensions of sustainability (environmental, social and economic). Explores innovative strategies and advanced trends of sustainable approaches, engineering, and industrial applications Analyzes sustainability assessments and their role in planning and project processes Reviews state-of-the-art sustainable technologies Evaluates approaches for organizations to achieve both sustainability assessment and sustainable solutions
| Author | : Mei-Yun Quan |
| Publisher | : Infinite Study |
| Total Pages | : 14 |
| Release | : |
| Genre | : Mathematics |
| ISBN | : |
With increasing global concerns toward environmental protection and sustainable development, green supply chain management (GSCM) has drawn much attention from academicians and practitioners. Selecting an optimal green supplier is a critical part of GSCM, which can be viewed as a kind of multi-criteria decision making (MCDM) problem. To derive the best result, large group of decision makers are often involved in the green supplier selection nowadays. Besides, decision makers tend to express their evaluations utilizing uncertain linguistic terms due to the vagueness of human thinking. Hence, this paper aims to propose a hybrid MCDM approach for green supplier selection within the large group setting. More concretely, interval-valued intuitionistic uncertain linguistic sets (IVIULSs) are applied for assessing the performance of green suppliers concerning each criterion. Ant colony algorithm is utilized to cluster decision makers into several subgroups. The linear programming technique for multidimensional analysis of preference (LINMAP) is adopted for the determination of the optimal weights of criteria objectively. Finally, an extended MULTIMOORA approach is utilized to generate the ranking of alternative suppliers. The practicality and usefulness of the developed large group green supplier selection framework is illustrated using an empirical example of a real estate company.
| Author | : Zude Zhou |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 373 |
| Release | : 2011-10-22 |
| Genre | : Technology & Engineering |
| ISBN | : 0857295640 |
The manufacturing industry will reap significant benefits from encouraging the development of digital manufacturing science and technology. Digital Manufacturing Science uses theorems, illustrations and tables to introduce the definition, theory architecture, main content, and key technologies of digital manufacturing science. Readers will be able to develop an in-depth understanding of the emergence and the development, the theoretical background, and the techniques and methods of digital manufacturing science. Furthermore, they will also be able to use the basic theories and key technologies described in Digital Manufacturing Science to solve practical engineering problems in modern manufacturing processes. Digital Manufacturing Science is aimed at advanced undergraduate and postgraduate students, academic researchers and researchers in the manufacturing industry. It allows readers to integrate the theories and technologies described with their own research works, and to propose new ideas and new methods to improve the theory and application of digital manufacturing science.
