Digital Transformation in the Construction Industry: Sustainability, Resilience, and Data-Centric Engineering delivers timely and much sought-after guidance related to novel, digital-first practices and the latest technological tools whose gradual adoption is being embraced to significantly reshape the way buildings and other infrastructure assets are designed, constructed, operated, and maintained. The book contains methodological and practice-informed investigations by scholars and researchers from across the globe, providing a wealth of knowledge relevant for, and applicable to, different geographical and economic contexts that are coherently collated in this comprehensive resource.This systematic analysis of cutting-edge developments [such as such as Building Information Modeling (BIM), Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Big Data, Augmented Reality (AR), Virtual Reality (VR), 3D Printing, and Structural Health Monitoring (SHM)] is accompanied by discussions on challenges and opportunities that digitalization engenders. Additionally, real-word case studies enrich the coverage, highlighting how these innovative solutions can contribute to establish working efficiencies which can at the same time aid the impactful realization of globally recognized sustainability goals.
The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches. Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable.Case studies and other practical discussions exemplify these methods’ promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide.
Electrochemistry of Organic and Organometallic Compounds is a comprehensive and up-to-date resource for researchers, practitioners and students in the field of electrochemistry, organic chemistry, and organometallic chemistry. The book addresses the growing interest in the use of electrochemical methods for the synthesis, characterization, and functionalization of organic and organometallic compounds. The book provides the the principles and applications of electrochemistry in the context of organic and organometallic compounds. It covers topics such as electrochemical synthesis and functionalization, characterization techniques, and applications in areas such as energy storage and catalysis. It focuses on practical examples and guidance, and provides the tools and knowledge needed to effectively use electrochemical methods for the synthesis and modification of organic and organometallic compounds. The book includes the latest advances in electrochemistry, how to apply these to the synthesis and modification of organic and organometallic compounds, as well as practical guidance on the use of electrochemical techniques. This helps you to keep up with the fast-paced developments in the field, to find reliable and up-to-date information, and to understand the complexities of electrochemical systems and their applications.
Fundamentals of Air Pollution, Sixth Edition offers an extensive study of the science of air pollution. With a highly interdisciplinary approach, the book's author examines air pollution through the lenses of chemistry, physics, meteorology, engineering, toxicology, regulation, and more. Students, faculty, and researchers alike will find a world of information in this comprehensive text that is strategically organized into six parts: Foundations of Air Pollution, The Risks of Air Pollution, Tropospheric Pollution, Biogeochemistry of Air Pollutants, Addressing Air Pollution, and The Future for Air Pollution Science and Engineering.Readers will find helpful features throughout, including case studies, topical sidebars, worked examples, calculations, and reference data. This valuable resource offers an up-to-date and comprehensive analysis of air pollution with its wealth of benefits to both students and researchers.
Advances in Optics of Charged Particle Analyzers: Part Two, Volume 233 merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The release in the series features articles on Electrostatic Energy, Mass Analyzers With Combined Electrostatic and Magnetic Fields, Mass Analyzers based on Fourier Transform, Principles of Time-of-Flight Mass Analyzers, Multi-Pass Time-of-Flight Mass Analyzers, and Radiofrequency Mass Analyzers.
Progress in Optics, Volume 70 is the latest release in a yearly publication that provides in-depth reviews on topics in experimental theoretical optics, as well as on optical engineering. Chapters in this new release include Phased-array lidar, Holographic metasurfaces, Schlieren imaging, Statistical Properties of Polarization Speckle, The Talbot effect, Space-time optics, Structured light, Application of partial coherence in the quantum domain, Natural mode expansions, and Skyrmionic beams.
Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data.
Open Radio Access Network (O-RAN) Systems Architecture and Design, 2nd edition, gives a jump start to engineers developing O-RAN hardware and software systems, providing a top-down approach to O-RAN systems design from an author with a silicon, software, and system background. It gives an introduction into why wireless systems look the way they do today before introducing relevant O-RAN and 3GPP standards. The remainder of the book discusses hardware and software aspects of O-RAN system design, including dimensioning and performance targets, and some practical use case examples that include 5G advanced topics. This edition includes comprehensive updates in key areas such as postquantum security and radio unit design. Additionally, it addresses emerging 5G advanced topics, including Industrial & URLLC, nonterrestrial networking, the role of artificial intelligence, 5G reduced capabilities for IoT, and self-organizing networks.
Resilient Cooperative Control and Optimization of Multi-Agent Systems addresses various resilient cooperative control and optimization problems of multi-agent systems that are vulnerable to physical failure and cyber attacks and consist of multiple decision-making agents that interact in a shared environment to achieve common or conflicting goals. Critical infrastructures, such as smart grids, wireless sensor network, multi-robot system, etc., are typical examples of multi-agent systems that consist of the large-scale physical processes which are monitored and controlled over a set of communication networks and computers.
Biomass for Environmental Remediation explores the pivotal role of biomass in revolutionizing environmental remediation. From wastewater treatment to air pollution control and soil remediation, this book delves into the myriad applications of biomass, including the synthesis of advanced nanomaterials for sustainable solutions. Users will find the latest advancements in harnessing organic resources for a cleaner and greener future, while also uncovering the diverse sources of biomass and the innovative techniques transforming them into powerful tools for environmental restoration.With insightful chapters on phytoremediation, microbial applications, and the production of biomass-derived nanomaterials, this book serves as a vital guide for professionals, researchers, and students at the forefront of environmental sustainability.