Design of Steel Structures: Materials, Connections, and Components systematically introduces the basic concepts and principles of the subject of "Design of steel structure". Sections cover materials, failure modes of steel structures, members under tension, compression, bending and combined loads, steel connections, typical steel structural systems, composite members and vibrations resistance of steel members and connections. In addition, development history and the general application of steel structures are introduced, along with development status trends and typical classifications of steel structures. Other chapters discuss materials of steel structures, including high-performance steel, cold-formed steel, and other new types. - Contains comprehensive, basic knowledge for designing steel structures - Introduces materials, connections, components and structural systems of steel structures - Includes theoretical calculating methods and engineering design methods - Presents a large number of engineering cases throughout the book, including new steel materials, new steel connections, new steel components and new construction technologies
This book presents a comprehensive review of recent developments in vanadium-based nanomaterials for next-generation electrochemical energy storage. The basic electrochemical energy storage and conversion equipment are elaborated, and the vanadium-based nanomaterials of the synthesis approaches, characterizations, electrochemical storage mechanisms, and performance optimization tactics are discussed. Examples are taken from various chemical energy storage devices to expound the functions of advanced vanadium-based nanomaterials for specific applications. Finally, various challenges and perspectives on vanadium-based nanomaterial development as an emerging energy storage solution are considered.
This study describes the fundamentals of assessing the vulnerability of coral islands, as well as environmental management and resource exploitation. Using seabird subfossils, such as bones, guano, eggshells etc., which have been well preserved on the Xisha Islands in the South China Sea, the author identifies the influences of climate change and human activity on seabird populations and diets. Understanding the past is of great importance for predicting the future, and seabird subfossils provide valuable information, which can be used to study changes in seabird ecology, paleoceanography and palaeoclimate. Furthermore, this study proposes examining the biogeochemical cycling of some elements present in the geosphere, hydrosphere, biosphere and atmosphere. Dr. Liqiang Xu works at the Hefei University of Technology, China.
This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic value, fashion compatibility modeling has gained increasing research attention in recent years. Although great efforts have been dedicated to this research area, previous studies mainly focused on fashion compatibility modeling for outfits that only involved two items and overlooked the fact that each outfit may be composed of a variable number of items. This book develops a series of graph-learning based outfit compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This systematic approach benefits readers by introducing the techniques for compatibility modeling of outfits that involve a variable number of composing items. To deal with the challenging task of outfit compatibility modeling, this book provides comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning. Moreover, this book sheds light on research frontiers that can inspire future research directions for scientists and researchers.
Nowadays, fashion has become an essential aspect of people's daily life. As each outfit usually comprises several complementary items, such as a top, bottom, shoes, and accessories, a proper outfit largely relies on the harmonious matching of these items. Nevertheless, not everyone is good at outfit composition, especially those who have a poor fashion aesthetic. Fortunately, in recent years the number of online fashion-oriented communities, like IQON and Chictopia, as well as e-commerce sites, like Amazon and eBay, has grown. The tremendous amount of real-world data regarding people's various fashion behaviors has opened a door to automatic clothing matching. Despite its significant value, compatibility modeling for clothing matching that assesses the compatibility score for a given set of (equal or more than two) fashion items, e.g., a blouse and a skirt, yields tough challenges: (a) the absence of comprehensive benchmark; (b) comprehensive compatibility modeling with the multi-modal feature variables is largely untapped; (c) how to utilize the domain knowledge to guide the machine learning; (d) how to enhance the interpretability of the compatibility modeling; and (e) how to model the user factor in the personalized compatibility modeling. These challenges have been largely unexplored to date. In this book, we shed light on several state-of-the-art theories on compatibility modeling. In particular, to facilitate the research, we first build three large-scale benchmark datasets from different online fashion websites, including IQON and Amazon. We then introduce a general data-driven compatibility modeling scheme based on advanced neural networks. To make use of the abundant fashion domain knowledge, i.e., clothing matching rules, we next present a novel knowledge-guided compatibility modeling framework. Thereafter, to enhance the model interpretability, we put forward a prototype-wise interpretable compatibility modeling approach. Following that, noticing the subjective aesthetics of users, we extend the general compatibility modeling to the personalized version. Moreover, we further study the real-world problem of personalized capsule wardrobe creation, aiming to generate a minimum collection of garments that is both compatible and suitable for the user. Finally, we conclude the book and present future research directions, such as the generative compatibility modeling, virtual try-on with arbitrary poses, and clothing generation.
Mine Design, Planning and Sustainable Exploitation in the Digital Age covers mine planning, design and exploitation taking cognizance of new developments, especially those associated with the Fourth Industrial Revolution and the positive influence that it has, and will have, on the mining industry. It refers to latest best practices with emphasis on the social license to operate and sustainable (green) mining. The book covers surface and underground mining in some detail and addresses relevant associated aspects such as risk management, green mining and the importance of real community relations. It is organized as follows: Surface Mining Underground Soft Rock Mining Underground Hard Rock (Metal/Non-metal) Mining Green and Sustainable Mining It has many relevant photos and figures that help the reader and includes appropriate support design and types commonly used in the various mining methods. Mine Design, Planning and Sustainable Exploitation in the Digital Age is mainly aimed at mining, geological engineering and other undergraduate and postgraduates interested in the mining resources industry. It will also serve as a useful reference book for practitioners in the mining industry who want an easy-to-use book.
Micro-videos, a new form of user-generated contents, have been spreading widely across various social platforms, such as Vine, Kuaishou, and Tik Tok. Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to its brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for the high-order micro-video understanding. Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of the venue categories to guide the micro-video analysis; (3) how to alleviate the influence of low-quality caused by complex surrounding environments and the camera shake; (4) how to model the multimodal sequential data, {i.e.}, textual, acoustic, visual, and social modalities, to enhance the micro-video understanding; and (5) how to construct large-scale benchmark datasets for the analysis? These challenges have been largely unexplored to date. In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. Learning across multiple social networks brings opportunities to new services and applications as well as new insights on user online behaviors, yet it raises tough challenges: (1) How can we map different social network accounts to the same social users? (2) How can we complete the item-wise and block-wise missing data? (3) How can we leverage the relatedness among sources to strengthen the learning performance? And (4) How can we jointly model the dual-heterogeneities: multiple tasks exist for the given application and each task has various features from multiple sources? These questions have been largely unexplored to date. We noticed this timely opportunity, and in this book we present some state-of-the-art theories and novel practical applications on aggregation of multiple social networks. In particular, we first introduce multi-source dataset construction. We then introduce how to effectively and efficiently complete the item-wise and block-wise missing data, which are caused by the inactive social users in some social networks. We next detail the proposed multi-source mono-task learning model and its application in volunteerism tendency prediction. As a counterpart, we also present a mono-source multi-task learning model and apply it to user interest inference. We seamlessly unify these models with the so-called multi-source multi-task learning, and demonstrate several application scenarios, such as occupation prediction. Finally, we conclude the book and figure out the future research directions in multiple social network learning, including the privacy issues and source complementarity modeling. This is preliminary research on learning from multiple social networks, and we hope it can inspire more active researchers to work on this exciting area. If we have seen further it is by standing on the shoulders of giants.
This book discusses topics related to power electronics, especially electromagnetic transient analysis and control of high-power electronics conversion. It focuses on the re-evaluation of power electronics, transient analysis and modeling, device-based system-safe operating area, and energy balance-based control methods, and presenting, for the first time, numerous experimental results for the transient process of various real-world converters. The book systematically presents both theoretical analysis and practical applications. The first chapter discusses the structure and attributes of power electronics systems, highlighting the analysis and synthesis, while the second chapter explores the transient process and modeling for power electronics systems. The transient features of power devices at switching-on/off, transient conversion circuit with stray parameters and device-based system-safe operating area are described in the subsequent three chapters. The book also examines the measurement of transient processes, electromagnetic pulses and their series, as well as high-performance, closed-loop control, and expounds the basic principles and method of the energy-balanced control strategy. Lastly, it introduces the applications of transient analysis of typical power electronics systems. The book is valuable as a textbook for college students, and as a reference resource for electrical engineers as well as anyone working in the field of high-power electronics system.
Design of Steel Structures: Materials, Connections, and Components systematically introduces the basic concepts and principles of the subject of "Design of steel structure". Sections cover materials, failure modes of steel structures, members under tension, compression, bending and combined loads, steel connections, typical steel structural systems, composite members and vibrations resistance of steel members and connections. In addition, development history and the general application of steel structures are introduced, along with development status trends and typical classifications of steel structures. Other chapters discuss materials of steel structures, including high-performance steel, cold-formed steel, and other new types. - Contains comprehensive, basic knowledge for designing steel structures - Introduces materials, connections, components and structural systems of steel structures - Includes theoretical calculating methods and engineering design methods - Presents a large number of engineering cases throughout the book, including new steel materials, new steel connections, new steel components and new construction technologies
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