This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.
This book first provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services. The authors give in-depth analyses of fog computing architecture and key technologies that fulfill the challenging requirements of enabling computing services anywhere along the cloud-to-thing continuum. Further, in order to make IoT systems more intelligent and more efficient, a fog-enabled service architecture is proposed to address the latency requirements, bandwidth limitations, and computing power issues in realistic cross-domain application scenarios with limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on this fog-enabled architecture, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as robot SLAM and formation control, wireless network self-optimization, intelligent transportation system, smart home and user behavior recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized. Provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services Presents a fog-enabled service architecture with detailed technical approaches for realistic cross-domain application scenarios with limited prior domain knowledge Outlines a series of data-driven self-learning applications (with new algorithms) in different industrial sectors and public services
This brief examines resource allocation and interference management for 4G femtocells. It introduces 4G femtocells in the context of 4G mobile networks and discusses related technical challenges in resource allocation and interference management. Topics include ant colony algorithm based downlink resource allocation, intelligent scheduling and power control, uplink and downlink for two-tier networks, quality of service (QoS) constraints and the cross-tier interference constraint. The authors present algorithms to alleviate common femtocell-related problems such as subchannel power allocation. The complexity of the proposed resource allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations. This concise and practical book directly addresses common problems relating to femtocells and resource management. It serves as a useful tool for researchers in the field. Advanced-level students or professionals interested in femtocells and networks will also find the content helpful.
Reported speech is a universal form across human languages. However, previous studies have tended to be limited because they mostly emphasize on the form and authenticity of reported speech, while its discourse and pragmatic functions have largely been ignored. Meanwhile, the studies mainly focus on English, with a comparative perspective with other languages largely missing. Acknowledging these limitations, this book analyzes the textual and pragmatic functions of reported speech in Chinese and English. The authors build a corpus comprising of twelve Chinese and English newspapers, including China Daily and The New York Times. They examine the classification and distribution of reported speech, the form and function in different news genres and contexts, and the socio-pragmatic interpretation of reported speech in news and other issues. This title can enrich comparative linguistic research, verify the feasibility of combining critical linguistics and corpus technology, and help improve the production and understanding of news reports. Students and scholars of critical discourse analysis, comparative linguistics, corpus linguistics, as well as communication studies will find this to be an essential guide.
In A Dialogue between Haizi’s Poetry and the Gospel of Luke Xiaoli Yang offers a conversation between the Chinese soul-searching found in Haizi’s (1964–1989) poetry and the gospel of Jesus Christ through Luke’s testimony. It creates a unique contextual poetic lens that appreciates a generation of the Chinese homecoming journey through Haizi’s poetry, and explores its relationship with Jesus Christ. As the dialogical journey, it names four stages of homecoming—roots, vision, journey and arrival. By taking an interdisciplinary approach—literary study, inter-cultural dialogue and comparative theology, Xiaoli Yang convincingly demonstrates that the common language between the poet Haizi and the Lukan Jesus provides a crucial and rich source of data for an ongoing table conversation between culture and faith.
Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.
This book investigates three novice high school mathematics teachers’ professional learning processes in the early stages of their careers at schools in Shanghai, China. Teacher professional learning is examined as a complex and dynamic system that connects both cognitive and situated perspectives on learning theory. Inspiring mathematics teachers to adopt student-focused pedagogies is challenging, particularly in China where tensions in teacher-centred, content-focused and examination-oriented practices are predominant. The three novice teachers who participated in this study brought different beliefs and knowledge derived from their different individual experiences to bear on their teaching practices. However, they were strongly influenced by the environments in which they taught and mainly adopted a professional learning approach to teacher-centred practices, despite reporting that they favoured student-centred teaching practices. The study also observed professional learning towards student-centred pedagogical aspects in a single teacher case with mentorship support, indicating that student-centred pedagogies may be promoted within the constraints of the existing dominant teaching practice.
This book studies the variety of organizational strategies selected to cope with critical uncertainties during crises. This research formulates and applies an institutional sense-making model to explain the selection of strategies for coping with uncertainties during crises to answer the question why some organizations select a rule-based strategy to cope with uncertainties, whereas others pursue a more ad hoc-based strategy. It finds that the level of institutionalization does not affect strategy selection in the initial phase of responding to crises; that three rigidity effects can be identified in the selection of sense-making strategies once organizations have faced the failure of their selected strategies; that discontinuities in the feedback loop of sense-making do not necessarily move organizations to switch their sense-making strategies, but interact with institutionalization to contribute to switching sense-making strategies. This book bridges the gap between institutional thinking and crisis management theorizing. A major step forward in the world of crisis management studies! ——Professor Arjen Boin, Leiden University, the Netherlands In a world of increasingly complex, sociotechnical systems interacting in high-risk environments, Professor Lu’s analysis of how organizations manage uncertainty is both timely and profound. ——Professor Louise K. Comfort, Director, Center for Disaster Management, University of Pittsburgh, USA Prof. Lu greatly enhances our understanding of how organizations cope with uncertainty and make sense of their challenges under the pressures of catastrophe. ——Dr. Arnold M. Howitt, Faculty Co-Director, Program on Crisis Leadership, Harvard Kennedy School, USA This book provides not only a theory of crisis management but also a key concept around which research and practice can be conducted. ——Professor Naim Kapucu, Director of School of Public Administration, University of Central Florida, USA A generic institutional model for analyzing and managing hazards, disasters and crises worldwide. ——Professor Joop Koppenjan, Erasmus University Rotterdam, the Netherlands This book has done an excellent job in opening the black box of how organizations make sense of the crisis situations they face and develop strategies to respond. It should be read by all of us who wish for a peaceful and safe world. ——Professor Lan Xue, Dean of School of Public Policy and Management, Tsinghua University, China
This book focuses on multi-model systems, describing how to apply intelligent technologies to model complex multi-model systems by combining stochastic jumping system, neural network and fuzzy models. It focuses on robust filtering, including finite-time robust filtering, finite-frequency robust filtering and higher order moment robust filtering schemes, as well as fault detection problems for multi-model jump systems, such as observer-based robust fault detection, filtering-based robust fault detection and neural network-based robust fault detection methods. The book also demonstrates the validity and practicability of the theoretical results using simulation and practical examples, like circuit systems, robot systems and power systems. Further, it introduces readers to methods such as finite-time filtering, finite-frequency robust filtering, as well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the modeling, analysis and design of the multi-model systems presented and implement filtering and fault detection analysis for various systems, including circuit, network and mechanical systems.
This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances. It explores how these tools can make the systems more applicable to fields such as economic systems, ecological systems and solar thermal central receivers, by limiting system trajectories in the desired bound in a given time interval. Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain focuses on multiple aspects of finite-time stability and control, including: finite-time H-infinity control; finite-time sliding mode control; finite-time multi-frequency control; finite-time model predictive control; and high-order moment finite-time control for multi-mode systems and also provides many methods and algorithms to solve problems related to Markovian jump systems with simulation examples that illustrate the design procedure and confirm the results of the methods proposed. The thorough discussion of these topics makes the book a useful guide for researchers, industrial engineers and graduate students alike, enabling them systematically to establish the modeling, analysis and synthesis for Markovian jump systems in the finite-time domain.
This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.
A detailed, up-to-date introduction to heterogeneous cellular networking, including discussion of practical design considerations and industry case studies.
This book first provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services. The authors give in-depth analyses of fog computing architecture and key technologies that fulfill the challenging requirements of enabling computing services anywhere along the cloud-to-thing continuum. Further, in order to make IoT systems more intelligent and more efficient, a fog-enabled service architecture is proposed to address the latency requirements, bandwidth limitations, and computing power issues in realistic cross-domain application scenarios with limited priori domain knowledge, i.e. physical laws, system statuses, operation principles and execution rules. Based on this fog-enabled architecture, a series of data-driven self-learning applications in different industrial sectors and public services are investigated and discussed, such as robot SLAM and formation control, wireless network self-optimization, intelligent transportation system, smart home and user behavior recognition. Finally, the advantages and future directions of fog-enabled intelligent IoT systems are summarized. Provides a comprehensive review of state-of-the-art IoT technologies and applications in different industrial sectors and public services Presents a fog-enabled service architecture with detailed technical approaches for realistic cross-domain application scenarios with limited prior domain knowledge Outlines a series of data-driven self-learning applications (with new algorithms) in different industrial sectors and public services
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