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Environmental Data Analysis
With the dramatic development of air-space-ground-sea environmental monitoring networks and large-scale high-resolution Earth simulators, Environmental science is facing opportunities and challenges of big data. Environmental Data Analysis focuses on state-of-the-art models and methods for big environmental data and demonstrates their applications through various case studies in the real world. It covers the comprehensive range of topics in data analysis in space, time and spectral domains, including linear and nonlinear environmental systems, feature extraction models, data envelopment analysis, risk assessments, and life cycle assessments. The 2nd Edition adds emerging network models, including neural networks, complex networks, downscaling analysis and streaming data on network. This book is a concise and self-contained work with enormous amount of information. It is a must-read for environmental scientists who struggle to conduct big data mining and data scientists who try to find the way into environmental science.
Multivariate Time Series Analysis in Climate and Environmental Research
This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.
Big Data Mining for Climate Change
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation’s big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data ...
Observer Design for Control and Fault Diagnosis of Boolean Networks
Boolean control networks (BCNs) are a kind of parameter-free model, which can be used to approximate the qualitative behavior of biological systems. After converting into a model similar to the standard discrete-time state-space model, control-theoretic problems of BCNs can be studied. In control theory, state observers can provide state estimation for any other applications. Reconstructibility condition is necessary for the existence of state observers. In this thesis explicit and recursive methods have been developed for reconstructibility analysis. Then, an approach to design Luenberger-like observer has been proposed, which works in a two-step process (i.e. predict and update). If a BCN ...
Mathematical and Physical Fundamentals of Climate Change
Mathematical and Physical Fundamentals of Climate Change is the first book to provide an overview of the math and physics necessary for scientists to understand and apply atmospheric and oceanic models to climate research. The book begins with basic mathematics then leads on to specific applications in atmospheric and ocean dynamics, such as fluid dynamics, atmospheric dynamics, oceanic dynamics, and glaciers and sea level rise. Mathematical and Physical Fundamentals of Climate Change provides a solid foundation in math and physics with which to understand global warming, natural climate variations, and climate models. This book informs the future users of climate models and the decision-mak...
Positive or Negative? The Effect of Emerging Technologies and Products on Mental Health
Emerging technologies and products such as digital health technology, computing platforms, wearable devices, smartphone sensors and electronic gadgets have the potential to transform and empower society while simultaneously presenting unprecedented challenges in our life. Some like electronic cigarettes (e-cigarettes) are for entertainment, some like online conference platforms are for convenience and some like social media have become a life necessity. However, there is an ongoing debate about whether the use of physical and virtual digital technology products can do harm to mental health. Some evidence-based research shows that frequent use of social media may cause depression and anxiety, and derived behavioral phenomena like cyberbullying and game addiction, which negatively affect people’s lives. Other scholars think digital technology products could provide insights into timely, personalized, engaging and accessible intervention, promotion and improvement of mental health. Given the ubiquity of digital devices and their complex and subtle associations with mental health, more research is needed to bring benefits to both research and daily life practices.
Proceedings of 2022 Chinese Intelligent Systems Conference
This book constitutes the proceedings of the 18th Chinese Intelligent Systems Conference, CISC 2022, which was held during October 15–16, 2022, in Beijing, China. The papers in these proceedings deal with various topics in the field of intelligent systems and control, such as multi-agent systems, complex networks, intelligent robots, complex system theory and swarm behavior, event-triggered control and data-driven control, robust and adaptive control, big data and brain science, process control, intelligent sensor and detection technology, deep learning and learning control guidance, navigation and control of aerial vehicles.
New Prospects in Environmental Geosciences and Hydrogeosciences
This edited book gives a general overview on current research, focusing on geoenvironmental issues and challenges in hydrogeosciences in model regions in Asia, Europe, and America, with a focus on the Middle East and Mediterranean region and surrounding areas. This proceedings book is based on the accepted papers for oral/poster presentations at the 2nd Springer Conference of the Arabian Journal of Geosciences (CAJG-2), Tunisia 2019. It offers a broad range of recent studies that discuss the latest advances in geoenvironmental and hydrogeosciences from diverse backgrounds including climate change, geoecology, biogeochemistry, water resources management, and environmental monitoring and asses...
Neural Information Processing
The three volume set LNCS 8226, LNCS 8227 and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.
