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This is an open access book. 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023), will be held on December 29–31, 2023 in Sanya, China. ICAESEE 2023 is to bring together innovative academics and industrial experts in the field of energy resources and environment engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in energy resources and environment engineering and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in energy resources and environment engineering and related areas.

This book is intended to show the great achievements and valuable experience of Chinese public health practices and epidemiological theories and methods. It is conducive to expanding medical workers'practical ability of disease prevention and control, and to bridging the gap between clinical medicine and public health.In part 1, it introduces the progress in epidemiology of 10 infectious diseases. In part 2, it covers 11 non-communicable diseases. The research method and prediction modelling and public health ethics are discussed in the 11 chapters of part 3. The contributors include epidemiologists and public health experts, as well as more clinicians, mathematicians, sociologists, philosophers (ethicists), bioinformatics and so on. Among them, there are not only professors from universities, but also researchers from scientific research institutes, and experts in the front line of disease prevention and control.

Question answering (QA) systems on the Web try to provide crisp answers to information needs posed in natural language, replacing the traditional ranked list of documents. QA, posing a multitude of research challenges, has emerged as one of the most actively investigated topics in information retrieval, natural language processing, and the artificial intelligence communities today. The flip side of such diverse and active interest is that publications are highly fragmented across several venues in the above communities, making it very difficult for new entrants to the field to get a good overview of the topic. Through this book, we make an attempt towards mitigating the above problem by providing an overview of the state-of-the-art in question answering. We cover the twin paradigms of curated Web sources used in QA tasks ‒ trusted text collections like Wikipedia, and objective information distilled into large-scale knowledge bases. We discuss distinct methodologies that have been applied to solve the QA problem in both these paradigms, using instantiations of recent systems for illustration. We begin with an overview of the problem setup and evaluation, cover notable sub-topics like open-domain, multi-hop, and conversational QA in depth, and conclude with key insights and emerging topics. We believe that this resource is a valuable contribution towards a unified view on QA, helping graduate students and researchers planning to work on this topic in the near future.

Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.

Advances in Energy, Environment and Chemical Engineering collects papers resulting from the conference on Energy, Environment and Chemical Engineering (AEECE 2022), Dali, China, 24-26 June, 2022. The primary goal is to promote research and developmental activities in energy technology, environment engineering and chemical engineering. Moreover, it aims to promote scientific information interchange between scholars from the top universities, business associations, research centers and high-tech enterprises working all around the world.The conference conducts in-depth exchanges and discussions on relevant topics such as energy engineering, environment technology and advanced chemical technology, aiming to provide an academic and technical communication platform for scholars and engineers engaged in scientific research and engineering practice in the field of saving technologies, environmental chemistry, clean production and so on. By sharing the research status of scientific research achievements and cutting-edge technologies, it helps scholars and engineers all over the world comprehend the academic development trend and broaden research ideas. So as to strengthen international academic research, academic topics exchange and discussion, and promote the industrialization cooperation of academic achievements.

This book is a compilation of selected papers from the 10th International Field Exploration and Development Conference (IFEDC 2020). The proceedings focuses on Reservoir Surveillance and Management, Reservoir Evaluation and Dynamic Description, Reservoir Production Stimulation and EOR, Ultra-Tight Reservoir, Unconventional Oil and Gas Resources Technology, Oil and Gas Well Production Testing, Geomechanics.The conference not only provides a platform to exchanges experience, but also promotes the development of scientific research in oil & gas exploration and production. The main audience for the work includes reservoir engineer, geological engineer, enterprise managers senior engineers as well as professional students.

This book addresses key aspects of recent developments in applied mathematical analysis and its use. It also highlights a broad range of applications from science, engineering, technology and social perspectives. Each chapter investigates selected research problems and presents a balanced mix of theory, methods and applications for the chosen topics. Special emphasis is placed on presenting basic developments in applied mathematical analysis, and on highlighting the latest advances in this research area. The book is presented in a self-contained manner as far as possible, and includes sufficient references to allow the interested reader to pursue further research in this still-developing field. The primary audience for this book includes graduate students, researchers and educators; however, it will also be useful for general readers with an interest in recent developments in applied mathematical analysis and applications.

Der Autor hat sich eines Themas angenommen, welches in Deutschland viel diskutiert, aber in China noch neu ist. Er geht in seiner rechtsvergleichenden Untersuchung der Frage nach, wie das Doppelspielproblem des Besitzmittlers beim gutgläubigen Erwerb zu behandeln ist. In Deutschland haben das Reichsgericht und der Bundesgerichtshof schon anlässlich der Lagerfälle und des Fräsmaschinenfalls Entscheidungen getroffen. In China finden ähnliche Fälle noch keine hinreichende Beachtung.

The 2016 International Conference on Energy, Environment and Materials Science (EEMS 2016) took place on July 29-31, 2016 in Singapore. EEMS 2016 has been a meeting place for innovative academics and industrial experts in the field of energy and environment research. The primary goal of the conference is to promote research and developmental activities in energy and environment research and further to promote scientific information exchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be organized every year making it an ideal platform for people to share views and experiences in energy, environment and materials science and related areas.

Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction toDynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.

This proceedings volume contains selected papers presented at the 2014 International Conference on Energy, Environment and Green Building Materials, held in Guilin-Guangxi, China. Contributions cover the latest developments and advances in the field of Energy, Environment and Green Building Materials.

Selected, peer reviewed papers from the International Conference on Materials Science and Manufacturing (ICMSM 2012), December 14-16, 2012, Zhangjia Jie, China

Most Americans today are aware that jobs are being outsourced to China, India, and other nations at an alarming rate. From factory jobs to white-collar, high-tech positions, the exporting of labor is one of the most controversial issues in America.Yet few people know much about the other end — about the people who are actually working these jobs and how their own lives have been throw into tumult by these new economic forces. Andrew Ross spent a year in China, interviewing local employees and their managers in Taiwan, Shanghai, and the far western provinces. In this engaging and informative book, he shows how the Chinese workforce has inherited many of the same worries as American workers, such as job instability, long hours, and awareness of their own expendability. He reports on the daily reality of corporate free trade and explores the growing competition between China and India. This is an eye-opening exploration of an unseen side of our globalized world.