Bücher von Lin Liu

Mit der Entwicklung der chinesischen Wirtschaft besteht ein immer größerer Bedarf, die chinesische Schiedsgerichtsbarkeit als ein Streitbeilegungsmittel zu internationalisieren. Die Beiträge zeigen die grundlegenden Rechtsfragen in Bezug auf die chinesische Schiedsgerichtsbarkeit, insbesondere die Rolle des staatlichen Gerichts im Schiedsverfahren, die nicht zu übersehen ist. Die Autorin forscht nicht nur die vielfältigen geltenden Rechtsgrundlagen, sondern auch zahlreiche praktischen Entscheidungen der chinesischen Gerichte. Daher dienen die Beiträge nicht nur dem akademischen Zweck, sondern haben auch eine praktische Relevanz.

This book highlights the fundamental physics of orbit theory, dynamical models, methods of orbit determination, design, measurement, adjustment, and complete calculations for the position, tracking, and prediction of satellites and deep spacecraft. It emphasizes specific methods, related mathematical calculations, and worked examples and exercises. Therefore, technicians and engineers in the aerospace industry can directly apply them to their practical work. Dedicated to undergraduate students and graduate students, researchers, and professionals in astronomy, physics, space science, and related aerospace industries, the book is an integrated work based on the accumulated knowledge in satellite orbit dynamics and the author¿s more than five decades of personal research and teaching experience in astronomy and aerospace dynamics.

Bachelor Thesis from the year 2019 in the subject Engineering - Industrial Engineering and Management, grade: 1,0, Vienna University of Technology, language: English, abstract: The research question of this thesis is: What relevant factors exist that enables humans and robots to collaborate most successfully to ensure optimal process-based workflows?Human-robot collaboration is a fairly new field of research, and for this reason, there has been barely shed light upon this topic up to today. Thus, the purpose of this work is to investigate and analyze which factors have an impact on the collaborative work of humans. Subsequently, based on this analysis of the relevant parameters, implications can be made for human-robot collaborations to ensure optimal work settings to facilitate effective teaming. The development of modern industrial robots is advancing year by year. Currently robots are more precise, faster and more powerful than ever before. However, despite these advancements, it is still unlikely that robots will reach the dexterity and intelligence of humans anytime soon. Therefore, at least for the foreseeable future, humans remain irreplaceable in many assembly operations. Still, this does not imply that humans and robots cannot benefit each other. On the contrary, combining the strengths of each individual creates new opportunities for collaboration and collaborative work.Robots exhibit high precision and repeatability, can handle heavy loads and operate without performance deterioration, even in difficult or dangerous environments. However, robot control systems quickly reach their limits in recognizing and handling unpredictable situations and uncertainties in their environment, which are normally no problem for humans. This is mainly due to the ability of humans to tackle unexpected obstacles, their awareness of a much larger part of the environment than formally declared and lastly humans show more dexterity in complex or sensitive tasks. Despite that humans are more prone to error, stress or fatigue, and their employment underlies strict health and safety regulations.Robots that interact with human beings are called collaborative robots or cobots for short. The goal of this very human-robot collaboration is not to replace the human but rather to create opportunities for humans and robots to work together towards a common aim by mutually increasing the efficiency and effectiveness of their team performance. This, for example, can be achieved by employing robots in sectors where manual labor is predominant.

This brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.

Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book.