Jun Yu – författare

Financial econometrics brings financial theory and econometric methods together with the power of data to advance understanding of the global financial universe upon which all modern economies depend. Financial Econometric Modeling is an introductory text that meets the learning challenge of integrating theory, measurement, data, and software to understand the modern world of finance. Empirical applications with financial data play a central position in this book's exposition. Each chapter is a how-to guide that takes readers from ideas and theories through to the practical realities of modeling, interpreting, and forecasting financial data. The book reaches out to a wide audience of students, applied researchers, and industry practitioners, guiding readers of diverse backgrounds on the models, methods, and empirical practice of modern financial econometrics.Financial Econometric Modeling delivers a self-contained first course in financial econometrics, providing foundational ideas from financial theory and relevant econometric technique. From this foundation, the book covers a vast arena of modern financial econometrics that opens up empirical applications with data of the many different types that are now generated in financial markets. Every chapter follows the same principle ensuring that all results reported in the book may be reproduced using standard econometric software packages such as Stata or EViews, with a full set of data and programs provided to ensure easy implementation.

In today’s world, where intelligent technologies are deeply transforming human-computer interaction and virtual reality, multi-modal human modeling, analysis and synthesis have become central topics in computer vision. As application scenarios grow increasingly complex, new technologies continue to emerge to address these challenges. These techniques demand systematic summarization and practical guidance.To meet this need, Multi-Modal Human Modeling, Analysis and Synthesis aims to adopt a structured perspective, building a comprehensive technical framework for multi-modal human modeling, analysis and synthesis—progressing from local details to holistic perspectives, and from face features to body dynamics.This book begins by examining the anatomy structures and characteristics of human faces and bodies, then analyzes how traditional methods and deep learning approaches provide robust optimization solutions for modeling. For example, it explores how to address challenges in face recognition caused by lighting changes, occlusions, face expressions and aging, as well as methods for body localization, reconstruction, recognition and anomaly detection in multi-modal scenarios. It also explains how multi-modal data can drive realistic face and body synthesis. A standout feature is its focus on Huawei’s MindSpore framework, bridging the gap between algorithms and engineering through practical case studies. From building face detection and recognition pipelines with the MindSpore toolkit to accelerating model training via automatic parallel computing, and solving large language model (LLM) training challenges, each step is supported by reproducible code and design logic.Designed for researchers and engineers in computer vision and AI, this book balances theoretical foundations with industry-ready technical details. Whether you aim to enhance the reliability of biometric recognition, explore creative possibilities in virtual-real interactions or optimize the deployment of deep learning frameworks, this guide serves as an essential link between academic advancements and real-world applications.

The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations

The papers are organized in topical sections on Internet of Things (IoT), antenna, microwave and cellular communication, wireless communications and networking, network and information security, communication QoS, reliability and modeling, pattern recognition and image signal processing, and information processing.

The papers are organized in topical sections on Internet of Things (IoT), antenna, microwave and cellular communication, wireless communications and networking, network and information security, communication QoS, reliability and modeling, pattern recognition and image signal processing, and information processing.

This proceedings constitutes the refereed proceedings of the 15th EAI International Conference on Communications and Networking, ChinaCom 2020, held in November 2020 in Shanghai, China. The papers are organized in topical sections on Transmission Optimization in Edge Computing; Performance and Scheduling Optimization in Edge Computing;

This proceedings constitutes the refereed proceedings of the 16th International Conference on Communications and Networking, ChinaCom 2021, held in November 2021. The papers are organized in topical sections on Scheduling and Transmission Optimization in Edge Computing; Edge Computing and Deep Learning;

This volume covers a state-of-the-art illustration of recent discoveries concerning obesity-related fatty liver diseases and liver cancer. The contents are extensive and comprehensive. It brings important topics in the field all together under one umbrella, from epidemiology and etiology, molecular pathogenesis, cellular biology, epigenetics, immunology, microbiology, animal models to therapeutic approaches and treatments. All the book contributors are leading experts in the field. It will appeal to researchers, clinicians and graduate students in obesity, fatty liver diseases, GI/Liver cancer field. It may also yield benefits for pharmaceutical companies with regard to drug discovery.

This volume covers a state-of-the-art illustration of recent discoveries concerning obesity-related fatty liver diseases and liver cancer. It will appeal to researchers, clinicians and graduate students in obesity, fatty liver diseases, GI/Liver cancer field.

This book covers state-of-the-art topics covering evidences indicate that the gut microbiota can be harnessed for cancer prevention as well as to modulate the efficacy of chemotherapy and immunotherapy.

This book covers state-of-the-art topics covering evidences indicate that the gut microbiota can be harnessed for cancer prevention as well as to modulate the efficacy of chemotherapy and immunotherapy.

Inflammation and cancer are two major disorders that cause huge concerns in our society. However, what one may not know is that both diseases are closely associated and, in particular, both occur in the gastrointestinal tract and liver. This book describes the mechanics of how inflammation can progress to cancer in these organs. The authors in this book comprehensively discuss the different biomarkers for early diagnosis, and current therapeutic treatments for these diseases. All of these would allow us to better understand the pathogenesis of both diseases. As such, this book provides comprehensive information concerning the interrelationship between inflammation and cancer in a cohesive manner, and the information derived would benefit not only basic scientists but also clinicians who are working in these fields.

The aim of this book series is to familiarize scientists, students and the general public with exciting new discoveries and developments in rice genomics. Leading scientists in rice genomics and related fields are invited to write articles in a cohesive format that appeals to both researchers and laypersons with an interest in genomics and biotechnology. The first volume provides the background information and highlights the major achievements in rice genomics; ongoing developments in this exciting field are also discussed. This volume promotes genomics as a holistic approach to rice research and genetic engineering. The chief editor of the series is Prof Huanming Yang of the Beijing Genomics Institute. As one of the most distinguished scientists in rice research today, Prof Yang led a team of researchers who successfully sequenced and analyzed the draft sequence of the indica rice subspecies. In Vol 1 of the series, he co-authors an article entitled “An International Campaign for Agricultural and Livestock Genomics”.