Di Wu – författare

Against the background of China's rapidly growing, and sometimes highly controversial, activities in Africa, this book is among the first of its kind to systematically document Sino-African interactions at the everyday level. Based on sixteen months of ethnographic fieldwork at two contrasting sites in Lusaka, Zambia—a Chinese state-sponsored educational farm and a private Chinese family farm—Di Wu focuses on daily interactions among Chinese migrants and their Zambian hosts. Daily communicative events, e.g. banquets, market negotiations, work-place disputes, and various social encounters across a range of settings are used to trace the essential role that emotion/affect plays in forming and reproducing social relations and group identities among Chinese migrants. Wu suggests that affective encounters in everyday situations—as well as failed attempts to generate affect—should not be overlooked in order to fully appreciate Sino-African interactions.Deeply researched and with rich ethnographic detail, this book will be relevant to scholars of anthropology, international development, and others interested in Sino-African relations.

Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.

Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You’ll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You’ll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI into your learning toolkit, using it for feedback, practice exercises, code reviews, and exploring advanced topics. Recommended AI prompts can help you identify areas for improvement, review key concepts, and track your progress.This book is designed for absolute beginners with no prior programming experience. It is ideal for individuals with busy schedules or limited time for studying.

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You’ll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You’ll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI into your learning toolkit, using it for feedback, practice exercises, code reviews, and exploring advanced topics. Recommended AI prompts can help you identify areas for improvement, review key concepts, and track your progress.This book is designed for absolute beginners with no prior programming experience. It is ideal for individuals with busy schedules or limited time for studying.

This book is designed for intermediate learners with a basic understanding of Python. Python programming is broken down here into easily digestible lessons of less than 5 minutes each, following a tried and tested BiteSize approach.

This book is designed for intermediate learners with a basic understanding of Python. Python programming is broken down here into easily digestible lessons of less than 5 minutes each, following a tried and tested BiteSize approach.

Against the background of China's rapidly growing, and sometimes highly controversial, activities in Africa, this book is among the first of its kind to systematically document Sino-African interactions at the everyday level. Based on sixteen months of ethnographic fieldwork at two contrasting sites in Lusaka, Zambia—a Chinese state-sponsored educational farm and a private Chinese family farm—Di Wu focuses on daily interactions among Chinese migrants and their Zambian hosts. Daily communicative events, e.g. banquets, market negotiations, work-place disputes, and various social encounters across a range of settings are used to trace the essential role that emotion/affect plays in forming and reproducing social relations and group identities among Chinese migrants. Wu suggests that affective encounters in everyday situations—as well as failed attempts to generate affect—should not be overlooked in order to fully appreciate Sino-African interactions.Deeply researched and with rich ethnographic detail, this book will be relevant to scholars of anthropology, international development, and others interested in Sino-African relations.

Decades-old calls to recognise China’s significance for anthropological theory and the social sciences are more urgent than ever. Yet, Chinese-grounded ideas remain marginal, with China often seen as an ‘Other’ rather than a source of widely applicable theory. Drawing on East Asian postcolonial scholarship, this volume argues that without taking China seriously as a knowledge producer and a key agent in a post-global world, social scientists risk misinterpreting the global present. As Western globalisation wanes and anthropology reassesses the relationship between ethnography and theory, we show how ‘China’ must be understood as an ordinary, integral context for research worldwide.

The 1st edition of the textbook Biological Wastewater Treatment: Principles, Modelling and Design was published in 2008 and it went on to become IWA Publishing's bestseller to date. In 2020, the 2nd updated and extended edition of the textbook was published because, since 2008, the knowledge and understanding of wastewater treatment had advanced extensively and moved further away from empirically-based approaches to a fundamental first-principles approach based on chemistry, microbiology, physical and bioprocess engineering, mathematics and modelling. The updated edition has already been available for more than two years and the feedback from readers has been overwhelming - the textbook won the IWA Publishing Best Scientific Book Prize in 2022. This inspired the authors to embark on a new challenge - to prepare this complementary book Biological Wastewater Treatment: Examples and Exercises. This new book is an extension of the 2nd edition textbook; each chapter corresponds to a chapter in the textbook and is structured similarly around five sections, namely, Introduction, Learning objectives, Examples, and Exercises, with solutions provided in an annex. The overall objective of the book is to deepen, expand and test the knowledge of the reader through a set of worked out examples, followed up by exercises and questions with provided answers. Where applicable, the book is supplemented with MS Office Excel files. The book is open access and can be downloaded (together with supplements) at the publisher's website. The target readership of the book remains young water professionals, who will still be active in the field of protecting our precious water resources long after the aging professors who are leading some of these advances have retired. The authors are aware that cleaning dirty water has become more complex but also that it is even more urgent now than before, and offer this new book to help young water professionals engage with the scientific and bioprocess engineering principles of wastewater treatment science and technology with deeper insight, advanced knowledge and greater confidence built on stronger competence.

This book aims to understand public diplomacy by examining its practice. It refers to the process of translating a public diplomacy policy goal—the specific order given to a governmental institution in order to achieve a general foreign policy objective—into public diplomacy practices and impact.

This book aims to understand public diplomacy by examining its practice. In particular, it focuses on the implementation of educational and exchange programs by the US Departments of State and Defense toward China. Implementation is the focal point of this study and is utilized both as a practical process and a methodology. It refers to the process of translating a public diplomacy policy goal—the specific order given to a governmental institution in order to achieve a general foreign policy objective—into public diplomacy practices and impact. In addition, it refers to a research method that centers implementation and accepts the prerequisite of discretion from studies of policy implementation. This book maps out where and by whom implementation discretion is exercised in public diplomacy. It argues that public diplomacy is in the eye of the beholder, and that its meanings can vary significantly according to different actors.

Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty.In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learningusing L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.

This book introduces recent development of technologies for mine waste management in China. The technology of consolidated tailings stockpile (CTS) that disposes tailings above-ground is introduced, and the application of this technology is also demonstrated.

This book introduces recent development of technologies for mine waste management in China. The technology of consolidated tailings stockpile (CTS) that disposes tailings above-ground is introduced, and the application of this technology is also demonstrated.

This book presents 28 practical case studies in detail and 49 case studies in brief. The collection of these case studies focuses on one or more aspects of exploration and practice on the following topics: smart campus and smart classroom, resource construction and sharing, new teaching mode, comprehensive quality evaluation of students, teacher professional development, application of teaching platform and tool, innovative application of online learning space, collaborative education, and school management and services. The selection and evaluation criteria of the case studies on school practice mainly include concept and implementation, effectiveness and characteristics, innovation and demonstration, and expression and structure. This book helps readers gain a rich understanding of the diverse innovative implementation of smart education in Chinese schools and inspires smart education development in schools in other countries.

This book presents 28 practical case studies in detail and 49 case studies in brief. The collection of these case studies focuses on one or more aspects of exploration and practice on the following topics: smart campus and smart classroom, resource construction and sharing, new teaching mode, comprehensive quality evaluation of students, teacher professional development, application of teaching platform and tool, innovative application of online learning space, collaborative education, and school management and services. The selection and evaluation criteria of the case studies on school practice mainly include concept and implementation, effectiveness and characteristics, innovation and demonstration, and expression and structure. This book helps readers gain a rich understanding of the diverse innovative implementation of smart education in Chinese schools and inspires smart education development in schools in other countries.