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This book introduces an ethnographic case study of two English majors of ethnic minority at YUN, a local university of nationalities in southwest China. Drawing on the theories of post-structuralism and critical multiculturalism, this book mainly studies two female multilingual individuals in Yunnan, China. By scrutinizing university policies, curriculum, personal learning histories, and by discussing the unequal power relationship between national policies, school curricula, and ethnic multilingual learners,this book provides information at a micro-level on how the two ethnic minority students, who have acquired three languages (L1-native, L2-Mandarin Chinese, and L3-English), successfully navigate the Chinese higher education system as multilingual learners despite various tensions, difficulties, and challenges. How these students construct their multiple identities as well as significant factors affecting such identity construction is also discussed. This book will contribute to the scholarship of policy and practice in ethnic multilingual education in China by addressing the challenges for tertiary institutions and ethnic multilingual learners. The author also points out that multiculturalism as a discourse of education might help ease the tension of being an ethnic minority and a Chinese national, and reduce the danger of being assimilated or being marginalized. .
Education. --- Applied linguistics. --- Language and education. --- Anthropology. --- Language Education. --- Applied Linguistics. --- Minorities --- Multilingualism --- Multicultural education --- Education --- Intercultural education --- Plurilingualism --- Polyglottism --- Culturally relevant pedagogy --- Language and languages --- Language and languages. --- Human beings --- Linguistics --- Foreign languages --- Languages --- Anthropology --- Communication --- Ethnology --- Information theory --- Meaning (Psychology) --- Philology --- Educational linguistics --- Primitive societies --- Social sciences --- Study and teaching. --- Language and languages Study and teaching --- Study and teaching --- Language and education --- Language schools
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Teaching --- Didactics of languages --- Educational sciences --- Ethnology. Cultural anthropology --- Linguistics --- onderwijs --- talenonderwijs --- linguïstiek --- opvoeding --- China
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This book introduces an ethnographic case study of two English majors of ethnic minority at YUN, a local university of nationalities in southwest China. Drawing on the theories of post-structuralism and critical multiculturalism, this book mainly studies two female multilingual individuals in Yunnan, China. By scrutinizing university policies, curriculum, personal learning histories, and by discussing the unequal power relationship between national policies, school curricula, and ethnic multilingual learners,this book provides information at a micro-level on how the two ethnic minority students, who have acquired three languages (L1-native, L2-Mandarin Chinese, and L3-English), successfully navigate the Chinese higher education system as multilingual learners despite various tensions, difficulties, and challenges. How these students construct their multiple identities as well as significant factors affecting such identity construction is also discussed. This book will contribute to the scholarship of policy and practice in ethnic multilingual education in China by addressing the challenges for tertiary institutions and ethnic multilingual learners. The author also points out that multiculturalism as a discourse of education might help ease the tension of being an ethnic minority and a Chinese national, and reduce the danger of being assimilated or being marginalized. .
Teaching --- Didactics of languages --- Educational sciences --- Ethnology. Cultural anthropology --- Linguistics --- onderwijs --- talenonderwijs --- linguïstiek --- opvoeding --- China
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The area of machine learning, especially deep learning, has exploded in recent years, producing advances in everything from speech recognition and gaming to drug discovery. Tomographic imaging is another major area that is being transformed by machine learning, and its potential to revolutionise medical imaging is highly significant. Written by active researchers in the field, Machine Learning for Tomographic Imaging presents a unified overview of deep-learning-based tomographic imaging. Key concepts, including classic reconstruction ideas and human vision inspired insights, are introduced as a foundation for a thorough examination of artificial neural networks and deep tomographic reconstruction. X-ray CT and MRI reconstruction methods are covered in detail, and other medical imaging applications are discussed as well. An engaging and accessible style makes this book an ideal introduction for those in applied disciplines, as well as those in more theoretical disciplines who wish to learn about application contexts. Hands-on projects are also suggested, and links to open source software, working datasets, and network models are included. Part of Series in Physics and Engineering in Medicine and Biology.
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