Dan Wang (王丹) is een gerenommeerd dichter en voormalig studentenleider van de pro-democratische beweging in China in 1989. Zijn literaire werk put vaak uit zijn persoonlijke ervaringen met activisme en politieke onderdrukking. Wangs poëzie wordt gekenmerkt door diepe reflecties op het verlies van vrijheid, de veerkracht van de menselijke geest en de zoektocht naar identiteit in turbulente tijden. Zijn geschriften resoneren met een krachtige persoonlijke stem en bieden een uniek perspectief op de complexiteit van de Chinese geschiedenis en maatschappij.
The book provides an in-depth ethnographic exploration of teachers in a rural Chinese school, highlighting their aspirations, challenges, and daily experiences. Through a compelling narrative, it uncovers the systemic issues affecting education in the region and examines the broader moral crisis emerging in Chinese society following years of capitalist reform. This insightful account sheds light on the complex interplay between individual struggles and societal changes.
Specially designed for young adult and adult learners, this four-level beginner Mandarin Chinese course employs a communicative approach to language learning. The Workbook extends and reinforces the material learnt in the Student's Book with a variety of speaking and listening activities to help students become confident Chinese language speakers.
Specially designed for young adult and adult learners, this four-level beginner Mandarin Chinese course employs a communicative approach to language learning. The Workbook extends and reinforces the material learnt in the Student's Book with a variety of speaking and listening activities to help students become confident Chinese language speakers.
The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities.