Dan Wang (王丹) es un reconocido poeta y exlíder estudiantil del movimiento prodemocrático de China en 1989. Su obra literaria a menudo se nutre de sus experiencias personales con el activismo y la opresión política. La poesía de Wang se caracteriza por profundas reflexiones sobre la pérdida de la libertad, la resiliencia del espíritu humano y la búsqueda de identidad en tiempos turbulentos. Sus escritos resuenan con una poderosa voz personal, ofreciendo una perspectiva única sobre las complejidades de la historia y la sociedad chinas.
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.