Dan Wang (王丹) è un affermato poeta ed ex leader studentesco del movimento pro-democrazia cinese del 1989. La sua opera letteraria attinge spesso dalle sue esperienze personali con l'attivismo e l'oppressione politica. La poesia di Wang è caratterizzata da profonde riflessioni sulla perdita della libertà, sulla resilienza dello spirito umano e sulla ricerca dell'identità in tempi turbolenti. I suoi scritti risuonano con una potente voce personale, offrendo una prospettiva unica sulle complessità della storia e della società cinese.
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.