Search results for ""Author Jun Xu""

The Roots & Soul of the Chinese People is a brave and ambitious attempt by author Mr Xu Jun to connect the dots between the 'socialist core values' drawing on Marxism espoused and promoted by the Communist Party of China (CPC) today with China's long cultural heritage - including Confucianism, Taoism, Buddhism, Mohism, Legalism and numerous other -isms - dating all the way back to the Spring and Autumn and Warring States periods and to the pre-historic mythological times of the Yellow Emperor and the Yan Emperor. So, in addition to a lot of information about China's history, culture and traditions, Roots & Soul touches on what Chinese consider to be some of the best of the rest of the world's great civilisations, including sections of chapters on the Mesopotamians, the Egyptians and India. Mr Xu is a Han Chinese born in 1958 who hails from Chengmai county, Hainan island (which is today a province in its own right after being spun off from Guangdong province in 1988). With an educational background in research at the central party school and currently serving as deputy director of the National People's Congress standing committee, Mr Xu's is very much a senior insider's view of how China's modern socialist path is linked to the illustrious past of China's long historical line of cultural traditions. With lots of references linking the threads running through current President Xi Jinping's modern-day speeches to China's past cultural traditions, the book presents plenty of food for thought about the relevance of the socialist path China has chosen to follow as well as the need for Chinese people not to forget where they have come from, not to worship everything modern and/or foreign and, above all, not to denigrate all of the Chinese traditions that have been passed down from generation to generation.

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Network Algorithmics: An Interdisciplinary Approach to Designing Fast Networked Devices, Second Edition takes an interdisciplinary approach to applying principles for efficient implementation of network devices, offering solutions to the problem of network implementation bottlenecks. In designing a network device, there are dozens of decisions that affect the speed with which it will perform – sometimes for better, but sometimes for worse. The book provides a complete and coherent methodology for maximizing speed while meeting network design goals. The book is uniquely focused on the seamless integration of data structures, algorithms, operating systems and hardware/software co-designs for high-performance routers/switches and network end systems. Thoroughly updated based on courses taught by the authors over the past decade, the book lays out the bottlenecks most often encountered at four disparate levels of implementation: protocol, OS, hardware and architecture. It then develops fifteen principles key to breaking these bottlenecks, systematically applying them to bottlenecks found in end-nodes, interconnect devices and specialty functions located along the network. Later sections discuss the inherent challenges of modern cloud computing and data center networking.

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Estimate and Interpret Results from Ordered Regression ModelsOrdered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption.The authors first introduce the three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R.This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable.Web ResourceMore detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.

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