Dan Chen

Explains why and how local critical reporting can exist in China despite the kinds of media control that are the hallmarks of authoritarian rule.Why and how does critical reporting persist at the local level in China despite state media control, a hallmark of authoritarian rule? Synthesizing ethnographic observation, interviews, survey and content analysis data, Convenient Criticism reveals evolving dynamics in local governance and the state-media relationship. Local critical reporting, though limited in scope, occurs because local leaders, motivated by political career advancement, use media criticism strategically to increase bureaucratic control, address citizen grievances, and improve governance. This new approach to governance enables the shaping of public opinion while, at the same time, disciplining subordinate bureaucrats. In this way, the party-state not only monopolizes propaganda but also expropriates criticism, which expands the notion of media control from the suppression of journalism to its manipulation. One positive consequence of these practices has been to invigorate television journalists' unique brand of advocacy journalism.

Explains why and how local critical reporting can exist in China despite the kinds of media control that are the hallmarks of authoritarian rule.Why and how does critical reporting persist at the local level in China despite state media control, a hallmark of authoritarian rule? Synthesizing ethnographic observation, interviews, survey and content analysis data, Convenient Criticism reveals evolving dynamics in local governance and the state-media relationship. Local critical reporting, though limited in scope, occurs because local leaders, motivated by political career advancement, use media criticism strategically to increase bureaucratic control, address citizen grievances, and improve governance. This new approach to governance enables the shaping of public opinion while, at the same time, disciplining subordinate bureaucrats. In this way, the party-state not only monopolizes propaganda but also expropriates criticism, which expands the notion of media control from the suppression of journalism to its manipulation. One positive consequence of these practices has been to invigorate television journalists' unique brand of advocacy journalism.

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors’ papers in top-tier, peer-reviewed, scientific conference proceedings and journals.The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms—such as simulation cloning methods and algorithms—that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.

In this book, the authors discuss the biophysical characteristics of Dendritic cells (DCs) at various differentiation stages and in tumor microenvironments in detail. A type of Chinese traditional herb, which can improve the biophysical and microrheological properties of DCs, is also introduced. DCs are potent and specialized antigen-presenting cells that play a crucial role in initiating and amplifying both the innate and adaptive immune responses. The biophysical and microrheological characteristics of DCs are important for their motility and normal immune function. In tumor microenvironments, the motility and immune functions of DCs are impaired, but the mechanisms are largely unknown. This book offers researchers a comprehensive and deep insight into the biophysical characteristics of DCs and may also help to improve the efficiency of anti-tumor therapy based on DCs.

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors’ papers in top-tier, peer-reviewed, scientific conference proceedings and journals.The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms—such as simulation cloning methods and algorithms—that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.