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This book provides a comparative analysis of shrinking cities in a
broad range of postsocialist countries within the so-called Global
East, a liminal space between North and South. While shrinking
cities have received increased scholarly attention in the past
decades, theoretical, and empirical research has remained
predominantly centered on the Global North. This volume brings to
the fore a range of new perspectives on urban shrinkage,
identifying commonalities, differences, and policy experiences
across a very diverse and vivid region with its various legacies
and contemporary controversial developments. With chapters written
by leading experts in the field, insider views assist in
decolonizing urban theory. Specifically, the book includes chapters
on shrinking cities in China, Russia, and postsocialist Europe,
presenting comparative discussions within countries and
crossnational cases on theoretical and policy implications. The
book will be of interest to students and scholars researching urban
studies, urban geography, urban planning, urban politics and
policy, urban sociology, and urban development.
Mobile crowdsensing is a new sensing paradigm that utilizes the
intelligence of a crowd of individuals to collect data for mobile
purposes by using their portable devices, such as smartphones and
wearable devices. Commonly, individuals are incentivized to collect
data to fulfill a crowdsensing task released by a data requester.
This “sensing as a service” elaborates our knowledge of the
physical world by opening up a new door of data collection and
analysis. However, with the expansion of mobile crowdsensing,
privacy issues urgently need to be solved. In this book, we discuss
the research background and current research process of privacy
protection in mobile crowdsensing. In the first chapter, the
background, system model, and threat model of mobile crowdsensing
are introduced. The second chapter discusses the current techniques
to protect user privacy in mobile crowdsensing. Chapter three
introduces the privacy-preserving content-based task allocation
scheme. Chapter four further introduces the privacy-preserving
location-based task scheme. Chapter five presents the scheme of
privacy-preserving truth discovery with truth transparency. Chapter
six proposes the scheme of privacy-preserving truth discovery with
truth hiding. Chapter seven summarizes this monograph and proposes
future research directions. In summary, this book introduces the
following techniques in mobile crowdsensing: 1) describe a
randomizable matrix-based task-matching method to protect task
privacy and enable secure content-based task allocation; 2)
describe a multi-clouds randomizable matrix-based task-matching
method to protect location privacy and enable secure arbitrary
range queries; and 3) describe privacy-preserving truth discovery
methods to support efficient and secure truth discovery. These
techniques are vital to the rapid development of privacy-preserving
in mobile crowdsensing.
This book investigates in detail large-scale group decision-making
(LSGDM) problem, which has gradually evolved from the traditional
group decision-making problem and has attracted more and more
attention in the age of big data. Pursuing a holistic approach, the
book establishes a fundamental framework for LSGDM with uncertain
and behavioral considerations. To address the behavioral
uncertainty and complexity of large groups of decision-makers, this
book mainly focuses on new solutions of LSGDM problems using the
interval type-2 fuzzy uncertainty theory and social network
analysis techniques, including the exploration of uncertain
clustering analysis, the consideration of social relationships,
especially trust relationships, the construction of consensus
evolution networks, etc. The book is intended for researchers and
postgraduates who are interested in complex group decision-making
in the new media era. Authors also investigate the similar features
between LSGDM problems and group recommendations to study the
applications of LSGDM methods. After reading this book, readers
will have a new understanding of the LSGDM study under the real
complicated context.
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Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
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