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The development of smart cities is one of the most important
challenges over the next few decades. Governments and companies are
leveraging billions of dollars in public and private funds for
smart cities. Next generation smart cities are heavily dependent on
distributed smart sensing systems and devices to monitor the urban
infrastructure. The smart sensor networks serve as autonomous
intelligent nodes to measure a variety of physical or environmental
parameters. They should react in time, establish automated control,
and collect information for intelligent decision-making. In this
context, one of the major tasks is to develop advanced frameworks
for the interpretation of the huge amount of information provided
by the emerging testing and monitoring systems. Data Analytics for
Smart Cities brings together some of the most exciting new
developments in the area of integrating advanced data analytics
systems into smart cities along with complementary technological
paradigms such as cloud computing and Internet of Things (IoT). The
book serves as a reference for researchers and engineers in domains
of advanced computation, optimization, and data mining for smart
civil infrastructure condition assessment, dynamic visualization,
intelligent transportation systems (ITS), cyber-physical systems,
and smart construction technologies. The chapters are presented in
a hands-on manner to facilitate researchers in tackling
applications. Arguably, data analytics technologies play a key role
in tackling the challenge of creating smart cities. Data analytics
applications involve collecting, integrating, and preparing time-
and space-dependent data produced by sensors, complex engineered
systems, and physical assets, followed by developing and testing
analytical models to verify the accuracy of results. This book
covers this multidisciplinary field and examines multiple paradigms
such as machine learning, pattern recognition, statistics,
intelligent databases, knowledge acquisition, data visualization,
high performance computing, and expert systems. The book explores
new territory by discussing the cutting-edge concept of Big Data
analytics for interpreting massive amounts of data in smart city
applications.
Premature cracking in asphalt pavements and overlays continues to
shorten pavement lifecycles and creates significant economic and
environmental burden. In response, RILEM Technical Committee TC
241-MCD on Mechanisms of Cracking and Debonding in Asphalt and
Composite Pavements has conducted a State-of-the-Art Review (STAR),
as detailed in this comprehensive book. Cutting-edge research
performed by RILEM members and their international partners is
presented, along with summaries of open research questions and
recommendations for future research. This book is organized
according to the theme areas of TC 241-MCD - i.e., fracture in the
asphalt bulk material, interface debonding behaviour, and advanced
measurement systems. This STAR is expected to serve as a long term
reference for researchers and practitioners, as it contributes to a
deeper fundamental understanding of the mechanisms behind cracking
and debonding in asphalt concrete and composite pavement systems.
Premature cracking in asphalt pavements and overlays continues to
shorten pavement lifecycles and creates significant economic and
environmental burden. In response, RILEM Technical Committee TC
241-MCD on Mechanisms of Cracking and Debonding in Asphalt and
Composite Pavements has conducted a State-of-the-Art Review (STAR),
as detailed in this comprehensive book. Cutting-edge research
performed by RILEM members and their international partners is
presented, along with summaries of open research questions and
recommendations for future research. This book is organized
according to the theme areas of TC 241-MCD - i.e., fracture in the
asphalt bulk material, interface debonding behaviour, and advanced
measurement systems. This STAR is expected to serve as a long term
reference for researchers and practitioners, as it contributes to a
deeper fundamental understanding of the mechanisms behind cracking
and debonding in asphalt concrete and composite pavement systems.
This book presents the latest advances in research to analyze
mechanical damage and its detection in multilayer systems. The
contents are linked to the Rilem TC241 - MCD scientific activities
and the proceedings of the 8th RILEM International Conference on
Mechanisms of Cracking and Debonding in Pavements (MCD2016).
MCD2016 was hosted by Ifsttar and took place in Nantes, France, on
June 7-9, 2016. In their lifetime, pavements undergo degradation
due to different mechanisms of which cracking is among the most
important ones. The damage and the fracture behavior of all its
material layers as well as interfaces must be understood. In that
field, the research activities aims to develop a deeper fundamental
understanding of the mechanisms responsible for cracking and
debonding in asphalt concrete and composite (e.g. asphalt overlays
placed on PCC or thin cement concrete overlay placed on asphalt
layer) pavement systems.
This book presents the latest advances in research to analyze
mechanical damage and its detection in multilayer systems. The
contents are linked to the Rilem TC241 - MCD scientific activities
and the proceedings of the 8th RILEM International Conference on
Mechanisms of Cracking and Debonding in Pavements (MCD2016).
MCD2016 was hosted by Ifsttar and took place in Nantes, France, on
June 7-9, 2016. In their lifetime, pavements undergo degradation
due to different mechanisms of which cracking is among the most
important ones. The damage and the fracture behavior of all its
material layers as well as interfaces must be understood. In that
field, the research activities aims to develop a deeper fundamental
understanding of the mechanisms responsible for cracking and
debonding in asphalt concrete and composite (e.g. asphalt overlays
placed on PCC or thin cement concrete overlay placed on asphalt
layer) pavement systems.
The development of smart cities is one of the most important
challenges over the next few decades. Governments and companies are
leveraging billions of dollars in public and private funds for
smart cities. Next generation smart cities are heavily dependent on
distributed smart sensing systems and devices to monitor the urban
infrastructure. The smart sensor networks serve as autonomous
intelligent nodes to measure a variety of physical or environmental
parameters. They should react in time, establish automated control,
and collect information for intelligent decision-making. In this
context, one of the major tasks is to develop advanced frameworks
for the interpretation of the huge amount of information provided
by the emerging testing and monitoring systems. Data Analytics for
Smart Cities brings together some of the most exciting new
developments in the area of integrating advanced data analytics
systems into smart cities along with complementary technological
paradigms such as cloud computing and Internet of Things (IoT). The
book serves as a reference for researchers and engineers in domains
of advanced computation, optimization, and data mining for smart
civil infrastructure condition assessment, dynamic visualization,
intelligent transportation systems (ITS), cyber-physical systems,
and smart construction technologies. The chapters are presented in
a hands-on manner to facilitate researchers in tackling
applications. Arguably, data analytics technologies play a key role
in tackling the challenge of creating smart cities. Data analytics
applications involve collecting, integrating, and preparing time-
and space-dependent data produced by sensors, complex engineered
systems, and physical assets, followed by developing and testing
analytical models to verify the accuracy of results. This book
covers this multidisciplinary field and examines multiple paradigms
such as machine learning, pattern recognition, statistics,
intelligent databases, knowledge acquisition, data visualization,
high performance computing, and expert systems. The book explores
new territory by discussing the cutting-edge concept of Big Data
analytics for interpreting massive amounts of data in smart city
applications.
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