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This collection brings together a series of empirical studies on
topics surrounding classrooms of Chinese as a second language (L2)
by drawing on a range of theoretical frameworks, methodological
strategies, and pedagogical perspectives. Over the past two
decades, research on classroom-based second language acquisition
(SLA) has emerged and expanded as one of the most important
sub-domains in the general field of SLA. In Chinese SLA, however,
scarce attention has been devoted to this line of research. With
chapters written by scholars in the field of SLA-many of whom are
experienced in classroom teaching, teacher education, or program
administration in Chinese as a second language-this book helps
disentangle the complicated relationships among linguistic targets,
pedagogical conditions, assessment tools, learner individual
differences, and teacher variables that exist in the so-called
"black-box" classrooms of L2 Chinese.
This collection brings together a series of empirical studies on
topics surrounding classrooms of Chinese as a second language (L2)
by drawing on a range of theoretical frameworks, methodological
strategies, and pedagogical perspectives. Over the past two
decades, research on classroom-based second language acquisition
(SLA) has emerged and expanded as one of the most important
sub-domains in the general field of SLA. In Chinese SLA, however,
scarce attention has been devoted to this line of research. With
chapters written by scholars in the field of SLA-many of whom are
experienced in classroom teaching, teacher education, or program
administration in Chinese as a second language-this book helps
disentangle the complicated relationships among linguistic targets,
pedagogical conditions, assessment tools, learner individual
differences, and teacher variables that exist in the so-called
"black-box" classrooms of L2 Chinese.
This book brings together a collection of high-quality empirical
studies which examine multiple aspects involved in the acquisition,
teaching and assessment of pragmatics in Chinese as a second
language (L2). The studies collectively address some of the most
cutting-edge issues in the field of L2 pragmatics, such as the
acquisition of key pragmatic features, methodological innovations
in pragmatics assessment, individual difference factors and virtual
learning contexts. The majority of the chapters include detailed
descriptions of the instruments used and additional material in the
appendices, making it a truly valuable collection for researchers
and students alike. Furthermore, the publication includes the most
comprehensive, state-of-the-art review of empirical research in L2
Chinese pragmatics published bilingually (in English and Chinese)
between 1995 and 2022, along with a supplemental annotated
bibliography. While the empirical studies all focus on Chinese as
the target language, the issues they address have implications for
L2 pragmatics research in general and this book will appeal to
those interested in the latest developments in the field.
In this book, we present our systematic investigations into
consensus in multi-agent systems. We show the design and analysis
of various types of consensus protocols from a multi-agent
perspective with a focus on min-consensus and its variants. We also
discuss second-order and high-order min-consensus. A very
interesting topic regarding the link between consensus and path
planning is also included. We show that a biased min-consensus
protocol can lead to the path planning phenomenon, which means that
the complexity of shortest path planning can emerge from a
perturbed version of min-consensus protocol, which as a case study
may encourage researchers in the field of distributed control to
rethink the nature of complexity and the distance between control
and intelligence. We also illustrate the design and analysis of
consensus protocols for nonlinear multi-agent systems derived from
an optimal control formulation, which do not require solving a
Hamilton-Jacobi-Bellman (HJB) equation. The book was written in a
self-contained format. For each consensus protocol, the performance
is verified through simulative examples and analyzed via
mathematical derivations, using tools like graph theory and modern
control theory. The book's goal is to provide not only theoretical
contributions but also explore underlying intuitions from a
methodological perspective.
This book discusses methods and algorithms for the near-optimal
adaptive control of nonlinear systems, including the corresponding
theoretical analysis and simulative examples, and presents two
innovative methods for the redundancy resolution of redundant
manipulators with consideration of parameter uncertainty and
periodic disturbances. It also reports on a series of systematic
investigations on a near-optimal adaptive control method based on
the Taylor expansion, neural networks, estimator design approaches,
and the idea of sliding mode control, focusing on the tracking
control problem of nonlinear systems under different scenarios. The
book culminates with a presentation of two new redundancy
resolution methods; one addresses adaptive kinematic control of
redundant manipulators, and the other centers on the effect of
periodic input disturbance on redundancy resolution. Each
self-contained chapter is clearly written, making the book
accessible to graduate students as well as academic and industrial
researchers in the fields of adaptive and optimal control,
robotics, and dynamic neural networks.
Twin and Family Studies of Epigenetics, Volume 27, the latest
release in the Translational Epigenetics series, gathers expert
opinions on epigenetic twin and family study research methods,
recent findings across various disease areas, and future
directions. The book provides in-depth coverage of epigenetics
fundamentals, twin and family epigenetic study design, and the
broader role of epigenetics in answering questions on the
developmental origins of health and disease. Throughout the volume,
twin and family studies are employed to examine causes of
epigenetic variation, the relationship between epigenetic
modifications and mental illness, cancers, cardiovascular disease,
diabetes, obesity, high blood pressure, and more. Emerging research
methods applied in twin and family studies discussed include
imaging epigenetics, exposure-specific DNA methylation changes, and
unravelling time trends in epigenetic effects.
This open access book focuses on robot introspection, which has a
direct impact on physical human-robot interaction and long-term
autonomy, and which can benefit from autonomous anomaly monitoring
and diagnosis, as well as anomaly recovery strategies. In robotics,
the ability to reason, solve their own anomalies and proactively
enrich owned knowledge is a direct way to improve autonomous
behaviors. To this end, the authors start by considering the
underlying pattern of multimodal observation during robot
manipulation, which can effectively be modeled as a parametric
hidden Markov model (HMM). They then adopt a nonparametric Bayesian
approach in defining a prior using the hierarchical Dirichlet
process (HDP) on the standard HMM parameters, known as the
Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The
HDP-HMM can examine an HMM with an unbounded number of possible
states and allows flexibility in the complexity of the learned
model and the development of reliable and scalable variational
inference methods. This book is a valuable reference resource for
researchers and designers in the field of robot learning and
multimodal perception, as well as for senior undergraduate and
graduate university students.
In this book, the authors focus on three aspects related to the
development of articulated agents: presenting an overview of
high-level control algorithms for intelligent decision-making of
articulated agents, experimental study of the properties of soft
agents as the end-effector of articulated agents, and accurate
management of low-level torque-control loop to accurately control
the articulated agents. This book summarizes recent advances
related to articulated agents. The motive behind the book is to
trigger theoretical and practical research studies related to
articulated agents.
This open access book focuses on robot introspection, which has a
direct impact on physical human-robot interaction and long-term
autonomy, and which can benefit from autonomous anomaly monitoring
and diagnosis, as well as anomaly recovery strategies. In robotics,
the ability to reason, solve their own anomalies and proactively
enrich owned knowledge is a direct way to improve autonomous
behaviors. To this end, the authors start by considering the
underlying pattern of multimodal observation during robot
manipulation, which can effectively be modeled as a parametric
hidden Markov model (HMM). They then adopt a nonparametric Bayesian
approach in defining a prior using the hierarchical Dirichlet
process (HDP) on the standard HMM parameters, known as the
Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The
HDP-HMM can examine an HMM with an unbounded number of possible
states and allows flexibility in the complexity of the learned
model and the development of reliable and scalable variational
inference methods. This book is a valuable reference resource for
researchers and designers in the field of robot learning and
multimodal perception, as well as for senior undergraduate and
graduate university students.
This open access book mainly focuses on the safe control of robot
manipulators. The control schemes are mainly developed based on
dynamic neural network, which is an important theoretical branch of
deep reinforcement learning. In order to enhance the safety
performance of robot systems, the control strategies include
adaptive tracking control for robots with model uncertainties,
compliance control in uncertain environments, obstacle avoidance in
dynamic workspace. The idea for this book on solving safe control
of robot arms was conceived during the industrial applications and
the research discussion in the laboratory. Most of the materials in
this book are derived from the authors' papers published in
journals, such as IEEE Transactions on Industrial Electronics,
neurocomputing, etc. This book can be used as a reference book for
researcher and designer of the robotic systems and AI based
controllers, and can also be used as a reference book for senior
undergraduate and graduate students in colleges and universities.
This open access book mainly focuses on the safe control of robot
manipulators. The control schemes are mainly developed based on
dynamic neural network, which is an important theoretical branch of
deep reinforcement learning. In order to enhance the safety
performance of robot systems, the control strategies include
adaptive tracking control for robots with model uncertainties,
compliance control in uncertain environments, obstacle avoidance in
dynamic workspace. The idea for this book on solving safe control
of robot arms was conceived during the industrial applications and
the research discussion in the laboratory. Most of the materials in
this book are derived from the authors' papers published in
journals, such as IEEE Transactions on Industrial Electronics,
neurocomputing, etc. This book can be used as a reference book for
researcher and designer of the robotic systems and AI based
controllers, and can also be used as a reference book for senior
undergraduate and graduate students in colleges and universities.
This is the first book to focus on solving cooperative control
problems of multiple robot arms using different centralized or
distributed neural network models, presenting methods and
algorithms together with the corresponding theoretical analysis and
simulated examples. It is intended for graduate students and
academic and industrial researchers in the field of control,
robotics, neural networks, simulation and modelling.
Web 2.0 technologies, open source software platforms, and mobile
applications have transformed teaching and learning of second and
foreign languages. Language teaching has transitioned from a
teacher-centered approach to a student-centered approach through
the use of Computer-Assisted Language Learning (CALL) and new
teaching approaches. Engaging Language Learners through Technology
Integration: Theory, Applications, and Outcomes provides empirical
studies on theoretical issues and outcomes in regards to the
integration of innovative technology into language teaching and
learning. This reference wok discusses empirical findings and
innovative research using software and applications that engage
learners and promote successful learning, essential tools for
educational researchers, instructional technologists, K-20 language
teachers, faculty in higher education, curriculum specialists, and
researchers.
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