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Comprehensive resource on design of power electronics converters
for three-phase AC applications Design of Three-phase AC Power
Electronics Converters contains a systematic discussion of the
three-phase AC converter design considering various converter
electrical, thermal, and mechanical subsystems and functions. .
Focusing on establishing converter components and subsystems models
needed for the design, the text demonstrates example designs for
these subsystems and for whole three-phase AC converters
considering interactions among subsystems. The design methods apply
to different applications and topologies. The text consists of four
parts. Part I is an introduction, which presents the basics of the
three-phase AC converter, its design, and the goal and organization
of the book. Part II focuses on characteristics and models
important to the converter design for components commonly used in
three-phase AC converters. Part III is on the design of subsystems,
including passive rectifiers, inverters and active rectifiers,
electromagnetic interference (EMI) filters, thermal management
system, control and auxiliaries, mechanical system, and application
considerations. Part IV is on design optimization, which presents
methodology to achieve optimal design results for three-phase AC
converters. Specific sample topics covered in Design of Three-phase
AC Power Electronics Converters include: Models and characteristics
for devices most commonly used in three-phase converters, including
conventional Si devices , and emerging SiC and GaN devices. Models
and selection of various capacitors; characteristics and design of
magnetics using different types of magnetic cores, with a focus on
inductors Optimal three-phase AC converter design including design
and selection of devices, AC line inductors, DC bus capacitors, EMI
filters, heatsinks, and control. The design considers both steady
state and transient conditions Load and source impact converter
design, such as motors and grid condition impacts. For researchers
and graduate students in power electronics, along with practicing
engineers working in the area of three-phase AC converters, Design
of Three-phase AC Power Electronics Converters serves as an
essential resource for the subject and may be used as a textbook or
industry reference.
Fashion trends may be ever-evolving, but the art of dressing up is
a timeless affair. From investing wisely in flattering pieces that
transcend the seasons to accentuating one's personality with the
right accessories, curating the perfect wardrobe can be a lifelong
quest worth pursuing for those who enjoy expressing themselves in
style. Drawing from his years of experience honed through
commissions for iconic brands around the world, Mr. SLOWBOY
presents his portraits of the modern gentleman in a variety of
delightful illustrations that inspire with their sense of
individuality and effortlessness. His book includes quintessential
tips for assembling a coveted closet and a sneak peek into his
creative background to appeal to both sartorialists and artists
alike.
This book constitutes the refereed proceedings of the Second CCF
Internet Conference of China, ICoC 2013, held in Zhangjiajie,
China, in July 2013. The 24 revised full papers presented were
carefully reviewed and selected from 63 submissions. The papers
address issues such as future Internet architecture, Internet
routing, network security, network management, data center
networks, green networks, wireless networks, P2P networks, mobile
Internet and the Internet of Things.
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Machine Learning in Medical Imaging - 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings (Paperback, 2013 ed.)
Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 4th
International Workshop on Machine Learning in Medical Imaging, MLMI
2013, held in conjunction with the International Conference on
Medical Image Computing and Computer Assisted Intervention, MICCAI
2013, in Nagoya, Japan, in September 2013. The 32 contributions
included in this volume were carefully reviewed and selected from
57 submissions. They focus on major trends and challenges in the
area of machine learning in medical imaging and aim to identify new
cutting-edge techniques and their use in medical imaging.
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Machine Learning in Medical Imaging - Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011, Proceedings (Paperback)
Kenji Suzuki, Fei Wang, Dinggang Shen, Pingkun Yan
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R1,585
Discovery Miles 15 850
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the Second
International Workshop on Machine Learning in Medical Imaging, MLMI
2011, held in conjunction with MICCAI 2011, in Toronto, Canada, in
September 2011. The 44 revised full papers presented were carefully
reviewed and selected from 74 submissions. The papers focus on
major trends in machine learning in medical imaging aiming to
identify new cutting-edge techniques and their use in medical
imaging.
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Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings (Paperback, Edition.)
Fei Wang, Pingkun Yan, Kenji Suzuki, Dinggang Shen
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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The first International Workshop on Machine Learning in Medical
Imaging, MLMI 2010, was held at the China National Convention
Center, Beijing, China on Sept- ber 20, 2010 in conjunction with
the International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI) 2010. Machine learning
plays an essential role in the medical imaging field, including
image segmentation, image registration, computer-aided diagnosis,
image fusion, ima- guided therapy, image annotation, and image
database retrieval. With advances in me- cal imaging, new imaging
modalities, and methodologies such as cone-beam/multi-slice CT, 3D
Ultrasound, tomosynthesis, diffusion-weighted MRI, electrical
impedance to- graphy, and diffuse optical tomography, new
machine-learning algorithms/applications are demanded in the
medical imaging field. Single-sample evidence provided by the
patient's imaging data is often not sufficient to provide
satisfactory performance; the- fore tasks in medical imaging
require learning from examples to simulate a physician's prior
knowledge of the data. The MLMI 2010 is the first workshop on this
topic. The workshop focuses on major trends and challenges in this
area, and works to identify new techniques and their use in medical
imaging. Our goal is to help advance the scientific research within
the broad field of medical imaging and machine learning. The range
and level of submission for this year's meeting was of very high
quality. Authors were asked to submit full-length papers for
review. A total of 38 papers were submitted to the workshop in
response to the call for papers.
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Medical Content-Based Retrieval for Clinical Decision Support - First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers (Paperback, Edition.)
Henning Muller, Tanveer Syeda-Mahmood, James Duncan, Fei Wang, Jayashree Kalpathy-Cramer
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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We are pleased to present this set of peer-reviewed papers from the
?rst MICCAI Workshop on Medical Content-Based Retrieval for
Clinical Decision Support. The MICCAI conference has been the
?agship conference for the m- ical imaging community re?ecting the
state of the art in techniques of segm- tation, registration, and
robotic surgery. Yet, the transfer of these techniques to clinical
practice is rarely discussed in the MICCAI conference. To address
this gap, we proposed to hold this workshop with MICCAI in London
in September 2009. The goal of the workshop was to show the
application of content-based retrieval in clinical decision
support. With advances in electronic patient record systems, a
large number of pre-diagnosed patient data sets are now bec- ing
available. These data sets are often multimodal consisting of
images (x-ray, CT, MRI), videos and other time series, and textual
data (free text reports and structuredclinicaldata). Analyzing
thesemultimodalsourcesfordisease-speci?c information across
patients can reveal important similarities between patients and
hence their underlying diseases and potential treatments.
Researchers are now beginning to use techniques of content-based
retrieval to search for disea- speci?c information in modalities to
?nd supporting evidence for a disease or to automatically learn
associations of symptoms and diseases. Benchmarking frameworks such
as ImageCLEF (Image retrieval track in the Cross-Language
Evaluation Forum) have expanded over the past ?ve years to include
large m- ical image collections for testing various algorithms for
medical image retrieval and classi?cation.
This book discusses efforts to control the low-frequency vibration
transmission of typical power equipment and pipeline systems of
ships, exploring the use of active and passive hybrid vibration
isolation and adjustable dynamic vibration absorption technologies.
It also proposes an adaptive feed-forward control strategy and
studies a distributed feed-forward control hardware system. In
addition, the book presents a three-way dynamic vibration
absorption theory used to design a pipeline-system adjustable
dynamic vibration absorber, which offers a number of advantages,
such as compact structure, easy assembly and disassembly, low power
consumption, excellent vibration control effect and wide frequency
band adjustable ability, etc. This book is a valuable resource for
researchers and engineers in the fields of noise and vibration
control, active control systems, active vibration isolation and
adaptive dynamic vibration absorption.
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Machine Learning in Medical Imaging - Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers (Paperback, 2012 ed.)
Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki
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R1,429
Discovery Miles 14 290
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the Third
International Workshop on Machine Learning in Medical Imaging, MLMI
2012, held in conjunction with MICCAI 2012, in Nice, France, in
October 2012. The 33 revised full papers presented were carefully
reviewed and selected from 67 submissions. The main aim of this
workshop is to help advance the scientific research within the
broad field of machine learning in medical imaging. It focuses on
major trends and challenges in this area, and it presents work
aimed to identify new cutting-edge techniques and their use in
medical imaging.
At the heart of modern power electronics converters are power
semiconductor switching devices. The emergence of wide bandgap
(WBG) semiconductor devices, including silicon carbide and gallium
nitride, promises power electronics converters with higher
efficiency, smaller size, lighter weight, and lower cost than
converters using the established silicon-based devices. However,
WBG devices pose new challenges for converter design and require
more careful characterization, in particular due to their fast
switching speed and more stringent need for protection.
Characterization of Wide Bandgap Power Semiconductor Devices
presents comprehensive methods with examples for the
characterization of this important class of power devices. After an
introduction, the book covers pulsed static characterization;
junction capacitance characterization; fundamentals of dynamic
characterization; gate drive for dynamic characterization; layout
design and parasitic management; protection design for double pulse
test; measurement and data processing for dynamic characterization;
cross-talk consideration; impact of three-phase system; and
topology considerations.
Reconfigurable machines can accelerate many applications by
adapting to their needs through hardware reconfiguration. Partial
reconfiguration allows the reconfiguration of a portion of a chip
while the rest of the chip is still working. Operating system for
partially reconfigurable machines (OS4RC) handles the scheduling
and placement of tasks. Some existing OS4RC models assume no data
exchange channel between IP (Intellectual Property) circuits
residing on a FPGA chip and between an IP circuit and FPGA I/O
pins. Other models assume inter-IP communication channels, but they
do not work well with 2-D partial reconfiguration. And frequently
they are very complicated to design and expensive. To address these
problems, a new chip architecture that can better support inter-IP
and IP-I/O communication is proposed and a corresponding OS4RC
kernel is then specified.The proposed FPGA architecture is based on
an array of clusters of CLBs, with each cluster serving as a
partial reconfiguration unit, and a mesh of segmented buses that
provides inter-IP and IP-I/O communication channels. Features of
the new architecture can reduce the kernel execution times and
enable the runtime scheduling,
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