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The book provides invaluable insight into the latest developments in point-of-care and laboratory diagnostic devices that are based on microfluidic principles. It presents a selection of important topics, making it an excellent introductory reading for graduate students in bioengineering and related disciplines.

From power electronics to power integrated circuits, smart power technologies to GaN power HEMTs, Integrated Power Devices and TCAD Simulation provides a complete picture of the power management and semiconductor industry. Instead of abstract theories and daunting equations, the text uses TCAD simulations to explain the design of integrated power devices. The book not only describes the physics inside devices such as LDMOSFETs, LIGBTs, and super junction LDMOSFETs but also delivers a simple introduction to power management systems essential to engineers and students.

This book explores issues in designing high-performance embedded computer systems and networks. The emphasis is on the fundamental concepts and analytical techniques that are applicable to a range of applications, rather than on specific system components, software, or system-level integration. Topics include the co-design of embedded systems, code optimization, power and performance trade-offs, and benchmarks for evaluating embedded systems and their components. Featuring contributions by researchers from around the world, it offers a global view of groundbreaking technologies and applications.

For decades, people have sought to harvest energy from natural sources. Lately, climate change has popularized solar or photovoltaic technology, while piezoelectric technology is being developed to power handheld devices, and thermoelectric technology is being explored to convert wasted engine heat into electricity. Written by experts from academia and industry, Energy Harvesting with Functional Materials and Microsystems presents current research and explains the field from a materials and device perspective, with resulting technologies capable of enabling low-power implantable sensors or large-scale electrical grids.

Although there have been extensive developments in computing and communications needs of integrated microsystems, the sensors required to conduct advanced and integrated tasks are only now seeing transformational change. With their huge potential interfacing applications for biological and medical fields, sensors will soon become ubiquitous. Focusing heavily on practical applications but remaining light on physics and math, this book addresses the developments necessary to make truly integrated sensors a reality in physical, biological, optical, and chemical sensing, as well as future micro- and nanotechnologies.

This book is a collection of chapters containing carefully selected topics on the most recent advancements in semiconductor radiation detector technologies. Relatively new detector materials, such as CdZTe and Cr compensated GaAs, are introduced, along with emerging applications of radiation detectors.

The book is divided into three sections: devices and technology for magnetic sensing, industrial applications (automotive/navigation), and emerging applications. It covers transmission speed sensor ICs, dynamic differential Hall ICs, chopped Hall switches, programmable linear output Hall sensors, low power Hall ICs, and electromagnetic levitation.

The book presents information written by international experts in the field of Systems on Chip (SoC) Coupling, including substrate and interconnect magnetic crosstalk, 2D and 3D circuits noise coupling, and TSV and simulation. It enables the reader to analyze crosstalk noise propagating through the parasitics interconnect and package and the PCB.

Sensor technologies and applications are evolving rapidly driven by the demand for new sensors for monitoring and diagnostic purposes to improve human health and safety. The book reviews the latest developments in sensor technology and gives the reader an overview of the state-of-the-art in key areas, such as sensors for diagnostics and monitoring.

This book explores up-to-date research trends and achievements on low-power and high-speed technologies in both electronics and optics. It offers unique insight into low-power and high-speed approaches ranging from devices, ICs, sub-systems and networks that can be exploited for future mobile devices, 5G networks, and Internet of Things (IoT).

The first portion of the book is on the algorithms. The second portion of the book is about applications, covering some of the major areas like computational imaging, medical imaging, biomedical signal processing and machine learning. The concentration of this book is on algorithms and applications.

The book puts emphasis on sensor materials, detector structures, front electronics technology and their designs as well as system optimization for different applications. Also, it includes characterization measurements of the developed detection systems.

This volume presents specific applications of the detection systems in medical imaging, industrial testing and security applications. These newely developed technologies start to play a vital role in the detection, diagnosis and tratment of major human diseases.

Compressed Sensing (CS) in theory deals with the problem of recovering a sparse signal from an under-determined system of linear equations. The topic is of immense practical significance since all naturally occurring signals can be sparsely represented in some domain. In recent years, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) and has also helped reduce the health hazard in X-Ray Computed CT. This book is a valuable resource suitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra.Covers fundamental concepts of compressed sensingMakes subject matter accessible for engineers of various levelsFocuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learningIncludes MATLAB examples for further development