Xiang Zhang – författare

Inorganic Controlled Release Technology: Materials and Concepts for Advanced Drug Formulation provides a practical guide to the use and applications of inorganic controlled release technology (iCRT) for drug delivery and other healthcare applications, focusing on newly developed inorganic materials such as bioresorbable glasses and bioceramics. The use of these materials is introduced for a wide range of applications that cover inorganic drug delivery systems for new drug development and the reformulation of existing drugs. The book describes basic concepts, principles, and industrial practices by discussing materials chemistry, physics, nano/microstructure, formulation, materials processing, and case studies, as well as the evaluation and characterization of iCRT systems commonly investigated during industrial R&D.

Provides the first book on inorganic controlled release technology (iCRT), covering key aspects from chemistry, physics, synthetic methods, formulation design, characterization and evaluation Includes several industry-related case studies to provide practical guidance on how to use iCRT as an alternative to organic polymers systems for both future drug developments and other active ingredient applications Demonstrates how iCRT offers an unmet business need for improved, controlled release of actives versus traditional CRT systems, which are known to have difficulty with the controlled delivery of both poorly and highly water soluble drug compounds

Deep Learning for EEG-based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms, and applications. BCI bridges humanity's neural world and the physical world by decoding an individuals' brain signals into commands recognizable by computer devices.This book presents a highly comprehensive summary of commonly-used brain signals; a systematic introduction of around 12 subcategories of deep learning models; a mind-expanding summary of 200+ state-of-the-art studies adopting deep learning in BCI areas; an overview of a number of BCI applications and how deep learning contributes, along with 31 public BCI datasets. The authors also introduce a set of novel deep learning algorithms aimed at current BCI challenges such as robust representation learning, cross-scenario classification, and semi-supervised learning. Various real-world deep learning-based BCI applications are proposed and some prototypes are presented. The work contained within proposes effective and efficient models which will provide inspiration for people in academia and industry who work on BCI.

The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18–21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming, and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications.” Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.

This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Computing, ICIC 2012, held in Huangshan, China, in July 2012.The 242 revised full papers presented in the three volumes LNCS 7389, LNAI 7390, and CCIS 304 were carefully reviewed and selected from 753 submissions. The papers in this volume (CCIS 304) are organized in topical sections on Neural Networks; Particle Swarm Optimization and Niche Technology; Kernel Methods and Supporting Vector Machines; Biology Inspired Computing and Optimization; Knowledge Discovery and Data Mining; Intelligent Computing in Bioinformatics; Intelligent Computing in Pattern Recognition; Intelligent Computing in Image Processing; Intelligent Computing in Computer Vision; Intelligent Control and Automation; Knowledge Representation/Reasoning and Expert Systems; Advances in Information Security; Protein and Gene Bioinformatics; Soft Computing and Bio-Inspired Techiques in Real-World Applications; Bio-Inspired Computing and Applications.

This is the first book to systematically state the fundamental theory of integrability and its development of ordinary differential equations with emphasis on the Darboux theory of integrability and local integrability together with their applications. It summarizes the classical results of Darboux integrability and its modern development together with their related Darboux polynomials and their applications in the reduction of Liouville and elementary integrabilty and in the center—focus problem, the weakened Hilbert 16th problem on algebraic limit cycles and the global dynamical analysis of some realistic models in fields such as physics, mechanics and biology. Although it can be used as a textbook for graduate students in dynamical systems, it is intended as supplementary reading for graduate students from mathematics, physics, mechanics and engineering in courses related to the qualitative theory, bifurcation theory and the theory of integrability of dynamical systems.

This is the first book to systematically state the fundamental theory of integrability and its development of ordinary differential equations with emphasis on the Darboux theory of integrability and local integrability together with their applications.

"A very handy feature of this book includes an appendix section consisting of fifteen parts, each dedicated to listing equations and solution examples for calculating various important quantities for optoelectronic devices. This book is an in-depth technical resource for understanding the principles of various types of optoelectronic devices and systems. Students, as well as working professionals, would find this book useful for calculating quantities needed in the design of optical system components. There is a section, at the end of the book, along with an extension reference list at the end of each chapter that provides problems from each chapter, making this book suitable for an undergraduate or graduate class in electrical engineering on optoelectronic theory."IEEE Electrical Insulation MagazineThis book provides a comprehensive treatment of the design and applications of optoelectronic devices. Optoelectronic devices such as light emitting diodes (LEDs), semiconductor lasers, photodetectors, optical fibers, and solar cells, are important components for solid state lighting systems, optical communication systems, and power generation systems. Optical fiber amplifiers and fiber lasers are also important for high power industrial applications and sensors. The applications of optoelectronic devices were first studied in the 1970's. Since then, the diversity and scope of optoelectronic device research and applications have been steadily growing.Optoelectronic Devices is self-contained and unified in presentation. It can be used as an advanced textbook by graduate students and practicing engineers. It is also suitable for non-experts who wish to have an overview of optoelectronic devices and systems. The treatments in the book are detailed enough to capture the interest of the curious reader and complete enough to provide the necessary background to explore the subject further.

This book is the first overview book on video surveillance issues within airport grounds. It delves into the distinctive design principles underpinning computer vision algorithms tailored specifically for airport ground video surveillance, while also documenting the latest advancements within this domain.The initial section of this book introduces a comprehensive array of airport ground video surveillance datasets, encompassing the AGVS series alongside other pertinent datasets. Subsequently, the second section delves into the ongoing research endeavors on airport-ground-oriented computer vision algorithms, examining segmentation, recognition, and tracking methodologies. Lastly, the book’s third segment elucidates the design methodologies and exemplary use cases of airport ground video surveillance applications.Written by the authors intimately involved in creating the datasets, algorithms, and applications outlined within, this book stands as an indispensable reference for researchers and graduate students operating within the realm of intelligent transportation.