The book focuses on the current research of the relation between protein phosphorylation and meat quality, reviews the influence mechanism of protein phosphorylation on meat quality, and summarizes the improvement of meat quality by regulating protein phosphorylation. It could help to clarify some dilemmas and encourage further research in this field, aiming for effective application of protein phosphorylation in meat quality in the near future. The book is written for researchers and graduate students in the field of meat science, food chemistry and molecular biology etc.
One-Dimensional Nanostructures: Electrospinning Technique and Unique Nanofibers is a comprehensive book depicting the electrospinning technique and related 1D unique electrospun nanofibers. The first part of the book focuses on electrospinning technique, with chapters describing Electrospinning setup, electrospinning theories, and related working parameter. The second part of the book describes in detail specific topics on how to control the electrospun fiber properties such as how to control the fiber direction, how to control the fiber surface morphology, how to control the fiber structure, and how to construct 3D structures by electrospun fibers. The final part of the book depicts the applications of the electrospun nanofibers, with sections describing in detail specific fields such as electrospun nanofiber reinforcement, filtration, electronic devices, lithium-ion batteries, fuel cells, biomedical field, and so on. One-Dimensional Nanostructures: Electrospinning Technique and Unique Nanofibers is designed to bring state-of-the-art on electrospinning together into a single book and will be valuable resource for scientists in the electrospinning field and other scientists involved in biomedical field, mechanical field, materials, and energy field. Dr. Zhenyu Li is an associate professor at the Dept. of Chemistry, Jilin University, Changchun, P. R. China. Currently, he also holds the position in Australian Future Fibres Research & Innovation Centre, Institute for Frontier Materials, Deakin University, Geelong, Victoria, Australia. Dr. Ce Wang is a professor at the Dept. of Chemistry, Jilin University, Changchun, P. R. China.
Objective Information Theory (OIT) is proposed to represent and compute the information in a large-scale complex information system with big data in this monograph. To formally analyze, design, develop, and evaluate the information, OIT interprets the information from essential nature, measures the information from mathematical properties, and models the information from concept, logic, and physic. As the exemplified applications, Air Traffic Control System (ATCS) and Smart Court SoSs (System of Systems) are introduced for practical OITs. This Open Access book can be used as a technical reference book in the field of information science and also a reference textbook for senior students and graduate ones in related majors.
In an article for Wired Magazine in 2006, Jeff Howe defined crowdsourcing as an idea for outsourcing a task that is traditionally performed by a single employee to a large group of people in the form of an open call. Since then, by modifying crowdsourcing into different forms, some of the most successful new companies on the market have used this idea to make people’s lives easier and better. On the other hand, software testing has long been recognized as a time-consuming and expensive activity. Mobile application testing is especially difficult, largely due to compatibility issues: a mobile application must work on devices with different operating systems (e.g. iOS, Android), manufacturers (e.g. Huawei, Samsung) and keypad types (e.g. virtual keypad, hard keypad). One cannot be 100% sure that, just because a tested application works well on one device, it will run smoothly on all others. Crowdsourced testing is an emerging paradigm that can improve the cost-effectiveness of software testing and accelerate the process, especially for mobile applications. It entrusts testing tasks to online crowdworkers whose diverse testing devices/contexts, experience, and skill sets can significantly contribute to more reliable, cost-effective and efficient testing results. It has already been adopted by many software organizations, including Google, Facebook, Amazon and Microsoft. This book provides an intelligent overview of crowdsourced testing research and practice. It employs machine learning, data mining, and deep learning techniques to process the data generated during the crowdsourced testing process, to facilitate the management of crowdsourced testing, and to improve the quality of crowdsourced testing.
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