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Brodsky brings together works by the expatriate Chinese painter Yun Gee (1906-1963) and his Chinese American daughter, Li-lan, exploring connections between each artist's life and paintings. As artists who have embraced multinational, multicultural, and multiracial experiences, Yun Gee and Li-lan have combined those experiences intrinsically, sometimes in spite of the pain that such a complex passage may entail. Joyce Brodsky is professor emeritus of art and theory at the University of California, Santa Curz.

"I talked with a father last week about his son, Brian. Brian just turned nine and is enjoying the new school year. The father was excited because this is the first year that Brian is in a class with other students who do not have a developmental disability. Brian is one of three kids with a developmental disability in the class, and he seems to enjoy school more since he has experienced a fuller amount of inclusion in his classroom. The father expressed feelings of relief, excitement, and encouragement-finally his son had a place at the table. He then paused, thought for a moment, and said, 'I wish it was the same at our church.'" There is a crisis occurring in the modern Church. The largest minority of people in the world-people with disabilities-find it challenging or even nearly impossible to participate in church. And, worse, most church goers don't even know it. In Accessible Faith, author Yun Li describes how this issue has weakened the American Church as well as what can be done about it. There is hope-if churches are willing to make disability accessibility a priority, our brothers and sisters in Christ with disabilities will be able to join us as we share Christ with the world.

This book combines the experience and achievements in engineering practice of the China Academy of Space Technology, Xi’an, with a focus on the field of high-power multipactor over recent decades. It introduces the main concepts, theories, methods and latest technologies of multipactor simulation, at both the theoretical level and as a process of engineering, while providing a comprehensive introduction to the outstanding progress made in the research technology of multipactor numerical simulation in China. At the same time, a three-dimensional numerical simulation method of multipactor for typical high-power microwave components of spacecraft is introduced. This book is an essential volume for engineers in the field of high-power microwave technology. It can also be used as a reference for researchers in related fields, or as a teaching reference book for graduate students majoring in Astronautics at colleges and universities.

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

With the rapid growth of Cloud computing, the size of Cloud data is expanding at a dramatic speed. A huge amount of data is generated and processed by Cloud applications, putting a higher demand on cloud storage. While data reliability should already be a requirement, data in the Cloud needs to be stored in a highly cost-effective manner. This book focuses on the trade-off between data storage cost and data reliability assurance for big data in the Cloud. Throughout the whole Cloud data lifecycle, four major features are presented: first, a novel generic data reliability model for describing data reliability in the Cloud; second, a minimum replication calculation approach for meeting a given data reliability requirement to facilitate data creation; third, a novel cost-effective data reliability assurance mechanism for big data maintenance, which could dramatically reduce the storage space needed in the Cloud; fourth, a cost-effective strategy for facilitating data creation and recovery, which could significantly reduce the energy consumption during data transfer. - Captures data reliability with variable disk rates and compares virtual to physical disks - Offers methods for reducing cloud-based storage cost and energy consumption - Presents a minimum replication benchmark for data reliability requirements to evaluate various replication-based data storage approaches

This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary. Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.