We are proud to present the Proceedings of the 2nd International Conference on Religion and Education 2020 (INCRE 2020). The Center for Research and Development of Ministry of Religious Affairs of Republic of Indonesia together together with other International organizations: International Islamic University Malaysia (IIUM), Sultan Sharif Ali Islamic University (UNNISA) of Brunei, State Islamic University of Syarif Hidayatullah Jakarta, and Asosasi Ma’had Ali Indonesia (AMALI) hosted and organized the second annual conference in the general field of education and religion. The conference provided a forum for education professionals engaged in research and development to share ideas, interact with others, present their latest works, and strengthen the collaboration among academics, researchers and professionals. It was a single-track, highly selective conference attended by leading experts from academia, industry, and government. Due to the Covid-19 Pandemic, we organized the conference virtually in 2 days event 11-12 November 2020 with 4 keynote speakers: Prof Prof Azyumardi Azra from State Islamic University of Syarif Hidayatullah Jakarta, Prof Abdul Wahab Abdul Rahman from International Islamic University Malaysia, Prof. Achmad Gunaryo from Research and Development, Ministry of Religious Affair, Indonesia, and Dr. Syamsi Ali from Jamaica Muslim Center, New York USA. The proceeding consisted of 34 accepted papers from the total of 82 submission papers. The proceeding consisted of 10 main areas of education and religion. They are: Modernizing madrasas in global contexts, Teacher and Education development, Student abilities in religion education, Education and Technology, World Class University in Indonesian religious university, Local wisdom and religion education, Citizenship in religion education, Religion and character education, Moderism in religion and education, and Islamic boarding school stretching. All papers have been scrutinized by a panel of reviewers who provide critical comments and corrections, and thereafter contributed to the improvement of the quality of the papers. We strongly believe that INCRE 2020 conference has become a good forum for all researcher, developers, practitioners, scholars, policy makers, especially post graduate students to discuss their understandings of current processes and findings, as well as to look at possibilities for setting-up new trends in Education and Religion. We also expect that the future INCRE conference will be as successful and stimulating, as indicated by the contributions presented in this volume.

Metal forming processes include bulk forming and sheet metal forming with numerous applications. This book covers some of the latest developments aspects of these processes such as numerical simulations to achieve optimum combinations and to get insight into process capability. Implementation of new technologies to improve performance based on Computer Numerical Control (CNC) technologies are also discussed, including the use of CAD/CAM/CAE techniques to enhance precision in manufacturing. Applications of AI/ML, the Internet of Things (IoT), and the role of tribological aspects in green engineering are included to suit Industry 4.0. Features: Covers latest developments in various sheet metal forming processes Discusses improvements in numerical simulation with various material models Proposes improvements by optimum combination of process parameters Includes finite element simulation of processes and formability Presents a review on techniques to produce ultra-fine-grained materials This book is aimed at graduate students, engineers, and researchers in sheet metal forming, materials processing and their applications, finite element analysis, manufacturing, and production engineering.

Despite being the leading paradigm in computer vision, deep neural networks are inherently limited by the visual and semantic information contained in their training set. In this thesis, we aim to design deep models operating with previously unseen visual domains and semantic concepts. We first describe different solutions for generalizing to new visual domains, applying variants of normalization layers to multiple challenging settings e.g. where new domain data is not available but arrives online or is described by metadata. In the second part, we incorporate new semantic concepts into pretrained deep models. We propose specific solutions for different problems such as multi-task/incremental learning and open-world recognition. Finally, we merge the two challenges: given images of multiple domains and categories, can we recognize unseen concepts in unseen domains? We propose an approach that is the first, promising step, towards solving this problem. Winner of the Competition “Prize for PhD Thesis 2020” arranged by Sapienza University Press.