Crossing and Conversion among North Korean Refugee-Migrants

While pivotal in the lives of North Korean refugee-migrants, the role of religion has been largely neglected in most studies. After being exposed to Protestant missionary networks, either while dwelling in Northeast China or en route to the South, about 80 percent of North Korean refugee-migrants arriving in South Korea affiliate themselves with Protestant churches. This implies that they are exposed to Protestant missionary networks either while dwelling in Northeast China or en route to the South. Some who leave South Korea for other countries or seek asylum in non-Korean societies develop their religiosity in various ways and for various reasons, as part of their aspirations, adjustment to new homes, and search for meaning. The present study aims to address this literature gap. Based on long-term ethnographic research with North Korean refugee-migrants living in South Korea, China, and Europe, the two ethnographic vignettes presented in this article represent those who are in Germany and the United Kingdom by discussing the religious encounters and conversions through which North Korean refugee-migrants make their lives and futures. It draws attention to religion as a lens through which the migrants’ negotiation of meanings, new selves and homelands, and hopes for the future can be better illuminated. The findings of this study suggest that when North Korean Christians experience religious conversion during their perilous journeys, it not only helps them to negotiate a new sense of belonging in their host societies, but it also mobilizes them to contest the existing order of things

Division and Unification: Seen through the Eyes of Korean Migrants in Berlin

Based on qualitative fieldwork among first generation Korean immigrants in Berlin, this article sheds light on their lived experiences of German division and unification. Our research questions are threefold; first, how do these immigrants from the divided Korea perceive the division and unification of Germany? Second, did the fact that the division of Germany could be overcome affect their views on the division and unification of the Korean Peninsula? Third, are there any differences between Koreans in Germany and Koreans in Korea with respect to their views on unification? Our research suggests that different from South Korea, where the discourses in the media and the academia tend to assume sharply antagonistic attitudes, discourses among Koreans in Germany are generally much more supportive of unification. This is because they have a positive perception of German unification in everyday life and, furthermore, have constructed for themselves a future-oriented identity as a people of the Korean Peninsula that will eventually be unified. Korean immigrants in Germany are considerably more optimistic about the possibility of Korean unification than people in South Korea

Street Crossing Aid Using Light-weight CNNs for the Visually Impaired

In this paper, we address an issue that the visually impaired commonly face while crossing intersections and propose a solution that takes form as a mobile application. The application utilizes a deep learning convolutional neural network model, LytNetV2, to output necessary information that the visually impaired may lack when without human companions or guide-dogs. A prototype of the application runs on iOS devices of versions 11 or above. It is designed for comprehensiveness, concision, accuracy, and computational efficiency through delivering the two most important pieces of information, pedestrian traffic light color and direction, required to cross the road in real-time. Furthermore, it is specifically aimed to support those facing financial burden as the solution takes the form of a free mobile application. Through the modification and utilization of key principles in MobileNetV3 such as depthwise seperable convolutions and squeeze-excite layers, the deep neural network model achieves a classification accuracy of 96% and average angle error of 6.15 degrees, while running at a frame rate of 16.34 frames per second. Additionally, the model is trained as an image classifier, allowing for a faster and more accurate model. The network is able to outperform other methods such as object detection and non-deep learning algorithms in both accuracy and thoroughness. The information is delivered through both auditory signals and vibrations, and it has been tested on seven visually impaired and has received above satisfactory responses.Comment: 10 pages, 5 figures, 7 tables, ICCV 2019 - 7th International Workshop on Assistive Computer Vision and Robotics (ACVR 2019