The purpose of this study is to analyze research trends in Korean language education for North Korean refugees. In pursuance of this goal, the study collected bibliographic information from 1,924 academic papers related to North Korean defectors and analyzed their research trends using language network analysis methods. The frequency and centrality of the academic papers were analyzed by year, using an analysis tool, NetMiner 4.0, which focuses on analyzing social networks. The findings of the analysis were as follows: First, the study of North Korean defectors began to explode in 2010. Second, the most central words were ‘education,’ ‘unification,’ ‘policy,’ ‘support,’ ‘experience’ and ‘relationship.’ Third, for North Korean defectors, Korean language education as a foreign language was more actively done than general Korean language education. Fourth, the analysis of 15 topics showed that topics on social issues accounted for the highest percentage at 25%. Finally, the areas of greatest interest in Korean language education were vocabulary, pronunciation, and intonation education. It is hoped that more research on Korean language education for North Korean defectors will be carried out in the future.

This paper proposes a bridge inspection system using a robot to manage the safety status of bridges. A conventional bridge inspection has a lot of problems because inspection is conducted manually by human. As an alternative, we are to develop a robot system having machine vision and this robot system is mounted on an end linkage of specially designed car having seven DOF (Degrees Of Freedom) to inspect cracks beneath bridge. This system is able to check a status of the bridge and record its changes every other year. As a result, the developed robot system offers us the inspection result of quality and reliability about the bridge inspection status. Also, we have tested the effectiveness of the suggested system through outdoor experiments.