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Global Unmanned Aerial Vehicle Utilization Research Trends
Moon, Ho-Gyeong,Kim, Han,Choi, Nak-Hyun,Kim, Dong-Pil National Institute of Ecology 2020 국립생태원회보(PNIE) Vol.1 No.1
The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on "UAV technology/industry trends" was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was "remote sensing technology/data analysis". In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.
배경태(Gyeong-Tae Bae),김귀남(Gwi-Nam Kim),최부영(Boo-Young Choi),문홍만(Hong-Man Moon),노정필(Jung-Pil Noh),허선철(Sun-Chul Huh) 한국해양공학회 2015 韓國海洋工學會誌 Vol.29 No.1
To improve the accuracy of a machine, research needs to be conducted on the relationship between the output variables and design variables of a spindle-shaped part from the thermal and static viewpoints. Therefore, research was carried out by examining the correlation of each variable to find the optimum conditions. Moreover, DOE (design of experiments) was extensively used. The model used in this study was a grinding spindle to which a hydrostatic bearing was applied. This model was used in a preliminary analysis based on the experimental results of the previous studies. The influences of the output variables and design variables were compared through a main effect analysis. Generated response surfaces were applied to the Kriging model. To optimize the model, a screening method was selected. In comparison with the initial model, the deformation of the optimized model designed by DOE decreased by 4.1 ㎛, while the thermal deformation decreased by 1.2 ㎛. Therefore, it was efficient to design a spindle-shaped part through DOE to improve the accuracy of the machine.
문호경 ( Ho Gyeong Moon ),김동필 ( Dong Pil Kim ),최송현 ( Song Hyun Choi ),권진오 ( Jin O Kwon ) 한국환경생태학회 2014 한국환경생태학회지 Vol.28 No.3
This study is to analyze the physical environment and conduct spatial data for bicycle road system in changwon. Index for evaluation index was developed based on literatures. Then the level of importance and weight have been modified through experts review. Finally, index with eight categories such as greenness(40% over), bicycle road connectivity(1.8, 9.8%), road type bike(bicycle lane, 24.4%), pave type(asphalt 72.5%), illegal parking(none, 93.9%), bike road surface visibility(exist, 46.8%), vehicle speed limits(30km, under), vehicle traffic(500/hr under, 44.3%) have been applied to empirical investigation. Collected data has been hierarchically classification by ArcGIS Program. The Highest grades(score 31-35, level 1) occupied 35% of target destination. High level of greenness and load type has contributed to high score. In addition, average level of greenness of those destination was 35% and higher, which provide high degree of security and freshness for bicycle riding. Meanwhile, lowest level(level 5, which earned 15 point or less) occupied 24.5%. illegal parking, low level of greenness, and no surface sign caused low score.