Abstract. Typical types of natural disasters that occur in Korea are damages from heavy rain, storm, and heavy snow. In order to prepare for this, the storm and flood damage insurance program is operated. For this purpose, the risk of these damages is calculated for each region, and the storm and flood damage insurance map is created based on the risk. This map can provide insight into the degree of risk to wind and flood, snow damage, as well as policies to prevent and prepare for each type of natural disaster. In order to support decision-making by utilizing this insurance map, it is necessary to use with disaster Information contents. In order to efficiently construct such disaster information contents, it is possible to utilize public data produced by various organizations. Korea has a public data portal to open various administrative information. The public data portal currently publishes and updates about 25,000 data from 700 organizations. In this study, the linkage system is designed that can construct disaster information contents by collecting public data and processing it so that it can be overlapped with the insurance map. The system automatically links public data to keep up-to-date disaster information content. It is expected that it will be able to prevent and prepare for natural disaster by supporting the decision making of decision makers related to flood damage.
Aortic valve dysfunction and stroke have recently been reported in transcatheter aortic valve implantation (TAVI) patients. Thrombus in the aortic sinus and neo-sinus due to hemodynamic changes has been suspected. In vitro experiments help investigate the hemodynamic characteristics in the cases where an in vivo assessment proves to be limited. In vitro experiments are also more robust, and the variable parameters are controlled readily. Particle image velocimetry (PIV) is a popular velocimetry method for in vitro studies. It provides a high-resolution velocity field such that even small-scale flow features are observed. The purpose of this study is to show how PIV is used to investigate the flow field in the aortic sinus after TAVI. The in vitro setup of the aortic phantom, TAVI for PIV, and the data acquisition process and post-processing flow analysis are described. The hemodynamic parameters are derived, including the velocity, flow stasis, vortex, vorticity, and particle residence. The results confirm that in vitro experiments and PIV help investigate the hemodynamic features in the aortic sinus.
Training has been identified as a means to reduce mental workload. However, there are limitations associated with many current mental workload measurement techniques. Thermography of the face has been identified as a potential workload measurement tool that may be more closely related to performance and subjective ratings of performance than many other physiological measures. The objective of this study was to validate the efficacy of thermography for assessing mental workload. Twenty participants, 10 males and 10 females, completed seven blocks of an alpha-numeric task. Changes in nose temperature (ANT), task accuracy, reaction time, and two subjective mental workload ratings were collected. Performance improved over time, while ANT and subjective mental workload ratings decreased. Nose temperature was found to be strongly correlated with both performance measures and subjective perceptions of mental workload.
Image fusion aims to synthesize multiple source images into a single image to integrate and enhance information. Specifically, we tackle the fusion of visible and infrared images. Previous works generally use structural similarity between the fusion and the paired source images to train a deep-learning-based fusion model. However, only using the structure often results in a texture-insufficient image. In this study, we aim to generate an image rich in texture. This study is inspired by the ability of an autoencoder to learn a compressed representation of the input image. Specifically, we learn a fusion image with the structure and texture of the source images. We propose a novel framework–Restorable visible and infrared Image Fusion, which consists of a fusion and decoupling network. The fusion network synthesizes source images, and the decoupling network restores the source images by decomposing a fusion image. Our framework can be trained by minimizing the difference between the source and restored images. The experimental results demonstrate that the fusion image generated by the proposed method maintains the texture of the source images.
The demand for 3D spatial data and effective dataset construction has been increasing.However, the construction of 3D spatial datasets is more time-consuming and costlier than that of 2D spatial data.In addition, maintaining 3D city models up to date long after their initial construction is difficult.In this study, we developed a method of updating 3D building information within a relatively short time frame using highly accurate 2D building information.This method can be used to correct 3D building information automatically.Unmanned aerial vehicle (UAV) imagery of the study area was obtained, and a 3D model was developed using commercial software.Subsequently, the 3D model information was mapped onto the 2D information.After transforming the paired objects into point data at a set interval, registration parameters were calculated by applying the iterative closest-point technique.The calculated parameters were used to reposition the 3D model, enabling the creation of a model that overlaps with more than 98% of the existing spatial information data.Thus, it was confirmed that 3D building models can be produced without ground control points and can be readily updated at low cost.
Abstract. Recently, UAV (Unmanned Aerial Vehicle) is used in a variety of fields such as the military service, fire prevention, traffic supervision, mapping, and etc. The increased demand for UAVs is typically attributed to the low manufacturing and operational costs, flexibility of the platforms to accommodate the consumer’s particular needs and the elimination of the risk to pilots’ lives in difficult missions. But, in South Korea, UAV might be first introduced to military service, and is still in its infancy, just being available for construction site monitoring, landscape photographing, spraying agricultural chemicals, broadcasting fields. This study presents the background and the aim of flood mapping, and presents the possibility analysis of how to use UAV effectively for flooding area. And author tries to overlap UAV image with the flooding area trace surveyed by ground surveys. As a result, it is expected that UAV photogrammetry will contributes to investigating the flooded area by providing images, which is describing the flooded area in near real-time and also making a decision like paying compensation.
본 연구는 KML내부 구문에 대해 알지 못하는 일반사용자들이 KML파일을 사용하기 위한 최적의 지도서비스와 고도화된 검증도구를 사용할 수 있게 국내외 대표적인 저작도구를 분석하였다. 분석된 결과를 이용해 기존의 검증도구를 고도화해 구글 어스나 브이월드 3D 데스크톱에서 사용가능 여부와 발생할 수 있는 문제점들을 사용자에게 알려주는 시스템을 설계했다. 사용자가 본 검증도구를 통해 검증을 완료하면 사용한 KML 정보를 지도기반으로 간단히 표현하고 구글 어스와 브이월드 3D데스크톱의 초기화면으로 보여주며 KML과 관련된 중요 사항을 알려준다. 만약 적당한 프로그램이 없거나 다른 프로그램을 선택한다면 해당 프로그램 사용 시 발생할 수 있는 문제들을 사용자에게 알려주어 KML의 호환성을 높일 수 있었다. The study has planned to analyze the most typical specification validation in Korea and the other countries, which shows the well-formed and schema validation, in purpose to enhance users' conveniences. Also, we suggested the validation system to provide the information compatibility regarding to application programs for non-expert. The featured KML specification supported by the VWorld 3D Desktop and the Google Earth. Based on this above estimation, the system has been designed to inform potential problems and the applicability in 3D Desktop and Google Earth for the user. The KML information passed through the proposed validation is simply expressed on the map, so as instructed the information on the program selection and additional details instruct users as a text file. When not being suitable for the proposed program, another program can be considered, and the problems which may be occurred are also announced to increase the compatibility of KML.
Abstract. Typical types of natural disasters that occur in Korea are damages from heavy rain, storm, and heavy snow. In order to prepare for this, the storm and flood damage insurance program is operated. For this purpose, the risk of these damages is calculated for each region, and the storm and flood damage insurance map is created based on the risk. This map can provide insight into the degree of risk to wind and flood, snow damage, as well as policies to prevent and prepare for each type of natural disaster. In order to support decision-making by utilizing this insurance map, it is necessary to use with Storm and Flood Damage Information contents. In order to efficiently construct such disaster information contents, it is possible to utilize public data produced by various organizations. Korea has a public data portal to open various administrative information. The public data portal currently publishes and updates about 25,000 data from 700 organizations. In this study, the linkage system is designed that can construct disaster information contents by collecting public data and processing it so that it can be overlapped with the insurance map. The system automatically links public data to keep up-to-date disaster information content. It is expected that it will be able to prevent and prepare for natural disaster by supporting the decision making of decision makers related to flood damage.
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