• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.3
• /
• pp.239-247
• /
• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• The Korean Journal of Physiology and Pharmacology
• /
• v.16 no.4
• /
• pp.281-285
• /
• 2012

A previous animal study has shown the effects of erythropoietin (EPO) and its non-erythropoietic carbamylated derivative (CEPO) on neurogenesis in the dentate gyrus. In the present study, we sought to investigate the effect of EPO on adult hippocampal neurogenesis, and to compare the ability of EPO and CEPO promoting dendrite elongation in cultured hippocampal neural progenitor cells. Two-month-old male BALB/c mice were given daily injections of EPO (5 U/g) for seven days and were sacrificed 12 hours after the final injection. Proliferation assays demonstrated that EPO treatment increased the density of bromodeoxyuridine (BrdU)-labeled cells in the subgranular zone (SGZ) compared to that in vehicle-treated controls. Functional differentiation studies using dissociated hippocampal cultures revealed that EPO treatment also increased the number of double-labeled BrdU/microtubulea-ssociated protein 2 (MAP2) neurons compared to those in vehicle-treated controls. Both EPO and CEPO treatment significantly increased the length of neurites and spine density in MAP2(+) cells. In summary, these results provide evidences that EPO and CEPO promote adult hippocampal neurogenesis and neuronal differentiation. These suggest that EPO and CEPO could be a good candidate for treating neuropsychiatric disorders such as depression and anxiety associated with neuronal atrophy and reduced hippocampal neurogenesis.

• Spatial Information Research
• /
• v.16 no.4
• /
• pp.455-465
• /
• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• Journal of Digital Convergence
• /
• v.16 no.1
• /
• pp.351-356
• /
• 2018

The aim of this study is to propose guidelines for bus-stop information design that is more congested with the advent of U-Shelter, via case studies and focus group interviews. First, the literature research explored the concept of information design and correlation of information design and route map. Second, raising problems and consider improvement plans through case study in korea, overseas. Finally, current information design was evaluated and user's requests were derived through focus group interview. The current information design had problems with lack of priority, information overlaying, and hard recognition. Priority shall be selected by bus route, direction of bus, arrival time, interval, and operating time, and information overlay can be reduced into one. Also visualize the connection and direction between the lines using schematic and two-dimensional lines and shapes for recognition. Through this study, it will be used as a reference material to help improve and develop the bus-stop information design.

• KIPS Transactions on Software and Data Engineering
• /
• v.13 no.1
• /
• pp.17-27
• /
• 2024

Video frame interpolation is an important technique used in the field of video and media, as it increases the continuity of motion and enables smooth playback of videos. In the study of video frame interpolation using deep learning, Kernel Based Method captures local changes well, but has limitations in handling global changes. In this paper, we propose a new U-Net structure that applies feature map differentiation and two directions to focus on capturing major changes to generate intermediate frames more accurately while reducing the number of parameters. Experimental results show that the proposed structure outperforms the existing model by up to 0.3 in PSNR with about 61% fewer parameters on common datasets such as Vimeo, Middle-burry, and a new YouTube dataset. Code is available at https://github.com/Go-MinSeong/SF-AdaCoF.

• Journal of Korean Society for Geospatial Information Science
• /
• v.5 no.1 s.9
• /
• pp.71-80
• /
• 1997

This paper suggests a Map Accuracy Standards by analyzing U.S. National Map Accuracy Standards, by considering korean terrain feature and statistical error theory for paper and digital maps on the scale of 1:50,000. Map accuracy standards require horizontal accuracy to be reported as a circular error with 90% confidence level through Linear Error Probable(LEP) theory and Circular Error Probable(CEP) theory. In order to verify the proposed methodology for positioning accuracy testing, several kinds of test point were selected and tested. These test points were extracted at the centers of roads and bridges, the comers of the independent building, the edges of geographical botany, and the tops of mountains. The positioning accuracy assessment was peformed by comparing the positions of test points in digital maps generated three different sources with those acquired by high accurate GPS surveying. The digital maps were produced from aerial photographs and SPOT satellite image using analytical plotter and 1:50,000 paper map.

• Journal of Environmental Health Sciences
• /
• v.49 no.1
• /
• pp.30-36
• /
• 2023

Background: Among various pollutants, fine particle (PM_2.5, defined as particle less than 2.5 nm in aerodynamic diameter) shows the most consistent association with adverse health effects. There is scientific evidence documenting a variety of adverse health outcomes due to exposure to PM_2.5. Objectives: This study aims to assess the health benefits of that would be achieved by meeting the World Health Organization's air quality guidelines for PM_2.5 using AirQ+ and BenMAP. Methods: We estimated PM_2.5 related health benefits in Korea from implementing the World Health Organization's air quality guidelines (annual average 5 ㎍/m³ and 10 ㎍/m³) and Korea's National Ambient Air Quality Standard (annual average 15 ㎍/m³). We used World Health Organization's AirQ+ and U.S. Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program. Results: The annual number of avoided PM_2.5 related premature deaths exceeding WHO guideline levels was assessed using both AirQ+ and BenMAP. We estimated that the health benefits of attaining the World Health Organization's air quality guidelines for PM_2.5 (annual average 5 ㎍/m³) would suggest an annual reduction of 26,128 (95% confidence interval [CI]: 17,363~34,024) and 26,853 (95% CI: 18,527~34,944) premature deaths. Conclusions: Our study provided useful information to policy makers and confirms that the reduction of PM_2.5 concentration would result in significant health benefits in Korea.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.62.1-62.1
• /
• 2015

Polarization of the light reflected off the Moon provides information on the size and composition of the particles in the lunar regolith. The mean particle size of the regolith can be estimated from the combination of the albedo and degree of polarization, while the color ratio of the parallel-component polarization (CP) has been suggested to be related to the amount of nanophase metallic iron (npFe^0) inside the regolith particles. Both the mean size and npFe^0 abundance of the particles have been used as maturity indicators of the regolith since sustained impacts of high energy particles and micro-meteoroids cause comminution of particles and production of npFe^0. Based on our multispectral polarimetric observations of the whole near side of the Moon in the U, B, V, R, and I bands, we compare the maps of the mean particle size, CP, and the optical maturity (OM). We find that the mean particle size map is sensitive to the most immature (~0.1 Gyr) soil, the OP map to the intermediate immaturity (a few 0.1 Gyr) soil, and the CP map to the least immature (~1 Gyr) soil.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.9-18
• /
• 2005

In order to systematically and visually understand well-known but qualitative and rotatively complicated relationships between synoptic fields in the BAIU season and heavy rainfall events in Japan, these synoptic fields were classified using the Self-Organizing Map (SOM) algorithm. This algorithm can convert complex nonlinear features into simple two-dimensional relationships, and was followed by the application of the clustering techniques of the U-matrix and the K-means. It was assumed that the meteorological field patterns be simply expressed by the spatial distribution of wind components at the 850 hPa level and Precipitable Water (PW) in the southwestern area including Kyushu in Japan. Consequently, the synoptic fields could be divided into eight kinds of patterns (clusters). One of the clusters has the notable spatial feature represented by high PW accompanied by strong wind components known as Low-Level Jet (LLJ). The features of this cluster indicate a typical meteorological field pattern that frequently causes disastrous heavy rainfall in Kyushu in the rainy season. From these results, the SOM technique may be an effective tool for the classification of complicated non-linear synoptic fields.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.3
• /
• pp.481-489
• /
• 2020

Safety and security during the handling of hazardous materials is a great concern for anyone in the field. One driving point in the security field is the ability to detect the source of the danger and take action against it as quickly as possible. Via the usage of a fully convolutional network, it is possible to create the label map of an input image, indicating what object is occupying the specific area of the image. This research employs the usage of U-net, which was constructed in biomedical field segmentation to segment cells, instead of the original FCN. One of the challenges that this research faces is the availability of ground truth with precise labeling for the dataset. Testing the network after training resulted in some images where the network pronounces even better detail than the expected label map. With better detailed label map, the network might be able to produce better segmentation is something to be studied in further research.