• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.157-167
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• 2006

During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.533-540
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• 2010

Dam is very important facility in water supply and flood control. Therefore study needs to analyze reservoir capacity accurately to manage Dam efficiently. This study compared time series reservoir capacity using multi-dimensional spatial information to Chungju Dam reservoir and major conclusions are as follows. First, LiDAR and multi beam echo sounder survey were carried out in land zone and water zone of Dam reservoir area. And calibration process was performed to enhance the accuracy of survey data and it could be constructed that multi dimensional spatial information which was clearly satisfied with the standard of tolerance error by validation with ground control points. Reservoir capacity by water level was calculated using triangle irregular network from detailed topographic data that was constructed by linked with airborne LiDAR and multi beam echo sounder data, and curve equation of reservoir capacity was developed through regression analysis in 2008. In the comparison of the reservoir capacity of 2008 with those of 1986 and 1996, the higher water level goes, total reservoir capacity of 2008 showed decrease because of the increase of sediment in reservoir. Also, erosion and sediment area could be analyzed through calculating the reservoir capacity by the range of water level. Especially the range of water level as 130.0~135.0 which is the upper part of average water level, showed the highest erosion characteristics during 1986~2008 and 1996~2008 and it is considered that the erosion of reservoir slant by heavy rainfall is major reason.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.381-388
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• 2023

Through artificial neural network education using spreadsheets, non-major undergraduate students can understand the operation principle of artificial neural networks and develop their own artificial neural network software. Here, training of the operation principle of artificial neural networks starts with the generation of training data and the assignment of correct answer labels. Then, the output value calculated from the firing and activation function of the artificial neuron, the parameters of the input layer, hidden layer, and output layer is learned. Finally, learning the process of calculating the error between the correct label of each initially defined training data and the output value calculated by the artificial neural network, and learning the process of calculating the parameters of the input layer, hidden layer, and output layer that minimize the total sum of squared errors. Training on the operation principles of artificial neural networks using a spreadsheet was conducted for undergraduate non-major students. And image training data and basic artificial neural network development results were collected. In this paper, we analyzed the results of collecting two types of training data and the corresponding artificial neural network SW with small 12-pixel images, and presented methods and execution results of using the collected training data for Orange machine learning model learning and analysis tools.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.4
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• pp.323-330
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• 2023

The skin's barrier structure is formed through the differentiation process of epidermal keratinocytes. It consists of corneocytes that are composed of keratin proteins and lipids that fill the spaces between them. During this process, the lipids such as phospholipid that made up the membrane of the basal layer cells of the epidermis are decomposed and replaced with newly synthesized components like ceramide. In this study, the effect of ginsenoside Rg3 components on the packing of the intercellular lipid structure of the skin barrier and the barrier function was confirmed. To confirm this, Rg3 components were treated during the differentiation process of 3D epidermal cells. The FT-IR and TEWL analysis on 3D epidermis showed an enhancement in the orthorhombic lipid packing and an improvement in barrier function. Additionally, in HaCaT cells, an increase in the expression of EVOL1 and EVOL4, which synthesize long-chain lipids, was detected, along with a decrease in CERS6, which synthesizes short-chain ceramide, and an increase in ACER6, which decomposes ceramide using phytosphingosine. This suggests the possibility that Rg3 affects lipid synthesis during the epidermal differentiation process, resulting in changes in barrier function.

• Korean Journal of Optics and Photonics
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• v.34 no.6
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• pp.241-247
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• 2023

We examine the spectral characteristics of laser-induced periodic surface structures (LIPSSs) formed on an amorphous silicon film irradiated by a 355-nm nanosecond laser. A Gaussian beam with a diameter of 196 ㎛ is used to perform a two-dimensional raster scan. The laser's pulse number is varied from 190 to 280, and its intensity is adjusted within 100-130 mJ/cm². LIPSSs with a periodicity of approximately 330 nm form on the surface of the Si film, aligned perpendicular to the laser's polarization. Transmission spectra of the samples show dips around 700 nm for transverse electric polarization and around 500 nm for transverse magnetic polarization. The features are investigated with a one-dimensional-grating model using a rigorous coupled-wave analysis. Simulations confirm that the observed dips are due to the resonant modes, depending on the polarization.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.859-873
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• 2023

Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea's first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.

• Journal of Life Science
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• v.33 no.12
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• pp.967-977
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• 2023

Rubus crataegifolius (RC) is a traditional Asian medicinal plant belonging to the Rosaceae family. The fruits of RC are known to prevent adult diseases through antioxidants. In this study, the effects of RC extract (RCex) on obesity and nonalcoholic fatty liver disease (NAFLD) were evaluated in animal models. Twenty-eight male C57BL/6J mice were induced to become obese for 8 weeks and then the extract was orally administered for 8 weeks. RCex reduced body weight, adipose tissue, liver weight. RCex improved biochemical biomarkers including lipid metabolism (alanine aminotransferase (ALT), aspartate aminotransferase (AST), plasma triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol). The activation of AMP-activated protein kinase (AMPK) reduced the expression of adipogenesis genes (liver × receptor (LXR), sterol regulatory element-binding protein-1c (SREBP-1c), fatty acid synthesis (FAS), acetyl-CoA carboxylase 1 (ACC1) and the effect of enhancing carnitine palmitoyltransferase (CPT) activity by RCex was verified. RCex also influence on plasma production of hormones (adiponectin & leptin) related on energy expenditure and metabolism. In addition, we confirmed that RCex improved glucose intolerance in HFD-induced obese rats. RCex was first demonstrated to have anti-obesity as well as anti-NAFLD effects by regulating fatty acid oxidation and fatty acid synthesis by phosphorylation of AMPK. This suggests that RCex could be a good supplement for the prevention of obesity and related NAFLD.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.