• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Journal of the Korean Applied Science and Technology
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• v.40 no.3
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• pp.534-546
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• 2023

In this study, we investigated the antioxidant and anti-winkle activity in human fibroblast cell (CCD-986sk) of Persimmon Leaves (PL) as a cosmetic ingredient. As a result of investigating antioxidant activity through electron-donating ability and ABTS⁺ radical scavenging assay, the PL showed concentration-dependent antioxidant activity similar to ascorbic acid, a control group, at a concentration of 1,000 ㎍/ml. As a result of investigating the anti-wrinkle effect through elastase inhibition and collagenase inhibition assay, the PL showed concentration-dependent antioxidant activity similar to epigallocatechin gallate, a control group, at a concentration of 1,000 ㎍/ml. As a result of measuring the synthesis rate of pro-collagen type I and the inhibition rate of MMP-1 in UVB-induced CCD-986sk cells, the control group EGCG showed a 90.2% pro-collagen synthesis rate at 20 ㎍/ml and PL showed an 88.5% synthesis rate at 30 ㎍/ml. In addition, the inhibition rate of MMP-1 of 33.0% and 40.8% were confirmed in EGCG 20 ㎍/ml and PL 30 ㎍/ml, respectively. As a result of measuring the protein expression of pro-collagen type I and MMP-1 in the PL through western blot, it was confirmed that the protein expression of pro-collagen type I increased, and MMP-1 decreased when the PL was treated together compared to the UVB alone group. According to the above experimental results, it is expected to be used as a natural product material for cosmetics by confirming that the PL prevent photoaging caused by UVB stimulation and have antioxidant and anti-wrinkle effects.

• Korea Science and Art Forum
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• v.20
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• pp.255-265
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• 2015

When it comes to how to define history·culture streets, people think of the streets as street environments that would create local identity in association with this local community's particular historical and cultural resources as well as urban streets. In order to build such streets, any relevant fields first need to apply some original design based on understanding on historical and cultural resources. With Street of Gaya in Gimhae selected as a research subject, this study aims to look into components and color characteristics of the history·culture street and finds ways to create other streets of that kind. As a frame to understand the history·culture streets, what this study would come up with is considered significant in that it helps the value to be re-recognized and promoted. In order to achieve the research goal, the study (1) extracted components of streetscapes referring to relevant previous researches and then, (2) analyzed a current status of these components of Street of Gaya via field investigation. (3) The study examined color characteristics of each of the components. Findings of the research are summarized as follows. (1) From a comprehensive point of view, the study categorized and subdivided the components of the history·culture street into nonphysical and physical elements. (2) After analyzing the current status of the components, the study learned that Street of Gaya basically consists of historical and cultural remains and sculptures as well as street facilities. (3) Results of the color investigation reported that the plan on designing of Street of Gaya had been processed with a focus laid on harmony of historical remains and cultural remains which are told to be natural components. However, the study also figured out that as long as relevant fields want to create different identity in each section and to efficiently deliver information, they should first prepare this smart design system to integrate each pieces of a streetscape as a whole.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.78-95
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• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2029-2035
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• 2014

In this study, we conducted the adsorption equilibrium and batch experiments of dissolved organic carbon (DOC) in the wastewater by granular activated carbon (GAC). The components of organic compound were Beef extract (1.8 mg/L), Peptone (2.7 mg/L), Humic acid (4.2 mg/L), Tannic acid (4.2 mg/L), Sodium lignin sulfonate (2.4 mg/L), Sodium lauryle sulfate (0.94 mg/L), Arabic gum powder (4.7 mg/L), Arabic acid (polysaccharide) (5.0 mg/L), $(NH_4)_2SO_4$ (7.1 mg/L), $K_2HPO_4$ (7.0 mg/L), $NH_4HCO_3$ (19.8 mg/L), $MgSO_4{\cdot}7H_2O$ (0.71 mg/L), The adsorption characteristics of DOC in synthetic wastewater was described using the mathematical model through a series of isotherm and batch experiments. It showed that there was linear adsorption region in the low DOC concentration (0~2.5 mg/L) and favorable adsorption region in high concentration (2.5~6 mg/L). The synthetic wastewater used was prepared using known quantities of organic and/or inorganic compounds. Adsorption modelling isotherms were predicted by the Freundlich, Langmuir, Sips and hybrid isotherm equations. Especially, hybrid isotherm of Linear and Sips equation was a good adsorption equilibrium in the region of the both the low concentration and high concentration. In applying carbon adsorption for treating water and wastewater, hybrid adsorption equation plus linear equation with Sips equation will be a good new adsorption equilibrium model. Linear driving force approximation (LDFA) kinetic equation with Hybrid (linear+Sips) adsorption isotherm model was successfully applied to predict the adsorption kinetics data in various GAC adsorbent amounts.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.609-617
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• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.2
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• pp.34-44
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• 2020

The purpose of this study was to investigate the difference in perceptions between gardens and park functions as recognized by two groups, Group A and Group B, in order to confirm the distinction between concepts and functions and then establish the importance of individual functions. The AHP was used to analyze the importance of each group's perceptions by dividing them into garden and park, Group A and non-Group A, respectively. In Group A, the importance of garden functions were considered in descending order of importance to be cultural function, ecological function, and social function. In the general group, ecological function, cultural function, and social function also appeared, but in a different order of importance. As for the park functions, Group A recognized the importance of functions in a similar order of importance to the gardens: cultural function, ecological function, and social function. Group B thought that social function, ecological function, and cultural function have the same significance. At the major classification level, Group A and Group B emphasized the social function of the parks. Group A recognized the importance of the garden's cultural function as the most important, whereas the general group emphasized the importance of the garden's ecological function. As for the mid-class level, Group A recognized the aesthetic beauty, health, ecological environment protection, and water circulation as important functions of the garden. For Group B, the ecological environment protection, aesthetic beauty, water cycle, and health were important. The concepts and functions of gardens and parks are still largely mixed but are gradually becoming differentiated. As a follow-up study, it is important to systematically manage the functions of gardens by establishing design, construction, and monitoring DB techniques for the garden type and examine the hierarchy of various other gardens.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.293-299
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• 2007

Intelligent pipeline inspection gauges (PIGs) are inspection vehicles that move along within a (gas or oil) pipeline and acquire signals (also called sensor data) from their surrounding rings of sensors. By analyzing the signals captured in intelligent PIGs, we can detect pipeline defects, such as holes and curvatures and other potential causes of gas explosions. There are two major data access patterns apparent when an analyzer accesses the pipeline signal data. The first is a sequential pattern where an analyst reads the sensor data one time only in a sequential fashion. The second is the repetitive pattern where an analyzer repeatedly reads the signal data within a fixed range; this is the dominant pattern in analyzing the signal data. The existing PIG software reads signal data directly from the server at every user#s request, requiring network transfer and disk access cost. It works well only for the sequential pattern, but not for the more dominant repetitive pattern. This problem becomes very serious in a client/server environment where several analysts analyze the signal data concurrently. To tackle this problem, we devise a fast in-memory cache manager, called T-Cache, by considering pipeline sensor data as multiple time-series data and by efficiently caching the time-series data at T-Cache. To the best of the authors# knowledge, this is the first research on caching pipeline signals on the client-side. We propose a new concept of the signal cache line as a caching unit, which is a set of time-series signal data for a fixed distance. We also provide the various data structures including smart cursors and algorithms used in T-Cache. Experimental results show that T-Cache performs much better for the repetitive pattern in terms of disk I/Os and the elapsed time. Even with the sequential pattern, T-Cache shows almost the same performance as a system that does not use any caching, indicating the caching overhead in T-Cache is negligible.

• Journal of Korean Ophthalmic Optics Society
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• v.19 no.3
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• pp.389-396
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• 2014

Purpose: The study examined dry eye symptoms of occupants in a newly constructed building and its effects on their work productivity and general activity. Methods: The study subjects were 33 office workers who spent more than eight hours per day on average in a new building constructed in the past three months. The indoor air quality of the new building was evaluated by measuring aldehydes, temperature and humidity. The level of dry eye symptoms was classified into normal, mild, moderate and severe by using the Ocular Surface Disease Index (OSDI). The experience of LASIK surgery, use of eye makeup, daily use time of a computer and smart-phone, and average daily working hours were also examined. The Work Limitation Productivity Questionnaire was used as the questionnaire about work productivity and general activity to measure the impairment level on a ten-point scale. Results: The concentration variation of formaldehyde in the office was $42.42{\pm}6.30{\mu}g/m^3$. The temperature and humidity were $26.2{\pm}0.70^{\circ}C$ and $40{\pm}1%$, respectively. The respondents with normal, mild, moderate and severe dry eye symptoms were 15.2%, 18.2%, 18.2% and 48.5%, respectively. The severity of dry eye symptoms and impairment of work productivity and general activity demonstrated high correlations of 0.599 and 0.655, respectively (p<0.001). Compared to the normal case, severe dry eye symptoms demonstrated significantly high impairment of work productivity and interruption of general activity (p<0.001). The case of serious dry symptoms showed the possibilities of having impairment level of work productivity and interruption of general activity above three points 3.26 times (p=0.032) and 2.25 times (p=0.045), respectively, higher than that of the normal case. Conclusions: It was confirmed that dry eye symptoms among office workers in a newly constructed building affects work productivity and general activity.