• 제목/요약/키워드: 데이터베이스 특성

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Construction of a Sub-catchment Connected Nakdong-gang Flood Analysis System Using Distributed Model (분포형 모형을 이용한 소유역 연계 낙동강 홍수해석시스템 구축)

  • Choi, Yun-Seok;Won, Young-Jin;Kim, Kyung-Tak
    • Proceedings of the Korea Water Resources Association Conference
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    • 한국수자원학회 2018년도 학술발표회
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    • pp.202-202
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    • 2018
  • 본 논문에서는 분포형 강우-유출 모형인 GRM(Grid based Rainfall-runoff Model)(최윤석, 김경탁, 2017)을 이용해서 낙동강 유역을 대상으로 대유역 홍수해석시스템을 구축하고, 유출해석을 위한 실행시간을 평가하였다. 유출모형은 낙동강의 주요 지류와 본류를 소유역으로 구분하여 모형을 구축하고, 각 소유역의 유출해석 결과를 실시간으로 연계할 수 있도록 하여 낙동강 전체 유역의 유출모형을 구축하였다. 이와 같이 하나의 대유역을 다수의 소유역시스템으로 분할하여 모형을 구축할 경우, 유출해석시스템 구성이 복잡해지는 단점이 있으나, 소유역별로 각기 다른 자료를 이용하여 다양한 해상도로 유출해석을 할 수 있으므로, 소유역별 특성에 맞는 유출모형 구축이 가능한 장점이 있다. 또한 각 소유역시스템은 별도의 프로세스로 계산이 진행되므로, 대유역을 고해상도로 해석하는 경우에도 계산시간을 단축할 수 있다. 본 연구에서는 낙동강 유역을 20개(본류 구간 3개, 1차 지류 13개, 댐상류 4개)의 소유역으로 분할하여 계산 시간을 검토하였으며, 최종적으로 21개(본류 구간 3개, 1차 지류 13개, 댐상류 5개)의 소유역으로 분할하여 유출해석시스템을 구축하였다. 댐 상류 유역은 댐하류와 유량전달이 없이 독립적으로 모의되고, 댐과 연결된 하류 유역은 관측 방류량을 상류단 하천의 경계조건으로 적용한다. 지류 유역은 본류 구간과 연결되고, 지류의 계산 유량은 본류와의 연결지점에 유량조건으로 실시간으로 입력된다. 이때 본류와 지류의 유량 연계는 데이터베이스를 매개로 하였다. 유출해석시스템의 성능을 평가하기 위해서 Microsoft 클라우드 서비스인 Azure를 이용하였다. 낙동강 유역을 20개 소유역으로 구성한 경우에서의 유출해석시스템의 속도 평가 결과 Azure virtual machine instance DS15 v2(OS : Windows Server 2012 R2, CPU : 2.4 GHz Intel $Xeon^{(R)}$ E5-2673 v3 20 cores)에서 1.5분이 소요 되었다. 계산시간 평가시 GRM은 'IsParallel=false' 옵션을 적용하였으며, 모의 기간은 24시간을 기준으로 하였다. 연구결과 분포형 모형을 이용한 대유역 유출해석시스템 구축이 가능했으며, 계산시간도 충분히 단축할 수 있었다. 또한 추가적인 CPU와 병렬계산을 적용할 경우, 계산시간은 더 단축될 수 있으며, 이러한 기법들은 분포형 모형을 이용한 대유역 유출해석시스템 구축시 유용하게 활용될 수 있을 것으로 판단된다.

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MLP-based 3D Geotechnical Layer Mapping Using Borehole Database in Seoul, South Korea (MLP 기반의 서울시 3차원 지반공간모델링 연구)

  • Ji, Yoonsoo;Kim, Han-Saem;Lee, Moon-Gyo;Cho, Hyung-Ik;Sun, Chang-Guk
    • Journal of the Korean Geotechnical Society
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    • 제37권5호
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    • pp.47-63
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    • 2021
  • Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

Korea Stress Map 2020 using Hydraulic Fracturing and Overcoring Data (수압파쇄와 오버코어링 자료를 활용한 한국응력지도 2020)

  • Kim, Hanna;Synn, Joong-Ho;Park, Chan;Song, Won Kyong;Park, Eui Seob;Jung, Yong-Bok;Cheon, Dae-Sung;Bae, Seongho;Choi, Sung-Oong;Chang, Chandong;Min, Ki-Bok
    • Tunnel and Underground Space
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    • 제31권3호
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    • pp.145-166
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    • 2021
  • Korea Stress Map database is built by integrating actual data of 1,400 in-situ stress measurements using hydraulic fracturing and overcoring method in South Korea. Korea Stress Map 2020 is presented based on the guideline proposed by World Stress Map Project. As detailed data, stress ratio and maximum horizontal stress direction distribution for each region are also presented. The dominant maximum horizontal stress direction in the Korean Peninsula is from northeast to southeast, and the magnitude of the in-situ stress is relatively distributed. There is some stress heterogeneity caused by local characteristics such as topographical and geological properties. We investigated case studies in which the in-situ stress was affected by mountainous topography, difference in rock quality of fracture zone, presence of mine or underground cavities, and geological structure of fault zone.

[Retracted]Case Study of Microseismic Monitoring System Installation based on Underground Mine Communication System ([논문철회]지하광산 갱내통신 기반 미소진동 모니터링 체계 구축 사례)

  • Heo, Seung;Choi, Yongkun
    • Tunnel and Underground Space
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    • 제32권2호
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    • pp.120-130
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    • 2022
  • In this study, the applicability of the microseismic monitoring system based on the underground mine communication system has been verified by operation test in the domestic underground mine. The microseismic data consists of wavelet data and meta-data for mine safety management, and both data should be transferred, stored, analyzed and managed with proper method according to the purpose and size of each data. In order to select the optimal communication system for the microseismic monitoring system considering the underground environment as well as properties of data, various types of communication system have been tested and compared during operation test after installing the optical cable communication system, 2.4 GHz and 900 MHz wireless communication system through the underground mine tunnel and overground area of the test site. The integrated microseismic monitoring software, which was developed to secure the stability of data management and ease of use, has been updated according to findings from operation test. Through the operation test of the microseismic monitoring system including the communication system and the monitoring software, the technical basis was established corresponding to various requirements of the domestic mine for adoption of the microseismic monitoring system.

The Effects of Self-Management Program and Its Measurement for the Elderly with Chronic Illness in the community (국내 지역사회 거주 만성질환 노인 대상 자기관리 프로그램의 효과 및 측정도구에 대한 고찰)

  • Shin, Ga-In;Park, Hae Yean
    • 한국노년학
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    • 제40권2호
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    • pp.257-267
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    • 2020
  • The purpose of this study is to identify the effectiveness of self-management programs and the measurement used for elderly people with chronic illness living in the community. Databases used for study search were Google Scholar, RISS, and Dbpia. And research questions were selected based on the PICO framework. We searched the study published from January 2010 to September 2019 and selected the final six studies by applying inclusion criteria and exclusion criteria. As a result, the selected study had qualitative level of Level 1-2. In general characteristics of the program, nurses conducted the most programs, and the program was operated for 50 elderly people or less. In addition, the program was conducted mainly in public health centers, senior centers. The subjects were the most studies for chronic patients with hypertension. The dependent variables of the program covered the cognitive domains in all the studies, and many of the studies measured the physical domains as the dependent variables. The results of this study provide the effectiveness of self-management intervention for the elderly with chronic diseases living in the community, and highlight the need for the development of programs for chronic diseases in the community. In addition, this study suggests measuring tools related to various cognitive, physical, mental, social and quality of life of the elderly, and suggests the necessity of multidisciplinary research.

Personalized insurance product based on similarity (유사도를 활용한 맞춤형 보험 추천 시스템)

  • Kim, Joon-Sung;Cho, A-Ra;Oh, Hayong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제26권11호
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    • pp.1599-1607
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    • 2022
  • The data mainly used for the model are as follows: the personal information, the information of insurance product, etc. With the data, we suggest three types of models: content-based filtering model, collaborative filtering model and classification models-based model. The content-based filtering model finds the cosine of the angle between the users and items, and recommends items based on the cosine similarity; however, before finding the cosine similarity, we divide into several groups by their features. Segmentation is executed by K-means clustering algorithm and manually operated algorithm. The collaborative filtering model uses interactions that users have with items. The classification models-based model uses decision tree and random forest classifier to recommend items. According to the results of the research, the contents-based filtering model provides the best result. Since the model recommends the item based on the demographic and user features, it indicates that demographic and user features are keys to offer more appropriate items.

A Systematic Review of Group Programs for Community-dwelling Elderly (지역사회 거주 노인 대상의 그룹 프로그램에 대한 체계적 고찰)

  • Jeong, Eun-Hwa;Ju, Yumi
    • Therapeutic Science for Rehabilitation
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    • 제10권2호
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    • pp.23-36
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    • 2021
  • Objective : The purpose of this study was to analyze group programs for the elderly living in communities and to provide basic data for applying effective occupational therapy programs for the elderly in the community. Methods : From January 2009 to December 2019, articles on group programs for the elderly in the community were searched for in the NDSL, DBPia, Riss, and PubMed databases. Based on the inclusion and exclusion criteria, a total 16 out of the 147 identified studies were selected and analyzed. This review analyzed the characteristics of the participants, contents of the group program, session and duration of the intervention, outcome measures, and effect of the group program. Results : Single group pre-post test studies with evidence level III were most common (8, 50.0%), and five (31.3%) of the studies were conducted on the community-dwelling elderly. Across all the 16 studies, there were 10 types of group programs, and the most frequently used was an exercise group program (25.0%). According to the analysis of the group program period, sessions and time, the intervention period was most commonly 12 weeks (37.5%), with 8 sessions or 12 sessions (25.0%). The intervention time in the group program was most commonly 60 minutes (43.8%). Conclusion : This study can be used as a basis for the development of effective group programs for the elderly and patients with dementia in community-based long-term care services.

Application Method of Regular Expressions and Suffixes to improve the Accuracy of Automatic Domain Identification of Public Data (공공데이터의 도메인 자동 판별 정확도 향상을 위한 정규표현식 및 접미사 적용 방법)

  • Kim, Seok-Kyoun;Lee, Kwanwoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제22권4호
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    • pp.81-86
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    • 2022
  • In this work, we propose a method for automatically determining the domain of columns of file data structured by csv format. New data can be generated through convergence between data and data, and the consistency of the joined columns must be maintained in order for these new data to become an important resource. One of the methods for measuring data quality is a domain-based quality diagnosis method. Domain is the broadest indicator that defines the nature of each column, so a method of automatically determining it is necessary. Although previous studies mainly studied domain automatic discrimination of relational databases, this study developed a model that can automate domains using the characteristics of file data. In order to specialize in the domain discrimination of file data, the data were simplified and patterned using a regular expression, and the contents of the data header corresponding to the column name were analyzed, and the suffix used was used as a derived variable. When derivatives of regular expressions and suffixes were added, the result of automatically determining the domain with an accuracy of 95% greater than the existing method of 87% was derived. This study is expected to reduce the quality measurement period and number of people by presenting an automation methodology to the quality diagnosis of public data.

Comparative Analysis and Implications of Command and Control(C2)-related Information Exchange Models (지휘통제 관련 정보교환모델 비교분석 및 시사점)

  • Kim, Kunyoung;Park, Gyudong;Sohn, Mye
    • Journal of Internet Computing and Services
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    • 제23권6호
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    • pp.59-69
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    • 2022
  • For effective battlefield situation awareness and command resolution, information exchange without seams between systems is essential. However, since each system was developed independently for its own purposes, it is necessary to ensure interoperability between systems in order to effectively exchange information. In the case of our military, semantic interoperability is guaranteed by utilizing the common message format for data exchange. However, simply standardizing the data exchange format cannot sufficiently guarantee interoperability between systems. Currently, the U.S. and NATO are developing and utilizing information exchange models to achieve semantic interoperability further than guaranteeing a data exchange format. The information exchange models are the common vocabulary or reference model,which are used to ensure the exchange of information between systems at the content-meaning level. The information exchange models developed and utilized in the United States initially focused on exchanging information directly related to the battlefield situation, but it has developed into the universal form that can be used by whole government departments and related organizations. On the other hand, NATO focused on strictly expressing the concepts necessary to carry out joint military operations among the countries, and the scope of the models was also limited to the concepts related to command and control. In this paper, the background, purpose, and characteristics of the information exchange models developed and used in the United States and NATO were identified, and comparative analysis was performed. Through this, we intend to present implications when developing a Korean information exchange model in the future.

Predicting Concentrations of Soil Pollutants and Mapping Using Machine Learning Algorithms (기계학습을 통한 토양오염물질 농도 예측 및 분포 매핑)

  • Kang, Hyewon;Park, Sang Jin;Lee, Dong Kun
    • Journal of Environmental Impact Assessment
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    • 제31권4호
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    • pp.214-225
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    • 2022
  • This study emphasized the soil of environmental impact assessment to devise measures to minimize the negative impact of project implementation on the environment. As a series of efforts for impact assessment procedures, a national inventory-based database was established for urban development projects, and three machine learning model performance evaluation as well as soil pollutant concentration distribution mapping were conducted. Here, nine soil pollutants were mapped to the metropolitan area of South Korea using the Random Forest model, which showed the best performance. The results of this study found that concentrations of Zn, F, and Cd were relatively concerned in Seoul, where urbanization is the most active. In addition, in the case of Hg and Cr6+, concentrations were detected below the standard, which was derived from a lack of pollutants such as industrial and industrial complexes that affect contents of heavy metals. A significant correlation between land cover and pollutants was inferred through the spatial distribution mapping of soil pollutants. Through this, it is expected that efficient soil management measures for minimizing soil pollution and planning decisions regarding the location of the project site can be established.