• 한국농림기상학회지
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• 제6권4호
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• pp.235-241
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• 2004

1월의 최저기온을 대상으로 1951년부터 2000년까지 14개 지점의 관측자료를 분석한 결과 11개 지점에서 전반기(1951-1980)에 비해 후반기(1971-2000)의 연차 변이가 오히려 감소한 것으로 나타났다 표준편차로 표현할 경우 제주, 전주, 울릉도를 제외한 나머지 11개 지점에서 많게는 0.35(서울)에서 적게는 0.03(강릉)까지 고르게 연차변이가 감소하였다. 이는 최근의 난동화 경향과 함께 겨울철 최저기온의 연차변이가 더 심해지고 있다는 당초의 예상과 다른 결과이다 연차변이의 공간분포양상은 최저기온의 절대값과 정의 상관을, 관측점의 해발고도와는 부의 상관을 보였다. 이 관계를 이용하여 남한전역의 1월 최저기온 30년 표준 편차 분포도를 작성하였으며, 이를 토대로 재현기간별로 기대되는 전국의 극최저기온 분포도를 제작하여 지역별 동해위험 평가에 이용토록 하였다.

• 대한건축학회논문집:구조계
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• 제35권8호
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• pp.157-168
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• 2019

Modular Construction is regarded as having enhanced safety compared to traditional construction since most of modular manufacturing process in plants. Unlike general consideration for safety in modular construction, several industrial accident data and studies have pointed out that the accident rate of modular construction is not enough less as much as the practitioners have expected. It means that there is a clear need for improvement of safety management in modular construction. To enhance safety, it is necessary to identify the type and cause of accident through accident cases in order to prevent safety accident in advance. In this consideration, this study analyzed the types and causes of accidents through root cause analysis procedure with accident cases of U.S. OSHA. The classification was carried out in the order of process type, accident type and cause of accident. By following the classification criteria in this study, the causal factor was derived and the root cause map was created. Based on the analysis results, cross-analysis was conducted and it is shown that activity characteristics of modular construction are related to safety accidents. In addition, prevention methods to reduce safety accident by major activity are presented in terms of organizational, educational and technical aspects. This study contributes that the result can be used as the basic safety management in the manufacturing and construction process of modular construction.

• 한국융합학회논문지
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• 제12권2호
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• pp.147-154
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• 2021

이 연구는 가상 피팅 서비스에서 제공하는 피팅창 구조와 인터페이스 디자인에 관한 것으로 현재 시장에서 유통 중인 유관 서비스 사례를 분석하고 FGI를 통해 서비스에 대한 사용자의 니즈를 파악하였다. 연구의 결과로 기존 웹페이지에서 피팅창을 찾을 때 아이콘의 크기가 작고 가시성이 낮은 문제는 사이트 접속과 동시에 피팅창이 열리게 하였고, 피팅맵을 초기 사용자도 잘 이해 할 수 있게 정보 전달 관련 문제를 해소하였다. 또한 사용자 성향에 필요한 항목을 제공하여 정확하고 쉽게 서비스를 사용할 수 있도록 디자인 하였다. 본 연구의 결과는 이어지는 가상 피팅 서비스 연구의 기초 자료로 활용되고 관련 산업에 종사하는 마케터에게 좋은 시사점을 제공할 것으로 기대한다.

• Investigative Magnetic Resonance Imaging
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• 제25권2호
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• 영어영문학
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• 제57권4호
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• pp.553-580
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• 2011

This article addresses how the British Empire administered the discipline of space in nineteenth century Ireland. Space control is a part of modern disciplinary practices. I approach this issue in light of the two modern mapping of space: the geometric mapping of space and the Romantic mapping of space. The former, as seen in map-making, is characterized by imposing a standardized, stratified grid on space by eliminating local characteristics of nature. On the other hand, the latter, as shown in picturesque landscaping, aims to balance a close-up observation of nature and a far-sighted view of it, with the result of creating an ironic tension of local diversity and perspectival totality. These modern disciplinary projects of space repeat themselves in the British management of the colonized Irish territory. As the British conquer other lands, they put to good use both geometric and Romantic disciplinary methods of space. Supervising the Ordnance Survey of Ireland from 1824 to 1846, Thomas Frederick Colby, British Director of Ordnance Survey, made a mathematically strict and scientific mapping of Ireland as a scale of six inches to one mile. Parallelled to this geometric colonization of space, the Romantic colonization of space is efficiently used for the Empire's management of Ireland as well. British tourists and pro-unionist Anglo-Irish landed gentries transform it into the nature of picturesque beauty; Ireland's wild boglands turn aesthetically into desolate but beautiful scenery. Picturesque landscape in England is reborn as an aesthetics of desolation in Ireland.

• Genomics & Informatics
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• 제19권4호
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• 대한원격탐사학회지
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• 제38권4호
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• pp.395-409
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• 2022

The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

• Earthquakes and Structures
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• 제24권1호
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• pp.37-51
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• 2023

Türkiye has made significant changes and updates in both seismic risk maps and design codes over time, as have other countries with high seismic risk. In this study, the last two seismic design codes and risk maps were compared for the Aegean Region (Western Türkiye) where the earthquake risk has once again emerged with the 2020 Izmir Earthquake (Mw=6.9). In this study, information about the seismicity of the Aegean Region was given. The seismic parameters for all provinces in the region were compared with the last two earthquake risk maps. The spectral acceleration coefficients of all provinces have increased and differentiated with the current seismic hazard map as a result of the design spectra used on a regional basis have been replaced by the geographical location-specific design spectra. In addition, section damage limits were obtained for all provinces within the scope of the last two seismic design codes. Structural analyses for a sample reinforced-concrete building were made separately for each province using pushover analysis. The deformations in the cross-sections were compared with the limit states corresponding to the damage levels specified in the last two seismic design codes for the region. Target displacement requests for all provinces have decreased with the current code. The differentiation of geographical location-specific design spectra both in the last two seismic design code and between provinces has caused changes in section damages and building performance levels. The main aim of this study is to obtain and compare both seismic and structural analysis results for all provinces in the Aegean Region (Western Türkiye).

• 스마트미디어저널
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• 제11권7호
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• pp.61-69
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• 2022

학습된 머신러닝은 시간 경과에 따른 학습 모델과 학습 데이터 측면의 표류 현상이 발생과 동시에 머신러닝의 성능이 퇴화하게 된다. 이를 해결하기 위한 방안으로 머신러닝의 재학습 시기를 결정하기 위한 ML 표류의 개념과 평가 방법을 제안하고자 한다. 딸기와 선명도에 따른 XAI 테스트 및 사과 이미지의 XAI 테스트를 진행하였다. 딸기의 경우 선명도 값에 따른 ML 모델의 XAI 분석의 변화는 미미하였으며 사과 이미지의 XAI의 경우 사과는 정상적으로 객체 분류 및 히트맵 영역을 표시하였으나 사과꽃 및 꽃봉오리의 경우 그 결과가 딸기나 사과에 비해 미미하였다. 이는 사과꽃 및 꽃봉오리의 학습 이미지 수가 부족하기에 발생한 것으로 예상되며 추후 더 많은 사과꽃 및 꽃봉오리 이미지를 학습하여 테스트할 계획이다.

• 지능정보연구
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• 제16권4호
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• pp.147-157
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• 2010

아이폰의 등장과 함께 스마트 폰에 대한 관심이 높아지고, 통신사업자를 통해야만 가능했던 다양한 서비스가 스마트 폰을 통해서 직접 제공할 수 있는 환경이 가능해졌다. 전세계적으로 해외 관광객이 증가하면서 관광가이드 없이 자신의 노력으로 여행을 다니는 개인관광객도 증가하고 있다. 그러나 우리나라를 방문하는 외국인들이 개인적으로 여행을 즐기기에는 언어소통이나 제공되는 정보의 부족으로 어려움을 느끼고 있다. 본 연구에서는 스마트 폰이 탑재하고 있는 GPS와 WiFi 또는 3G 무선망을 통해서 사전에 설정된 관광 정보 카테고리에 따라서 관광객의 위치에 따른 관련 정보를 자동으로 제공함으로써 관광객의 편의성을 높이는 서비스 기술을 개발하였다. 개발된 서비스는 인사동을 대상으로 시험하였으며, 사용자의 선택과 같은 불편함 없이 주변정보를 제공함으로써 관광에 대한 편의성을 최대한 높였다.