• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.1-13
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• 2021

In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.407-413
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• 2022

In this study, the empirical formula for evaluating cable tension based on long-term measurement for about 3 years according to temperature change was proposed by proving the correlation between the expansion joint displacement of the upper road bridge and the cable tension of the lower railway bridge. The tension prediction results using the empirical formula for tension evaluation each cables proposed in this study were found to be in good agreement with the cable tension using the vibration method within 3%. Therefore, it was analyzed that it could be applied together with the vibration method that was an experimental technique, to predict and evaluate the cable tension in serviced railway steel composite bridge. As a result of applying the estimated temperature calculated by the empirical formula for expansion proposed in this study to the empirical formula, it was analyzed that a high level of reliability could be secured when compared with the vibration method. Therefore, it is judged that the empirical formula for cable tension evaluation reflecting the estimated temperature proposed in this study can be used to predict the tension of cables according to climate change in the future and establish a maintenance plan.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1490-1499
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• 2022

Arrhythmia is a condition in which the heart has an irregular rhythm or abnormal heart rate, early diagnosis and management is very important because it can cause stroke, cardiac arrest, or even death. In this paper, we propose arrhythmia classification using hybrid combination model of CNN-BLSTM. For this purpose, the QRS features are detected from noise removed signal through pre-processing and a single bit segment was extracted. In this case, the GAN oversampling technique is applied to solve the data imbalance problem. It consisted of CNN layers to extract the patterns of the arrhythmia precisely, used them as the input of the BLSTM. The weights were learned through deep learning and the learning model was evaluated by the validation data. To evaluate the performance of the proposed method, classification accuracy, precision, recall, and F1-score were compared by using the MIT-BIH arrhythmia database. The achieved scores indicate 99.30%, 98.70%, 97.50%, 98.06% in terms of the accuracy, precision, recall, F1 score, respectively.

• Journal of the Korea Institute of Building Construction
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• v.22 no.2
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• pp.207-218
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• 2022

Changes in megatrends occurring within the spatial range of the production process can be critical factors that affect the performance of unit projects in construction industry, one of the representative order industries. Although changes in the megatrend are a prerequisite for successful performance achievement, previous studies suggested methods for performance measurement and management within the production process as major results. Accordingly, this study analyzed the megatrend related to domestic construction projects and presented critical impact factors(CIFs) that can be affect a project's performance. CIFs were set by combining keywords derived by reviewing major contents of related laws and policies and future strategy reports, and the importance of each indicator was quantitatively analyzed using analytic hierarchy process(AHP). It is expected that the findings of this study can provide meaningful basic data that the various stakeholders in a construction project can refer to when establishing the strategies to achieve successful performance.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.161-171
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• 2009

In this paper, we propose an automatic method for setting data constraints of a data cleansing service, which is for managing the quality of data exchanged between composite services based on SOA(Service-Oriented Architecture) and enables to minimize human intervention during the process. Because it is impossible to deal with all kinds of real-world data, we focus on business data (i.e. costumer order, order processing) which are frequently used in services such as CRM(Customer Relationship Management) and ERP(Enterprise Resource Planning). We first generate an extended-element vector by extending semantics of data exchanged between composite services and then build a rule-based system for setting data constraints automatically using the decision tree learning algorithm. We applied this rule-based system into the data cleansing service and showed the automation rate over 41% by learning data from multiple registered services in the field of business.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.59-59
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• 2020

온실가스 증가로 전구평균기온은 지속적으로 상승하고 있으며, 이러한 지구시스템 변화는 수자원의 시·공간적인 변동을 증대시킬 것으로 전망된다. 보다 적극적인 기후변화 대응을 위해 2015년 파리협정이 채택됨에 따라 전 세계에서는 온실가스 감축을 실천하고 있으며, 선진국에서는 산업화 이전 대비 1.5℃ 및 2.0℃ 전구기온상승에 따른 분야별 영향평가 및 적응방안을 마련하고 있다. 그러나 국내의 경우 아직까지 전구기온 상승에 따른 수자원 영향평가가 미흡한 실정이다. 본 연구에서는 AR5 기후변화 시나리오를 기반으로 1.5℃ 및 2.0℃ 전구기온 상승으로 인한 국내 수자원 변화 특성을 분석하였다. 이를 위해 몬순특성을 고려하여 적정 5 GCMs을 선정하였으며, 시간샘플링 기법을 활용하여 1.5℃ 및 2.0℃ 전구기온 상승시기를 추정하였다. 통계적상세화 기법을 적용하여 상세 기후변화 시나리오를 생산하고, 수문모형(VIC)에 적용하여 미래 수문변화를 전망하였다. 과거 대비 1.5℃, 2.0℃ 전구기온 상승에 따른 수문기상인자의 변화를 분석한 결과 연평균 강수량 및 유출량은 전구기온상승에 따라 증가하며, 계절별 변동성은 심화될 것으로 전망되었다. 유출량의 변화는 강수량 변화경향과 대체로 일치하였으나, 강수량 대비 전망결과의 불확실성이 크게 나타났다. 한편, 수문순환은 전 지역에서 가속화되는 것으로 확인되었으며, 모든 GCM의 전망결과에서 동일한 경향을 보였다. 수문기상인자(강수량, 증발산량, 유출량)의 강도별 발생빈도 및 총량은 저강도 구간에서 감소, 고강도 구간에서 증가하는 것으로 분석되었다. 이러한 특성은 강수량 및 유출량의 극대값 증가에 기여하여 수자원 관리의 어려움을 가중시킬 것으로 예상된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.431-431
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• 2021

4차 산업혁명의 도래로 사회기반시설물의 계획 및 운영관리에 있어 데이터 분석을 통한 가치추출에 대한 관심은 매우 높은 상황이다. 데이터의 가용성과 접근성, 정부 지원 등을 평가하는 공공데이터 개방지수에서 한국은 1점 만점에 0.93점을 획득하여 경제협력개발기구 회원국 중 1위(2019년 기준)를 할 정도로 매우 높은 수준(평균 0.60점)이다. 그러나 공식적으로 발표 및 배포되는 사회기반시설물 관련 정보와 심도 있는 연구 분석이 필요한 정보는 접근이 여전히 제한적이라 할 수 있다. 특히 대표적인 사회기반시설물인 상수도시스템은 대부분 국가중요시설로 지정되어 있어 다양한 정보를 획득하고 분석하는데 제약이 존재하며, 관련 국가통계인 상수도통계에서는 누수사고 등과 같은 비정상적 상황에 대한 사고지점, 원인 등과 같은 세부정보는 제공하고 있지 않다. 본 연구에서는 웹크롤링 및 빅데이터 분석기술을 활용하여 과거 일정기간 발생한 지자체의 상수도 누수사고 관련 뉴스를 전수조사하고 도출된 사고건수를 국가 공인 정보인 상수도통계자료와 비교·분석하였다. 독립적인 누수사고 기사를 추출하기 위해서 중복기사의 제거, 누수 관련 키워드 정립, 상수도분야 이외의 관련기사 제거 등의 절차가 필요하며, 이와 같은 기법은 R프로그래밍을 통해 구현되었다. 추가적으로 뉴스기사의 자연어 처리기반 정보추출기법을 통해 누수사고 건수 뿐만 아니라 사고발생일, 위치, 원인, 피해정도, 그리고 대상 관로의 크기 등을 획득하여 상수도 통계에서 제시하고 있는 정보보다 많은 가치를 추출하여 연계할 수 있는 방안을 제시하였다. 제시된 방법론을 국내 A광역시에 적용하여 누수사고 건수를 비교한 결과 상수도통계에서 제시하고 있는 누수발생건수와 유사한 규모의 사고건수를 뉴스기사분석을 통해 도출할 수 있었다. 제안된 방법론은 추가적인 정보의 추출이 가능하다는 점에서 향후 활용성이 높을 것으로 기대된다.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.93-102
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• 2023

Building supervision can be defined as a major task that involves managing and supervising the construction process to support the creation of high-quality results. To successfully perform supervision work, it is necessary to collect various information generated in uncertain field conditions, but today, supervision is performed based on documents such as reports, so there are limitations in collecting information. In fact, it has also been reported that the recent collapse of an apartment building in Korea was caused by limitations of information communication in th supervision work. Accordingly, this study analyzed the types of digital technologies that can be used to improve the efficiency of building supervision work, and presented the prioritized application of them. Priority application was quantitatively evaluated using analytic hierarchy process on data through a survey. It is expected that the results of this study can be used as basic data to set the roadmap of digital technology for building supervision in the future.

• Korean Journal of Construction Engineering and Management
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• v.18 no.2
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• pp.58-70
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• 2017

The planning for material lifting operations is one of the key processes in high-rise building construction. Several previous studies have used rough calculations by referring to existing practices or establishing a target value for lifting cycle time or operating rate. Therefore, the purpose of this study is to propose a material lifting process optimization method for reducing the lifting cycle time and increasing the operating rate. In this study, we improve the cyclic operation network (CYCLONE) modeling method that considers the duration and zone information of each work task. This method can be used to hand over work tasks to another crew group in the work process. According to this methodology, this study optimizes the material lifting process, performs a sensitivity analysis, and evaluates the field applicability of the proposed material lifting process optimization method. Therefore, the optimized process was then applied to a high-rise building construction site. The lifting work process time and operating rate for the simulated as - is lifting process data, optimized process data, and field application result data were compared for each lifting height. From this comparison, the effectiveness of the optimization methodology was confirmed.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.2
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• pp.49-57
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• 2015

The purpose of this study is to provide the visual landscape modelling on Josun royal tombs and surrounding. The visual landscape of traditional heritage is illustrated by the main view points of analysis. This analysis examines limited view points and cannot reflect a reality of environments. Nowadays various equipments and methodologies are developed for the visual landscape research. This study used new tools for analysis which are Sketch up (3D simulation) and mini helicopter (UAV). With those tools, this research examines not only view points of the analysis but also axis views and disincentive environments as a complex analysis. First of all, the research examined 3D modelling for the virtual simulation and drew coordinates and routes for the UAV operating. Secondly, UAV followed this routes and took linear and continuous views that are real scenes. As a result, it drew 3D simulation could illustrate and control the changing of environments such as the forest density and seasonal variations. Thus, comparing both of them shows efficiently landscape analysis. Thirdly, the study compared virtual and real landscape. Using this 3D modelling, this paper able to elaborate heritage environment and surrounding which omitted by view point analysis. Although this study has limitation practice and exercise on the field, the results and suggestions contribute to the various historic heritage managements and conservations. Moreover, it helps to explain the complex and dimensional landscape analysis.