• 한국물환경학회지
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• 제23권3호
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• pp.385-390
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• 2007

Reliable flow measurement for dry season is very important to set up the in-stream flow exactly and total maximum daily load control program in the basin. Especially, in the points which tidal current effects are dominant because reliability of the low measurement decrease. The reliable measuring methods are needed. In this study, we analysis the water surface elevation difference of water surface elevation. Quantity relationship to consider tidal currents in these regions. It is known that tidal current effects from Nakdong river barrage are dominant in Samrangjin measuring station. We developed multiple regression equation with water surface elevation, quantity, and difference of water surface elevation and compared these results water measured rating curve. All of these regression equation including linear regression equation and log regression equation fits better measured data them existing water surface elevation quantity line and Among three equations, the log regression equation is best to represent the measured the rating curve in Samrangjin point. The log regression equation is useful method to obtain the quantity in the regions which tidal currents are dominant.

• Advances in concrete construction
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• 제9권4호
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• pp.337-343
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• 2020

In the present study, by employing fragility analysis, the seismic vulnerability of a concrete girder bridge, one of the most common existing structural bridge systems, has been performed. To this end, drift demand model as a fundamental ingredient of any probabilistic decision-making analyses is initially developed in terms of the two most common intensity measures, i.e., PGA and Sa (T₁). Developing a probabilistic demand model requires a reliable database that is established in this paper by performing incremental dynamic analysis (IDA) under a set of 20 ground motion records. Next, by employing Bayesian statistical inference drift demand models are developed based on pre-collapse data obtained from IDA. Then, the accuracy and reasonability of the developed models are investigated by plotting diagnosis graphs. This graphical analysis demonstrates probabilistic demand model developed in terms of PGA is more reliable. Afterward, fragility curves according to PGA based-demand model are developed.

• 응용통계연구
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• 제21권1호
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• pp.159-168
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• 2008

수익률 기간구조(term structure of interest rates, 이하 수익률곡선)는 자료의 성격이 경시적(longitudinal)이므로 만기까지 기간과 시간을 동시에 입력변수로 고려해야만 유용하고 효율적인 함수추정이 가능하다. 고러나 이러한 방법은 다루어야 하는 자료가 대용량이기 때문에 대용량 자료에 적합하고 실행속도가 빠른 추정기법을 개발하는 것이 필요하다. 한편 자료에 내재하는 자기상관성 구조 때문에 과대 적합된 추정 결과를 얻기 쉽다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해서 가중 LS-SVM(least squares support vector machine, 최소제곱 서포트벡터기계)의 혼합모형을 제안한다. 미국 재무부 채권에 대한 사례연구를 통해서 추정 결과가 증권시장 붕괴 같은 이례적 사건의 현상을 잘 반영하고 있음을 확인할 수 있었다.

• Nuclear Engineering and Technology
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• 제37권5호
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• pp.491-502
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• 2005

Reliable human performance is a prerequisite in securing the safety of complicated process systems such as nuclear power plants. However, the amount of available knowledge that can explain why operators deviate from an expected performance level is so small because of the infrequency of real accidents. Therefore, in this study, a database that contains a set of useful information extracted from simulated emergencies was developed in order to provide important clues for understanding the change of operators' performance under stressful conditions (i.e., real accidents). The database was developed under Microsoft Windows TM environment using Microsoft Access $97^{TM}$ and Microsoft Visual Basic $6.0^{TM}$. In the database, operators' performance data obtained from the analysis of over 100 audio-visual records for simulated emergencies were stored using twenty kinds of distinctive data fields. A total of ten kinds of operators' performance data are available from the developed database. Although it is still difficult to predict operators' performance under stressful conditions based on the results of simulated emergencies, simulation studies remain the most feasible way to scrutinize performance. Accordingly, it is expected that the performance data of this study will provide a concrete foundation for understanding the change of operators' performance in emergency situations.

• Genomics & Informatics
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• 제9권4호
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• pp.181-188
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• 2011

In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences. Genotype frequency data, utilizing a sub sampling method, from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support.

• 정보과학회 논문지
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• 제43권4호
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• pp.404-410
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• 2016

대부분의 차량에서 GPS 기반의 내비게이션을 사용함에 따라, 도로 지도를 자동적으로 생성하는 것은 중요한 연구 문제이다. 본 논문에서는 지도 정보 없이 GPS 궤적을 이용한 교차로 검출 기법을 제안한다. 이 기법은 궤적이 교차로에서 여러 갈래로 나누어지는 것을 이용한다. 이전의 교차로 검출 연구에서는 정차 빈도나 회전방향을 이용하였다. 그러나 제안하는 교차로 검출 기법은 이러한 복잡한 정보를 이용하지 않는다. 이 기법은 주어진 궤적에 대한 부분 궤적 매칭 결과를 이용하여 교차로에 진입한 궤적들이 서로 다른 도로로 나뉘어 이동하는 것을 이용한다. 강남구에서 수집된 실제 차량 궤적 1266개를 대상으로 실험하였다. 실험 결과 제안한 기법은 일반적인 십자 모양의 교차로에서 좋은 성능을 보였다. 제안 시스템은 선정한 교차로에 대해 재현율 75%, 민감도 78%의 성능을 보였다. 더 많은 궤적을 이용하면 더 신뢰할 수 있는 검출 결과를 낼 수 있을 것으로 예상된다.

• 한국지반공학회논문집
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• 제24권11호
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• pp.17-24
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• 2008

하천 교각에서 유발되는 국부세굴은 교량의 붕괴를 유발하는 요인들 가운데 하나로 알려져 있다. 그러나, 교각주위 하천 흐름은 매우 복잡하기 때문에 국부세굴을 정확하게 산정하는 경험식을 도출하기가 쉽지 않다. 따라서, 기존의 경험식들은 특정 세굴 자료에는 좋은 상관 관계를 보이지만 다양한 현장 세굴자료들에 대해 신뢰성 있는 예측 정도를 갖기는 어렵다. 본 연구에서는 많은 현장 계측자료를 바탕으로 국부세굴심을 산정할 수 있는 인공신경망 모델을 제안하고자 하였다. 제안된 산정식은 교각 형상, 교각 폭, 교각 길이, 흐름 입사각, 흐름 속도, 수심 및 $D_{50}$의 총 7개의 변수의 함수로 구성되었다. 인공신경망 모델의 학습과 검증에 총 426개의 현장 계측자료들이 사용되었으며, 인공신경망 모델이 기존 경험 식들에 비하여 개선된 예측정도를 보임을 확인하였다.

• 전기학회논문지
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• 제57권12호
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• pp.2313-2321
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• 2008

In order to develop reliable on-site partial discharge(PD) pattern recognition algorithm, the fuzzy neural network based on fuzzy set(FNN) and the polynomial network pattern classifier based on fuzzy Inference(PNC) were investigated and designed. Using PD data measured from laboratory defect models, these algorithms were learned and tested. Considering on-site situation where it is not easy to obtain voltage phases in PRPDA(Phase Resolved Partial Discharge Analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithms. As input vectors of the algorithms, PRPD data themselves were adopted instead of using statistical parameters such as skewness and kurtotis, to improve uncertainty of statistical parameters, even though the number of input vectors were considerably increased. Also, results of the proposed neuro-fuzzy algorithms were compared with that of conventional BP-NN(Back Propagation Neural Networks) algorithm using the same data. The FNN and PNC algorithms proposed in this study were appeared to have better performance than BP-NN algorithm.

• Smart Structures and Systems
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• 제30권2호
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• pp.145-157
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• 2022

The design of safe and economical structures depends on the reliable live load from load survey. Live load surveys are traditionally conducted by randomly selecting rooms and weighing each item on-site, a method that has problems of low efficiency, high cost, and long cycle time. This paper proposes a deep learning-based method combined with Internet big data to perform live load surveys. The proposed survey method utilizes multi-source heterogeneous data, such as images, voice, and product identification, to obtain the live load without weighing each item through object detection, web crawler, and speech recognition. The indoor objects and face detection models are first developed based on fine-tuning the YOLOv3 algorithm to detect target objects and obtain the number of people in a room, respectively. Each detection model is evaluated using the independent testing set. Then web crawler frameworks with keyword and image retrieval are established to extract the weight information of detected objects from Internet big data. The live load in a room is derived by combining the weight and number of items and people. To verify the feasibility of the proposed survey method, a live load survey is carried out for a meeting room. The results show that, compared with the traditional method of sampling and weighing, the proposed method could perform efficient and convenient live load surveys and represents a new load research paradigm.

• 수산해양기술연구
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• 제53권2호
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• pp.169-176
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• 2017

Tuna purse seine fishery in the western and central Pacific Ocean (WCPO) has been rapidly developed since early 1980s due to massive investment of major distant water fishing nations, and catch by purse seine fishery operating in the WCPO accounts for nearly half of the world's tuna total catch. As fishing efficiency is reflected by not only improving of individual vessel's capacity but also increasing number of active vessel, it is essential to understand vessel capacity for reliable assessment result on how fishery affects stock status of target species. In this study, fishing efficiency was analyzed by main factors which are representative of vessel capacity using fishing data and vessel information related to Korean tuna purse seine fishery operating in the western and central Pacific Ocean from 1992 to 2014. It showed that fishing efficiency of vessel tends to be higher when having larger vessel tonnage, higher engine power, lower vessel age and larger length of vessel. As for fishing efficiency by set type, CPUE of associated set with floating objects was generally higher than that of free school set, and CPUE of free school set seemed to have a greater effect on engine power and vessel age compared to other factors.