• 품질경영학회지
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• 제45권4호
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• pp.649-664
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• 2017

Purpose: This paper introduces the technology of prognostics for Industry 4.0 and presents its application procedure for fitness-for-service assessment of natural gas pipelines according to ISO 13374 framework. Methods: Combining data-driven approach with pipe failure models, we present a hybrid scheme for the gas pipeline prognostics. The probability of pipe failure is obtained by using the PCORRC burst pressure model and First Order Second Moment (FOSM) method. A fuzzy inference system is also employed to accommodate uncertainty due to corrosion growth and defect occurrence. Results: With a modified field dataset, the probability of failure on the pipeline is calculated. Then, its residual useful life (RUL) is predicted according to ISO 16708 standard. As a result, the fitness-for-service of the test pipeline is well-confirmed. Conclusion: The framework described in ISO 13374 is applicable to the RUL prediction and the fitness-for-service assessment for gas pipelines. Therefore, the technology of prognostics is helpful for safe and efficient management of gas pipelines in Industry 4.0.

• 응용통계연구
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• 제18권3호
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• pp.597-606
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• 2005

대개의 표본조사에서 무응답은 필연적으로 발생되고 있고, 직접 표본조사에 참가하지 않은 데이터의 사용자는 무응답의 원인을 알 수 없는 것이 일반적이므로 데이터 분석에 어려움을 갖는다. 또 대부분의 통계분석 방법은 무응답을 전제하지 않고 있어 무응답이 있는 항목은 데이터 분석의 걸림돌이 된다고 하겠다. 최근 무응답에 대해 대체법이 하나의 표준적인 처리 방법이 되고 있어 현재까지 대체법에 대한 많은 연구가 있었으나 대부분의 대체법은 정규성 등을 가정한 연속형 변수의 대체법에 대한 것이었다. 그러나 표본조사에서 많은 중요한 항목들이 순서 범주에 의해 측정되는 경우가 많으므로 범주형변수의 대체법에 대한 연구가 필요하며, 본 연구에서는 보조변수가 있는 경우 Bayesian 모형에 의한 순서범주형 항목의 대체법에 대해 알아본다.

• 한국정보통신학회논문지
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• 제18권11호
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• pp.2691-2696
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• 2014

SNOMED CT는 전자의무기록(EMR) 및 전자건강기록(EHR) 시스템에서 표준화된 용어를 사용하여 진로기록을 작성하고 관리하기 위한 표준 의학용어 체계이다. 이 용어체계는 용어의 방대함 및 설계 구조로 인해 용어 체계가 매우 복잡한 특징이 있다. SNOMED CT에서 제공하는 의학 용어를 검색하기 위해 진료 과정에서 사용하는 기존의 브라우저들은 용어체계의 복잡성을 반영하지 못하여 진료기록의 작성 단계에서 그 효용성이 떨어지는 문제가 있다. 본 연구에서는 SNOMED CT 브라우저에 내재된 문제점을 제시하고 용어체계의 분석을 통해 의학 용어를 빠르고 효율적으로 검색하기 위한 검색 브라우저의 요건을 분석하고 개선안을 제시한다.

• 방송공학회논문지
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• 제13권1호
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• pp.86-91
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• 2008

네트워크 데이터 분석에 있어서 추정모델이 얼마나 모집단을 대표하느냐는 반드시 연구되어야 한다. 본 논문에서는 네트워크 데이터의 각 추출 가능한 표준 정보를 이용하여 현재 공개되어 사용하고 있는 MIT Lincoln Lab의 네트워크 데이터와 모델링 된 KDD CUP 99 데이터를 비교 분석한다. 비교, 분석에 있어서 두 데이터에 공통으로 포함되고 표준 정보인 프로토콜 정보를 이용하여 분석한다. 분석은 통계적 분석 방법인 대응 분석 방법을 이용하여 분석하고, SVD를 이용해 2차원 공간에 표현하며, 가중 유클리드 거리를 이용해 네트워크 데이터를 수량화하였다.

• 응용통계연구
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• 제28권2호
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• pp.335-342
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• 2015

경시적 자료는 각 환자마다 시간에 따라 반복 측정되는 코호트 연구 등에서 많이 쓰인다. 본 연구는 반응변수 간 상관성을 고려할 수 있는 결합 다단계 일반화 선형모형을 이용하여, 다변량 경시적 자료 분석을 수행하였다. 한국 유전체 역학 연구에서 실시한 코호트 자료를 적합하고 결과를 해석한다. 조건부 아카이케 정보 기준을 이용하여 모형 선택을 하고, 변량효과들의 추정치들을 설명한다.

• 한국멀티미디어학회논문지
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• 제24권10호
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• pp.1380-1390
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• 2021

The video face recognition (FR) is one of the most popular researches in the field of computer vision due to a variety of applications. In particular, research using the attention mechanism is being actively conducted. In video face recognition, attention represents where to focus on by using the input value of the whole or a specific region, or which frame to focus on when there are many frames. In this paper, we propose a novel attention based deep learning method. Main novelties of our method are (1) the use of combining two loss functions, namely weighted Softmax loss function and a Triplet loss function and (2) the feasibility of end-to-end learning which includes the feature embedding network and attention weight computation. The feature embedding network has a positive effect on the attention weight computation by using combined loss function and end-to-end learning. To demonstrate the effectiveness of our proposed method, extensive and comparative experiments have been carried out to evaluate our method on IJB-A dataset with their standard evaluation protocols. Our proposed method represented better or comparable recognition rate compared to other state-of-the-art video FR methods.

• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.1-10
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• 2021

This paper compares the performance of Fama-French three-factor and five-factor models using a dataset of 20 Pakistani commercial banks for the period 2011 to 2020. We focus on an emerging economy as the findings from earlier studies on developed countries cannot be generalized in emerging markets. For empirical analysis, twelve portfolios were developed based on size, market capitalization, investment strategy, and growth. Subsequently, we constructed five Fama-French factors namely, R_M, SMB, HML, RMW, and CMA. The OLS regression technique with robust standard errors was applied to compare the predictive power of both the Fama-French models. Further, we also compared the mean-variance efficiency of the Fama-French models through the GRS test. Our empirical analysis provides three unique and interesting findings. First, both asset pricing models have similar predictive power to explain the expected portfolio returns in most cases. Second, our results from the GRS test suggest that there is no noticeable difference in the mean-variance efficiency of one asset pricing model over the other. Third, we find that all factors of both Fama-French models are statistically significant and are important for explaining the volatility of expected commercial bank returns in the context of Pakistan.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.11-19
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• 2018

In the Unmanned Aerial Vehicle Line-Of-Sight datalink system, there is a possibility that the communication line is disconnected because line of sight can not be secured by one antenna due to changes in position and posture of the air vehicle. In order to prevent this, both top and bottom of air vehicle are equipped with antennas. At this time, if the signal can be transmitted and received by switching to an antenna advantageous for securing the line of sight, communication disconnection can be minimized. The legacy antenna switching method has disadvantages such that diffraction, fading due to the surface or obstacles, interference and reflection of the air vehicle are not considered, or antenna switching standard is not clear. In this paper, we propose an airborne antenna switching method for improving the performance of UAV LOS datalink system. In the antenna switching method, the performance of each of the upper and lower parts of the mounted antenna according to the position and attitude of the air vehicle is predicted by using the deep learning in an UAV LOS datalink system in which only the antenna except the receiver is duplicated. Simulation using flying test dataset shows that it is possible to switch antennas considering the position and attitude of unmanned aerial vehicle in the datalink system.

• 전기전자학회논문지
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• 제23권2호
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• pp.557-570
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• 2019

In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF) in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vessel ensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used to enhance the vessels at different orientations and radius. In the combination with HF filter, our method can simultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-fine strategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels in different sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically, based on information of the main extracted vessels, we introduce a new method to extract junctions on the vascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate and extract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate that the proposed approach can outperform standard method and attain the accuracy of 71.34%.

• 천문학회보
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• 제44권1호
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• pp.82.2-82.3
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• 2019

Korea Astronomy and Space Science Institute (KASI), in collaboration with the NASA Goddard Sparce Flight Center (GSFC), will develop a next generation coronagraph for the International Space Station (ISS). COronal Diagnostic EXperiment (CODEX) uses multiple filters to obtain simultaneous measurements of electron density, temperature, and velocity within a single instrument. CODEX's regular, systematic, comprehensive dataset will test theories of solar wind acceleration and source, as well as serve to validate and enable improvement of space-weather/operational models in the crucial source region of the solar wind. CODEX subsystems include the coronagraph, pointing system, command and data handling (C&DH) electronics, and power distribution unit. CODEX is integrated onto a standard interface which provides power and communication. All full resolution images are telemeters to the ground, where data from multiple images and sequences are co-added, spatially binned, and ratioed as needed for analysis.