• 한국측량학회지
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• 제19권1호
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• pp.77-83
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• 2001

지상사진측량 방법에 의한 도면 작성은 다소의 번거로운 입체영상의 획득 과정과 고가의 해석기기를 바탕으로 한 도화 과정을 필요로 한다. 이에, 본 연구에서는 이러한 영상 해석 과정을 탈피하여 보다 용이한 방법으로 영상을 획득하고 처리하여 대상물에 대한 도면을 작성하고자 하였다. 이를 위해, 단-사진 정사투영 영상을 생성하기 위한 기하보정 시스템을 구축하고 건축물을 대상으로 다양한 워핑 기법을 적용하여 보정 영상들의 성과를 비교·분석하였다. 이로서, 단-사진 기하보정의 수행성을 평가할 수 있었으며 다양한 비-지형 측정 분야에 이의 활용을 기대한다.

• 대한안전경영과학회지
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• 제10권1호
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• pp.191-195
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• 2008

The present study contributes reviewing and suggesting various models for measurement system analysis (MSA). Measurement errors consist of accuracy, linearity, stability, part precision, repeatability and reproducibility (R&R). First, the major content presents split-plot design, and the combination method of crossed and nested design for obtaining gage R&R. Second, we propose $\bar{x}-s$ variable control chart for calculating the gage R&R and number of distinct category. Lastly, investigating the determination of gage performance curve which establishes the control specification propagating calibration uncertainties and measurement errors is described.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1361-1369
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• 2008

The analysis of software reliability model provides the means to analysts, software engineers, and systems analysts and developers who want to predict, estimate, and measure failure rate of occurrences in software. In this paper, reliability growth model, in which the operating time between successive failure is a continuous random variable, is proposed. This model is based on order statistics of two parameters Burr type XII distribution. We propose the measure based on U-plot. Also the performance of the suggested model is tested on real data set.

• 한국정보통신학회논문지
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• 제7권8호
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• pp.1840-1847
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• 2003

본 논문에서는 다중표적 추적을 위한 데이터 결합 기법 중에서 MHDA 스킴을 제안하였다. 이 구조는 기본의 JPDA보다 계산면에서 단축이 가능하여 실제 응용에 많은 적용이 기대된다. 인위적인 측정값과 표적을 이용하여 시뮬레이션을 수행한 결과 MHDA는 기존의 JPDA보다 성능도 비슷한 특성을 보이는 것을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.397-412
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• 2020

In this paper, a notion of data depth is used to propose nonparametric multivariate two sample tests for difference between scale parameters. Data depth can be used to measure the centrality or outlying-ness of the multivariate data point relative to data cloud. A difference in the scale parameters indicates the difference in the depth values of a multivariate data point. By observing this fact on a depth vs depth plot (DD-plot), we propose nonparametric multivariate two sample tests for scale parameters of multivariate distributions. The p-values of these proposed tests are obtained by using Fisher's permutation approach. The power performance of these proposed tests has been reported for few symmetric and skewed multivariate distributions with the existing tests. Illustration with real-life data is also provided.

• Bulletin of the Korean Chemical Society
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• 제20권1호
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• pp.59-64
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• 1999

Based on the study of hydrolysis behaviour of U(Ⅵ) ion and major fission product metal ions such as Cs(Ⅰ), Ce(Ⅲ), Nd(Ⅲ), Mo(Ⅵ), Ru(Ⅱ), and ZR(Ⅳ) in the titration media, the performance of noncomplexing-alkalimetric titration method for the determination of free acid in the presence of these metal ions was investigated and its results were compared to those from the completing methods. The free acidities could be determined as low as 0.05 meq in uranium solutions in which the molar ratio of U(Ⅵ)/H+ was less than 5, when the end-point of titration was estimated by Gran plot. The biases in the determinations were less than 1% and about +3% respectively for 0.4 meq and 0.05 meq of free acid at the U(Vl)/H+ molar ratio of up to 5. Applicability of this method to the determination of free acid in spent fuel solutions was confirmed by the analysis of nitric acid content in simulated spent fuel solutions and in a real spent fuel solution.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1081-1087
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• 2015

This article aims to provide a design method of warning thresholds for active safety systems based on the performance-based approach considering driver behaviors. Both positive and negative consequences of warnings are considered, and the main idea is to choose a warning threshold where the positive consequence is maximized, whereas the negative consequence is minimized. The process of the performance-based approach involves: Defining the operating scenarios; setting the trajectory models, including human characteristics; estimating the alert and nominal trajectories; estimating the performance metrics; generating a performance-metric plot; and determining the alert thresholds. This paper chose a lane-departure warning system as an example to show the usefulness of the performance-based approach. Both human and sensor characteristics were considered in the system design, and this paper provided a quantitative method to include human factors in designing active safety systems.

• 전기학회논문지P
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• 제59권1호
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• pp.64-70
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• 2010

This paper presents how to decide on tuning factor(${\delta}$) and quality factor(Q) values in design of single-tuned passive harmonic filters. Tuning factor(${\delta}$) and quality factor(Q) values have to consider before decision on circuit parameters of passive filters. A Study on these two value has not been scarcely performed and only experienced values has been used in passive harmonic filter design by far. As a experienced value, in cases of 5th and 7th filter, tuning factor(${\delta}$) is about 0.94 and 0.96 respectively and quality factor(Q) is, in all cases of, 50. If Single-tuned passive harmonic filter will be off-tuned, performance of filter will be decreased steeply and occur to parallel resonance between system reactance and filter capacitance. Therefore During the operation, In order not to off-tuning, Filter must be tuned at former order than actual tuning order. This is the same that total impedance of filter must have a reactive impedance. In this paper, Tuning factor(${\delta}$) is decided via example of real system and using the bode-plot and then performance of filters confirmed by filter current absorbtion rate. And Quality factor(Q) decided using the bode plot in example system and then performance of filters confirmed by filter current absorbtion rate also, which makes a calculated filter parameters to satisfy IEEE-519 distortion limits. Finally, Performance of the designed passive harmonic filter using the tuning factor(${\delta}$) and quality factor(Q) values, decided in this paper is verified by experiment and shows that 5th, 7th, 9th, 11th and 13th current harmonic distortions are decreased within IEEE-519 distortion limits, respectively.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.189-192
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• 2021

항적추적 기술에 딥러닝 기반 LSTM(Long Short-Term Memory) 모델을 적용하는 연구로서 기존의 항적추적기술의 경우, 항공기의 등속, 등가속, 급기동, 선회(3D) 비행 등 비행 특성에 따른 칼만 필터 기반의 LMIPDA를 활용한 실시간 항적 추적 시 등속, 등가속, 급기동, 선회(3D) 비행 가중치가 자동으로 변경된다. 이러한 과정에서 등속 비행 중 급기동 비행과 같이 비행 특성이 변경될 때, 항적 손실 및 항적 추적 성능이 하락하여 비행 특성 가중치 변경성능을 향상시킬 필요성이 있다. 본 연구는 레이더의 오차 모델이 적용된 시뮬레이터의 Plot과 표적을 딥러닝 기반 LSTM(Long Short-Term Memory) 모델을 적용하여 학습시키고, 칼만 필터를 활용한 항적추적 결과와 딥러닝 기반 LSTM(Long Short-Term Memory) 모델을 적용한 항적추적결과를 비교함으로써 미리 비행 특성의 변경과정을 예측하여 등속, 등가속, 급기동, 선회(3D) 비행 가중치변경을 신속하게 함으로써 항적추적성능을 향상하기 위한 연구이다.

• Korean Journal of Radiology
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• 제22권4호
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• pp.612-623
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• 2021

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988-0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618-0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion: The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.