• Fire Science and Engineering
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• v.31 no.1
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• pp.89-97
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• 2017

This study analyzed the case of diesel car fires that occurred while driving in a tunnel 5 days after maintenance at a car service center. The results of the investigation and analysis found that a large amount of white foreign matter adhered to the inside of the exhaust port and the insulating plate above the DPF (diesel particulate filter) installed in the middle of the exhaust pipe was melted and lost. In particular, the metal floor of the car above the DPF was molten and pierced, and the rubber mat placed on the metal floor was burnt. Moreover, while the exhaust pipe in front of the DPF showed no overheating mark, such a mark was observed in the exhaust pipe from the DPF to the exhaust port. Because these findings may appear only when the DPF is overheated and ignited, this car fire is believed to have been caused by internal overheating of the DPF. The car fire investigation of this study suggests that if white foreign matter is found in the inside of the exhaust port during a fire cause investigation of a diesel car, the cause of the fire should be determined by removing the DPF and examining the internal damage of the DPF.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.423-426
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• 2002

Fourier 변환은 연속이며, 무한 회 미분 가능한 함수인 반면, Wavelet 변환은 시간적으로도, 주파수적으로도 국재화 시키는 함수를 사용하는 점에서 차이가 있다. Fourier 변환에 비해 Wavelet 변환은 고주파 성분에 대해서는 시간 분해능이 높고, 저주파 성분에 대해서는 주파수 분해능이 높아지므로, 주어진 신호에 대한 지식이 없이도 시간-주파수 해석이 가능하고, 고주파 성분을 갖는 특이점의 검출에도 적합하다. 그러므로 Wavelet 변환의 이러한 성질을 이용하여 변압기의 출고전 권선의 완전한 절연을 검증하고자 한다. 이때 시행하는 뇌 임펄스 내전압 시험 시 나타난 푸리에 변환과 Wavelet 변환 곡선을 비교 분석 및 해석을 통하여 유의수준 및 신뢰 구간 둥의 통계학적 분석을 이용, 해석하여 보다 정확한 그래프를 산출하므로서 과도구간에 대한 정밀한 해석을 하고자 한다.

• Child Health Nursing Research
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• v.20 no.3
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• pp.215-224
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• 2014

Purpose: This study was conducted to identify risk factors in hospitalized children, and to develop and validate a fall-risk assessment tool for hospitalized children. Methods: A retrospective chart review was performed at one university children's hospital, and an analysis was done of the characteristics of all patients who fell during a 44-month period (n=48). These patients were compared with another 149 hospitalized children who did not fall. Results: Significant predictors of falls as identified in a multivariate logistic regression analyses were age of less than 3 years old, neurological diagnosis including epilepsy, children's dependency of ADL, physical developmental delay, multiple usage of fall-risk-increasing drugs. The respective odds ratios ranged from 2.4 to 7.1 with 95% confidence interval (p<0.05). Accordingly, defining patients with either 5 risk factors as fall-prone hospitalized children provided a sensitivity of 93.6% and specificity of 16.2%. Conclusion: The results show that this tool has an acceptable level of sensitivity to assess the risk factors of fall in hospitalized children even though the specificity was low, suggesting that this tool may enable nurses to predict the risk level of childhood falls, and develop preventive strategies against pediatric falls in children's units.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.39-45
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• 2016

In this study, with arbitrary reference points on the water, photogrammetry accuracy analysis was conducted using unmanned aerial vehicle(UAV). A small reservoir is a research area, and twenty buoys were used as arbitrary reference points. Errors of location coordinate were identified with control of amounts of used reference points. cases are categorized by index scores per photos. Accuracy of X is 0.141m~0.166m and accuracy of Y is 0.136m~0.241m. Considering that allowable error for the maritime boundary survey is ${\pm}2m$, it is possible to get the accuracy data available for the photogrammetry of UAV using an reference point. In addition, the coefficient of correlation between the number of reference points per unit and number of buoys used as reference point and the ratio of the reference point per square measure, and percentage of buoys used as reference point and the coefficient of x and y were performed. Each element, x, and y showed a strong correlation and the coefficient of number of buoys used as reference point was irrelevant. The results of this correlation analysis can be analyzed that the number of reference points used in each picture is greater than the actual number of reference points used in location accuracy.

• Journal of Plant Biology
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• v.36 no.4
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• pp.377-382
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• 1993

Rice (Oryza saliva L.) calli containing both embryogenic callus (EC) and non embryogenic callus (NEC) regions were initiated from the mature seed on MS medium supplemented with 2.0 mg/L 2,4-D, 0.5 mg/L kinetin. The calli were developed into two callus type which can be distinguished by visual examination depending on color and appearance. In order to illucidate the polypeptide composition between EC and NEC, the total protein extracted from two types of callus was analysed by electrophoresis. By one-dimesional anlaysis of SDS-PAGE and Isoelectric focusing, several protein bands showed quantitative and qualitative difference in each type of callus. The further analysis of the total protein with two-dimensional electrophoresis showed at least 20 EC specific protein and 10 NE specific protein. Also 3 specific protein spots showing micro heterogeneity of 90, 65, 50 kD were detected in EC, while a series of acidic heterologous protein spots were visualized in NEC.in NEC.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.107-108
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• 2020

최근 센서데이터 활용 영역이 넓어지면서 데이터 분석 서비스가 활성화되고, 분석을 용이하게 할 수 있는 환경으로 진화하고 있다. 이에 따라 센서데이터의 신뢰성 보장이 필요하다. 신뢰성을 갖는 환경모니터링을 위해서는 센서로부터 수집된 환경 데이터의 분포 및 값을 살펴본 후 데이터가 표현하는 현상을 더 잘 이해하고, 센서 및 센서데이터에 대한 잠재적인 특이점을 발견을 선행하여야 한다. 이를 위해 EDA를 통해 수집된 센서 값을 시각화하고 분석에 주어진 데이터의 개별 속성의 특징 및 상관관계를 도출한다. 본 연구의 EDA 분석 결과는 센서데이터의 신뢰성을 평가하기 위해 사용한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1305-1311
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• 2022

With the recent rapid development of mobile terminals and personal computers and the advent of neural network technology, real-time face swapping using images has become possible. In particular, the cycle generative adversarial network made it possible to replace faces using uncorrelated image data. In this paper, we propose an input data processing scheme that can improve the quality of face swapping with less training data and time. The proposed scheme can improve the image quality while preserving facial structure and expression information by combining facial landmarks extracted through a pre-trained neural network with major information that affects the structure and expression of the face. Using the blind/referenceless image spatial quality evaluator (BRISQUE) score, which is one of the AI-based non-reference quality metrics, we quantitatively analyze the performance of the proposed scheme and compare it to the conventional schemes. According to the numerical results, the proposed scheme obtained BRISQUE scores improved by about 4.6% to 14.6%, compared to the conventional schemes.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1531-1532
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• 2015

본 논문에서는 태양광 발전설비 보급에 따라 증가하고 있는 태양광 접속함의 화재 사례를 분석하고 착화재현실험을 통하여 전기화재 위험성을 분석하였다. 전압 및 전류에 따른 태양광 접속함의 온도변화 특성을 분석하였으며, 특히 태양광 접속함의 트래킹에 의한 착화실험과정 통하여 전기적 특이점을 분석하고 트래킹에 의한 전기화재 예방대책을 제시하였다.

• Information Systems Review
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• v.21 no.4
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• pp.175-195
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• 2019

This study conducted both big data and netnography analysis to analyze consumer needs and behaviors of online consumer community. Big data analysis is easy to identify correlations, but causality is difficult to identify. To overcome this limitation, we used netnography analysis together. The netnography methodology is excellent for context grasping. However, there is a limit in that it is time and costly to analyze a large amount of data accumulated for a long time. Therefore, in this study, we searched for patterns of overall data through big data analysis and discovered outliers that require netnography analysis, and then performed netnography analysis only before and after outliers. As a result of analysis, the cause of the phenomenon shown through big data analysis could be explained through netnography analysis. In addition, it was able to identify the internal structural changes of the community, which are not easily revealed by big data analysis. Therefore, this study was able to effectively explain much of online consumer behavior that was difficult to understand as well as contextual semantics from the unstructured data missed by big data. The big data-netnography integrated model proposed in this study can be used as a good tool to discover new consumer needs in the online environment.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.97-108
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• 2018

It has been routine practice in regression analysis to check the validity of the assumed model by the use of regression diagnostics tools. Outliers and influential observations often distort the regression output in an undesired manner. Jang and Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014) proposed a graphical method (called a firework plot) so that there could be an exploratory visualization of the trace of the impact of the possible outliers and influential observations on individual regression coefficients and the overall residual sum of the squares measure. This paper further extends a graphical approach to a multi-response surface methodology problem.