• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.426-426
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• 2022

하천에서 유사량은 침식(Erosion), 유송(Transport), 퇴적(Deposition)의 3단계 과정으로 진행되며 이 과정에서 다양한 유사 문제가 수반되고 있다. 특히, 하상변동의 예측, 하천계획 수립 등 수자원 개발을 위해 유사량 조사는 반드시 필요하다. 따라서 국외에서는 오래전부터 하천 유사이송과정에 대한 이론적인 개념을 정립하고 양질의 유사량 자료를 위해 연구해 오고 있다. 국내에서는 대표적으로 한국수자원조사기술원에서 유사량조사 업무를 수행하고 있으며 국가유사량관측망 중 매년 약 20개소~30개소의 지점을 대상으로 신뢰성 있는 자료를 만들기 위해 지속적으로 연구하고 있다. 유사량 조사의 항목 중 부유사 채취를 위한 측선수는 하천 폭(ISO 기준)에 따라 5개~7개의 측선에서 부유사를 채취하고 있으며, 강우가 활발한 홍수기 전, 후로 단면측량 및 하상토 자료를 통해 총유사량을 산정하고 있다. 본 연구의 분석방법으로는 이신재(2021)가 제안한 방법을 착안하였고, 측선별 부유사농도와 평균부유사농도의 비교분석 통해 상관계수(R²)가 가장 높은 측선을 선택하여 지표부유사량(Index Suspended Sediment) 산정에 활용하였다. 대상지점으로는 연속 유사량 자료 생산이 가능한 낙동강유역의 함안군(계내리) 관측소와 영산강유역의 구례군(구례교) 관측소를 선정하였다. 먼저, 지표 유사량은 평균부유사농도와 측선별 부유사농도를 비교분석하였으며, 함안군(계내리) 관측소는 5번 측선(R²=0.9869), 구례군(구례교) 관측소는 2번 측선(R²=0.9929)을 통해 지표부유사량을 산정하였다. 그 결과 하천특성에 따라 측정된 부유사량과 지표부유사량의 편차율(함안군(계내리) : 최대 33%, 최소 1%, 구례군(구례교) : 최대 25%, 최소 1%)이 다소 상이한 구간이 발생하였지만 이들의 상관계수(R²)는 각각 0.9922, 0.9947로 매우 높게 산정되었다. 이러한 결과를 통해 제시한 지표 설정은 실제 업무에서 활용 가능할 것으로 판단되며, 추후 과거년도의 하천특성과 수리특성 분석을 통해 해당지점의 대표적인 측선을 선정해 연속적인 지표 유사량 자료 생산이 가능하다면 향후 자동 유사량 채수장치 설치를 통해 안정된 유사량 자료 제공이 가능할 것으로 기대된다.

• Journal of the Korea Knowledge Information Technology Society
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• v.12 no.1
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• pp.69-78
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• 2017

KOIN (Korean medicine 人, http://www.koin.re.kr) is a Korean medicine knowledge portal developed for users who are interested in Korean medicine to share relevant information. The purpose of the present study is to seek methods for advancing the quality of the contents and services of KOIN to secure future users of the portal services before fully initiating the KOIN service. The crowd testing method was applied to test the functionality and usability of the current KOIN service, and domestic and international websites providing similar services were investigated and analyzed. About 150 errors were found in this functional testing procedure, but the identified functional problems were all corrected. An average score of 3.33 was calculated in the usability test, in which the reliability and the playfulness showed the highest and lowest score, respectively. We in this paper surveyed the 15 relevant websites with respect to KOIN in the traditional medicine and the modern medicine fields. The strengths and weaknesses of similar websites were analyzed to improve the KOIN services. In particular, it is shown that the evidence-based Korean medicine knowledge is KOIN's biggest strength. Users' needs and demand for the KOIN services will be continuously gathered to provide the Korean medicine knowledge services that the users require.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.391-407
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• 2008

In order to observe from a cross-cultural point of view, the temperament and character of German and Korean adolescents were compared. The 715 German subjects aged 12-18(M=14.70, SD=1.80) and 1411 Korean subjects of the same age(M=15.18, SD=1.69) were assessed through JTCI 12-18 as to whether there exist differences in temperament and character between the two groups. According to the outcomes of the t-test, the German and Korean adolescents show significant differences in all 6 main scales of temperament and character, with only one exception in the character scale, that of 'self-transcendence.' If we analyze the effect size, because even small differences in great samples becomes statistically significant differences, the significant outcomes appeared only in two scales, one of temperament(Harm Avoidance) and the other of character(Self-Directedness): Korean subjects showed a higher tendency of Harm Avoidance related to inhibitions and anxiety and a lower tendency of Self-Directedness, meaning self-acceptance, purposefulness etc. Sex-differences according to the effect size showed only on the scale of Reward Dependence, which was the same in both samples. The outcomes are discussed according to the concepts of individualism and collectivism which are used to divide the Western and Asian cultures. It is also suggested to view these outcomes in the education-political and social bases of each country.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.420-429
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• 2023

GC-MS/MS using liquid-liquid extraction (LLE) and C18 cartridges was used to identify and quantify levels of chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin and permethrin in bulk raw milk. A calibration curve spanning 10 ng/mL to 200 ng/mL was obtained with a satisfactory correlation coefficient of 0.99. The limits of detection (LOD) and limits of quantitation (LOQ) for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in the matrix ranged from 0.06 to 1.81 ng/mL and 0.19 to 6.04 ng/mL, respectively. The recoveries of 5 pesticides from spiked samples at 37.5-125 ng/mL ranged from 86.1 to 102.1%. The measurement of uncertainty of the GC-MS/MS method for these five pesticides was developed based on the analytical process and quantification. An analysis method that is easier and faster than the method specified in the Korean food standards codes for analyzing these five pesticides in raw material milk was developed. Moreover, the analytical method for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in bulk raw milk by GC-MS/MS was established.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.887-897
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• 2023

Leading waste disposal countries, such as Sweden, Switzerland, and the United Kingdom, conduct safety assessments across all stages of High-Level Radioactive Waste Deep Geological Disposal Facilities-from planning and site selection to construction, operation, closure, and post-closure management. As safety assessments are repeatedly performed at each stage, generating vast amounts of diverse data over extended periods, it is essential to construct a database for safety assessment and establish a data management system. In this study, the safety assessment data management systems of leading countries, were analyzed, categorizing them into 1) input and reference data for safety assessments, 2) guidelines for data management, 3) organizational structures for data management, and 4) computer systems for data management. While each country exhibited differences in specific aspects, commonalities included the classification of safety assessment input data based on disposal system components, the establishment of organizations to supply, use, and manage this data, and the implementation of quality management systems guided by instructions and manuals. These cases highlight the importance of data management systems and document management systems for securing the safety and enhancing the reliability of High-Level Radioactive Waste Disposal Facilities. To achieve this, the classification of input data that can be flexibly and effectively utilized, ensuring the consistency and traceability of input data, and establishing a quality management system for input data and document management are necessary.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.770-778
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• 2023

Purpose: In order to reduce forklift industrial accidents, it is necessary to classify them into institutional, technical, and educational factors and conduct research on whether each factor affects disaster reduction. Method: Descriptive statistical analysis, validity analysis, reliability analysis, and multiple regression analysis were conducted using SPSS 18 program based on an offline questionnaire based on a 5-point Likert scale. Result: As a result of multiple regression analysis, it was found that institutional, technical, and educational factors, which are independent variables for disaster reduction, explain about 62.5% of the variance in disaster prevention, which is the dependent variable. The regression model verification was found to be statistically significant with F=118.775 and significance probability p<0.01. Conclusion: First, there is a need to prevent disasters by including electric forklifts weighing less than 3 tons in the inspection system. Second, there is a need to make it mandatory to install front and rear cameras and forklift line beams to prevent forklift collision disasters. Third, there is a need to conduct special training related to forklifts every year, and drivers and nearby workers need to be included in the special training for forklifts.

• Information Systems Review
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• v.25 no.1
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• pp.1-26
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• 2023

Consumers tend to trust information provided by other consumers more than information provided by sellers. Therefore, while inducing consumers to write high-quality reviews is a very important task for companies, it is not easy to produce such high-quality reviews. Based on previous research on review writing and memory recall, we decided to develop a way to use digital nudge to help consumers naturally write high-quality reviews. Specifically, we designed an experiment to verify the effect of uploading a photo during the online review process on the quality of review of the review writer. We then recruited subjects and then divided them into groups that upload photos first and groups that do not. A task was assigned to each subject to write positive and negative reviews. As a result, it was confirmed that the behavior of uploading a photo first increases the review length. In addition, it was confirmed that when online users who upload photos first have extremely negative satisfaction with the product, the extent of two-sidedness of the review content increases.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.1-16
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• 2024

Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.