• 대한원격탐사학회지
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• 제37권6_1호
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• pp.1527-1543
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• 2021

본 논문에서는 포인트 클라우드 데이터를 기반으로 자동으로 군집형 솔리드 건물 모델을 생성하는 기술을 다양한 데이터에 적용, 실험을 수행하여 적용 가능성과 효용성을 탐색한다. 또한 자동 건물 모델링 기술의 한계로 인해 부족한 모델의 품질을 향상시키기 위하여 건물의 형상 편집 및 텍스처 조정 기술을 개발, 실험을 통해 결과를 확인하였다. 자동 건물 모델 생성 기술의 적용 가능성 탐색을 위하여 무인항공기 영상 기반으로 생성된 포인트 클라우드와 LiDAR(Light Detection and Ranging) 자료를 사용해 실험하였으며, 자동으로 생성된 건물 모델에 건물 형상 편집 및 텍스처 조정 기술을 적용하여 모델의 품질의 향상 실험을 수행하였다. 이를 통해 포인트 클라우드 데이터 기반의 자동 군집형 솔리드 건물 모델링 기술의 적용 가능성과 모델의 품질 향상기술의 효용성을 확인하였다. 개발된 기술은 기존의 건물 모델링 기술과 비교하여 처리시간의 비용이 크게 감소하며, 잦은 모델 갱신이 필요한 지역에 대한 관리 측면에서도 강점이 있을 것으로 기대된다.

• 성인간호학회지
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• 제24권4호
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• pp.428-437
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• 2012

Purpose: The purpose of the study was to develop a predictive model of Health-related Quality of Life (HRQoL) for Korean Goose daddies - they live alone in Korea to support their families who moved overseas for children's education. Methods: Data were collected from 151 goose daddies from May to June of 2011 by using the structured self-reported questionnaires. The collected data were analyzed using SAS program (version 9.2) and SAS CALIS procedure. Results: Frequency of exercise, monthly income, depression, perceived physical health, and perceived mental health had direct effects on HRQoL and Depression was the variable accounting for major total effect on HRQoL. It could be explained that predictor variables accounted for 76% of the health-related quality of life. Conclusion: In order to improve Goose daddies' HRQoL, predictive factors, such as age, exercise, nutritional status, monthly income, depression, perceived physical health, and perceived mental health, should be considered. Furthermore, should the need of the exercise and diet program, early detection of depression and the treatment for it be emphasized. Also, there is a need to establish institutional structures to support goose daddies in adversity.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.715-721
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• 2000

In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

• 한국콘텐츠학회논문지
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• 제19권5호
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• pp.553-561
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• 2019

본 연구에서는 개인정보 비식별화 데이터의 통계적 유용성에 대한 품질 측정 방안에 대하여 통계 모형화에 따른 예측 정확도 측면에서 고찰하였다. 4차 산업혁명 시대에서 정보통신기술을 통한 혁신에는 반드시 빅데이터의 효과적인 활용이 필수적이지만, 개인정보 이슈는 적극적인 빅데이터 활용에 제약이 되고 있다. 이를 해결하기 위해 비식별화 가이드라인이 제정되었으며 다양한 개인정보 비식별화 방법이 활용되면서 개인정보의 실질적인 재식별 가능성은 매우 낮아졌다. 반면에 강력한 비식별화는 데이터의 유용성을 떨어뜨리는 부작용이 나타날 수 있다. 그 동안은 재식별 불가능한 비식별화 방법이 연구의 주를 이루어 왔다면 본 연구에서는 대표적인 비식별 방법인 KLT 모형에 의한 비식별화 데이터에 대한 통계적 유용성 측면의 품질 측정에 대하여 연구하였다. 비식별화 데이터에 대한 통계적 예측모형의 정확도에 기반하여 비식별화 된 데이터의 통계적 유용성이 어느 정도 훼손되는지에 대하여 사례분석을 수행하였다. 또한, 비식별 자료에 어느 정도의 비식별화 되지 않은 자료가 추가되어야 예측모형의 정확도를 회복하는 지를 살펴봄으로써 비식별화된 자료의 데이터 유용성 정도에 대한 새로운 측정지표를 제안하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.517-523
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• 2021

Audit quality encompasses the key elements that create an environment that maximizes the likelihood that quality audits are performed consistently. This study aimed to identify the impact of auditing quality on the market value of the manufacturing companies listed on the Amman Stock Exchange (ASE). The analytical method was adopted in this research to extract and collect the necessary data. This study hypothesizes that audit quality leads to an increase in the market value by the offering of high-quality services. The study used the panel data approach to analyze cross-sectional data for 41 industrial companies that included time series data for the period (2019-2019). To test its hypotheses, the study used the fixed-effect model. The study found that the audit quality factors (audit office size, client retention period, auditor's fees, and linking with international audit offices) did not have a significant impact on market value. It found also the positive impact of the audit office size on the market value of the listed companies on the ASE for the period from 2009 to 2019. The study recommended the management of the company realize the importance of contracting with audit offices of large size and good reputation because these offices are more capable of increasing their efficiency, qualifying their employees, and thus be fully prepared for the audit process efficiently and effectively.

• Asian Journal of Business Environment
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• 제12권3호
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• pp.31-39
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• 2022

Purpose: This research aims to analyze the quality and characteristics of foreign tourists to Indonesia. Research design, data and methodology: The indicator used to see the quality of foreign tourists is their expenditure while in Indonesia. The data used is secondary data and the statistical analysis used is panel data regression to see the effect of Economic Distance, GDP per capita, Average Length of Stay and Exchange Rate on the quality of Foreign Tourists from 2010 to 2019. Results: Foreign tourists to Indonesia are dominated by young tourists, male and stay about 8.87 days. Their expenditure is relatively low, mostly spent on accommodation, food and beverage. The variables of average length of stay, exchange rate, economic distance, and GDP per capita have a significant and positive effect on the quality of foreign tourists to Indonesia. Conclusions: The number of foreign tourists visiting Indonesia in 2010-2019 tends to increase where the majority of tourists come from countries that are geographically close to Indonesia, young tourists, and male. The quality of tourists in terms of spending is still relatively low. The characteristics of foreign tourists and economic indicators used in the study have a positive effect on improving the quality of tourists.

• 한국CDE학회논문집
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• 제10권4호
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• pp.262-273
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• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.

• 품질경영학회지
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• 제48권2호
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• pp.297-307
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• 2020

Purpose: The purpose of this study is to analyze the factors that affect ammunition performance by applying data mining techniques to the Ammunition Stockpile Reliability Program (ASRP) data of the 155mm propelling charge. Methods: The ASRP data from 1999 to 2017 have been utilized. Logistic regression and decision tree analysis were used to investigate the factors that affect performance of ammunition. The performance evaluation of each model was conducted through comparison with an artificial neural networks(ANN) model. Results: The results of this study are as follows; logistic regression and the decision tree analysis showed that major defect rate of visual inspection is the most significant factor. Also, muzzle velocity by base charge and muzzle velocity by increment charge are also among the significant factors affecting the performance of 155mm propelling charge. To validate the logistic regression and decision tree models, their classification accuracies have been compared with the results of an ANN model. The results indicate that the logistic regression and decision tree models show sufficient performance which conforms the validity of the models. Conclusion: The main contribution of this paper is that, to our best knowledge, it is the first attempt at identifying the significant factors of ASPR data by using data mining techniques. The approaches suggested in the paper could also be extended to other types ammunition data.

• 한국습지학회지
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• 제21권1호
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• pp.77-83
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• 2019

2002년 및 2014년 수행된 황구지천 하천기본계획 수립에 있어서 수질오염농도의 예측을 수행하였지만, 수질 예측모델링 과정에서 관행적으로 적용한 반응계수를 적용함으로써 수질 예측 결과의 신뢰도가 낮은 것으로 평가되고 있다. 본 연구에서는 황구지천 국가하천 약 7.8 km 본류구간인 세마교와 수직교사이에서의 탈산소계수를 평가하여 기존 수질모델링에서 적용한 탈산소계수와 비교하고자 하였다. 관측자료를 통하여 황구지천 세마교 지점(HGJ2)부터 수직교 지점(HGJ3)구간에서 풍수 기간일 경우 탈산소계수는 $0.078day^{-1}{\sim}0.748day^{-1}$, 갈수 기간일 경우는 $0.053day^{-1}{\sim}0.505day^{-1}$ 등으로 산정되었다. 2002년에 수행된 황구지천 수질 예측모델링에서 적용한 탈산소계수는 $0.02day^{-1}{\sim}3.4day^{-1}$ 범위의 값을 적용하였으며, 2014년에는 $0.043day^{-1}$을 적용하였다. 따라서 2002년에는 실제 관측된 수질보다 긍정적으로 예측되었으나, 2014년에는 실제 관측 수질보다 부정적으로 예측되었다. 이는 여러 요인이 있겠지만 적정한 탈산소계수의 적용도 상당한 요인이 작용한 것으로 보이며, 향후 수질예측모델링에서 관측자료가 있는 경우에는 관측자료에 의한 탈산소계수의 결정을 통하여 수행할 필요가 있다고 판단된다.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.335-343
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• 2021

This paper investigates the effect of institutional quality on FDI inflows by using FDI outflows from Asian countries from 2009 to 2017. We used the FDI data from five major Asian economies, which are South Korea, China, Japan, Singapore, and Hong Kong. The gravity model was used to examine the effect of institutional quality on FDI flows. The regression model considers several independent variables, and we select the most appropriate variables by using the Bayesian Model Averaging (BMA) estimator. We have shown that foreign direct investment from Asian countries depends on the size of home and the partner countries, geographical distance, trade interaction between two countries, economic freedom, labor supply, tariff rate, and capacity of the government. The results of different estimation techniques emphasize that multinational enterprises prefer to invest in those countries which have a higher income, which shows the evidence for Lucas's paradox. The results also show that economic freedom and control of corruption have a positive impact on FDI inwards. The regression results show that better institutional quality in host countries encourages more FDIs from Asian economies. It suggests that the state should control corruption and create a free economic environment to attract FDIs.