• Korean Journal of Social Welfare
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• v.63 no.2
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• pp.207-231
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• 2011

This study aims to identify constructs of cultural competency specifically relevant to the Korean society and to test its reliability and validity among human service workers. For the purpose of the study, authors conducted focus group interviews and conferences with human service workers to draw the concept of cultural competency. Further, this study conducted to two separate pilot tests with 20 social workers with practice experiences in order to clarify descriptions and relevance of scale items. Based on the literature review on the concept of cultural competency and analysis of focus group interviews, 40 items were initially constructed and then were reduced to a 32-item scale after two separate pilot studies. Meantime, suggestions made by an advisory group were also reflected in the scale development process. Finally, one hundred ninety four workers in social service agencies were recruited to evaluate the relevance of the scale items in a 5 point Likert scale. Through exploratory and confirmatory factor analysis, 4 main factors were identified: 1) competency to use culturally relevant skills, 2) cultural awareness and sensitivity, 3) cultural knowledge, and 4) efforts to overcome cultural differences. These factors were consistent with sub-concepts of cultural competency in other studies. Confirmatory factor analysis also showed that the model fitness was at the high level and convergent analysis with the similar scale also showed high correlations. Internal consistency also remained at a high level. Based on the results, implication for social work practice and education were discussed.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.783-789
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• 2017

In terms of 3D orientation estimation based on nine-axis IMMU(inertial and magnetic measurement unit), there are two disturbance components decreasing estimation accuracy: one is external acceleration disturbing accelerometer's signals and the other is magnetic disturbance related to magnetometer's signals. In order to minimize effects by these two disturbances, two approaches including switching approach and model-based approach have been suggested and further research comparing these two has also been conducted. Nevertheless, effect of disturbance modeling differences on orientation estimation accuracy in model-based approach has not been studied before. This paper compares the recently reported two orientation estimation algorithms that have difference in disturbance models, in order to investigate the effect of disturbance models on accuracy of IMMU-based orientation estimation under various operating conditions. This research shows that the difference in disturbance models leads to difference in process noise covariance matrix. Consequently, this affected the orientation estimation, i.e., the estimation differences between the algorithms were root mean square errors of $1.35^{\circ}$ in average and $3.63^{\circ}$ in yaw estimation.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.2072-2072
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• 2009

최근 연구들에서, 증강 현실(Augmented Reality; AR) 환경에서의 촉각 상호작용에 대한 가능성이 논의되었다. 비젼 기반의 트래킹을 기초로 한 증강 현실 기술은 미리 정의된 2차원 마커(marker)를 이용하여, 카메라로부터 획득된 실시간 영상 위에 가상 물체를 증강한다. 그러나, 카메라로부터 획득된 데이터는 몇몇 오차 요인들, 예를 들어 마커의 위치를 인식하는데 나타나는 오차, 카메라 안에 존재하는 센서 잡음 등으로 인해서 마커 잡음(마커를 인식하면서 나타나는 잡음)이 불가결하게 발생하게 된다. 이러한 이유로 인해서, 사용자가 한 손에는 마커를, 다른 한 손으로는 촉감 장치를 이용하여, 마커에 증강된 물체를 만질 때, 마커 잡음은 힘의 떨림(force trembling)을 발생시킨다. 심지어, 이러한 현상은 정지된 마커에 증강된, 마커가 움직이지 않는 상황에서도 발생한다. 게다가, 마커 위에 증강된 물체가 약간 빠른 속도로 이동하게 될 경우, 측정된 이동 거리는 연속적인 프레임(frame)들 간의 불연속적일 수 있다. 만약 사용자가, 대략 30Hz로 위치와 방향이 갱신되는 가상물체를 촉각적으로 상호작용하려 한다면, 계산되는 반력은 급작스런 힘의 변화를 생성하게 될 수도 있다. 이러한 현상을 극복하기 위해서, 마커 잡음을 최소화하기 위해서 정적 임계값(constant threshold)을 이용할 뿐만 아니라, 보간법을 같이 사용한 방법이 있었다. 하지만, 이러한 방법은 정적 임계값을 이용하고, 영상 프레임 갱신 속도와(video frame rate)와 촉각 프레임 갱신 속도가 일정하다는 가정을 사용하였기 때문에, 여전히 힘의 불연속적인 발생이 나타난다. 따라서, 이 논문에서는 두 가지 방법을 이용하여 증강 현실 내에서, 발생할 수 있는 힘의 불연속적인 변화를 보정하는 두 가지 방법, 잡음 제거를 위한 확장된 칼만 필터(Extend Kalman Filter)와 영상과 촉각 갱신 속도 차이에 따른 갑작스런 힘의 변화를 제거하기 위한 적응적 외삽법(Adaptive Extrapolation method)을 제안한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.10-20
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• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• Food Science of Animal Resources
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• v.21 no.2
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• pp.163-168
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• 2001

This study was conducted to analyze the errors occurred between standard plate count(SPC) and Bactometer, Malthus, Bactoscan and to investigate correlation coefficient(r) between SPC and each equipments for the purpose of making new calibration curve. Correlation coefficients of three different types of equipments to SPC value were 0.71, 0.81, 0.84 respectively(n=287) and that of three types of equipments were 0.71∼0.82 relatively low. In raw milk, correlation coefficients of three types of equipments of SPC were in the range of 0.67∼0.73 below 3.0${\times}10^4$(CUF/ml) of bacterial number, and those between the three types of equipments were 0.68∼0.72. Between 3.0${\times}10^4$∼5.0${\times}10^5$(CFU/ml) of bacterial number, correlation coefficients of the three different types of equipments were 0.71∼0.81. and those between the three different types of equipments were 0.64∼0.77. Over 5.0${\times}10^5$(CFU/ml), correlation coefficient of the three types equipments were 0.66∼0.83 and those between them were 0.70∼0.85 respectively. The error of the three different types equipments to SPC value was significantly high, 37∼53% of them was under 50% of error range, and in case of raw milk less than 3.0${\times}10^4$ of bacterial number, 44∼67% of them showed over 100% of error.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.260-267
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• 2014

For the purpose of improving the accuracy of Wide Area Differential GNSS (WA-DGNSS), estimation performance of ionospheric delay error which has a great impact on GPS error sources should be enhanced. This paper applied multi-constellation GNSS which represents GPS in USA, GLONASS in Russia, and Galileo in Europe to WA-DGNSS algorithm in order to improve performance of ionospheric delay estimation. Furthermore, we conducted simulation to analyze ionospheric delay estimation performance in Korean region by increasing the number of reference stations. Consequently, using multi-constellation GNSS to improve performance of ionospheric delay estimation is more effective than increasing the number of reference stations in spite of similar number of measurements which are in use for estimation. We expect this result can contribute to improvement for ionospheric delay estimation performance of single-frequency SBAS (Satellite Based Augmentation System) user.

• Journal of the Korean Chemical Society
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• v.57 no.2
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• pp.279-288
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• 2013

In this study, we analyzed the values of ionization and ionization constants in the chemistry textbooks developed during 1945-2009 year. The chemistry teachers compared strength of strong acids in aqueous solution by questionnaire. In the questionnaire, we searched chemistry teachers' cognitions about the discordance reason of ionization constant formulation and the values in the textbooks. The subjects were 46 chemistry teachers. As results, the teachers compared the strength of strong acids in aqueous solution based on the ionization and ionization constant values in the textbooks. They didn't notice the problem of discordance of ionization constant formulation and the values in the textbooks. Even though they recognized the problem, they could not find the solution, and thought the problem arrived by experiment error or measurement error.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.