• 품질경영학회지
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• 제43권4호
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• pp.521-532
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• 2015

Purpose: The purpose of this study is to compare two multivariate cumulative sum (MCUSUM) charts designed for spatio-temporal surveillance in terms of not only temporal detection performance but also spatial detection performance. Method: Experiments under various configurations are designed and performed to test two CUSUM charts, namely SMCUSUM and RMCUSUM. In addition to average run length(ARL), two measures of spatial identification accuracy are reported and compared. Results: The RMCUSUM chart provides higher level of spatial identification accuracy while two charts show comparable performance in terms of ARL. Conclusion: The RMCUSUM chart has more flexibility, robustness, and spatial identification accuracy when compared to those of the SMCUSUM chart. We recommend to use the RMCUSUM chart if control limit calibration is not an urgent task.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.69-71
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• 2010

In this paper, we focus on the accuracy estimation of laser scanning mobile mapping system using Lynx Mobile Mapper. For this, we surveyed checkpoints(181 points) in study areas. A method to estimate the accuracy of laser scanning mobile mapping system based on the measurement range, interval of control points and gps signal environments. As a result, to ensure reliable measurement results, we must be made a plan considering Measure range(60m or under) and operation. The estimation results showed the need for improving accuracy using control points about 150m interval according to environment error source.

• Korean Journal of Geomatics
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• 제2권2호
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• pp.99-105
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• 2002

The accuracy of the Digital Photologging System, designed for the construction of the road Facility Database, highly depends on the positions and attitudes of the cameras from GPS/INS integration. In this paper, the development of a loosely coupled GPS/INS is presented. The performance of the system is verified through a simulation as well as a real test data processing. Since the IMU used in this study shows large systematic errors, the possible accuracy of the positions and attitudes of this low-performance IMU when combined with precise GPS positions are assigned. Currently, the integrated system shows the positional accuracy better than 5cm in real data processing. Although the accuracy of attitude based on real test could not be assigned at this time, it is expected that better than 0.5 degrees and 1.8 degrees for horizontal and down component are achievable according to the simulation result.

• Journal of Advanced Marine Engineering and Technology
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• 제20권4호
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• pp.90-100
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• 1996

To maintain high spacial accuracy and rapid CPU time in interpolating data from grid to random position or inversely in PIV, proposed many technuques are compared and discussed mainly in terms of interpolating error and computing time. And artificial PIV atmosphere data is furnished by CFD result. First, for interpolation from grid to random position, multiquadric method gives the highest accuracy with the longest CPU time and Taylor series expansion methods give reasonable accuracy with less calculating load. Secondly, the sub-pixel resolution analysis in estimating the coordinates of the maximum correlation coefficients essential in the grey level correlation PIV reveal that 8-neighbours 2nd-order least square interpolation gives utmost accuracy in terms of the real flow conditions.

• Journal of Advanced Marine Engineering and Technology
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• 제20권4호
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• pp.412-412
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• 1996

To maintain high spacial accuracy and rapid CPU time in interpolating data from grid to random position or inversely in PIV, proposed many technuques are compared and discussed mainly in terms of interpolating error and computing time. And artificial PIV atmosphere data is furnished by CFD result. First, for interpolation from grid to random position, multiquadric method gives the highest accuracy with the longest CPU time and Taylor series expansion methods give reasonable accuracy with less calculating load. Secondly, the sub-pixel resolution analysis in estimating the coordinates of the maximum correlation coefficients essential in the grey level correlation PIV reveal that 8-neighbours 2nd-order least square interpolation gives utmost accuracy in terms of the real flow conditions.

• International Journal of Reliability and Applications
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• 제3권1호
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• pp.37-50
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• 2002

Simultaneous estimation of accuracy and probability corresponding to a prediction interval is considered in this study. Traditional application of confidence interval forecasting consists in evaluation of interval limits for a given significance level. The wider is this interval, the higher is probability and the lower is the forecast precision. In this paper a measure of stochastic forecast accuracy is introduced, and a procedure for balanced estimation of both the predicting accuracy and confidence probability is elaborated. Solution can be obtained in an optimizing approach. Suggested method is applied to constructing confidence intervals for parameters estimated by normal and t distributions

• 대한산업공학회지
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• 제24권4호
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• pp.601-611
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• 1998

The machining accuracy of CNC machine tools will decrease the production lead time because the coordinate compensation of the tool path will be unnecessary to meet design specifications. Improving the accuracy of machined parts enhances the reliability and functionality of the assembly as well as the life of the product. Among various factors affecting the accuracy of machined parts, the ambient temperature is the major factor that refers to the temperature surrounding the machine and workpiece. In this study, an experiment was conducted to confirm the dimensional variations caused by changes in the ambient temperature. The ambient temperature resulted in overcutting when it increased. A developed pre-processor converts the CNC program to compensate the dimensional variations caused by temperature changes. This methodology can be used to determine the machining accuracy and improve the positioning accuracy of a machine tool.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.397-406
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• 2022

Recently, research and development to revitalize smart construction are being actively carried out. Accordingly, 3D mapping technology that digitizes construction site is drawing attention. To create a 3D digital map for construction site a point cloud generation method based on LiDAR(Light detection and ranging) using MMS(Mobile mapping system) is mainly used. The purpose of this study is to analyze the accuracy of MMS LiDAR-based point cloud data. As a result, accuracy of MMS point cloud data was analyzed as dx = 0.048m, dy = 0.018m, dz = 0.045m on average. In future studies, accuracy comparison of point cloud data produced via UAV(Unmanned aerial vegicle) photogrammetry and MMS LiDAR should be studied.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.210-213
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• 2017

The construction industry has witnessed an exponential growth of drones used in the field over the past few years. Likewise, the field of maintenance has paid increasing attention to using drones with a view to improving the efficiency of condition checks in high-rise buildings and major space. Although operators manipulate drones to inspect buildings at present, drones are expected to autonomously move around without operators in a few years. Also, for indoor maintenance, it is important for drones to find accurate locations, which is implemented by real-time locating systems(RTLS). Yet, the accuracy of RTLS varies across the types of systems and indoor settings, which warrants a locating system suitable for indoor space and a location correction system designed to improve the accuracy. Hence, the current study investigated the accuracy of real-time locating systems(RTLS) for the maintenance of indoor space of buildings with drones and delved into the methods of correcting the location information to improve the accuracy of RTLS.

• 대한상한금궤의학회지
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• 제14권1호
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• pp.41-50
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• 2022

Objective : The purpose of this study is to explore the most suitable machine learning model algorithm for Shanghanlun diagnostic system classification using natural language processing (NLP). Methods : A total of 201 data items were collected from 『Shanghanlun』 and 『Clinical Shanghanlun』, 'Taeyangbyeong-gyeolhyung' and 'Eumyangyeokchahunobokbyeong' were excluded to prevent oversampling or undersampling. Data were pretreated using a twitter Korean tokenizer and trained by logistic regression, ridge regression, lasso regression, naive bayes classifier, decision tree, and random forest algorithms. The accuracy of the models were compared. Results : As a result of machine learning, ridge regression and naive Bayes classifier showed an accuracy of 0.843, logistic regression and random forest showed an accuracy of 0.804, and decision tree showed an accuracy of 0.745, while lasso regression showed an accuracy of 0.608. Conclusions : Ridge regression and naive Bayes classifier are suitable NLP machine learning models for the Shanghanlun diagnostic system classification.