• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.539-550
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• 2014

High resolution satellite images have to be oriented and geometrically processed from GCPs(Ground Control Points) to generate precise DEMs(Digital Elevation Models) and topographic maps. In Korea, thousands of national UCPS(Unified Control Points) are established and distributed all over the country by the Korean NGII(National Geographic Information Institute). For that reason, UCPs can be easily searched and downloaded by the national-control-point-record-issues system. Following the study, we suggested the sky-view and road-view from web-portals for searching and identifying UCPs on the images. To evaluate the usefulness of UCPs in RPCs(rational polynomial coefficients) adjustment of the high resolution satellite images, the one UCP, which of using simple the control point, has been applied to adjust the vendor-provided RPCs of the KOMPSAT-3 images. As a result, the positioning error of corrected RPCs was approximately one pixel and one meter. From this experiment, we conclude that the UCPs will be able to replace the survey GCPs for mapping with the satellite images or aerial images.

• The Journal of Korean Society for Radiation Therapy
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• v.15 no.1
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• pp.53-60
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• 2003

I. Purpose It is essential to have the correct body contour information for the calculation of dose distribution. The role of CT images in the radiation oncology field has been increased. But there still exists a method to use cast or lead wire for the body contour drawing. This traditional method has drawbacks such as in accurate and time consuming procedure. This study has been designed to overcome this problem. II. Materials and Methods A digital camera is attached to a pole which stands on the opposite side of the gantry. Positional information was acquired from an image of the phantom which is specially designed for this study and located on the isocenter level of the simulator Laser line on the patients skin or on the phantom surface was digitized and reconstructed as the contour. Verification of usefulness this technique has been done with various shape of phantoms and a patients chest III. Results and Conclusions Contours from the traditional method with the cast or lead wire and the digital image method showed good agreement within experimetal error range. This technique showed more efficiente in time and convenience. For irregular shaped contour, like H&N region, special care are needed. The results suggest that more study is needed. To use of the another photogrammatory techinique with two camera system may be better for the actual clinical application

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.57-65
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• 2007

This paper presents the design of single phase PFC(Power Factor Correction) using a DSP(TMS320F2812). In order to realize the proposed boost PFC converter in average current mode control, the DSP requires the A/D sampling values for a line input voltage, a inductor current, and the output voltage of the converter. Because of a FET switching noise, these sampling values contain a high frequency noise and switching ripple. The solution of A/D sampling keeps away from the switching point. Because the PWM duty is changed from 5% to 95%, we can#t decide a fixed sampling time. In this paper, the three A/D converters of the DSP are started using the prediction algorithm for the FET ON/OFF time at every sampling cycle(40 KHz). Implemented A/D sampling algorithm with only one timer of the DSP is very simple and gives the autostart of these A/D converters. From the experimental result, it was shown that the power factor was about 0.99 at wide input voltage, and the output ripple voltage was smaller than 5 Vpp at 80 Vdc output. Finally the parameters and gains of PI controllers are controlled by serial communication with Windows Xp based PC. Also it was shown that the implemented PFC converter can achieve the feasibility and the usefulness.

• Management & Information Systems Review
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• v.37 no.1
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• pp.41-53
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• 2018

This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.155-170
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• 2018

Predicting a company's financial bankruptcy is traditionally one of the most crucial forecasting problems in business analytics. In previous studies, prediction models have been proposed by applying or combining statistical and machine learning-based techniques. In this paper, we propose a novel intelligent prediction model based on the simulated annealing which is one of the well-known optimization techniques. The simulated annealing is known to have comparable optimization performance to the genetic algorithms. Nevertheless, since there has been little research on the prediction and classification of business decision-making problems using the simulated annealing, it is meaningful to confirm the usefulness of the proposed model in business analytics. In this study, we use the combined model of simulated annealing and machine learning to select the input features of the bankruptcy prediction model. Typical types of combining optimization and machine learning techniques are feature selection, feature weighting, and instance selection. This study proposes a combining model for feature selection, which has been studied the most. In order to confirm the superiority of the proposed model in this study, we apply the real-world financial data of the Korean companies and analyze the results. The results show that the predictive accuracy of the proposed model is better than that of the naïve model. Notably, the performance is significantly improved as compared with the traditional decision tree, random forests, artificial neural network, SVM, and logistic regression analysis.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.199-226
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• 2024

In response to the era of transformation necessitating the introduction of Artificial Intelligence (AI) and digital technologies, educational innovation is undertaken with the implementation of AI digital textbooks in Mathematics, English, and Information subjects by 2025 in Korea. Within this context, this study analyzed the perceptions and needs of elementary school teachers regarding mathematics AI digital textbook. Based on a survey conducted in November 2023, involving 132 elementary school teachers across the country, the analysis revealed that the majority of elementary school teachers had a low perception of the introduction and need for mathematics AI digital textbooks. However, some recognized the potential for personalized learning and effective teaching support. Furthermore, among the core technologies of the AI digital textbook, teachers highly valued the necessity of learning diagnostics and teacher reconfiguration functions and had the most positive perception of their usefulness in math lessons, while their perception of interactivity was relatively low. These findings suggest the need for changing teachers' perceptions through professional development and information provision to ensure the successful adoption and use of mathematics AI digital textbooks. Specifically, providing concrete and practical ways to use the AI digital textbook, exploring alternatives to digital overload, and continuing development and research on core technologies.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.10-27
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• 2014

HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.