• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.251-256
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• 2019

A capsule endoscopy is a medical device that can capture an entire digestive organ from the esophagus to the anus at one time. It produces a vast amount of images consisted of about 8~12 hours in length and more than 50,000 frames on a single examination. However, since the analysis of endoscopic images is performed manually by a medical imaging specialist, the automation requirements of the analysis are increasing to assist diagnosis of the disease in the image. Among them, this study focused on automatic detection of polyp images. A polyp is a protruding lesion that can be found in the gastrointestinal tract. In this paper, we propose a weighted-image generation method to enhance the polyp image learning by multi-scale analysis. It is a way to extract the suspicious region of the polyp through the multi-scale analysis and combine it with the original image to generate a weighted image, that can enhance the polyp image learning. We experimented with SVM and RF which is one of the machine learning methods for 452 pieces of collected data. The F1-score of detecting the polyp with only original images was 89.3%, but when combined with the weighted images generated by the proposed method, the F1-score was improved to about 93.1%.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.325-332
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• 2023

Currently, the world's population has already entered a super-aging era, and the rate is expected to increase rapidly to about 40% by 2050. However, the rapid development of automation technology and the online service sector, the main technologies of the Fourth Industrial Revolution, are still further isolating them in a world where many inconveniences and development technologies are applied. As such, alienation in daily life is widely expanded in various fields, but the financial service sector is one of the must-use areas regardless of age because of its strong nature in the public service sector, and is a very important factor in the period when branches are rapidly decreasing. However, the current utilization rate of mobile banking services is not around 5%, so users over 60 are rarely able to use them. The UX design of the most frequently used remittance service screen in mobile banking services was proposed, and the difficulty of trying to find the preferred bank among 56 or more banks was solved by analyzing the usage rate of each bank and dividing it into three stages by age group from 50 or older. In addition, it was designed to strengthen customized services by showing their recently used banks as the top priority. The design proposed in this study obtained an average of 4.8 points or more out of 5 points as a result of usability satisfaction through interviews with less than 50 senior groups. This study is believed to help each bank upgrade its different mobile banking designs in a unified manner.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.281-289
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• 2023

PURPOSE. This study aimed to predict the positional coordinates of incisor points from the scan data of conventional complete dentures and verify their accuracy. MATERIALS AND METHODS. The standard triangulated language (STL) data of the scanned 100 pairs of complete upper and lower dentures were imported into the computer-aided design software from which the position coordinates of the points corresponding to each landmark of the jaw were obtained. The x, y, and z coordinates of the incisor point (X_P, Y_P, and Z_P) were obtained from the maxillary and mandibular landmark coordinates using regression or calculation formulas, and the accuracy was verified to determine the deviation between the measured and predicted coordinate values. Y_P was obtained in two ways using the hamularincisive-papilla plane (HIP) and facial measurements. Multiple regression analysis was used to predict Z_P. The root mean squared error (RMSE) values were used to verify the accuracy of the X_P and Y_P. The RMSE value was obtained after crossvalidation using the remaining 30 cases of denture STL data to verify the accuracy of Z_P. RESULTS. The RMSE was 2.22 for predicting X_P. When predicting Y_P, the RMSE of the method using the HIP plane and facial measurements was 3.18 and 0.73, respectively. Cross-validation revealed the RMSE to be 1.53. CONCLUSION. Y_P and Z_P could be predicted from anatomical landmarks of the maxillary and mandibular edentulous jaw, suggesting that Y_P could be predicted with better accuracy with the addition of the position of the lower border of the upper lip.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.609-617
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• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.