• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.520-525
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• 2019

Mines are an important infrastructure for securing resources, but safety problems can arise in the course of operation. Recently, the mining process is very complicated due to the large scale and mechanization. Therefore, it is necessary to construct accurate geospatial information on mine for systematic and safe mine operation. The geospatial information construction using the existing total station has a disadvantage that a lot of work time is required because the target must be collimated and measured. In this study, the data of the mines were acquired with the total station and the 3D laser scanner, and the mine spatial information was constructed by using the shape based registration method. By using the static scanner data of some area applying the reference point surveying result of the total station, it was possible to construct the accurate result on the wide area acquired by the mobile scanner effectively. Also, the accuracy of the constructed geospatial information was evaluated and the deviation of mean 0.083m was shown. Point cloud products constructed through the research can contribute to the efficiency improvement of mine management by enabling quantitative analysis such as visualization of mine shape, distance, area and slope, and automation of drawing creation for cross section shape.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.323-328
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• 2019

In order to construct 3D geospatial information about the terrain, current measurement using a total station, remote sensing, GNSS(Global Navigation Satellite System) have been used. However, ground survey and GNSS survey have time and economic disadvantages because they have to be surveyed directly in the field. In case of using aerial photographs and satellite images, these methods have the disadvantage that it is difficult to obtain the three-dimensional shape of the terrain. The terrestrial LiDAR can acquire 3D information of X, Y, Z coordinate and shape obtained by scanning innumerable laser pulses at densely spaced intervals on the surface of the object to be observed at high density, and the processing can also be automated. In this study, terrestrial LiDAR was used to analyze slope displacement. Study area slopes were selected and data were acquired using LiDAR in 2016 and 2017. Data processing has been used to generate slope cross section and slope data, and the overlay analysis of the generated data identifies slope displacements within 0.1 m and suggests the possibility of using slope LiDAR on land to manage slopes. If periodic data acquisition and analysis is performed in the future, the method using the terrestrial lidar will contribute to effective risk slope management.

• 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.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.105-111
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• 2018

Purpose Quality control of instrument takes up a large part in the Radioimmunoassays. The gamma-ray instrument, which is one of the important instruments in the laboratory, observes the condition and performance of instrument and performs quality control of the instrument by measuring the Normalization, Calibration, Background and etc. However, there are some automation instruments which can't measure the counting efficiency of gamma-ray meters, resulting in insufficient management in terms of performance evaluation of gamma-ray meters. Therefore, the purpose of this paper is to manage the quality control continuously and regularly by suggesting how to measure the counting efficiency of gamma-ray instruments. Materials and Methods In case of a comparative measurement method to a gamma-ray instrument dedicated to nuclear medical examination, the CPM and counting efficiency can be obtained after the measurement of normalization by inserting the I-125 $200{\mu}L$(CPM 50,000~500,000) into the test tube. With this CPM and counting efficiency values, it's possible to calculate the measurement of the DPM value and count the CPM from the automation instrument from the same source, and enter the DPM to calculate the counting efficiency using a comparative measurement method. Another method is to calculate the counting efficiency by estimating the half life using the radiation source information of the tracer in B test reagents of company A. Results According to the calculation formula using the DPM obtained by counting the normalization of gamma-ray meters, the detection efficiency was 75.16% for Detector 1, 76.88% for Detector 2, 77.13% for Detector 3, 75.36% for Detector 4 and 73.2% for Detector 5 respectively. Using another calculation formula estimated from the shelf life, the data of the detection efficiency from Detector 1 to Detector 5 were 74.9%, 75.1%, 76.5%, 74.9% and 73.2% respectively. Conclusion Although the accuracy of counting efficiencies of both methods are insufficient, this is considered to be useful for ongoing management of quality control if counting efficiency is managed after setting the acceptable ranges. For example, if the measurement efficiency is set to 70% or higher, the allowed %difference between measurements is within 3% and the %difference with the detector wall is set within 5%.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.541-551
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• 2021

Among the numerous duties of a librarian in a library, the work of arranging books is a job that the librarian has to do one by one. Thus, the cost of labor and time is large. In order to solve this problem, the interest in book-arranging robots based on artificial intelligence has recently increased. In this paper, we propose the K-ACO algorithm, which is the shortest path algorithm for multi-stops that can be applied to the library book arrangement robots. The proposed K-ACO algorithm assumes multiple robots rather than one robot. In addition, the K-ACO improves the ANT algorithm to create K clusters and provides the shortest path for each cluster. In this paper, the performance analysis of the proposed algorithm was carried out from the perspective of book arrangement time. The proposed algorithm, the K-ACO algorithm, was applied to a university library and compared with the current book arrangement algorithm. Through the simulation, we found that the proposed algorithm can allocate fairly, without biasing the work of arranging books, and ultimately significantly reduce the time to complete the entire work. Through the results of this study, we expect to improve quality services in the library by reducing the labor and time costs required for arranging books.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.104-112
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• 2021

In this study, emotional analysis was conducted based on the basic attribute data of music and the emotional model in psychology, and the result was applied to the visualization rules in the formative arts. In the existing studies using musical parameter, there were many cases with more practical purposes to classify, search, and recommend music for people. In this study, the focus was on enabling sound data to be used as a material for creating artworks and used for aesthetic expression. In order to study the music visualization as an art form, a method that can include human emotions should be designed, which is the characteristics of the arts itself. Therefore, a well-structured basic classification of musical attributes and a classification system on emotions were provided. Also, through the shape, color, and animation of the visual elements, the visualization of the musical elements was performed by reflecting the subdivided input parameters based on emotions. This study can be used as basic data for artists who explore a field of music visualization, and the analysis method and work results for matching emotion-based music components and visualizations will be the basis for automated visualization by artificial intelligence in the future.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.1-13
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• 2021

The concept of integrated pest management (IPM) first developed in the 1950s, and the concept of economic control via pest management was established in the 1960s. Research on IPM began in the United States and Europe, and IPM studies in Korea started with citrus insects and paddy field pests following the distribution of high-yield varieties of rice. Apple IPM in Korea began with research on pest control using chemical pesticides and pesticides resistant to insect pests, studies on the ecology of insect pests and their natural enemies, and the exploitation of sex pheromones on insect pests. Since the 1990s, IPM research and field projects have been carried out simultaneously for farming households. In the 2000s, the development of pest monitoring and forecasting models centered on mating disturbances, database programs for pests, and networks for sharing information. IPM technology has expanded via the development of unmanned forecasting systems and automation technologies in the 2010s.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.104-112
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• 2021

For extrusion processes in the process industry, the need to build smart factories is increasing. However, in most extrusion production sites, the production method is continuous, and because the properties of the data are undeed, it is difficult to process the data. In order to solve this problem, we present a methodology utilizing a near field communication (NFC) sensor rather than water-based data entry. To this end, a wireless network environment was built, and a data management method was designed. A non-contact NFC method was studied for the production performance-data input method, and an analysis method was implemented using the pivot function of the Excel program. As a result, data input using NFC was automated, obtaining a quantitative effect from reducing the operator's data processing time. In addition, using the input data, we present a case where a bottleneck is improved due to quality problems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.