• Economic and Environmental Geology
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• v.55 no.5
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• pp.429-438
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• 2022

This study evaluated the effect of the degree of weathering on the particle size distribution and the amount of fine particles generated in the aggregate production process during the crushing of igneous rock. Rock samples were collected from three areas with differences in strength from the Schmith hammer measurement at the aggregate quarry in Geochang, Gyeongsangbuk-do. After crushing with a jaw crusher under the same conditions in laboratory, particle size analysis, mineral analysis, chemical analysis, and weathering index were calculated. The Schmidt hammer measurements were 56, 28, and <10, and the CIA and CIW values of weathering index were also different, so the rock samples were classified into hard rock, soft rock, and weathered rock according to the weathering degree. It shows a smaller particle size distribution toward weathered rocks under the microscope, and the proportion of altered clay minerals such as sericite increased. The composition of feldspar and quartz was high for hard rock, and the ratio of muscovite and kaolinite was low. As a result of the crushing of the jaw crusher, hard rock produced a lot of coarse crushed material (13.2mm), while soft rock and weathered rock produced fine crushed material (4.75mm). The former showed the characteristics of the beta distribution curve, and the latter showed the bimodal distribution curve. The production of fine rock particles (based on 0.71mm of sieve, wt. %) increased to 13%<21%<22% in hard rock, soft rock, and weathered rock, and the greater the degree of weathering, the more fine rock particles were generated. The fine particles are recovered by the operation of the sand unit in the wet aggregate production process. Therefore, in order to minimize the amount of sludge generated in the aggregate production process, it was judged that a study on the optimal operation of cyclones could be necessary.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.263-271
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• 2019

The recent phenomenon of job "Miss Match", which is inconsistent with knowledge in the demand of educational training institutes and industries, has spread to an increase in private education costs for reeducation and employment of new hires, resulting in weak individual job competency and poor employment capability, as well as economic and material waste at the national level. To compensate for these problems, the National Competency Standards(NCS), which are available immediately in practice and look for a standard point of national job competency with the aim of fostering human resources sought by industries, were developed, and even the NCS-based qualification system was launched in line with the stream of times. This study is intended to look into the importance and priority of competency units and competency unit elements at the NCS-based qualification L3 level in the skin care field for an overall check of the NCS-based qualification level at a time when educational institutes are organizing and operating the school curriculums according to the NCS and NCS-based qualification level. And it is attempted to provide basic data for the development of curriculum in fostering professional human resources required by industries. To analyze the needs for competency units and competency unit elements at the L3 level, a survey using AHP method was carried out to a group of field experts and a group of education experts. In addition, the SPSS(Statistical Package for Social Science) ver. 21.0 and Expert Choice 2000, an AHP-only solution was used to do statistical processing through the processes of data coding and data cleaning. The findings showed that there was a partial difference of opinion between a group of field experts and a group of education experts. This indicates that the inconsistencies between educational training institutes and industrial sites should be resolved at this time of change with the aim of fostering field customized human resources with professional skills. Consequently, the solution is to combine jobs at industrial sites and standardized educations of educational institutes with human resources required at industrial sites.