• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.124-132
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• 2002

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum Input images, the angle between camera and illumination was found out to be with in 90$^{\circ}$. In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.

• Journal of Gifted/Talented Education
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• v.13 no.4
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• pp.95-117
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• 2003

This study is to suggest the alternative to limits of intelligence focused on Psychometric tests. Through this study, it was found that triarchic theory of intelligence and thinking styles, which were suggested by Sternberg, were useful. The subjects are 122 student who are at three science-high-schools. The results show that the subjects preferred judicial, executive, and hierarchical rather than conservative styles of thinking, and they had strong analytical, creative, and practical ability. The correlation between academic achievement and triarchic intelligence except automation was significant. The difference of academic achievements was not significant by styles of thinking related to creativity and pattern of triarchic intelligence. There was no interaction between two variables as we expected. The practical ability illustrated the total academic performance very well. And executive, judicial thinking styles were prediction variable in case of considering with triarchic intelligence. Through the results, it could be suggested that triarchic intelligence and thinking styles of non cognitive concept could be important standard referred to selection for the science-gifted, and argued that the reform of the science-high-school was needed to produce the creative-productive science-gifted student.

• Current Research on Agriculture and Life Sciences
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• v.20
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• pp.19-24
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• 2002

This study was conducted to determine the optimum intervals of shelves and seed-tray layout in container for raising rice seedlings at automatic facility. The seedling characteristics were evaluated with 10-day to 20-day old seedling grown under the different intervals of nursery shelves and seed-tray arrangement in the containers. The plant height was increased as the shelf intervals in nursery containers from 17 cm to 23 cm. The difference in plant height was larger in seedlings seeded at May 10 than those at June 10 and in 20-day old seedlings as compared with 10-day old seedlings. The growth characteristics of seedlings was significantly varied with the layout intervals of nursery tray on the containers. The seedling height was shorter as the extension of layout intervals of the tray on the shelf of nursery containers, but the seedling quality was increased in the seedling which grown on the trays arranged at 3 to 5 cm intervals. The light intensity was remarkably different from the position of nursery tray in the container. The illumination intensity was the highest on the uppermost tray. However the seedling height was shorter as the raising of tray position from the lowest shelf to the highest it in nursery container. The best results based on the seedling characteristics was obtained from the seedlings which grown in the tray arranged at 3 cm interval on the ten-shelf container with 20 cm intervals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.206-211
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• 2016

Various applications require dry air at low temperature, such automation equipment, semiconductor manufacturing, chemical production lines, and coating processes for the shipbuilding industry. Four evaporators for low temperature (below $0^{\circ}C$) were installed for a dehumidification system. Moist air is cooled sequentially over three evaporators. The first evaporator has an evaporation temperature of $13^{\circ}C$, that of the second evaporator is $5^{\circ}C$, and that of the third evaporator is maintained at $-1.3^{\circ}C$. In the fourth evaporator implantation thereby the moisture contained in the moisture air. A pressure regulator (CPCE 12) is used at this point and is defrosted when the vapor pressure is below a set value. The non-implantation moisture of the air is a heating system that uses the waste heat of a condenser with high temperature. It develops the cooling type's dehumidifier, which is important equipment that prevents the destruction of protein and measures the temperature and humidity at each interval by changing the front air velocity from 1.0 m/s to 4.0 m/s. The cooling capacity was also calculated. The greatest cooling capacity was 1.77 kcal/h for a front air velocity of 2.0 m/s

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.86-86
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• 2018

본 연구는 한국의 도시재생과 스마트 물 관리의 정책 분석을 위하여 도시재생과 스마트 물 관리의 등장 배경, 주요 현안 및 연계성을 모색하고 도시재생방안으로서 스마트 물 관리체계의 가능성을 검토하는 것을 목적으로 한다. 1950년대의 도시재건(Urban Reconstruction)과 1970~80년대의 도시재개발(Urban Renewal, Urban Redevelopment) 등의 정비 사업은 물리적 환경정비에 초점을 맞추었다. 그러나 1990년대 환경문제가 세계적 이슈로 등장하면서 교외지역 난개발 문제에 대한 대응책이 필요하게 되었고 도시의 물리 환경적, 산업 경제적, 사회 문화적 측면을 부흥시키는 도시재생 접근법이 출현하였다. 한국 정부는 2017년부터 시작한 '도시재생 뉴딜사업'의 일환으로 스마트 기술을 적용한 도시재생사업을 통해 스마트도시 선도국가 도약과 세계적 흐름에 부합하는 도시성장을 기대하고 있다. 1980년대 초 등장한 스마트 기술은 2000년대 들어와 스마트 도시, 스마트 인프라, 스마트 그리드 등의 분야로 확대, 진보하였다. 물 분야의 스마트 기술은 2009년 스마트워터그리드 이니셔티브(Smart Water Grid Initiative)의 발족과 함께 IBM, CISCO, Intel 등의 IT 기반 물 관리 워킹그룹 형성, Suez, Veolia, Siemens 등 수처리 기업의 스마트워터그리드 분야 진출 모색과 함께 발전하기 시작하였다. 이후 2012년 유엔 스마트 물 관리 포커스 그룹(ITU-T SG 5)의 스마트 물 관리 표준화 연구가 착수되었고 한국은 국토교통부 건설교통기술 연구 개발사업 중 하나로 스마트 물 관리 장기 연구 사업을 시작하였다. 스마트 물 관리는 수자원 및 상하수도 관리의 효율성 제고를 위하여 스마트 미터, 센서, 디지털지도제작 등 ICT를 이용한 차세대 물 관리시스템이라고 정의할 수 있다. 구체적인 대상 분야를 고려한다면 하천수, 우수, 지하수, 하폐수처리수, 해수담수 등 다양한 수자원의 관리, 물의 생산과 수송, 사용한 물의 처리 및 재이용 등 물 관리 전 분야를 포함한다. 그러나 스마트 물 관리의 용어와 개념을 처음으로 도입한 미국 등 선진국과 관련기업들은 스마트 물 관리를 '스마트 워터 미터, 센서, 첨단 모델링, 수문 지도제작, 스마트 관개농업, 자동화 로봇 등 다양한 기술을 통합적으로 운영하는 지능적인 수자원 관리를 위한 정보네트워크'로 정의한다. 일찍이 도시재생으로의 패러다임 전환을 실시한 영국 및 일본과 달리 한국의 도시재생은 개념, 구성요소, 범위, 사업방식 등의 여러 가지 측면에서 아직 형성단계에 있다. 또한 한국의 스마트 물 관리 논의는 개념정립 측면에서 심층적 논의가 거의 부재하였다. 기존의 논의들은 수자원 혹은 상하수도서비스 분야에서의 연구결과와 기술개발성과를 기계적으로 적용하고 확대하는 측면만을 부각시켰다. 그러나 이와 같은 스마트 물 관리에 대한 논의는 정보통신기술과 물 관리 서비스를 단편적으로 연결하고 적용범위를 제한할 수도 있다는 점에서 한계성이 있다. 본 연구는 국내외 문헌검토를 바탕으로 한국의 도시재생과 스마트 물 관리의 정책을 분석하고 지금까지 별개로 간주된 두 개념의 장점을 융합하여 향후 지속가능한 도시개발 사업으로서의 가능성을 검토하고자 한다.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.63-70
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• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.889-898
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• 2021

Currently, due to the demographic cliff phenomenon in Republic of Korea, A serious defense vacuum could occur due to the lack of South Korean military's personal strength. As a result, The South Korean military has a possibility to implement the polices the prepare for military provocations and preemptive strikes by the North Korean military while resolving the South Korean defense vacuum caused by the shrinking population. It seems like that the only way for the South Korean military to solve the shortage of personal strength due to the population decline is to reduce the number of Mechanized Units(MU) other than, infantry and automate, and autonomous driving the weapons system of the Mechanized Units(MU). In this paper, we propose the use of the virtual autonomous driving of the self propelled artillery K-9's in self selection of the position and occupation of position and self positioning in the position. At the same time in this paper, the self propelled artillery K-9 model robot is used to simulate and the explain about the operation method, necessity and feasibility in the self propelled artillery K-9. In addition, this paper predicted the problems that would arise if the South Korean military deployed autonomous driving self propelled K-9, in real combat.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Journal of the Korea Institute of Building Construction
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• v.19 no.2
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• pp.175-184
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• 2019

This paper presents a modeling prototype that optimizes construction processes implementing information communication technology (ICT). Using "IAMB", each and every actual steps of the construction process may be defined visually and explicitly by elaborating ICT to improve productivity and management efficiency. It contributes to identify the features on what parts of construction task are covered by ICT, and the effects of ICT on process performance. After analyzing 10 real project cases, ICT application types are classified into four categories according to ICT type, job functions that ICT applied, and the project phase in which ICT used. As a reuslt, it was confirmed that the positive outcomes on the construction process were beneficial to mostly the general contractors and mainly obtained by automated information processing, external consignment and consistent information use. Negative effects, which were occurred by mainly manual manipulation and duplication of information handling, were accrued to general contractors minimally, but to subcontractors maximally. Expert focus group commends that several important issues should be considered when implementing ICT.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.