• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.273-273
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• 2020

환경부 홍수통제소의 경우는 전국단위의 강수량(지상, 레이더), 하천수위, 유사량 관측과 국부적으로 증발산량과 토양수분 관측이 이루어지고 있는 상황이며, 기상청 및 다른 공공기관도 각 목적에 맞게 수문기상관측이 이루어지나 유역(또는 지역) 단위의 물순환 과정(강우량, 유출량, 증발산량, 지하수함양량, 토양수분량 등 포함)을 규명하는 조사·연구는 매우 미비한 실정이다. 개별적인 물순환 성분별 수문조사에서 벗어난 전체적인 관점을 고려한 유역단위의 물순환 과정을 규명하는 것은 매우 중요하다. 즉 물순환 성분별 명확한 수문량 산정 결과는 수자원 개발과 물환경 보전에 중요한 정보를 제공할 수 있다. 따라서 물순환 성분별 명확한 분석을 위해서는 중·소규모 유역 단위를 대상으로 지속적이고 신뢰성 있는 자료의 획득과 축적이 중요하므로 중·소규모 유역단위의 대표성 있는 시험유역의 운영은 매우 의미가 있다고 볼 수 있다. 본 논문에서는 한국건설기술연구원에서 운영하는 차탄천 유역(유역면적 190.64㎢, 유로경사 0.96%, 경기도 연천군 소재)의 신뢰성 높은 2019년 관측자료를 이용하여 물순환 성분인 강우량, 하천유출량, 증발산량의 자료를 산정하였으며, 물순환 성분별 균형을 이루는 자료를 생성하였다. 기본 관측자료인 강우량은 각 지점강우량의 관측자료의 비교·검토 등 품질관리를 통해 자료를 확정하고 유역평균강우량을 산정하였다. 하천수위는 기준수위표와의 검토, 상·하류 검토를 통해 자료를 확정하였으며, 하천유출량은 유량측정성과와 단면검토를 통해 수위-유량관계곡선식을 개발하고, 확정된 수위자료를 적용하여 산정하였다. 그리고 증발산량은 유역내의 기상관측자료를 활용하여 잠재증발산량을 산정하였다. 각 물순환 성분별로 산정된 자료는 과거년 자료와 비교·평가를 통해 균형성을 판단하였다. 각 성분별 최대치와 최소범위, 평균값을 고려하고, 강우일수, 강우의 강우강도와 지속기간, 기상자료(기온, 일조시간, 습도, 풍속 등)를 충분히 고려하였다. 각 물순환 성분별로 생성된 2019년의 차탄천 유역의 총강우량은 975.9mm이며, 하천유출량은 507.9mm(총강우량 대비 52.0%), 실제증발산량은 366.4mm(37.5%), 지하수함양량은 101.6mm(10.4%)이다. 여기서, 실제증발산량은 유역내 1개 지점의 잠재증발산량을 산정하여 추정한 값이며, 지하수 함양량을 산정을 위한 지하수위 관측정이 부재한 상황이나 물순환의 폐합 조건을 고려하여 산정하였다. 이와 같이 산정된 물순환 성분별 자료는 유역의 물순환 과정 규명을 위한 기초자료로 매우 유용하게 활용될 수 있으며, 유역 물관리를 위한 의사결정 과정에 중요한 역할을 할 수 있을 것으로 기대된다.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.60-71
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• 2024

The present study aims to investigate the level difference of floor impact noises of composite floor structure using EVA resilient materials. In order to this, four different types of resilient materials were designed combining PET, PP sheet and EVA mount including Flat type, Deck type, Cavity type and Mount type. Totally 9 different samples were made for acoustic measurements which were carried out twice with bang-machine and impact ball as the heavy-weight floor impact noise sources. All the floor impact noise measurements were undertaken at the authentication institution. As a result, concerning Flat and Cavity types, it was found that 2 dB ~ 5 dB of heavy-weight floor impact noise was reduced supplementally when PET was added, while floor impact noise larger than 50 dB was acquired when single resilient material was used. Especially, most high performance was obtained for Mount type with 1st grade of light-weight floor impact noise and 2nd grade of heavy-weight floor impact noise. This is because of material property with low dense PET sound absorption materials which fill all around EVA mounts. Also, it was considered that this results are due to the sound impact absorption by the both EVA mounts and the air cavity between EVA mount and PP sheet. Also, it was found that at least 36 EVA mounts per 1m2 area of resilient panel make more noise reduction of heavy-weight floor impact noises.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.71-81
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• 2024

In response to the COVID-19 pandemic, the global airport industry is actively introducing 4th Industrial Revolution technology-based systems for quarantine and passenger safety, and test bed construction and prior verification using airport infrastructure and resources are actively being conducted. Analysis of recent cases shows that despite the changing travel patterns of airport users and the diversification of airport service demands, most testbeds construction studies are still focused on suppliers, and task prioritization is also determined by decision makers. There is a tendency to rely on subjective judgment. In order to find practical ways to become a first mover that leads innovation in the aviation industry, this study selected tasks and derived priorities to build testbeds from a service perspective that reflects various customer service needs and changes. Research results using the AHP analysis method resulted in priorities in the order of access transportation and parking services (29.2%), security screening services (23.4%), and departure services (21.8%), and these analysis results were tested in the airport industry. It shows that innovation in testbeds construction is an important factor. In particular, the establishment of smart parking and UAM transportation testbeds not only helps strengthen airports as centers of technological innovation, but also promotes cooperation with companies, research institutes, and governments, and provides an environment for testing and developing new technologies and services. It can be a foundation for what can be done. The results and implications produced through this study can serve as useful guidelines for domestic and foreign airport practitioners to build testbeds and establish strategies.

• Journal of Food Hygiene and Safety
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• v.39 no.4
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• pp.299-303
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• 2024

Collagen, as an indicator of skin health, has been developed and used for various purposes. The development of an optimized collagen product suitable for use has become an important research field as the consumption of collagen increases. In particular, various efforts are being made to increase its absorption rate. In this study, the transdermal and oral epithelial cell permeabilities of various molecular weight collagen products sold in Korea were compared using a Franz diffusion cell system. The collagen absorption rate of oral mucosal tissue compared to skin epidermis/dermis tissue was significantly higher than that of collagen at M.W. 500 and 1,000 (approximately 10 times and 2 times higher, respectively). Additionally, collagen with a molecular weight of 500 Da increased the absorption rates by 2-3 times compared with products with a molecular weight of 1,000. Collagen with a molecular weight of 500 Da showed the highest Cmax and AUCt values, and all parameters in the oral mucosal cell test group were higher than those in the skin epidermis/dermis cells. Our findings suggest an increased absorption rate through oral mucosal cells rather than skin absorption, confirming that low molecular weight collagen is a major factor increasing the absorption rate.

• Journal of IKEEE
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• v.28 no.3
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• pp.474-478
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• 2024

In this paper, we proposes a deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers. The proposed deep learning network is specifically designed for pharmaceutical containers by using data produced in real manufacturing environments, leading to more accurate quality inspection. Additionally, the use of an inline-capable deep learning network allows for an increase in inspection speed. The development of the deep learning network for quality inspection in the multi-camera inline inspection system consists of three steps. First, a dataset of approximately 10,000 images is constructed from the production site using one line camera for foreign substance inspection and three area cameras for dimensional inspection. Second, the pharmaceutical container data is preprocessed by designating regions of interest (ROI) in areas where defects are likely to occur, tailored for foreign substance and dimensional inspections. Third, the preprocessed data is used to train the deep learning network. The network improves inference speed by reducing the number of channels and eliminating the use of linear layers, while accuracy is enhanced by applying PReLU and residual learning. This results in the creation of four deep learning modules tailored to the dataset built from the four cameras. The performance of the proposed deep learning network for quality inspection in the multi-camera inline inspection system for pharmaceutical containers was evaluated through experiments conducted by a certified testing agency. The results show that the deep learning modules achieved a classification accuracy of 99.4%, exceeding the world-class level of 95%, and an average classification speed of 0.947 seconds, which is superior to the world-class level of 1 second. Therefore, the effectiveness of the proposed deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers has been demonstrated.

• Journal of IKEEE
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• v.28 no.3
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• pp.469-473
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• 2024

In this paper proposes a study on the development of a multi-camera inline inspection system using machine vision for quality inspection of pharmaceutical containers. The proposed technique captures the pharmaceutical containers from multiple angles using several cameras, allowing for more accurate quality assessment. Based on the captured data, the system inspects the dimensions and defects of the containers and, upon detecting defects, notifies the user and automatically removes the defective containers, thereby enhancing inspection efficiency. The development of the multi-camera inline inspection system using machine vision is divided into four stages. First, the design and production of a control unit that fixes or rotates the containers via suction. Second, the design and production of the main system body that moves, captures, and ejects defective products. Third, the design and development of control logic for the embedded board that controls the entire system. Finally, the design and development of a user interface (GUI) that detects defects in the pharmaceutical containers using image processing of the captured images. The system's performance was evaluated through experiments conducted by a certified testing agency. The results showed that the dimensional measurement error range of the pharmaceutical containers was between -0.30 to 0.28 mm (outer diameter) and -0.11 to 0.57 mm (overall length), which is superior to the global standard of 1 mm. The system's operational stability was measured at 100%, demonstrating its reliability. Therefore, the efficacy of the proposed multi-camera inline inspection system using machine vision for the quality inspection of pharmaceutical containers has been validated.

• Journal of Korean Library and Information Science Society
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• v.55 no.3
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• pp.213-239
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• 2024

This study comprehensively reconstructs the life of Baek Rin (1923-2015), who dedicated 43 years of his life as a university librarian, and provides an overview of his influence on the development of library science and his academic achievements. After passing the librarian recruitment exam at Seoul National University in 1948, he excelled as a librarian, handling various Korean, Chinese, Japanese, and Western literary materials. During the Korean War, he was in charge of the practical tasks of transporting and storing the National Treasures from Gyujanggak to Busan. After the war, he was responsible for organizing, cataloging, and classifying the books of Gyujanggak at Seoul National University. He prepared the initial drafts of book classification and served as an executive in several organizations, including the Korean Library Association. While teaching at universities after obtaining a master's degree in library science from Yonsei University, he published 49 academic articles and 7 edited and authored books. It is highly regarded that he was the first scholar to chronologically write the history of libraries in Korea. In 1973, he transferred to Harvard University's Yenching Library as a Korean studies cataloging librarian, and until his retirement in 1991, he cataloged East Asian classical texts and Korean books at Harvard's Yenching Library and supported the research of professors there. Baek Rin is a first-generation research librarian and teacher who laid the foundation for the barren Korean library science world.

• Journal of Life Science
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• v.19 no.5
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• pp.581-586
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• 2009

Bell pepper plants (Capsicum annuum cv. Plenty) were grown under low night temperatures (LNT: day/night temperature of $28/13^{\circ}C$) and optimum night temperatures (ONT: day/night temperature of $28/20^{\circ}C$) in growth chambers. Pollen grains were collected from plants in the growth chamber and incubated at 10, 15, 20, 25, and $30^{\circ}C$. After 24 hr incubation, in both ONT and LNT, the highest percent pollen germinations were observed at $25^{\circ}C$ followed by germinations at $30^{\circ}C$. Percent pollen germination at $25^{\circ}C$ was 42% in ONT - two times higher than in LNT at 21%. Pollen tube length was much longer at ONT than at LNT, regardless of incubation temperature. Compared with other treatments, earlier and quicker pollen tube elongation was observed in ONT pollen grains incubated at $25^{\circ}C$. To find pollen viability in plant growing conditions, pollen grains were incubated in LNT ($28/13^{\circ}C$) and ONT ($28/20^{\circ}C$) growth chambers for 24 hr. Petri-dishes with pollen grains were put in the growth chambers at the beginning of the night condition. Pollen grains in the LNT growth chamber did not germinate at night ($13^{\circ}C$), but began to germinate when the day condition ($28^{\circ}C$) started. Pollen grains in the ONT condition, however, started germinating from the early night ($20^{\circ}C$) and germination continued during the day ($28^{\circ}C$). Plants in LNT showed increased flower stalk length, ovary diameter, stamen length, flower weight, and fruit length. LNT conditions did not impair seed set. There were no differences in seed sets between fruits at LNT and ONT. Normal seed sets in LNT show that fertilization may be completed during daytime. However, further investigation is needed to find what extent of temperature stress causes malformed and/or parthenocarpic fruits in this bell pepper.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.1
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• pp.9-15
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• 1995

This study was carried out to investigate the effects of the optimal fertilizer application levels and planting space at different seeding parts on Chinese yam from 1992 to 1993. The results obtained was as follows： The earlist day to emergence was 42~56 days at tuber section, 37~46 days at an aerial tuber, and 50~56 days at an exposed parent material. in turn. The days to emergence were delayed by increasing fertilizer application levels. In the growth of the under-ground parts, vine length was increased in a tuber section, aerial tuber, and an exposed parent material in turn. The tuber section by 60${\times}$20cm at planting space, 56-56-64 Kg/10a at fertilizer application levels was appeared to be good growth among underground parts. As planted close, the growth of tuber section was decreased. The totoal yield was appeared to be increased about 19% in a tuber section planted as 30${\times}$20cm compared with 60${\times}$20cm. In an exposed parent ma-terial, the planting space, 30${\times}$15cm, was increased 10% compared with 45${\times}$15cm, and in an aerial tuber, the planting space, 10${\times}$10cm, was increased about 10% comparing 30${\times}$10cm. Fertilization level(N-$P_2O_2K_2O$) in 56-56-64Kg/10a was increased 39 to 47% comparing 28-28-32 Kg/10a. And the heavy dressing and the close planting space were appeared to be produced the highest yield. In considering commercial quality, the optimal combination between seeding parts and planting space is recommended to improve commercial qualities and high yield.