• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.21-27
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• 2023

This paper is a study on the development of an app that assists in putting alignment in golf. The proposed app measures the position and size of the hole cup on the green to provide the distance between the hole cup and the aiming point. To achieve this, artificial intelligence object recognition technology was applied in the development process. The app measures the position and size of the hole cup in real-time using object recognition technology on the camera image of the smartphone. The app then displays the distance between the aiming point and the hole cup on the camera image to assist in putting alignment. The proposed app was developed for iOS on the iPhone. Performance testing of the developed app showed that it could sufficiently recognize the hole cup in real-time and accurately display the distance to provide helpful information for putting alignment.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.302-302
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• 2023

최근 도시의 왜곡된 물순환 문제를 해결하기 위해서 저영향개발(Low Impact Development, LID) 기법을 적극적으로 도입하고 있다. 저영향개발은 자연의 침투, 증발산, 여과 등의 자연기작을 모방하여 강우유출수를 침투 및 저류시키는 기법으로 물순환 체계를 회복시킬 수 있다. 저영향개발 기법의 하나인 벽면녹화는 건축물이나 기반 시설물의 벽면과 같은 인공지반에 기반을 조성하고 식물을 식재하는 시설로 짧은 시간에 녹지 면적을 만들 수 있다. 또한, 건축물로 인해 생겨난 수직적인 면을 녹지로 활용할 수 있어 도시에 매우 특화된 시설이다. 본 연구는 벽면녹화의 저영향개발 시설로서의 성능을 확인하기 위해 실내 실험을 진행하여 강우유출수 저감효과 및 지체시간 지연효과를 확인하였다. 강우유출수 저감효과는 유입량 대비 저류량을 기준으로 유출저감률을 산정하여 분석하였으며, 총 유출시간을 측정하여 지연효과를 판단하였다. 벽면녹화 현장실험 대상지는 경상남도 양산시 물금읍 부산대학교 양산캠퍼스에 위치한 한국 녹색인프라저영향개발센터이며, 실내에 플랜터형 벽면녹화 시스템을 적용하였다. 부산시 금정구 2012년~2021년의 강수량을 사용해 백분위수 강우사상을 기준으로 30, 50, 70mm/hr의 강우 시나리오를 선정하였다. 물순환 효과를 판단하기 위해 불투수면을 대조군으로 설정하여 불투수면의 유출이 종료되는 시점까지 지표면 유출을 모니터링 하였다. 그 결과, 30, 50, 70mm/hr 시나리오별 유출률은 91.76%, 92.18%, 94.54%로 불투수면과 대비하여 유출이 적게 발생하였으며 총 유출시간은 불투수면대비 47분, 88분, 58분 증가하여 지연효과가 있음을 확인하였다. 본 연구는 실험을 통해 벽면녹화의 수문학적 성능을 분석하고자 유출량 저감효과와 지연효과를 확인하였다. 추후 다양한 강우 시나리오와 제원에 따라 실험이 수행된다면 더 정확히 벽면녹화의 물순환 효과를 확인할 수 있을 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.158-158
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• 2021

도시에 불투수면적이 증가하고, 기후변화가 극심해져감에 따라 홍수 및 열섬현상과 같은 도시의 물 문제가 발생하고 있다. 이를 해결하기 위한 정책의 일환으로 우리나라의 녹색건축인증제도(Green Standard for Energy and Environmental Design, G-SEED)에서는 물순환 관리를 평가하고 있다. 하지만, 현재 G-SEED의 평가방법을 살펴보면 빗물관리시설의 설치 정도로 평가하고 있고, 강우 특성 또한 고려되고 있지 않다. 그러므로 본 연구에서는 G-SEED의 빗물관리 및 이용 항목에 대해 수문 모델을 통해 효과를 정량화함으로써 성능에 따라 평가할 수 있는 방법을 제안하였다. 빗물관리 항목에서는 유출저감률을, 빗물이용 항목에서는 빗물이용률을 평가지표로 선정하였고, 각 평가인자를 산출하기 위하여 개념모델을 적용하였다. 빗물이용시설의 경우 초기우수배제장치 용량과 필터 효율에 따른 빗물유입량의 변화와 급수인원에 따른 수요량 변화를 고려한 수문모델을 개발하였고, 수요량과 빗물저장조 용량에 따른 유출저감률과 빗물이용률을 알아보기 위해 MATLAB을 이용하여 모의해보았다. 또한, 옥상녹화의 경우에는 강우, 저류, 증발산, 유출을 고려한 수문흐름모델을 적용하였고, 토층의 두께와 배수(저장) 층의 용량에 따라 모의하여 평가기준을 선정하였다. 제안된 수문모델의 검증을 위하여 서울대학교 기숙사와 35동 옥상녹화의 실측데이터를 비교하였고, 적용성 평가를 위해 RMSE(Root Mean Square Error)와 NSE(Nash-Sutcliffe Efficiency)를 이용하였다. 본 연구에서 제안된 방법을 통해 빗물관리시설의 수문학적 성능에 따른 평가가 가능해질 것이며 설계자와 건축가들로 하여금 실질적인 효과를 내는 시설을 설치하게끔 유도할 수 있을 것이다.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.14-23
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• 2017

In high-density high-rise cities such as Hong Kong, buildings account for nearly 90% of energy consumption and 61% of carbon emissions. Therefore, it is important to study the design of buildings, especially high-rise buildings, to achieve lower carbon emissions in the city. The carbon emissions of a building consist of embodied carbon from the production of construction materials and operational carbon from energy consumption during daily operation (e.g., air-conditioning and lighting). An integrated analysis of both types of carbon emissions can strengthen the design of low carbon buildings, but most of the previous studies concentrated mainly on either embodied or operational carbon. Therefore, the primary objective of this study is to develop a holistic methodology framework considering both embodied and operational carbon, in order to enhance the sustainable design of low carbon high-rise buildings. The framework will be based on the building information modeling (BIM) technology because BIM can be integrated with simulation systems and digital models of different disciplines, thereby enabling a holistic design and assessment of low carbon buildings. Structural analysis program is first coupled with BIM to validate the structural performance of a building design. The amounts of construction materials and embodied carbon are then quantified by a BIM-based program using the Dynamo programming interface. Operational carbon is quantified by energy simulation software based on the green building extensible Markup Language (gbXML) file from BIM. Computational fluid dynamics (CFD) will be applied to analyze the ambient wind effect on indoor temperature and operational carbon. The BIM-based framework serves as a decision support tool to compare and explore more environmentally-sustainable design options to help reduce the carbon emissions in buildings.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.241-242
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• 2022

Recently, related studies on the application of bacterial spores to self-healing concrete have been widely reported. Using the self-healing method of bacterial spores as a kind of pro-environment, the green method is very attractive, but because the living environment of bacterial spores is relatively harsh, it is necessary to have a way to separate the living environment of bacterial spores from the harsh external environment, And release bacterial spores when needed. Therefore, capsules are widely used in self-healing concrete. To enhance the self-healing effect, the capsules need to be evenly distributed in the concrete. Furthermore, we develop a CIP-based smart capsule with controllability. We determined the magnetic force of each capsule by mixing CIP in resin, then mass-fabricating the capsules for self-healing by a microfluidic method, and by measuring the kinetic distance of the capsules containing different amounts of cip under the action of a magnetic field strength. The results show that with the increase of the amount of cip, the active distance of the capsule also increases. When the cip is 8wt%, the active distance reaches 1.75cm. We believe this research can provide momentum for the development of self-healing capsule applications.

• Advances in concrete construction
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• v.14 no.3
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• pp.195-204
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• 2022

As a brittle failure mode, punching-shear failure can be widely found in traditional RC slab-column connections, which may lead to the entire collapse of a flat plate structure. In this paper, a novel RC slab-column connection with inner steel truss was proposed to enhance the punching strength. In the proposed connection, steel trusses, each of which was composed of four steel angles and a series of steel strips, were pre-assembled at the periphery of the column capital and behaved as transverse reinforcements. With the aim of exploring the punching behavior of this novel RC slab-column connection, a static punching test was conducted on two full-scaled RC slab specimens, and the crack patterns, failure modes, load-deflection and load-strain responses were thoroughly analyzed to explore the contribution of the applied inner steel trusses to the overall punching behavior. The test results indicated that all the test specimens suffered the typical punching-shear failure, and the higher punching strength and initial stiffness could be found in the specimen with inner steel trusses. The numerical models of tested specimens were analyzed in ABAQUS. These models were verified by comparing the results of the tests with the results of the analyzes, and subsequently the sensitivity of the punching capacity to different parameters was studied. Based on the test results, a modified critical shear crack theory, which could take the contribution of the steel trusses into account, was put forward to predict the punching strength of this novel RC slab-column connection, and the calculated results agreed well with the test results.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.164-164
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• 2022

The soybean (Glycine max(L.) Merrill), an important food crop in the world, is popular because of its high quality protein and oil content. Soybeans as a food have long been known for their beneficial effects on health and are well-recognized globally. Isoflavones, significant soybean secondary metabolic products, may be crucial in avoiding some cancers and lowering the risk of cardiovascular disorders. This study investigates the correlation between plant growth regulator and the effect on the isoflavone levels in soybean leaves. The study was carried out in the green-house of the southern crop department in miryang. Soybeans(Seonpung) were cultivated in 1/2000 of the Wagner pot. Ethephon(500, 1000, 2000 ppm) and ABA(100, 200, 400 ppm) were used as plant growth regulators, and they were each treated on R2, R5, and R7 stage. After treatment, leaves were sampled three times at intervals of 5 days, and the content of 6 isoflavones and coumestrol was analyzed. Soybean isoflavones were analyzed using Ultra Performance Liquid Chromatography (Acquity UPLC H-Class system, Waters). The isoflavones content showed an overall highly in the R5 stage, and the level was similar to that of no treatment in the R2 and R7 stage. The difference between the growth regulators was found to be higher than that of ethephon when ABA was treated. The coumestrol content was confirmed to be high in the order of R7, R5, and R2 on the treatment time, and it was found that the content increased as the treatment time was delayed. In the treatment with the growth regulator, the coumestrol content tended to be higher when ethephon was treated than ABA.

• Advances in nano research
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• v.15 no.5
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• pp.467-484
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• 2023

Despite the significant features of fiber-reinforced cementitious composites (FRCCs), including better mechanical, fractural, and durability performance, their high content of cement has restricted their use in the construction industry. Although ground granulated blast furnace slag (GGBFS) is considered the main supplementary cementitious material, its slow pozzolanic reaction stands against its application. The addition of nano-sized mineral modifiers, including nano-silica (NS), is an alternative to address the drawbacks of using GGBFS. The main object of this empirical and numerical research is to examine the effect of NS on the strain-hardening behavior of cementitious composites; ten mixes were designed, and five levels of NS were considered. This study proposes a new method, using a four-point bending test to assess the use of nano-silica (NS) on the flexural behavior, first cracking strength, fracture energy, and micromechanical parameters including interfacial friction bond strength and maximum bridging stress. Digital image correlation (DIC) was used for monitoring the initiation and propagation of the cracks. In addition, to attain a deep comprehension of fiber/matrix interaction, scanning electron microscope (SEM) analysis was used. It was discovered that using nano-silica (NS) in cementitious materials results in an enhancement in the matrix toughness, which prevents multiple cracking and, therefore, strain-hardening. In addition, adding NS enhanced the interfacial transition zone between matrix and fiber, leading to a higher interfacial friction bond strength, which helps multiple cracking in the composite due to the hydrophobic nature of polypropylene (PP) fibers. The findings of this research provide insight into finding the optimum percent of NS in which both ductility and high tensile strength of the composites would be satisfied. As a concluding remark, a new criterion is proposed, showing that the optimum value of nano-silica is 2%. The findings and proposed method of this study can facilitate the design and utilization of green cementitious composites in structures.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1145-1153
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• 2023

Urban trees play an important role in absorbing carbon dioxide from the atmosphere, improving air quality, mitigating the urban heat island effect, and providing ecosystem services. To effectively manage and conserve urban trees, accurate spatial information on their location, condition, species, and population is needed. In this study, we propose an algorithm that uses a high-resolution urban tree cover map constructed from deep learning approach to separate trees from the urban land surface and accurately detect tree locations through local maximum filtering. Instead of using a uniform filter size, we improved the tree detection performance by selecting the appropriate filter size according to the tree height in consideration of various urban growth environments. The research output, the location and height of individual trees in human settlement over Suwon, will serve as a basis for sustainable management of urban ecosystems and carbon reduction measures.