• 한국환경복원기술학회지
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• 제15권1호
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• pp.27-33
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• 2012

This study was performed in the Tropical Plant Resources Research Center of Korea National Arboretum to assess the effects of natural enemy attack on aphid population feeding on tropical plants. We measured the density of leaf-feeding aphids, Myzus persicae and Aphis gossypii, cohabiting with 5 types of tropical plants at intervals of approximately 2 weeks after introducing their natural enemy, Aphidius colemani. The density of aphids cohabiting with 4 types of tropical plants-Sanchezia parvibracteata, Hibiscus rosa-chinensis, Ficus kurzii, and Aloysia triphylla-started decreasing after 2 weeks of observation and was completely in control after 4 weeks of observation; however, the density of aphids cohabiting with the tropical plant, Hamelia patens, increased during 22 weeks of observation but decreased after the $23^{rd}$ week of observation. We suggest that a banker plant is necessary for the maintenance of A. colemani in tropical greenhouses, and monitoring studies on H. patens, which was weakest against the aphids, should be performed. Our results indicate that biological pest management strategies using their natural enemies were formulated for the construction of new tropical greenhouses.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Journal of the Korean Wood Science and Technology
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• 제41권2호
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• pp.158-163
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• 2013

Cross laminated timber (CLT) has been an rising issue as a promising building material replacing steel-concrete in mid story rise construction. But, there was no specific standard for CLT because it had been developed in industrial section. Recently, new draft for requirements of CLT was proposed by EN which suggested to evaluate the performance of adhesive in CLT by the same method as glulam. But, it has been reported that shear performance of cross laminated timber is governed by rolling shear. Therefore, block shear tests were carried out to compare parallel to grain laminating and cross laminating using commercial one component PUR (Poly urethane resin). The result showed that the current glulam standard for evaluating bonding performance is not appropriate for CLT. Beacause shear strength of cross laminating decreased to 1/3 of parallel to grain laminating and this strength was representing shear performance of wood itself not the bond. However, cross laminating showed no significant effect on wood failure. Thus, wood failure can be used as a requirement of CLT bonding. Based on the results, cross laminating effect should be included when evaluating adhesive performance of CLT correctly and should be considered as an important factor.

• 한국정보기술학회논문지
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• 제16권11호
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• pp.23-34
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• 2018

본 논문에서는 고효율 고역률 LED 조명장치용 전원공급장치를 제안한다. 제안한 전원공급장치는 풀브리지 다이오드 정류기와 플라이백 컨버터로 구성된 단일단 전력구조이며, 이에 따라 하나의 제어기 IC와 하나의 전력반도체스위치만을 사용하여 역률개선과 출력전압조정을 동시에 수행한다. 또한 제안한 전원공급장치는 회생스너버를 이용하여 주스위치의 전압스트레스와 스위칭손실을 감소시키며, 동기정류기를 이용하여 시스템 효율을 향상한다. 적용된 동기정류기는 새로운 전압구동형이며 동작과 구성이 간단하다. 본 논문에서는 역률개선부와 주전력변환부의 동작분석을 통하여 제안한 전원공급장치의 동작원리를 설명하고 동기정류기의 동작에 관하여 간략하게 설명한다. 또한 40W급 프로토타입 전력회로의 설계예시를 제시하며, 설계된 회로파라미터들에 의해 제작된 프로토타입의 실험 결과를 통하여 제안한 전원공급장치의 동작특성을 입증한다.

• 대한건축학회논문집:계획계
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• 제36권5호
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• pp.93-103
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• 2020

The purpose of this study is to suggest a supervisory way to improve the efficiency of Building Supervision using Deep Learning, especially object detecting technology. Since the establishment of the Building Supervision system in Korea, it has been changed and improved many times systematically, but it is hard to find any improvement in terms of implementing methods. Therefore, the Supervision is until now the area where a lot of money, time and manpower are needed. This might give a room for superficial, formal and documentary supervision that could lead to faulty construction. This study suggests a way of Building Supervision which is more automatic and effective so that it can lead to save the time, effort and money. And the way is to detect the hoop-bars of a column and count the number of it automatically. For this study, we made a hoop-bar detecting network by transfor learnning of YOLOv2 network through MATLAB. Among many training experiments, relatively most accurate network was selected, and this network was able to detect rebar placement in building site pictures with the accuracy of 92.85% for similar images to those used in trainings, and 90% or more for new images at specific distance. It was also able to count the number of hoop-bars. The result showed the possibility of automatic Building Supervision and its efficiency improvement.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.57-73
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• 2021

The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.

• Ecology and Resilient Infrastructure
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• 제10권1호
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• pp.1-10
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• 2023

제방은 기본적으로 물이 넘치지 않도록 하기 위하여 조성되는 구조물이다. 개발된 제방보강 기술은 바이오폴리머와 골재를 혼합하여 제방의 붕괴로 발생되는 대규모 재난을 방지하기 위한 기술로 제방의 세굴 및 붕괴 등을 억제하는데 목적이 있다. 개발된 기술은 호안 사면 등에도 활용이 가능하지만 시공성이 수월하여 월류파괴에 대한 대응 기술로 적용하기 용이하다. 개발된 기술을 현장에 적용하기 위해서는 기술의 안전성을 확보해야 하므로 현장시범사업 등 실제 적용에 대한 연구가 필요하다. 하지만 월류 파괴는 현장에서 시범사업을 수행할 수 없으므로 본 연구에서는 실규모 실험을 통해 현장 적용성 연구를 수행하였다. 실규모실험은 안동에 위치한 하천실험센터에서 수행하였으며, 인위적인 월류를 통하여 제방 세굴 및 붕괴 상황을 검토하였다. 실험결과 개발기술이 월류파괴에 대해 대응 가능하고 붕괴를 억제할 수 있는 기술로의 실증을 수행하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.177-179
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• 2022

Google Deepmind Challenge match에서, Alphago가 바둑 대결에서 4승1패로 한국의 이세돌(인간)에 승리하였다. 드디어, 인공지능은 인간 지능의 활용을 넘어서고 있는 것이다. 한국 정부의 디지털뉴딜의 사업예산은 2022년 9조원이며, 인공지능 학습용 data 구축사업은 301종을 추가로 확보한다. 2023년부터는 산업의 전 분야에서 인공지능의 학습의 활용과 적용으로 산업 패러다임이 변화될 것이다. 본 논문은 인공지능 알고리즘을 활용하기 위한 연구를 한다. 인공지능 학습에서 data의 분석과 판단을 중심으로, 인공지능 머신러닝과 딥러닝 학습에서의 알고리즘의 적절한 활용 대상과 활용 범위에 대한 연구를 한다. 본 연구는 4차산업혁명기술의 인공지능과 5차산업혁명기술의 인공지능로봇 활용의 기초자료를 제공할 것이다.

• 대한토목학회논문집
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• 제26권2D호
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• pp.325-333
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• 2006

현재, 대규모 지역에 대한 환경문제를 감시하는 기술로서 위성원격탐사 기술이 활발히 이용되고 있다. 이는 위성원격탐사 기술이 비교적 넓은 지역을 평가하기에 적절한 기술이기 때문이다. 그러나 최근에 들어서는 도로, 댐, 공항 등과 같은 대규모적인 토목공사 후의 녹화지대나 녹화 법면의 식생감시 등 비교적 좁은 영역을 정밀하게 조사할 수 있는 원격탐사 기법에 대한 수요가 발생되고 있다. 본 연구에서는 시판의 CCD 카메라와 새롭게 개발된 특수한 카메라 장치 등을 사용한 지상형 원격탐사 저고도 원격탐사 기술을 개발하고자 하였다. 본 연구에서 얻어진 결과는 다음과 같다. 네가지 지상형 원격탐사 장비간의 상호비교 실험에 사용된 필터의 투과 특성을 조사할 수 있었고, 식생지수를 추출하는 화상형 분광반사계로서 근적외선 디지털 카메라가 유용함을 알 수 있었다. 그리고, 식생지수의 일중 변화현상을 실험을 통해 조사할 수 있었다. 마지막으로 새롭게 개발된 지상형 원격탐사 장비를 통해 산불 발생지역에서의 식생지수의 변화현상을 조사할 수 있었다.

• Advances in concrete construction
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• 제14권3호
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• pp.153-167
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• 2022

The interaction between blast load and structures, as well as the interaction among structural members may well affect the structural response and damages. Therefore, it is necessary to analyse more realistic reinforced concrete structures in order to gain an extensive knowledge on the possible structural response under blast load effect. Among all the civilian structures, columns are considered to be the most vulnerable to terrorist threat and hence detailed investigation in the dynamic response of these structures is essential. Therefore, current research examines the effect of blast loads on the reinforced concrete columns via development of Pressure- Impulse (P-I) diagrams. In the finite element analysis, the level of damage on each of the aforementioned RC column will be assessed and the response of the RC columns when subjected to explosive loads will also be identified. Numerical models carried out using LS-DYNA were compared with experimental results. It was shown that the model yields a reliable prediction of damage on all RC columns. Validation study is conducted based on the experimental test to investigate the accuracy of finite element models to represent the behaviour of the models. The blast load application in the current research is determined based on the Lagrangian approach. To develop the designated P-I curves, damage assessment criteria are used based on the residual capacity of column. Intensive investigations are implemented to assess the effect of column dimension, concrete and steel properties and reinforcement ratio on the P-I diagram of RC columns. The produced P-I models can be applied by designers to predict the damage of new columns and to assess existing columns subjected to different blast load conditions.