유도탄용 레이돔 시선각 오차 보정 기법

김광희,Kim, Gwang-Hee 한국군사과학기술학회 2005 한국군사과학기술학회지 Vol.8 No.3

The radome boresight error degrades the microwave seeker ability and the missile guidance performance. It increases the miss distance, also. This paper propose a method of radome boresight error measurement and compensation. The compensation method consist of radome analysis and radome compensation. In the radome analysis stage, we can know that the electromagnetic characteristics distorted by radome. In the compensation stage, the look-up table is built and used for compensation. The test uses a FMS(Flight motion simulator) and adjusts the FMS setup error for more accuracy. The result shows that not using an elaborate radome measurement equipment, the radome boresight error is well compensated easily.

학교건축공사에 감성안전도입을 위한 근로자 선호도 조사 -감성안전센서와 감성안전 시설물 중심으로-

김광희,Kim, Gwang-Hee 한국교육녹색환경연구원 2011 교육·녹색환경연구 Vol.10 No.1

The deaths caused by industrial accidents during the construction of the mortality rate is considerably higher than in other industries. To prevent such a disaster workers and to minimize unsafe behavior measures to be drawn, and construction companies recently to stimulate the emotions of the workers to participate in voluntary activities are safe. In this study, the construction workers can stimulate emotions and activities on the environment by examining the preferences of the workers on-site management will want to take advantage. This study revealed that the construction workers prefer the incentive most and then working environment.

共同住宅 工事費 豫測 정확도 비교에 관한 硏究-事例基盤推論 技法과 神經網을 중심으로-

김광희(Kim Gwang-Hee),김상용(Kim Sang-Yong),강경인(Kang Kyung-In) 대한건축학회 2004 大韓建築學會論文集 : 構造系 Vol.20 No.5

Prediction of the cost estimation of apartment houses is an important task in the management of construction projects.<br/> Early project estimates represent a key ingredient in construction project's decision making and often become the basis for<br/> a project's ultimate funding. This study predicts the cost of apartment houses using case-based reasoning(CBR) and<br/> artificial neural networks(ANN) techniques. CBR has been recently favored because it seems to resemble more closely the<br/> psychological process such as human ideas when trying to apply their knowledge to the solution of problems. ANN has<br/> proved themselves to be very useful in various modeling applications, because it can represent complex mapping functions<br/> and discover the representations using powerful learning algorithm. This study is conducted by using the same 540 cases<br/> which are obtained in Korea. 30 cases among the data are used for testing. Testing error rates of 3.68% in the CBR and<br/> 6.66% in the ANN were obtained. Results showed that CBR can produce slightly more accurate results and achieve higher<br/> computational efficiency than ANN. If the use of CBR and ANN is understood better, as a result, cost estimation can be<br/> predicted with reasonability and reliability, all parties involved in the construction process could save considerable money.

사례기반추론 기법을 이용한 공동주택 초기 공사비 예측에 관한 연구

김광희(Kim Gwang-Hee),강경인(Kang Kyung-In) 대한건축학회 2004 大韓建築學會論文集 : 構造系 Vol.20 No.5

The purpose of this study is to propose the cost estimation system using case-based reasoning technique at the early project<br/> stage. To predict construction cost is difficult because of the lack of information about project at the early project stage and the complex interrelationships between many factors of influencing the construction cost. Case-based reasoning means using old<br/> experience to solve new problems. In this study, the used old experience is the direct cost of 530 apartment buildings,<br/> constructed from 1997 to 2001; the additional 10 cases are used for testing. The accuracy rate of predicting construction cost is<br/> compared using the CBR system with using regression analysis for verifying the CBR system. The prediction error rate of 4.74%<br/> in CBR system and 9.80% in regression analysis are obtained. This study conclude that utilizing the case-based reasoning for<br/> predicting construction cost in construction project is possible

위합성용액에서 과일주스에 노출한 Non-O157 Shiga Toxin-Producing Escherichia coli의 산 저항성 평가

김광희(Gwang-Hee Kim),오덕환(Deog-Hwan Oh) 한국식품영양과학회 2016 한국식품영양과학회지 Vol.45 No.4

다양한 환경에서 분리된 시가독소 생산성 대장균(Shiga toxin-producing E. coli, STEC, n=18)을 초산혼합용액(AAS; 400 mM, pH 3.2, 30°C)에 노출한 후 산 저항성을 측정하였다. 또한, 선정된 4종류의 non-O157:H7 STEC균을 사과주스, 파인애플주스, 오렌지주스, 딸기주스(pH 3.8)에 정봉하여 4°C와 20°C에서 24시간 산 적응시킨 후 위합성용액(SGF, pH 1.5)에서 2시간 동안 생존능력을 평가하였다. Non-O157:H7 STEC를 AAS에 노출했을 때 O111 혈청형의 STEC는 평균 0.12 log CFU/mL 감소하여 다른 혈청형에 비하여 가장 강한 산 저항성을 나타냈고 O157:H7 STEC와 유의적 차이가 없었으며(P>0.05), O26 혈청형의 STEC는 가장 민감한 것으로 나타났다. 반면, AAS에 glutamic acid를 첨가하였을 경우 모든 STEC는 혈청형과 관계없이 초산에 매우 강한 저항성을 나타내었다(P>0.05). SGF에서 생존능력을 측정한 결과, 06E0218(O157:H7)은 다른 non-O157:H7 STEC 균들보다 생존능력이 낮았고 03-4669(O145:NM)가 가장 강한 생존능력을 나타내었다. 한편, 과일주스 중에서는 파인애플주스에 산 적응된 STEC가 SGF에 가장 강한 생존능력을 나타내었다. 4°C의 과일주스에 STEC를 산 적응시켰을 경우 20°C보다 SGF에 대한 생존능력이 현저하게 높았다(P<0.05). 따라서 과일주스에 의한 non-O157:H7 STEC의 산 적응력 증가는 위장관 내 생존율 및 식중독 발생을 높일 수 있으므로 이에 대한 적절한 연구와 안전관리 옵션을 제공할 필요가 있을 것으로 판단된다. The objectives of this study were Ⅰ) to compare the acid resistance (AR) of seven non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups, including O26, O45, O103, O111, O121, O145, and O157:H7 STEC isolated from various sources, in 400 mM acetic acid solution (AAS) at pH 3.2 and 30°C for 25 min with or without glutamic acid and Ⅱ) to determine strain survival upon exposure to simulated gastric fluid (SGF, pH 1.5) at 37°C for 2 h after acid adaptation in apple, pineapple, orange, and strawberry juices at pH 3.8, 4°C and 20°C. Results show that the O111 serogroup strains had the strongest AR (0.12 log reduction CFU/mL) which was very similar to that of O157:H7 STEC (P>0.05), compared to other serogroups in AAS without glutamic acid, whereas O26 serogroup strains showed the most sensitive AR. However, there was no significant (P>0.05) difference of AR among seven serogroups in AAS with glutamic acid. In the SGF study, 05-6545 (O45:H2), 08023 (O121:H19), and 03-4669 (O145:NM) strains adapted in fruit juices at 4°C and 20°C displayed enhanced survival with exposure to SGF for 60 min compared to 06E0218 (O157:H7) strains (P<0.05). In addition, 4 STEC strains adapted in pineapple juice at 4°C showed enhanced survival with exposure to SGF for 60 min compared to those strains acid-adapted in the other fruit juices. Generally, adaptation at 4°C in fruit juices resulted in significantly enhanced survival levels compared to acid-adapted at 20°C and non-adapted conditions. The AR caused by adaptation in fruit juices at low temperature may thus increase survival of non-O157 STEC strain in acidic environments such as the gastrointestinal tract. These results suggest that more careful strategies should be provided to protect against risk of foodborne illness by non-O157 STEC.

초고층 건물 공기단축을 위한 기둥철근 3개층 선조립공법에 관한 연구

김광희(Kim, Gwang Hee),김재엽(Kim, Jae Yeob),서덕석(Seo, Deok Seok),안성훈(An, Sung Hoon),최희복(Choi, Hee Bok),정병원(Jung, Beong Won) 한국생태환경건축학회 2007 한국생태환경건축학회 논문집 Vol.7 No.2

遺傳子 알고리즘에 의한 神經網 構造의 最適化를 이용한 共同住宅의 初期 工事費 豫測에 관한 硏究

김광희(Kim Gwang-Hee),강경인(Kang Kyung-In) 대한건축학회 2004 大韓建築學會論文集 : 構造系 Vol.20 No.2

The purpose of this study was to propose the method of improving generalization of neural networks by optimizing NN's architecture and parameters using genetic algorithms. The models of NN s and regression analysis applied were error back-propagation network and linear multi-regression analysis respectively. This study applied the historical data of apartment buildings' direct costs to each model for training and verifying the validity of it. The results of this study were as follows: (1) the model that NN's architecture and parameters were optimized by GAs was superior to the regression model in cost estimation of apartment buildings. (2) the application of genetic algorithms may be a proper solution to the problem that user have because of the lack of adequate rules for determining the parameters of neural networks in utilizing neural networks.

건축공사 작업자의 생산성 관련 요인선정 및 요인별 중요도 관련 연구

김광희(Kim Gwang-Hee),정영철(Jung Young-Chul),김진동(Kim Jin-Dongn),이영도(Lee Young-Do) 대한건축학회 2012 大韓建築學會論文集 : 構造系 Vol.28 No.9

As the construction sites are exposed to various potential dangers and the construction workers are not sufficiently guaranteed of their wages and job security, the young people do not want to enter to the construction labor market. So, due to the shortage of young workers into the construction industry, the construction workers are getting older and the construction sites are hard in getting young workers. This study conducted the quantitative analyses of productivity factors using the importance analysis, variance analysis which affect the productivity of construction workers. The results of this study would help the construction managers to gradually meet the factors which affect the construction productivity and conduct the reasonable personnel management and this study also will be the basic data for future study on the enhancement of productivity of the construction workers.

共同住宅 프로젝트의 初期 工事費 豫測을 위한 神經網 學習에 遺傳子 알고리즘을 適用한 모델에 관한 硏究

김광희(Kim Gwang-Hee),강경인(Kang Kyung-In) 대한건축학회 2003 大韓建築學會論文集 : 構造系 Vol.19 No.10

The purpose of this study was to propose a model of neural networks training by genetic algorithms for predicting preliminary cost estimates about apartment projects at the early project stage. In previous studies, neural network model is superior to the regression model in cost estimation. But it has a problem that could be trapping local minima.<br/> Therefore, this study applied genetic algorithms to train the weights of neural networks. The result of the research revealed that training neural networks using genetic algorithms is effective in estimating the preliminary costs of apartment projects at the early project stage.

건물 골조수량 산출 시 BIM모델 기반 수량과 2D도면 기반 수량 차이 요인 분석

김광희 ( Kim¸ Gwang-hee ) 한국건축시공학회 2023 한국건축시공학회지 Vol.23 No.5

Recently, research on the use of Building Information Modeling(BIM) for various construction management activities is being actively conducted, and interest in 3D model-based estimation is increasing because it has the advantage of being able to be automatically performed using the attribute information of the 3D model. Therefore, this study aimed that the difference in the quantities is calculated the quantity based on the 2D drawing of a building and is extracted from the 3D model created by the Revit software was compared and tried to find out the cause. The difference in the quantity calculated by the two methods was the largest in the formwork, followed by the smallest in the order of the quantity of rebar and concrete. The reason for this difference is that there is a part where the quantity extraction in the 3D model is not suitable for the quantity calculation standard, and in particular, in the case of formwork, it was difficult to separate only the quantity of the necessary part. In addition, since the quantity of rebar was not separated by member, it was impossible to accurately compare the quantity and identify the cause of the difference. Therefore, it is considered to be the most reasonable to use application software that imports only the numerical information necessary for quantity calculation from the 3D model and applies a separate calculation formula.