• 호남수학학술지
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• 제32권2호
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• pp.307-331
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• 2010

The notion of intuitionistic fuzzy semi-pre interior (semi-pre closure) is introduced, and several related properties are investigated. Characterizations of an intuitionistic fuzzy regular open set, an intuitionistic fuzzy semi-open set and an intuitionistic fuzzy ${\gamma}$-open set are provided. A method to make an intuitionistic fuzzy regular open set (resp. intuitionistic fuzzy regular closed set) is established. A relation between an intuitionistic fuzzy ${\gamma}$-open set and an intuitionistic fuzzy semi-preopen set is considered. A condition for an intuitionistic fuzzy set to be an intuitionistic fuzzy ${\gamma}$-open set is discussed.

• 한국군사과학기술학회지
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• 제10권1호
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• pp.144-149
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• 2007

Behaviour of a thread joint of a rocket motor case show complex structural characteristics. Pre-torque must be applied to the threads to prevent the loosening of the interface from the additional pressure load. During the pressurization of the rocket motor case, the jointing face may be opened if the pre-torque were not set properly or the structure may be failed if the local concentrated stress exceeds the strength of the material. In this paper, the structural behaviour of a thread joint of a rocket motor case were analyzed by the finite element method and the results were compared to the experimental ones. A method to set a pre-torque for a thread joint were proposed to ensure the structural safety.

• 핵의학기술
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• 제15권2호
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• pp.41-46
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• 2011

영상장치를 이용한 검사 시 영상의 질은 검사결과와 밀접하게 연관되어 있으며, 이는 영상획득 조건들과 이에 대한 평가방법으로 인해 달라 질 수 있다. 본 연구에서는 영상획득 시 사전설정법(Pre-set method)차이에 따른 영상의 질을 평가하였다. 장비는 PET/CT Discovery STe16(GE Healthcare, Milwaukee, USA)을 사용하였으며, Chest PET Phantom (실험 1)과 94 NEMA Phantom (실험 2)을 이용하였다. 실험 1의 경우 3.5, 6.0, 8.6 kBq/mL, 실험 2의 경우는 3.3, 5.5, 7.7, 9.9, 12.1, 16.5 kBq/mL의 $^{18}F$-FDG를 채웠고, 열소와 배후방사능과의 방사능 농도는 4:1의 비율을 유지하였다. 각 실험은 CT 투과촬영 후 3D로 2분 30초/프레임으로 시간설정법(Time-set method)과 1억 계수의 계수설정법 (Count-set method)을 적용하여 방출촬영 하였다. 영상의 질에 대한 평가는 잡음 등가 계수율 (Noise Equivalent Count Rate, NECR)과 신호 대 잡음비 (Signal to Noise Ratio, SNR)를 이용하였다. 실험 1에서 NECR과 SNR은 방사능 농도의 증가에 따라 시간설정법에서 53.7, 66.9, 91.4 과 7.9, 10.0, 11.7로 평가 모두에서 증가함을 보였으나, 계수설정법은 53.8, 69.1, 97.8과 14.1, 14.7, 14.4로 SNR은 NECR과 다르게 증감현상을 보이지 않았다. 또 다른 모형실험인 실험 2에서도 NECR과 SNR은 방사능 농도가 증가에 따라 시간설정법에서 45.1, 70.6, 95.3 115.6 134.6 162.2 과 7.1, 8.8, 10.6, 11.5, 12.7, 14.0으로 증가함을 보였으나, 계수설정법에서는 42.1 67.3 92.1 112.2 130.7 158.7 과 15.2, 15.9, 15.6, 15.4, 15.5, 14.9로 실험 1에서와 마찬가지로 SNR에서는 증감현상을 보이지 않았다. 사전설정법 변화와 관계없이 단위 질량당 방사능량 증가는 영상의 질도 비례하여 향상된다. 그러나 동일한 단위 질량당 방사능량에서는 영상획득의 시간을 늘려 총계수값을 증가시켜도 NECR에 영향을 주지는 않는다. 이는 NECR을 이용한 영상 질 평가는 영상획득 시 얻은 총 계수 값보다는 단위 시간당의 계수율이 영향을 준다는 것을 의미한다고 할 수 있다. 실험 모두에서 계수설정법으로 얻은 경우에는 단위 질량당 방사능량의 증가에도 불구하고 거의 비슷한 SNR값을 보이게 된다. 따라서 좋은 질의 영상을 얻기 위해서는 총 계수값의 증가보다는 단위질량당 방사능량을 높여야 하며, SNR만을 이용한 영상의 질에 대한 평가는 적절하지 않을 수 있다는 점을 고려하여야 한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.1197-1200
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• 2003

Urban subways usually make environmental problems because subway vibrations are transmitted to building structures. However, when the buildings are designed, vibrations due to subway are not usually considered in advance. This results in many environmental vibration problems after buildings are constructed. This study was carried out to set up and evaluate a pre-assessment technique for the environmental impact of urban subway vibration on newly planned buildings near a subway line. for this purpose, semi-emperical method was set up and vibration measurements were made on site in accordance with construction schedule. Computer simulation was also performed using ANSYS software to predict the building vibration and compared with the measured results for evaluation of the pre-assessment technique.

• 설비공학논문집
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• 제26권10호
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• pp.467-473
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• 2014

Since the operating conditions of HVAC systems are different from those for which they are designed, on-going commissioning is required to optimize the energy consumed and the environment in the building. This study presents a methodology to analyze operational data and its applications. A predicted operation model is to be produced through a statistical data analysis using multiple regressions in SPSS. In this model, the dependent variable is the pre-cooling time, and the independent variables include the power output of the supply air inverter during pre-cooling, the supply air set temperature during pre-cooling, the indoor temperature-indoor set temperature just before pre-cooling, supply heat capacity, and the lowest outdoor air temperature during non-cooling/non-heating hours. The correlation coefficient R2 of the multiple regression model between the pre-cooling hour and the internal/external factors is of 0.612, and this could be used to provide information related to energy conservation and operating guidance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 C
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• pp.1827-1829
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• 2002

This paper describes AC test for long delivered drum length of cable using pre-breakdown partial discharge detection(PPD) method, which can be applied to observe the causes of electrical breakdown of EHV XLPE insulation. This method is to de-energize applied voltage to cable rapidly using pre-breakdown partial discharge, and is able to prevent complete breakdown. By this effect, defects such as voids, metal particles and protrusion in cable can be observed clearly. AC resonant test set was used for PPD method. Localization of partial discharge was performed by time difference detection of the traveling wave. Accuracy of localization was 1% to the length of test cable. Through several experiments with XLPE cable, successful results of PPD method were obtained.

• 정보학연구
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• 제7권2호
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• pp.43-54
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• 2004

홉필드 네트웍(Hopfield Network)은 존 홉필드(John J. Hopfield) 박사에 의해 제안된 이래 패턴인식과 최적화 문제에 활용되어 왔다. 특히 리(Jian-Hua Li)에 의해 제안된 방식은 SVD(singular value decomposition) 기법을 사용하여 입력패턴을 재구성함으로써 효율향상에 기여하였다. 본 논문은 리(Li)가 제안한 홉필드 네트웍에 사용할 패턴 집합의 선형 선처리 방식에 따른 성능 향상을 실험하였다. 선형 선처리 방식에 하다마드 방식과 랜덤 방식이 최대 30%, 하다마드 방식이 최대 15%의 성능이 향상되었다. 수렴시간 측면에서 보면 랜덤 방식이 최대 5 이터레이션, 하다마드 방식이 최대 2.5 이터레이션의 성능 향상을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.151-152
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• 2019

본 논문에서는 동물 이미지 분류를위한 작은 데이터 세트를 기반으로 개선 된 심층 학습 방법을 제안한다. 첫째, CNN은 소규모 데이터 세트에 대한 교육 모델을 작성하고 데이터 세트를 사용하여 교육 세트의 데이터 세트를 확장하는 데 사용된다. 둘째, VGG16과 같은 대규모 데이터 세트에 사전 훈련 된 네트워크를 사용하여 작은 데이터 세트의 병목을 추출하여 새로운 교육 데이터 세트 및 테스트 데이터 세트로 두 개의 NumPy 파일에 저장하고, 마지막으로 완전히 연결된 네트워크를 새로운 데이터 세트로 학습한다.

• 설비공학논문집
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• 제16권11호
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• pp.1060-1067
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• 2004

To apply an analysis method of life cycle cost when assessing economics of equipment system, we should basically set up preconditions such as useful life, price escalation rate, interest rate, etc. as well as consider a calculation algorism of source energy and heat source system, which is a complex process for life cycle costing. For this reason, equipment designers tend to plan heat source systems, without a thorough investigation on economics of alternative systems at the pre-design phase. In this process, architectural designers should adopt a proper heat source system, which is one of the most important factors for planning an appropriate architectural design, through a discussion with equipment designers in a short time. In order to offer an evaluation method for equipment designers to analyze economics of an alternative heat source system easily at the pre-design phase, this research would define the simplified economics, evaluation method through analysis of existing papers for economics evaluation, and examine validity through comparison of simplified method values ($LCC_{EC}$) and life cycle costing values ($LCC_{15}$) for six alternative heat source systems.

• 한국측량학회지
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• 제36권5호
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• pp.423-432
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• 2018

Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.