• Honam Mathematical Journal
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• v.32 no.2
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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.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.1
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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.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.41-46
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• 2011

Purpose: The result of exam using an imaging device is very closely related with the image quality. Moreover, this image quality can be changed according to the condition of image acquisition and evaluation method. In this study, we evaluated the image quality according to the difference of pre-set method in PET/CT image. Materials & Methods: PET/CT Discovery STe16 (GE Healthcare, Milwaukee, USA), Chest PET phantom (Experiment 1) and 94 NEMA phantom (Experiment 2) were used. Phantom were filled with $^{18}F$-FDG maintaining hot sphere and background ratio to 4:1. In the case of experiment 1, we set the radio activity concentration on 3.5, 6.0, 8.6 kBq/mL. In the case of experiment 2, we set the radio activity concentration on 3.3, 5.5, 7.7, 9.9, 12.1, 16.5 kBq/mL. All experiments were performed with the time-set method for 2 minutes 30 seconds per frame and the count-set method with one hundred million counts in 3D mode after CT transmission scan. For the evaluation of the image quality, we compared each results by using the NECR and SNR. Results: In the experiment 1, both the NECR and SNR were increased as radioactivity concentration getting increased. The NECR was shown as 53.7, 66.9, 91.4. and SNR was shown as 7.9, 10.0, 11.7. Both the NECR and SNR were increased in time-set method. But the count-set method's pattern was not similar with the time-set method. The NECR was shown as 53.8, 69.1, 97.8, and SNR was shown as 14.1, 14.7 14.4. The SNR was not increased in count-set method. In experiment 2, results of both the NECR and SNR were shown as 45.1, 70.6, 95.3, 115.6, 134.6, 162.2 and 7.1, 8.8, 10.6, 11.5, 12.7, 14.0. These results were shown similar patten with the experiment 1. Moreover, when the count-set method was applied, the NECR was shown as 42.1, 67.3, 92.1, 112.2, 130.7, 158.7, and SNR was shown as 15.2, 15.9, 15.6, 15.4, 15.5, 14.9. The NECR was increased but SNR was not shown same pattern. Conclusion: Increment of administered radioactivity improves the quality of image unconcerned with the pre-set method. However, NECR was not influenced by increment of total acquisition counts through simple increasing scan duration without increment of administered activity. In case of count-set method, the SNR was shown similar value despite of increment of radioactivity. So, the administered activity is more important than the scan duration. And we have to consider that evaluation of image quality using only SNR may not be appropriate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.10
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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.

• Proceedings of the KIEE Conference
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• 2002.07c
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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.

• The Journal of Information Technology
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• v.7 no.2
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• pp.43-54
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• 2004

Since Dr. John J. Hopfield has proposed the HOpfield network, it has been widely applied to the pattern recognition and the routing optimization. The method of Jian-Hua Li improved efficiency of Hopfield network which input pattern's weights are regenerated by SVD(singluar value decomposition). This paper deals with Li's Hopfield Network by linear pre-processing. Linear pre-processing is used for increasing orthogonality of input pattern set. Two methods of pre-processing are used, Hadamard method and random method. In manner of success rate, radom method improves maximum 30 percent than the original and hadamard method improves maximum 15 percent. In manner of success time, random method decreases maximum 5 iterations and hadamard method decreases maximum 2.5 iterations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.151-152
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• 2019

In this paper, we propose an improved learning method based on a small data set for animal image classification. First, CNN creates a training model for a small data set and uses the data set to expand the data set of the training set Second, a bottleneck of a small data set is extracted using a pre-trained network for a large data set such as VGG16 and stored in two NumPy files as a new training data set and a test data set, finally, learn the fully connected network as a new data set.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.11
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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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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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.