• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.7
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• pp.581-588
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• 2014

The inlet/outlet flow in the tube-side of the shell and tube heat exchanger was experimentally measured to investigate the effect of the porous baffle on uniform flow distribution. A 1/3rd scale-downed model of a heat exchanger was used and particle image velocimetry was applied for measuring the instantaneous velocity vector fields. The absolute errors in the flow rate were calculated and compared for the tube-side with and without the porous baffle, by varying the flow rate from 60 to 90 LPM. The results revealed that the porous baffle can improve flow uniformity and reduce the absolute error in the flow rate of the model with the baffle by about 74%, compared to that without the baffle. This result can be used for improving the performance and design of the shell and tube heat exchanger.

• Journal of the Mineralogical Society of Korea
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• v.15 no.1
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• pp.44-58
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• 2002

A new polymorph of tridymite, an incommensurately modulated phase (IC phase), has been identified. While the symmetry of the IC lattice is same as that of the Ll phase, the geometry of the IC lattice structure is same as the basis of the L3 structure with a different modulation (modulation vector q=0.22 $c*_{H}$;$\lambda$ 37 ). On the other hand, the characteristic curved diffuse diffration observed from the Ll atoms could occur even at room phase suggests that the dynamic disordering of atoms, especially oxygen atoms could occur even at room temperature. The phase transition of Ll to L3 by grinding is gradual but very conspicuous: LllongrightarrowL1+IClongrightarrowIC+L3longrightarrowL3. However, it is revealed that real transition processes of individual grains are directly related to the local stress fields and preexisting microstructures.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.484-491
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• 2015

Aerial scene is greatly increased by the introduction and supply of the image due to the growth of digital optical imaging technology and development of the UAV. It has been used as the extraction of ground properties, classification, change detection, image fusion and mapping based on the aerial image. In particular, in the image analysis and utilization of deep learning algorithm it has shown a new paradigm to overcome the limitation of the field of pattern recognition. This paper presents the possibility to apply a more wide range and various fields through the segmentation and classification of aerial scene based on the Deep learning(ConvNet). We build 4-classes image database consists of Road, Building, Yard, Forest total 3000. Each of the classes has a certain pattern, the results with feature vector map come out differently. Our system consists of feature extraction, classification and training. Feature extraction is built up of two layers based on ConvNet. And then, it is classified by using the Multilayer perceptron and Logistic regression, the algorithm as a classification process.

• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.27-29
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• 2007

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.

• Journal of KIISE
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• v.44 no.12
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• pp.1290-1295
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• 2017

Document classification, a task of classifying the category of each document based on text, is one of the fundamental areas for natural language processing. Document classification may be used in various fields such as topic classification and sentiment classification. Neural network models for document classification can be divided into two categories: word-level models and character-level models that treat words and characters as basic units respectively. In this study, we propose a neural network model that combines character-level and word-level models to improve performance of document classification. The proposed model extracts the feature vector of each word by combining information obtained from a word embedding matrix and information encoded by a character-level neural network. Based on feature vectors of words, the model classifies documents with a hierarchical structure wherein recurrent neural networks with attention mechanisms are used for both the word and the sentence levels. Experiments on real life datasets demonstrate effectiveness of our proposed model.

• Proceedings of the Microbiological Society of Korea Conference
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• 2003.05a
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• pp.83-86
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• 2003

Major advances in positive-sense RNA virus research have been facilitated by the development of reverse genetics systems. These systems consist of an infectious cDNA clone that encompasses the genome of the virus in question. This clone is then used as a template for the subsequent synthesis of infectious RNA for the generation of synthetic viruses. However, the construction of infectious cDNA for the Japanese encephalitis virus (JEV) has been repeatedly thwarted by the instability of its cDNA. As JEV is an important human pathogen that causes permanent neuropsychiatric sequelae and even fatal disease, a reliable reverse genetics system for this virus is highly desirable. The availability of this tool would greatly and the development of effective vaccines as well as facilitate studies into the basic biology of the virus, including the molecular mechanisms of viral replication, neurovirulence, and pathogenesis. We have successfully constructed a genetically stable infectious JEV cDNA containing full-length viral RNA genome. Synthetic RNA transcripts generated in vitro from the cDNA were highly infectious upon transfection into susceptible cells, and the cDNA remained stable after it had been propagated in E. coli for 180 generations. Using this infectious JEV cDNA, we have successfully expressed a variety of reporter genes from the full-length genomic and various subgenomic RNAs in vitro transcribed from functional JEV cDNAS. In summary, we have developed a reverse genetics system for JEV that will greatly facilitate the research on this virus in a variety of different fields. It will also be useful as a heterologous gene expression vector and aid the development of a vaccine against JEV.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.191-196
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• 2005

Although the technology for emotion recognition is important one which was demanded in various fields, it still remains as the unsolved problems. Especially, there is growing demand for emotion recognition technology based on racial image. The facial image based emotion recognition system is complex system comprised of various technologies. Therefore, various techniques such that facial image analysis, feature vector extraction, pattern recognition technique, and etc, are needed in order to develop this system. In this paper, we propose new emotion recognition system based un previously studied facial image analysis technique. The proposed system recognizes the emotion by using the fuzzy classifier. The facial image database is built up and the performance of the proposed system is verified by using built database.

• The Plant Pathology Journal
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• v.25 no.2
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• pp.151-156
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• 2009

Tomato spotted wilt virus (TSWV) has occurred on fields annually disease occurrence rates were 73.3% in 2005, 53.3% in 2006 and 41.6% in 2007 at Anyang area in Gyeonggi Province. Seasonal occurrence pattern of TSWV showed a dramatic increase from 8.7% in late May to 30.1 % in early June in 2007 at Anyang area, coincided with the high population of a thrip, Frank-liniella occidentalis at that time. The rate of viruliferous thrips with TSWV on lettuce and red pepper was 20.2% and 52.1%, respectively, in greenhouses. Dazomat, soil fumigation pesticide, reduced TSWV disease incidence drastically on table tomato as treatment the chemical into the soil with humidity in early spring in 2006 and 2007. Spraying insecticide periodically after treatment with Dazomat was more effective to control TSWV than spraying if on plants or applying into the soil of the insecticide during growing season. Control efficiency through treatments both of the soil fumigation and of spraying insecticide was significantly high with 85.3% in 2006 and 87.8% in 2007. Removing the potential vector from the soil of TSWV infested area can be an effective strategy for reducing TSWV disease.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.21-27
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• 2018

In this paper, we propose a real-time interaction method using user's mouth wind in mobile device. In mobile and virtual reality, user interaction technology is important, but various user interface methods is still lacking. Most of the interaction technologies are hand touch screen touch or motion recognition. In this study, we propose an interface technology that can interact with real time using user's mouth wind. The direction of the wind is determined by using the angle and the position between the user and the mobile device, and the size of the wind is calculated by using the magnitude of user's mouth wind. To show the superiority of the proposed technique, we show the result of visualizing the flow of the vector field in real time by integrating the mouth-wind interface into the Navier-Stokes equations. We show the results of the paper on mobile devices, but can be applied in the Agumented reality(AR) and Virtual reality(VR) fields requiring interface technology.