• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.349-354
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• 2020

The preliminary investigation to expand the green space requires a lot of cost and time. In this paper, we solve the problem by measuring the ratio of green space in a specific region through a convolutional neural network based the green space classification using Google Earth images. First, the proposed method collects various region images in Google Earth and learns them by using the convolutional neural network. The proposed method divides the image recursively to measure the green space ratio of the specific region, and it determines whether the divided image is green space using a trained convolutional neural network model, and then the green space ratio is calculated using the regions determined as the green space. Experimental results show that the proposed method shows high performance in measuring green space ratios in various regions.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.1
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• pp.37-47
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• 2002

Recently gasoline direct injection method has been applied to gasoline engine to reduce fuel consumption rate by controlling fuel air mixture on lean condition by means of stratified charging, and to reduce simultaneously. Pollutant emissions especially NOx and CO by lowering the combustion temperature. But difficulty of controling local fuel air ratio at ignition area in flammability limit unavoidably appeared, because it is merely controlled by injection timing with spatial and temporal distribution of fuel mixture. In this study, the authors devised a uniquely shaped combustion chamber so called three-chamber GDI engine, intended to keep the more reliable fuel air ratio at ignition area. The combustion chamber is divided into three regions. The first region is in the rich combustion division, where the fuel is injected from the fuel injection valve and ignited by the spark plug. The second region is in the lean combustion division, where the combustion gas from the rich combustion division flows out and burns on lean condition. And the last region is in the main combustion division ie in the cylinder, where the gas from the above two combustion divisions mixed together and completes the combustion during expansion stroke. They found that the stable range of operation of three-chamber GDI engine on low-load condition exists in the lean area of average equivalence ratio. And they also found that the reformed engine reveals less specific fuel consumption and less pollutant emissions compared with conventional carburettor type gasoline engine.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.679-682
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• 2004

$SrGa_2S_4$:Eu green phosphor and SrS:Eu red phosphor have been synthesized by co-precipitation method, respectively. Two sulfide phosphors were influenced by oxygen defect in host materials. Excitation spectra of these phosphors have high efficiency at the long wavelength region. And emission efficiency is increased under the excitation wavelength of 465nm. The combination of thiogallate green phosphor and sulfide red phosphor based on blue light InGaN chip has made it possible to emit white light.

• International Journal of Industrial Entomology and Biomaterials
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• v.33 no.1
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• pp.36-40
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• 2016

Mulberry fruits also have tremendous potential for providing various valuable industrial products of very high economic value for human beings. Nevertheless, through global warming, the popcorn disease caused by sclerotia forming fungi reduces the productivity of mulberry fruits in worldwide. So, in this study, we investigated damage ratio of mulberry popcorn disease in mulberry fruit production farm (Buan, Jeongueb, Sangju, Gochang in Korea). In Jeonbuk Buan, popcorn disease rate was the highest about 30%, on the other hand, in case of Gyungbuk Sangju and Jeonbuk Gochang, not damage. Also, we investigated about popcorn disease prevention by various of chemical treatment methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2287-2312
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• 2018

Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.463-474
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• 2010

In this study, we evaluate the efficiency of Construction Industry using Data Envelopment Analysis(DEA). Since the Construction Industry has been traditionally operated through competition, it is important to measure the efficiency. In this paper, we empirically analyze the Efficiency of the 50 Korean Construction Industry. In detail, we used the scale of efficiency in order that efficiency cannot be affected by the total technical efficiency of each company and the scale of DMU by applying CCR or BBC model. Also, we analyzed the changes of measurement DEA model score. we adopted the basic DEA, RTS Region and MPSS(Most Productive Scale Size) method which are combined with efficiency measurement model in order to analyze the operational status. Furthermore, by complementing the shortfalls of the scale efficiency value of the DEA Model, RTS Region Model can be recommended to be appropriate in the evaluation of ideal input/output Quantity. In particular, input variables are total assets, construction capacity, the technical staff and output variables are sales volume, operating income. The result of RTS Region and MPSS shows that 9 DMUs of the efficiency frontier in the Construction Industry are analyzed to be relatively efficient DMUs, and 41 DMUs are analyzed to be inefficient DMUs, and finally inefficient DMUs are separated with Region 1 and Region 6.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.12
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• pp.609-619
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• 2015

A preprocessing scheme utilizing multi-division of the ROI (region of interest) in a chemiluminescence image during inversion is proposed. The resulting inverted image shows the flame's structure, which can be useful for studying combustion instability. The flame structure is often quantitatively visualized with PLIF (planar laser-induced fluorescence) images as well. The chemiluminescence image, which is a line-integral of the flame, needs to be preprocessed before inversion, mainly due to the inherent noise and the assumption of axisymmetry during the inversion. The feasibility of the multi-division preprocessing technique has been tested with experimentally-obtained OH PLIF and $OH^*$ chemiluminescence images of jet and swirl-stabilized flames burning substitute natural gas (SNG). It turns out that the technique outperforms two conventional methods, specifically, the technique without preprocessing and the one with uni-division, reconstructing the SNG flame structures much better than its two counterparts when compared using corresponding OH PLIF images. The characteristics of the optimum degree of polynomials to be applied for curve-fitting of the flame region data for the multi-division method involving two flames has also been investigated.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.37-47
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• 2024

In the summer of 2018, the Korea-Japan (KJ) region experienced an extremely severe and prolonged heatwave. This study examines the GloSea6 model's prediction performance for the 2018 KJ heatwave event and investigates how its prediction skill is related to large-scale circulation patterns identified by the k-means clustering method. Cluster 1 pattern is characterized by a KJ high-pressure anomaly, Cluster 2 pattern is distinguished by an Eastern European high-pressure anomaly, and Cluster 3 pattern is associated with a Pacific-Japan pattern-like anomaly. By analyzing the spatial correlation coefficients between these three identified circulation patterns and GloSea6 predictions, we assessed the contribution of each circulation pattern to the heatwave lifecycle. Our results show that the Eastern European high-pressure pattern, in particular, plays a significant role in predicting the evolution of the development and peak phases of the 2018 KJ heatwave approximately two weeks in advance. Furthermore, this study suggests that an accurate representation of large-scale atmospheric circulations in upstream regions is a key factor in seasonal forecast models for improving the predictability of extreme weather events, such as the 2018 KJ heatwave.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.841-848
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• 2009

A simple model to analyze non-linear density-wave instability in a sodium-cooled helically coiled steam generator is developed. The model is formulated with three regions with moving boundaries. The homogeneous equilibrium flow model is used for the two-phase region and the shell-side energy conservation is also considered for the heat flux variation in each region. The proposed model is applied to the analysis of two-phase instability in a JAEA (Japan Atomic Energy Agency) 50MWt No.2 steam generator. The steady state results show that the proposed model accurately predicts the six cases of operating temperatures on the primary and secondary sides. The sizes of three regions, the secondary side pressure drop according to the flow rate, and the temperature variation in the vertical direction are also predicted well. The temporal variations of the inlet flow rate according to the throttling coefficient, the boiling and superheating boundaries and the pressure drop in the two-phase and superheating regions are obtained from the unsteady analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.523-528
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.