• 한국균학회소식:학술대회논문집
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• 2014.10a
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• pp.11-11
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• 2014

Fungal pathogens have huge impact on health and economic wellbeing of human by causing life-threatening mycoses in immune-compromised patients or by destroying crop plants. A key determinant of fungal pathogenesis is their ability to undergo developmental change in response to host or environmental factors. Genetic pathways that regulate such morphological transitions and adaptation are therefore extensively studied during the last few decades. Given that epigenetic as well as genetic components play pivotal roles in development of plants and mammals, contribution of microbial epigenetic counterparts to this morphogenetic process is intriguing yet nearly unappreciated question to date. To bridge this gap in our knowledge, we set out to investigate histone modifications among epigenetic mechanisms that possibly regulate fungal adaptation and processes involved in pathogenesis of a model plant pathogenic fungus, Magnaporthe oryzae. M. oryzae is a causal agent of rice blast disease, which destroys 10 to 30% of the rice crop annually. Since the rice is the staple food for more than half of human population, the disease is a major threat to global food security. In addition to the socioeconomic impact of the disease it causes, the fungus is genetically tractable and can undergo well-defined morphological transitions including asexual spore production and appressorium (a specialized infection structure) formation in vitro, making it a model to study fungal development and pathogenicity. For functional and comparative analysis of histone modifications, a web-based database (dbHiMo) was constructed to archive and analyze histone modifying enzymes from eukaryotic species whose genome sequences are available. Histone modifying enzymes were identified applying a search pipeline built upon profile hidden Markov model (HMM) to proteomes. The database incorporates 22,169 histone-modifying enzymes identified from 342 species including 214 fungal, 33 plants, and 77 metazoan species. The dbHiMo provides users with web-based personalized data browsing and analysis tools, supporting comparative and evolutionary genomics. Based on the database entries, functional analysis of genes encoding histone acetyltransferases and histone demethylases is under way. Here I provide examples of such analyses that show how histone acetylation and methylation is implicated in regulating important aspects of fungal pathogenesis. Current analysis of histone modifying enzymes will be followed by ChIP-Seq and RNA-seq experiments to pinpoint the genes that are controlled by particular histone modifications. We anticipate that our work will provide not only the significant advances in our understanding of epigenetic mechanisms operating in microbial eukaryotes but also basis to expand our perspective on regulation of development in fungal pathogens.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.1-7
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• 2011

Recently, various researches have been proposed to accelerate GPU-based volume ray-casting. However, those researches may cause several problems such as bottleneck of data transmission between CPU and GPU, requirement of additional video memory for hierarchical structure and increase of processing time whenever opacity transfer function changes. In this paper, we propose an efficient GPU-based empty space skipping technique to solve these problems. We store maximum density in a brick of volume dataset on a vertex element. Then we delete vertices regarded as transparent one by opacity transfer function in geometry shader. Remaining vertices are used to generate bounding boxes of non-transparent area that helps the ray to traverse efficiently. Although these vertices are independent on viewing condition they need to be reproduced when opacity transfer function changes. Our technique provides fast generation of opaque vertices for interactive processing since the generation stage of the opaque vertices is running in GPU pipeline. The rendering results of our algorithm are identical to the that of general GPU ray-casting, but the performance can be up to more than 10 times faster.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.787-813
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• 2009

Because of global warming, the thawing of the Arctic ice cap is slowly accelerating. That is the hot issue nowadays. According to the each country's climate change policy, it is boom in the world to lessen the consuming of the fossil fuel those are oil, coal and natural gas. But on the contrary the thawing of the Arctic ice cap is the chance to make the natural gas producing unit cost lower. The purpose of this paper is to search the Arctic policy of each country under the contradictory relationship between promoting the climate change policy and exploiting the natural gas on the Arctic. Specially, there are huge natural gas reserves in Russia on the Arctic region, Russia's exploiting the natural gas on the Arctic will affect on the natural gas supply-demand balance of world natural gas market strongly in the future. Therefore it needs to prepare the future energy alternative policy for Korea's energy security. Russia has Yamal Peninsular where is abundant on natural gas reserver, and she can supply natural gas by LNG ship all over the world via the Arctic route. This means that the structure of world natural gas market be changed gradually. It will be possible in 2030~2040. And such a change is very important because new natural gas trading type can do it through not only overcoming the geological restriction but also shifting the main trading type from PNG(Pipeline Natural Gas) to LNG(Liquified Natural Gas). Therefore it is necessary that we should let this be a good lesson to ourselves through the government action of other countries (China, Japan) those also have no sovereignty over the Arctic as Korea.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.69-77
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• 2022

Several studies have been conducted to analyze the risk of ground subsidence occurring in urban areas. Recently, the correlation between the density of underground utilities (i.e., the quantity of buried utilities in the analysis area) and the recorded ground subsidence has been explored to analyze such risk through. Choi et al. (2021) proposed an algorithm to optimize the correlation between the ground subsidence and normalized linear density of underground pipelines. In this study, the optimization algorithm was modified for analysis based on the risk grade. The analysis results using the modified optimization algorithm were compared with the correlation analysis results between the density of underground utilities and recorded ground subsidence presented by Choi et al. (2021). Compared with Choi et al. (2021), three analysis results showed equal or higher accuracy in the correlation analysis with recorded ground subsidence according to risk grade. In particular, for R100, it was divided into five grades and compared with the ratio of the recorded ground subsidence that occurred in grades 4 or higher. As a result, Choi et al. (2021) showed that 86% of recorded ground subsidence occurred in grades 4 or higher, whereas this study showed 93%. It was confirmed that the accuracy of the modified optimization algorithm was improved. The modified optimization algorithm can be applied to develop a ground subsidence risk map for each grade in an urban area, which can be used as basic data for decision-making for underground utility maintenance.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.461-470
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• 2023

While speech animation generation employing deep learning has been actively researched for English, there has been no prior work for Korean. Given the fact, this paper for the very first time employs supervised deep learning to generate Korean speech animation. By doing so, we find out the significant effect of deep learning being able to make speech animation research come down to speech recognition research which is the predominating technique. Also, we study the way to make best use of the effect for Korean speech animation generation. The effect can contribute to efficiently and efficaciously revitalizing the recently inactive Korean speech animation research, by clarifying the top priority research target. This paper performs this process: (i) it chooses blendshape animation technique, (ii) implements the deep-learning model in the master-servant pipeline of the automatic speech recognition (ASR) module and the facial action coding (FAC) module, (iii) makes Korean speech facial motion capture dataset, (iv) prepares two comparison deep learning models (one model adopts the English ASR module, the other model adopts the Korean ASR module, however both models adopt the same basic structure for their FAC modules), and (v) train the FAC modules of both models dependently on their ASR modules. The user study demonstrates that the model which adopts the Korean ASR module and dependently trains its FAC module (getting 4.2/5.0 points) generates decisively much more natural Korean speech animations than the model which adopts the English ASR module and dependently trains its FAC module (getting 2.7/5.0 points). The result confirms the aforementioned effect showing that the quality of the Korean speech animation comes down to the accuracy of Korean ASR.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.4
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• pp.215-229
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• 2023

In this study, non-destructive technologies that can be applied to evaluate the integrity of valve materials, safety against internal pressure caused by corrosion, and the blocking function of large-diameter water valves during operation without requiring specimen collection or manpower entering the inside of the valve were tested to assess the reliability of the technologies and their suitability for field application. The results showed that the condition of the graphite structure inside the valve body can be evaluated directly through the optical microscope in the field without specimen collection for large-diameter water butterfly valves, and the depth of corrosion inside the valve body can be determined by array ultrasound and the tensile strength can be measured by instrumented indentation test. The reliability of each of these non-destructive techniques is high, and they can be widely used to evaluate the condition of steel or cast iron pipes that are significantly smaller in thickness than valves. Evaluation of blocking function of the valves with mixed gas showed that it can be detected even when a very low flow rate of mixed gas passes through the disk along with the water flow. Finally, as a result of evaluating the field applicability of non-destructive technologies for three old butterfly valves installed in the US industrial water pipeline, it was found that it is possible to check the material and determine the suitability of large-diameter water valves without taking samples, and to determine the corrosion state and mechanical strength. In addition, it was possible to evaluate safety through the measurement results, and it is judged that the evaluation of the blocking function using mixed gas will help strengthen preventive response in the event of an accident.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.2
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• pp.67-75
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• 2012

Carbon-dioxide capture and storage (CCS) process is consisted by capturing carbon-dioxide from large point source such as power plant and steel works, transporting and sequestrating captured $CO_2$ in a stable geological structure. During CCS process, it is inevitable of introducing impurities from combustion, capture and purification process into $CO_2$ stream. Impurities such as $SO_2$, $H_2O$, CO, $N_2$, Ar, $O_2$, $H_2$, can influence on process efficiency, capital expenditure, operation expense of CCS process. In this study, experimental apparatus is built to simulate the behavior of $CO_2$ transport under various impurity composition and process pressure condition. With this apparatus, $N_2$ impurity effect on $CO_2$ mixture transportation was experimentally evaluated. The result showed that as $N_2$ ratio increased pressure drop per mass flow and specific volume of $CO_2-N_2$ mixture also increased. In 120 and 100 bar condition the mixture was in single phase supercritical condition, and as $N_2$ ratio increased gradient of specific volume change and pressure drop per mass flow did not change largely compared to low pressure condition. In 70 bar condition the mixture phase changed from single phase liquid to single phase vapor through liquid-vapor two phase region, and it showed that the gradient of specific volume change and pressure drop per mass flow varied in each phase.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.