• Journal of Sasang Constitutional Medicine
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• v.14 no.3
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• pp.1-6
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• 2002

1.Objects of Research This research is purposed to find methods of treatment on serious diseases, through summarizing etiology, classification and treatment on serious diseases proposed in Sasang constitutional medicine 2.Methods of Research It was researched as bibliologically with Dong-mu's chief medical writings such as ${\ulcorner}$Dongyi Soose Bowon(東醫壽世保元)${\lrcorner}$, ${\ulcorner}$Dongyi Soose Bowon Sasang Chobongyun(東醫壽世保元四象草本卷)${\lrcorner}$ 3.Results and Conclusions 1. The principle of treatment in the previous medicine is to treat each disease by 'Assisting-Good Qi' and 'Removig-Bad Qi'. but The principle of treatment in Sasang Constitutional medicine is to manage incurable disease by helping 'Essential Qi of each constitution(體質正氣)' 2. Incurable disease is classified into a chronic disease by 'Nature(性氣)' and a acute disease by 'Emotion(情慾)'. Both diseases became serious through 'Noi-Ok(牢獄)' and 'Wi-Gyoung(危傾)'. A chronic disease is much in the middle years of life and become senile disease. A acute disease is much in the young years of life and make patients die young. 3. prognoses of incurable disease are different from degree of Inherent vitality(命脈實數) and term of disease. The case in which Inherent vitality is exhausted is thought that is unable to treat. 4. The prevention of incurable disease Is more important the treatment of one in Sasang Constitutional Medicine. but if incurable disease is caught, Medicine(醫藥) and management(調養) must be used together for treatment of incurable disease. Medicine is more important in the level of 'Noi-Ok(牢獄)' and management is more important in the level of 'Wi-Gyoung(危傾)'. 5. Therefore, incurable disease should be treated by method that 'Essential Qi of each constitution(體質正氣)' is recovered and declination is removed through 'controlling mind(治心) and correcting Qi(正氣), so then the state of 'Golden mean(中庸)'　is reached.

• Journal of the Korean GEO-environmental Society
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• v.6 no.2
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• pp.21-30
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• 2005

The purpose of this study was to evaluate the effect of vegetation on the cutting slope applied by vegetation system in the whole land. The engineering characteristics of slopes were investigated using the face mapping and physical tests. From the statistical methods, a relationship between a geologic stratum and degree of covering was independent. Therefore, the afforestation of slope was affected more by condition of vegetation as direction and opening of joints, and a topsoil state than by conventional classification of layer. It was concluded that the adjustable vegetation on the slope considering condition of geometric shape of slope, joint data and spontaneous type could make useful early afforestation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.13-21
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• 2002

In the interior lighting, usually we refer to TAL and general lighting. The last one is that we generally adopt it in the interior lighting conditions. Here, glare is most important factor of them, especially in working place using VDT. Reference or development of estimation on glare has been studied in CIE, IESNA etc. and these of glare regulations now are applied differently in the interior lighting design or estimation on glare. But we have no glare regulation in detail, of course except G classification, which has limit of itself, so in my case it is impossible to apply in the interior lighting. On this paper, with some of main glare regulations in the world and our conditions in the interior lighting which are selected carefully, in an actual state it has been estimated So, it intended to blow which one is most suitable or what factors are considered of them, also show glare index which are appropriate to our interior lighting.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.449-459
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• 1996

The main goal of this paper is to introduce a novel definition for fuzzy mathematical morphology and a neural network implementation. The generalized- mean operator plays the key role for the definition. Such definition is well suited for neural network implementation. The first stage of the shared-weight neural network has adequate architecture to perform morphological operation. The shared- weight network performs classification based on the features extracted with the fuzzy morphological operation defined in this paper. Therefore, the parameters for the fuzzy definition can be optimized using neural network learning paradigm. Learning rules for the structuring elements, degree of membership, and weighting factors are precisely described. In application to handwritten digit recognition problem, the fuzzy morphological shared-weight neural network produced the results which are comparable to the state-of art for this problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3203-3212
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• 2014

Company. s support for culture and arts started from mecenat activities. After then, it played a role as a tool of the company to satisfy consumers. cultural desires and improve the company. s image. As time goes by, it became a culture marketing which encourages business activities. Therefore, many companies try to develop their culture marketing activities in various fields. Especially art marketing has increased consumers. expectation and interest about art activities. Also, art marketing has become important as it has helped consumers to have critical view about products and improve their standard of life. As a way of art marketing, a company provides diverse exhibitions, sponsors and education programs related to art in either a specific space of the company building or a separate place. It can be said that this example of art marketing is a kind of an image marketing and public welfare at the same time. This article presents the concept of culture marketing and current condition of company. s support for culture and arts. In addition, the article depicts the concept and classification of art marketing. Furthermore, through analysis of company exhibition space and programs, the article illustrates the features and typology of art galleries managed by companies.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.1-8
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• 2009

There are a lot of influences, such as location of camera, luminosity, brightness, and direction of light, which affect the performance of 2-dimensional image recognition. This paper suggests an adaptive method for face-image recognition in noisy environments using evolvable filtering and feature extraction which uses one sample image from camera. This suggested method consists of two main parts. One is the environmental-adjustment module which determines optimum sets of filters, filter parameters, and dimensions of features by using "steady state genetic algorithm". The other another part is for face recognition module which performs recognition of face-image using the previous results. In the processing, we used Gabor wavelet for extracting features in the images and k-Nearest Neighbor method for the classification. For testing of the adaptive face recognition method, we tested the adaptive method in the brightness noise, in the impulse noise and in the composite noise and verified that the adaptive method protects face recognition-rate's rapidly decrease which can be occurred generally in the noisy environments.

• International Area Studies Review
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• v.12 no.2
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• pp.27-53
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• 2008

This paper investigates factors determining the level of nontraditional activities at banks around the world. Specifically, the paper examines what kinds of firm-specific and country-specific characteristics determine the level of noninterest income using a comprehensive multi-country database. This paper focuses beyond the traditional U.S. based analyses and provides detailed asset-liability management practices of banks around the world.The findings suggest that banks' size and loan loss provision, explicit deposit insurance, banking restriction, banking freedom ranking of respective countries, the extent of state and foreign ownership, governance, and transparency of the country have positive effects on the level of nontraditional activities. Greater dependence on traditional lending and financing, market based economy, and multiple bank supervisory bodies in the country have negative associations with noninterest income. The economic development of country however affects the extent of the relationship.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.212-225
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• 2015

UAV (Unmanned Aerial Vehicle), the pilotless plane or drone, draws researchers' attention at these days for its extended use to various area. The research was initiated for military use of the UAV, but the area of applicable field is extended to surveillance, communication, and even delivery for commercial use. As increasing the interest in UAV, the needs of research for operating the flying object which is not directly visible when it conducts a certain mission to remote place is obviously grown as much as developing high performance pilotless plane is required. One of the project supported by government is related to the use of UAV for logistics fields and controlling UAV to deliver the certain items to isolated or not-easy-to-access place is one of the important issues. At the initial stage of the project, the previous researches for controlling UAV need to be organized to understand current state of art in local researches. Thus, this study is one of the steps to develop the unmanned system for using in military or commercial. Specifically, we focused on reviewing the approaches of controlling UAV from origination to destination in previous in-country researches because the delivery involves the routing planning and the efficient and effective routing plan is critical to success to delivery mission using UAV. This routing plan includes the method to avoid the obstacles and reach the final destination without a crash. This research also present the classification and categorization of the papers and it could guide the researchers, who conduct researches and explore in comparable fields, to catch the current address of the research.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.30-34
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• 2019

We analyzed how the features in plasma information based virtual metrology (PI-VM) for SiO₂ etching depth with variation of 5% contribute to the prediction accuracy, which is previously developed by Jang. As a single feature, the explanatory power to the process results is in the order of plasma information about electron energy distribution function (PI_EEDF), equipment, and optical emission spectroscopy (OES) features. In the procedure of stepwise variable selection (SVS), OES features are selected after PI_EEDF. Informative vector for developed PI-VM also shows relatively high correlation between OES features and etching depth. This is because the reaction rate of each chemical species that governs the etching depth can be sensitively monitored when OES features are used with PI_EEDF. Securing PI_EEDF is important for the development of virtual metrology (VM) for prediction of process results. The role of PI_EEDF as an independent feature and the ability to monitor variation of plasma thermal state can make other features in the procedure of SVS more sensitive to the process results. It is expected that fault detection and classification (FDC) can be effectively developed by using the PI-VM.

• Journal of Korean Society on Water Environment
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• v.37 no.4
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• pp.275-285
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• 2021

Algal bloom is an important issue in maintaining the safety of the drinking water supply system. Fast detection and classification of algae images are essential for the management of algal blooms. Conventional visual identification using a microscope is a labor-intensive and time-consuming method that often requires several hours to several days in order to obtain analysis results from field water samples. In recent decades, various deep learning algorithms have been developed and widely used in object detection studies. YOLO is a state-of-the-art deep learning algorithm. In this study the third version of the YOLO algorithm, namely, YOLOv3, was used to develop an algae image detection model. YOLOv3 is one of the most representative one-stage object detection algorithms with faster inference time, which is an important benefit of YOLO. A total of 1,114 algae images for 30 genera collected by microscope were used to develop the YOLOv3 algae image detection model. The algae images were divided into four groups with five, 10, 20, and 30 genera for training and testing the model. The mean average precision (mAP) was 81, 70, 52, and 41 for data sets with five, 10, 20, and 30 genera, respectively. The precision was higher than 0.8 for all four image groups. These results show the practical applicability of the deep learning algorithm, YOLOv3, for algae image detection.