• Progress in Medical Physics
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• v.19 no.4
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• pp.231-240
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• 2008

We developed a user-friendly program to independently verify monitor units (MUs) calculated by radiation treatment planning systems (RTPS), as well as to manage beam database in clinic. The off-axis factor, beam hardening effect, inhomogeneity correction, and the different depth correction were incorporated into the program algorithm to improve the accuracy in calculated MUs. A beam database in the program was supposed to use measured data from routine quality assurance (QA) processes for timely update. To enhance user's convenience, a graphic user interface (GUI) was developed by using Visual Basic for Application. In order to evaluate the accuracy of the program for various treatment conditions, the MU comparisons were made for 213 cases of phantom and for 108 cases of 17 patients treated by 3D conformal radiation therapy. The MUs calculated by the program and calculated by the RTPS showed a fair agreement within ${\pm}3%$ for the phantom and ${\pm}5%$ for the patient, except for the cases of extreme inhomogeneity. By using Visual Basic for Application and Microsoft Excel worksheet interface, the program can automatically generate beam data book for clinical reference and the comparison template for the beam data management. The program developed in this study can be used to verify the accuracy of RTPS for various treatment conditions and thus can be used as a tool of routine RTPS QA, as well as independent MU checks. In addition, its beam database management interface can update beam data periodically and thus can be used to monitor multiple beam databases efficiently.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.422.2-422.2
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• 2014

가스장 이온원(GFIS: Gas Field Ionization Source)은 전자현미경보다 분해능이 향상된 이온현미경의 광원으로 사용하기 위하여 연구되고 있고, 큰 각전류 밀도, 작은 크기의 가상 이온원 그리고 좁은 에너지 퍼짐을 특징으로 한다. 여러 가지 장점을 가지고 있는 GFIS을 개발하기 위해서는 GFIS에서 발생된 이온빔의 형상을 관찰 것이 매우 중요하며, 이러한 관찰을 위한 시스템에는 주로 마이크로 채널 플레이트 (MCP: Micro Channel Plate)가 사용된다. MCP는 채널내부에 입사한 입자의 에너지에 의해서 생성된 이차전자를 수 천 배에서 수 백 만 배 이상 증폭시켜 형광판에 조사하고 발광시키는 방법으로 작은 신호를 영상으로 관찰 할 수 있도록 한다. MCP의 큰 증폭비는 작은 크기의 신호를 큰 신호로 증폭하여 관찰하는데 용이하여, GFIS 방법으로 생성된 이온빔(이온빔 전류 값은 pA 수준)을 관찰하기에 적합하다. 그러나 MCP를 이용하여도 증폭된 이온빔의 세기가 매우 작기때문에 생성된 이온빔 형상을 정확하게 관찰하기 위해서는 MCP의 형광판을 촬영하는 카메라 노출시간을 길게하여 데이터 수집 시간을 늘려야 하는 문제가 있다. 본 발표에서는 이온빔 형상 관찰에 소요되는 시간을 단축하기 위하여 MCP의 잡음이 GFIS의 이온빔 이미지 관찰에 미치는 영향을 분석하고 이를 제거 방법을 소개한다. 본 연구에서는 GFIS 방출 이온빔의 이미지에 포함된 MCP 잡음 특성을 장(전계)이온현미경 (Field Ion Microscope)실험을 통하여 분석하였고, 디지털 이미지 처리 방법을 이용하여 방출 이온빔 이미지에서 MCP 잡음을 제거하여 방출 이온빔 이미지만 추출할 수 있었다. 본 연구에서 제안한 방법을 GFIS 방출 이온빔 관찰시스템에 적용함으로써 기존 방법에 비해 노출시간을 단축하여 방출 이온빔을 관찰 할 수 있었으며, 노이즈 제거 효과로 향상된 이온빔 형상을 얻을 수 있었다. 본 연구결과의 관찰시간 단축과 향상된 이온빔 형상 획득은 이온현미경 개발에 필수적인 단원자 이온빔을 보다 효율적으로 개발할 수 있으며 디지털 이미지 처리로 GFIS 이온빔 생성을 자동화하는데 응용할 수 있다. 더불어 기존방법에 비해 이미지 획득을 위한 MCP의 노출시간을 단축할 수 있으므로 실험장비 수명 단축 방지 및 관리에 큰 장점이 있다.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.59-76
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• 2015

Recent wide spread of embedded devices and technology growth of broadband communication has led to rapid increase in the volume of created and managed data. As a result, data centers have to increase the storage capacity cost-effectively to store the created data. Data deduplication is one way to save the storage space by removing redundant data. This work propose IO extent based deduplication schemes called CORE-Dedup that exploits content-preserving access locality. We acquire IO traces from block device layer in virtual machine host, and compare the deduplication performance of chunking method between the fixed size and IO extent based. At multiple workload of 10 user's compile in virtual machine environment, the result shows that 4 KB fixed size chunking and IO extent based chunking use chunk index 14500 and 1700, respectively. The deduplication rate account for 60.4% and 57.6% on fixed size and IO extent chunking, respectively.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.77-84
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• 2020

This study is apply 3D spatial information per traditional landscape space by comparing spatial information data created using a small drone and 3D scanner used for 3D spatial information construction for efficient preservation and management of traditional landscaping space composed of areas such as scenic sites and traditional landscape architectures. The analysis results are as follows. First, aerial photogrammetry data is less accurate than 3D scanners, but it was confirmed to be more suitable for monitoring landscape changes by reading RGB images than 3D scanners by texture mapping using digital data in constructing orthographic image data. Second, the orthographic image data constructed by aerial photogrammetry in a traditional landscaping space consisting of a fixed area, such as Gwanghalluwon Garden, produced visually accurate and precise results. However, as a result of the data extraction, data for trees, which is one of the elements that make up the traditional landscaping, was not extracted, so it was determined that 3D scanning and aerial surveying had to be performed in parallel, especially in areas where trees were densely populated. Third, The surrounding trees in Soswaewon Garden caused many errors in 3D spatial information data including topographic data. It was analyzed that it is preferable to use 3D scanning technology for precise measurement rather than aerial photogrammetry because buildings, landscaping facilities and trees are dense in a relatively small space. When 3D spatial information construction data for a traditional landscaping space composed of area using a small drone and a 3D scanner free from temporal and spatial constraints and compared the data was compared, the aerial photogrammetry is effective for large site such as Hahoe Village, Gyeongju and construction of a 3D space using a 3D scanner is effective for traditional garden such as Soswaewon Garden.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.807-816
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• 2015

In general, the water stage-discharge relationship curve is established based on the assumptions of linearity and homoscedasticity. However, the relationship between the water stage and discharge is affected from geomorphological factors, which violates the basic assumptions of the water stage-discharge relationship curve. In order to reduce the error due to the violations, the curve is divided into several sections based on the manager's judgement considering change of cross-sectional shape. In this research, the objective-splitting criteria of the curve is proposed based on the measured data without the subjective decision. First, it is assumed that the coefficient of variation follows the normal distribution. Then, if the newly calculated coefficient of variation is outside of the 95% confidential interval, the curve is divided. Namely, the groups is divided by the characteristics of the coefficient of variation and the reasonable criteria is provided for establishing a multi-segmented rating curve. To validate the proposed method, it was applied to the data generated by three artificial power functions. In addition, to confirm the applicability of the proposed method, it is applied to the water stage and discharge data of the Muju water stage gauging station and Sangegyo water stage gauging station. As a result, it is found that the automatically divided rating curve improves the accuracy and extrapolation accuracy of the rating curve. Finally, through the residual analysis using Shapiro-Wilk normality test, it is confirmed that the residual of water stage-discharge relationship curve tends to follow the normal distribution.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Journal of Korea Game Society
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• v.10 no.2
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• pp.37-47
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• 2010

Along with language, emotion is an effective means of expression. By expressing our emotions as well as speaking language, we can deliver our message better. Because each person expresses the same emotion differently, this expression is a useful gauge to measure an individual personality. To avoid monotonous emotional expression from virtual characters, therefore, it is necessary to adjust the creation and deletion of the same emotion depending on each character's personality. This paper has attempted to define personality characteristics that have an impact on each emotion and propose a method to adjust the emotions. Furthermore, the relationship between particular emotion and personality characteristics has been defined by matching the significance of specified personality characteristics with the lexical meaning. In addition, using the Raw Score, the weighted value which is necessary for the adjustment, continuance and deletion of each emotion has been defined. Then, emotion was properly adjusted. When the same emotion was adjusted using actual personality test data, different results have been observed by personality. This paper has been conducted using NEO Personality Inventory (NEO-PI) which consisted of 5 broad domains and 30 sub domains.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.195-199
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• 2009

Augmented reality is a field of computer research which deals with the combination of real-world and computer-generated data, where computer graphics objects are blended into real footage in real time and it has tremendous potential in visualizing geospatial information. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or marker based approaches. Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed RF based tracking and localization. However, it does cause deployment problems of large sensors and readers. In this paper, we present a noble markerless AR approach for indoor navigation system only using a camera. We will apply this work to mobile seamless indoor/outdoor u-GIS system.