• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.643-651
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• 2001

Paddlewheel-driven circulation in a culture pond has been simulated based on the depth integrated 2 dimensional hydrodynamic model. Acceleration by paddlewheel is expressed as shaft force divided by water mass discharged by paddlewheel blades. The model has been calibrated and applied to culture ponds as following steps:- i) The model predicted velocities at every 10 m along longitudinal direction from the paddlewheel. The model was calibrated comparing the results with the measured values at mass correction factor $\alpha$ and dimensionless eddy viscosity constant $\gamma$, respectively, in a range $15\~20$ and 6. ii) Wind shear stress was simulated under conditions of direction $0^{\circ}C,\;90^{\circ}C\;and\;180^{\circ}C$ and speed 0.0, 2.5, 5.0 and 7.5 m/s. Change rate of current speed was <$1\%$ at wind in parallel or opposite direction to the paddlewheel-driven jet flow, while $4\%$ at orthogonal angle. iii) The model was then applied to 2 culture ponds located at the Western coast of Korea. The measured and predicted currents for the ponds were compared using the regression analysis. Analysis of flow direction and speed showed correlation coefficients 0.8928 and 0.6782 in pond A, 0.8539 and 0.7071 in pond B, respectively. Hence, the model is concluded to accurately predict circulation driven by paddlewheel such that it can be a useful tool to provide pond management strategy relating to paddlewheel operation and water quality.

• Progress in Medical Physics
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• v.23 no.2
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• pp.81-90
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• 2012

The effect of setup uncertainties on CTV dose and the correlation between setup uncertainties and setup margin were evaluated by Monte Carlo based numerical simulation. Patient specific information of IMRT treatment plan for rectal cancer designed on the VARIAN Eclipse planning system was utilized for the Monte Carlo simulation program including the planned dose distribution and tumor volume information of a rectal cancer patient. The simulation program was developed for the purpose of the study on Linux environment using open source packages, GNU C++ and ROOT data analysis framework. All misalignments of patient setup were assumed to follow the central limit theorem. Thus systematic and random errors were generated according to the gaussian statistics with a given standard deviation as simulation input parameter. After the setup error simulations, the change of dose in CTV volume was analyzed with the simulation result. In order to verify the conventional margin recipe, the correlation between setup error and setup margin was compared with the margin formula developed on three dimensional conformal radiation therapy. The simulation was performed total 2,000 times for each simulation input of systematic and random errors independently. The size of standard deviation for generating patient setup errors was changed from 1 mm to 10 mm with 1 mm step. In case for the systematic error the minimum dose on CTV $D_{min}^{stat{\cdot}}$ was decreased from 100.4 to 72.50% and the mean dose $\bar{D}_{syst{\cdot}}$ was decreased from 100.45% to 97.88%. However the standard deviation of dose distribution in CTV volume was increased from 0.02% to 3.33%. The effect of random error gave the same result of a reduction of mean and minimum dose to CTV volume. It was found that the minimum dose on CTV volume $D_{min}^{rand{\cdot}}$ was reduced from 100.45% to 94.80% and the mean dose to CTV $\bar{D}_{rand{\cdot}}$ was decreased from 100.46% to 97.87%. Like systematic error, the standard deviation of CTV dose ${\Delta}D_{rand}$ was increased from 0.01% to 0.63%. After calculating a size of margin for each systematic and random error the "population ratio" was introduced and applied to verify margin recipe. It was found that the conventional margin formula satisfy margin object on IMRT treatment for rectal cancer. It is considered that the developed Monte-carlo based simulation program might be useful to study for patient setup error and dose coverage in CTV volume due to variations of margin size and setup error.

• Journal of dental hygiene science
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• v.9 no.2
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• pp.161-167
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• 2009

The purpose of this Study was to examine the effect of perfectionism on stress and anxiety during scaling practice in an effort to find efficient way of helping students with getting good skills. The subjects in this study were students who practiced a scaling at the oral hygiene practice lab in the Department of dental hygiene in S college from May 1 to May 31, 2008. They were divided into four groups based on their subscales of perfectionism : mixed perfectionist group, achievement striving perfectionist group, failure avoidance perfectionist group and non-perfectionist group. The measurements used were Two-Dimensional Perfectionism Scale, Stress level, Trait anxiety, State anxiety. There were no significant differences in the stress level before practice between 4 groups. There were significant differences in trait anxiety, state anxiety, total anxiety before scaling practice between 4 groups. However, these results were due to differences between mixed perfectionist group and non-perfectionist group. After practice, total anxiety was decreased from 93.71 to 89.66 and state anxiety was decreased from 45.49 to 43.38. These results were statistically significant. In order to investigate the influence of achievement striving factor and failure avoidance factor on the change of state anxiety during the scaling practice Standard Multiple Regression were employed for the statistical analysis. Failure avoidance factor was related with the increase of state anxiety during the scaling practice. So leachers have to give all effort to reduce the anxiety of students during scaling practice and provide students with motivation of achievement.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.232-245
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• 2021

The present study is about a brand development strategy that utilizes Korean traditional patterns. The global culturenomics phenomenon confirms the value of the cultural aspects of design when a national brand is established. People succeed with their unique aesthetic sense and reinterpret it in a modern view, and this design acts as today's national brands. In this way, people used traditional patterns and original designs, along with regional characteristics and formative style, in developing their designs. However, due to recent changes in the global environment, modern people live in an "untact" world, and consumption culture shifted toward online marketing. In this environment, where one is isolated from social activities, there needs to be a strong image that can dramatically change the mood of one's home. I would like to re-examine the Dan-Chung pattern, whose painting depends on the aesthetic characteristics of architecture to protect the wooden members of the framework in traditional architecture. The pattern and color of Dan-Chung, coated in traditional architecture, differs by the type of construction used, which includes a palace, a Buddhist temple, and a Confucianism Dan Chung. The Geummoon pattern contains aesthetic factors to add solemnity to the Main Buddhist Halls, which contain Buddha. This is a new medium that continues the current traditions instead of remaining in the past. Among different Dan Chung patterns, Geummoon has magnificent decoration consisting of the highest grade materials and unique composition; therefore, it is suitable to be reinterpreted in modern terms. The same pattern can be interpreted in different ways with different colors, so there is a great aesthetic impression in the Geummoon pattern. The value of preservation for exploration and theoretical study of the traditional pattern is important, but recreating the pattern into modern formative art can present a new angle of view and national brand, bearing pride in our cultural assets. The study used multidimensional molding methods for realistic presentation after going through the two-dimensional design process. The significant value of Korean molding beauty which hangs onto the past will play a crucial role in establishing our national brand.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.618-626
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• 2019

Stem cell therapy is not expected to bestow any therapeutic benefit because of the low engraftment rates after transplantation.Various cell-carrying scaffolds have been developed in order to overcome this problem. When the scaffold is formed by 3-dimensional (3D) printing, it is possible to create various shapes of scaffolds for specific regions of injury. At the same time, scaffolds provide stem cells as therapeutic-agents and mechanically support an injured region. PCL is not only cost effective, but it is also a widely used material for 3D printing. Therefore, rapid and economical technology development can be achieved when PCL is printed and used as a cell carrier. Yet PCL materials do not perform well as cell carriers, and only a few cells survive on the PCL surface. In this study, we tried to determine the conditions that maximize the cell-loading capacity on the PCL surface to overcome this issue. By applying a plasma treated condition and then collagen coating known to improve the cell loading capacity, it was confirmed that the 3% collagen coating after plasma treatment showed the best cell engraftment capacity during 72 hours after cell loading. By applying the spheroid cell culture method and scaffold structure change, which can affect the cell loading ability, the spheroid cell culture methods vastly improved cell engraftment, and the scaffold structure did not affect the cell engraftment properties. We will conduct further experiments using PCL material as a cell carrier and as based the excellent results of this study.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• Journal of Service Research and Studies
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• v.11 no.4
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• pp.1-20
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• 2021

This study was conducted to derive a model of the legal system that is the basis for realizing the service economy, political administration, and social education system. Based on the experience of mankind's legal system operation in the historical era for the past 5,000 years, a legal system model that will make the future human society sustainable has been established. The problems of the current legal system were analyzed at the fundamental level. The root cause of injustice and unfairness was analyzed and a new legal system was designed. Through the legal systems of various national societies that have been attempted in the history of mankind, the structure of the legal system that is desirable for the modern society was designed. Human society, which has experienced how much good legal system has been and is being abused by human irrationality and nonsense, needs to make an effort to change the legal system paradigm itself by learning lessons from failure. This study derives the basis for a legal system that can realize justice and a fair society in the long term. It proposed a model for improving the legal system that allows human society to be happy for a long time. To this end, the fundamental role of the legal system was analyzed at the ideological level and the problems of the current legal system were presented. In addition, the problem of fundamental assumptions about human nature was analyzed and improved assumptions were presented. The structural system of the current legal system was analyzed and a new structure was proposed. In addition, a plan for the operation of a new legal system based on a new structure was suggested. The new legal system was named servicism system. This is because it is a model centered on thorough checks and balances between all opponents, not a simple linear one-dimensional legal system, but a multidimensional legal system, and because it is a viewpoint that clearly recognizes both human reason and desire. The new system is a model that reflects the confrontation between the rule of law and the non-law rule and the confrontation between the power people and the general public. A follow-up study is needed on a concrete plan for transitioning from the current legal system to a new legal system.