• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.123-136
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• 2006

The prefetching technique is an effective way to reduce the latency caused memory access. However, excessively aggressive prefetch not only leads to cache pollution so as to cancel out the benefits of prefetch but also increase bus traffic leading to overall performance degradation. In this thesis, a prefetch filtering scheme is proposed which dynamically decides whether to commence prefetching by referring a filtering table to reduce the cache pollution due to unnecessary prefetches In this thesis, First, prefetch hashing table 1bitSC filtering scheme(PHT1bSC) has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete block address table filtering scheme(CBAT) has been introduced to be used as a reference for the comparative study. A prefetch block address lookup table scheme(PBALT) has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the PHT1bSC scheme, the contents of each entry have the fields the same as CBAT scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. On commonly used prefetch schemes and general benchmarks and multimedia programs simulates change cache parameters. The PBALT scheme compared with no filtering has shown enhanced the greatest 22%, the cache miss ratio has been decreased by 7.9% by virtue of enhanced filtering accuracy compared with conventional PHT2bSC. The MADT of the proposed PBALT scheme has been decreased by 6.1% compared with conventional schemes to reduce the total execution time.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.15-22
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• 2017

Purpose During Brain SPECT study, critical factor for proper study with $^{99m}Tc-ECD$ or $^{99m}Tc-HMPAO$ is one of the important causes to patent's movement. It causes both improper diagnosis and examination failure. In this study, we evaluated the effect of Dynamic Continuous Mode Acquisition compared to Step and Shoot Mode to raise efficacy and reject the data set with movement, as well as, be reconstructed in certain criteria. Materials and Methods Deluxe Jaszczak phantom and Hoffman 3D Brain phantom were used to find proper standard data set and exact time. Step and Shoot Mode and Dynamic Continuous Mode Acquisition were performed with SymbiaT16. Firstly, Deluxe Jaszczak phantom was filled with $Na^{99m}TcO_4$ 370 MBq and obtained in 60 minutes to check spatial resolution compared with Step and Shoot Mode and Dynamic Continuous Mode. The second, the Hoffman 3D Phantom filled with $Na^{99m}TcO_4$ 74 MBq was acquired for 15 Frame/minutes to evaluate visual assessment and quantification. Finally, in the Deluxe Jaszczak phantom, Spheres and Rods were measured by MI Apps program as well as, checking counts with the frontal lobe, temporal lobe, occipital lobe, cerebellum and hypothalamus parts was performed in the Hoffman 3D Brain Phantom. Results In Brain SPECT Study, using Dynamic Continuous Mode rather than current Step and Shoot Mode, we can do the reading using the 20 to 50 % of the acquired image, and during the test if the patient moves, we can remove unneeded image to reduce the rate of restudy and reinjection. Conclusion Dynamic Continuous Mode in Brain study condition enhances effects compared to Step and Shoot Mode. And also is powerful method to reduce reacquisition rate caused by patient movement. The findings further indicate that it suggest rejection limit to maintain clinical value with certain reconstruction factors compared with Tomo data set. Further examination to improve spatial resolution, SPECT/CT should be the answer for that.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.111-118
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• 2019

Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.

• Journal of Korean Society of Neurocognitive Rehabilitation
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• v.10 no.2
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• pp.53-62
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• 2018

The purpose of this study was to propose an alternative for the eating habits of modern people and coping with the diseases. The purpose of this study was to apply the principles of eating habits of people living in Roma Linda to modern dietary life and to help healthy life and prevent disease. The period of this study was from May 1, 2016 to February 28, 2018. Literature search was conducted using Pubmed and Korean academic web sites. Based on the recognition of wrong eating habits, we classify and classify diseases according to eating habits. A total of more than 100 papers were selected and 60 papers and a database were prepared. People living in Roma Linda have eight health principles. The Roma Linda practiced balanced nutritional intake, sufficient exercise, adequate water intake, sunlight, temperance (abstinence from alcohol etc.), fresh air, adequate rest, and trust in eating habits. People living in Roma Linda have a high intake of vegetables, fruits and nuts. People living in Roma Linda are educated about nutrition, and among them, there is a low prevalence of coronary heart disease and cancer, because they mostly do not smoke or drink alcohol. Unhealthy eating habits and dietary behavior are associated with many diseases. Many chronic, degenerative diseases are due to bad eating habits and stress. If you take good food habits of people living in the Roma Linda area and practice it steadily, it will have a great effect on disease prevention.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.137-144
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• 2021

Purpose : The usability of X-Jaw split VMAT was evaluated by comparative analysis of the dose distribution between the treatment plan divided by X-Jaw and Full field VMAT treatment plan in left breast cancer treatment including supraclavicular lymph nodes. Materials and Methods : 10 patients with left breast cancer, including supraclavicular lymph nodes, were simulated using vacuum cushion, and 2 Full field Arc VMAT and 4 X-Jaw split Arc VMAT were planned The treatment plan was designed to include more than 95% of the Planning Target Volume (PTV) and to be minimally irradiated in the surrounding Organ at risk (OAR). Dose analysis of PTV and OAR was performed through dose volume histogram (DVH). Results : The Full field VMAT treatment plan and the X-Jaw split VMAT treatment plan of 10 patients were expressed as average values and compared. The difference between the two treatment plans was not large, with a Conformity index (CI) of 1.05±0.04, 1.04±0.03, and a Homogeneity index (HI) of 1.07±0.008, 1.07±0.009. For OAR, V5 in the left lung is 56.1±6.50%, 50.4±6.30%, and V20 is 20.0±4.15%, 13.52±3.61%. Compared to Full field VMAT, V5 decreased by 10.0% V20 by 32.6% in X-Jaw split VMAT. The V30 of the heart is 3.68±1.85%, 2.23±1.52%, and the Mean dose is 8.93±1.65 Gy, 7.67±1.52 Gy. In the X-Jaw split VMAT, V30 decreased by 39.3% and the Mean dose decreased by 14.1%. The left lung and heart, which are normal tissues, were found to have a statistical significance of that p-value is less than 0.05. Conclusion : In the case of left breast cancer treatment, which includes Supraclavicular lymph nodes with a large PTV volume and a length of X Jaw of 15 cm or more, the X-Jaw split VMAT shows improved dose distribution, which can reduce radiation dose of OAR such as lungs and heart, while maintaining similar PTV coverage with HI and CI equivalent to Full field VMAT. It is thought to be effective in reducing radiation complications.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.651-662
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• 2022

The electrochemical impedance spectroscopy(EIS) method was used to evaluate the concrete deterioration process related to chloride-induced steel corrosion with various corrosion levels(initiation, rust propagation and acceleration periods). The impressed current technique, with four total current levels of 0C, 13C, 65C and 130C, was used to accelerate steel corrosion in concrete cylinder samples with w/c ratio of 0.4, 0.5, and 0.6, immersed in a 0.5M NaCl solution. A series of EIS measurements was performed to monitor concrete deterioration during the accelerated corrosion test in this study. Some critical parameters of the equivalent circuit were obtained through the EIS analysis. It was observed that the charge transfer resistance(R_c) dropped sharply as the impressed current increased from 0C to 13C, indicating a value of approximately 10kΩcm². However, the sensitivity of R_c significantly decreased when the impressed current was further increased from 13C to 130C after corrosion of steel had been initiated. Meanwhile, the double-layer capacitance value(C_dl) linearly increased from 50×10^-6μF/cm² to 250×10^-6μF/cm² as the impressed current in creased from 0C to 130C. The results in this study showed that monitoring C_dl is an effective measurement parameter for evaluating the progress of internal concrete damages(de-bonding between steel and concrete, micro-cracks, and surface-breaking cracks) induced by steel corrosion. The findings of this study provide a fundamental basis for developing an embedded sensor and signal interpretation method for monitoring concrete deterioration due to steel corrosion at various corrosion levels.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.81-93
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• 2022

Since 2008, China's shipping industry has been in a slump, with shipbuilding orders falling sharply, and high-growth excess capacity has become increasingly apparent, leaving many firms with sharply reduced orders at risk of bankruptcy and shutdown. To ensure the development of the shipbuilding industry and enhance the international competitiveness of the shipbuilding industry, it is necessary to analyze the present situation of the shipbuilding industry and the financial situation of the shipbuilding enterprises. And analyzing the problems faced by enterprises from the perspective of capital structure is very meaningful to the shipbuilders with high capital operation. We are trying to analyze the determinants of capital structure of China's shipbuilding listed companies. 30 listed Chinese shipbuilding and listed companies have been designated as sample companies that can obtain financial statements for 13 consecutive years. They also divided 30 sample companies into shipbuilding, shipbuilding-related manufacturing, and shipbuilding-related transportation. Dependent variable is the debt level of the year, independent variable includes the debt level of the previous year, fixed asset ratio, profitability ratio, depreciation cost ratio and asset size. The regression model of the panel used to analyze determinants is capital structure. The results of the empirical analysis are as follows. First, a fixed-effect model for the entire entity showed that the debt-to-equity ratio and the size of the asset in the previous period had a positive effect on the debt-to-equity ratio in the current period. Second, the impact of the profitability ratio on the debt level in the prior term also supports the capital procurement ranking theory rather than the static counter-conflict theory. Third, it was shown that the ratio of the depreciation of the prior term, which replaces the non-liability tax effect, affects the debt-to-equity ratio in the current period.