• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.317-324
• /
• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• (The)Study of the Eastern Classic
• /
• no.66
• /
• pp.303-330
• /
• 2017

The purpose of this article is figuring out the modern understanding of SimChong Jeon's narrative and its storytelling strategy in the movie (2014). In the movie, there are three steps which are based on the temporal flow of narrative. shows the web-like structure of desire especially by focusing on the male character Sim Hakkyu. The relationship among characters in is gradually broken because of the desire. Moreover, the desire pushes Sim Chong who is Sim Hakkyu's daughter into the sacrifice. This part seems similar with the narrative of SimChong-Jeon which has been transmitted since 18~19 century in Choson dynasty. However, also tells a different story which describes the progress of Sim Hakkyu's seeking the real relationship filled with love. This difference is able to make people read with the 'stroytelling' point of view. All the lack or problem in is closely related to the desire of Sim Hakkyu. His narrative is something different from the typical story of SimChong-Jeon. A new narrative of Sim Hakkyu is not Sim Chong centered story but rather the anti of it. 'The other narrative' in seems social practice of storytelling in order to break down the preconception of SimChong-jeon called 'cannon'. This is the storytelling strategy of and it suggests the another way of creating new narrative which is based on the classical cannon.

• Journal of the Korean Society of Radiology
• /
• v.15 no.6
• /
• pp.781-788
• /
• 2021

Due to the high sensitivity to radiation, excessive exposure needs to be prevented by accurately measuring the dose irradiated to the skin during radiation therapy. Although clinical trials use dosimeters such as film, OSLD, TLD, glass dosimeter, etc. to measure skin dose, these dosimeters have difficulty in accurate dosimetry on skin curves. In this study, to solve these problems, we developed a skin dosimeter that can be attached according to human flexion and evaluated its response characteristics. For the manufacture of the dosimeter, lead oxide (PbO) with high atomic number (Z_Pb: 82, Z_O: 8) and density (9.53 g/cm³) and silicon binders that can bend according to human flexion were used. In the case of a dosimeter made of PbO material, the performance degradation has been prevented by using parylene and others due to the presence of degradation due to oxidation, but the previously used parylene is affected by bending, so a new form of passive layer was produced and applied to the skin dosimeter. The characteristic evaluation of the skin dosimeter was evaluated by analyzing SEM, reproducibility, and linearity. Through SEM analysis, bending was evaluated, reproducibility and linearity at 6 MeV energy were evaluated, and applicability was assessed with a skin dosimeter. As a result of observing the dosimeter surface through SEM analysis, the parylene passive layer PbO dosimeter with the positive layer raised to the parylene produced cracks on the surface when bent. On the other hand, no crack was observed in the silicon passive layer PbO dosimeter, which was raised to silicon passive layer. In the reproducibility measurement results, the RSD of the silicon passive layer PbO dosimeter was 1.47% which satisfied the evaluation criteria RSD 1.5% and the linearity evaluation results showed the R² value of 0.9990, which satisfied the evaluation criteria R² 9990. The silicon passive layer PbO dosimeter was evaluated to be applicable to skin dosimeters by demonstrating high signal stability, precision, and accuracy in reproducibility and linearity, without cracking due to bending.

• The Southeast Asian review
• /
• v.28 no.2
• /
• pp.213-247
• /
• 2018

Thailand in 2017 the public sentiment has turned against the military government. The four pledges the military declared immediately after the 2014 coup, restoration of democracy, addressing of divisive politics, eradication of corruption, and stimulation of the economy have all failed. In the same year, however, Thai military junta began to recover it's diplomatic relationship with western countries including US and EU owing to promulgation of the new constitution endorsed by King Maha Vajiralongkorn and the lavish funeral of late King Bhumibol Adulyadej which was attended by huge number of condolence delegations from around the world including US Defense Secretary James Mattis. Since the 2014 coup, US has sanctioned the country under military junta led by General Prayuth Chan-o-cha for urging them back to the barracks. EU also joined this sanction measures. US signaled change in it's policy when General Prayuth got the chance to visit US and meet President Donal Trump in 2017. General Prayuth Chan-o-cha's military junta could start to restore it's reputation internationally. Domestically, he used absolute powers based on section 44 of the interim constitution, also guranteed in the new constitution. Oversea and national human rights groups have criticized that the interim constitution for permitting the NCPO, Thai military junta's official name, to carry out policies and actions without any effective oversight or accountability for human rights violations. On 1 December 2017, Thailand marked the one-year anniversary of King Maha Vajiralongkorn's accession to the throne as the country's new monarch, Rama X. In the first year of King Rama X's reign, arrests, prosecutions, and imprisonment under Article 112 of Thailand's Criminal Code (lese-majeste) have continued unabated in Thailand. NCPO has continued to abuse Article 112 to detain alleged violators and curb any form of discussion regarding the monarchy, particularly on social media. In this worsening human rights environment General Prayuth Chan-o-cha enforced continuously campaign like Thai-style democracy- an effort to promote largely autocratic 'Thainess' in such a way that freedom of expression is threatened. It is a resurgence of 'Sarit Model'. In the beginning of 2017 Thai military government raised the slogan of 'opportunity Thailand' in the context of 'Thailand 4.0' project which attempts to transform Thai economy based on industry-driven to innovation-driven for recovering robust growth. To consider freedom and liberty as a source of innovation, 'Thailand 4.0' led by 'Sarit Model' without democracy would be skeptical.

• Journal of Life Science
• /
• v.32 no.12
• /
• pp.929-937
• /
• 2022

To investigate the anti-inflammatory activity of the grains of sorghum, three Sorghum bicolor (L.) Moench variants (Hwanggeumchal, Huinchal, and Chal) being cultivated in Korea, the 80% ethanol (EtOH) extracts of individual sorghum grains were compared for their inhibitory activity against nitric oxide (NO) production in lipopolysaccharide (LPS)-stimulated RAW264.7 murine macrophage cell line. Among them, the EtOH extract of sorghum Hwanggeumchal grains could exert the highest inhibitory effect on the LPS-induced NO production. However, under these conditions, the viability of RAW264.7 cells was not affected. When the EtOH extract of sorghum Hwanggeumchal grains was sequentially fractionated with n-hexane, methylene chloride (MC), ethyl acetate (EtOAc), and n-butanol, the anti-NO production activity was predominantly detected in both MC and EtOAc fractions. In particular, treatment with the MC fraction reduced dose-dependently the expression levels of iNOS, COX-2 and pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) in LPS-stimulated RAW264.7 cells. Simultaneously, the MC fraction could prevent LPS-induced activating phosphorylation of p38 mitogen-activated protein kinase (MAPK), c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK). HPLC analysis of the MC fraction showed gentisic acid and naringenin as the major phenolic components. Both gentisic acid and naringenin commonly exhibited a potent inhibitory activity against LPS-induced NO production in RAW264.7 cells. Together, these results provide the evidence of the inhibitory activity of Hwanggeumchal grains on LPS-induce inflammatory responses in RAW264.7 murine macrophage cells and also suggest that sorghum grains possess beneficial health effects which can be applicable in development of the grain-based functional foods.

• Fashion & Textile Research Journal
• /
• v.24 no.6
• /
• pp.667-685
• /
• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.2
• /
• pp.188-196
• /
• 2023

Among marine accidents caused by bad weather, visibility restrictions caused by sea fog occurrence cause accidents such as ship strand and ship bottom damage, and at the same time involve casualties caused by accidents, which continue to occur every year. In addition, low visibility at sea is emerging as a social problem such as causing considerable inconvenience to islanders in using transportation as passenger ships are collectively delayed and controlled even if there are local differences between regions. Moreover, such measures are becoming more problematic as they cannot objectively quantify them due to regional deviations or different criteria for judging observations from person to person. Currently, the VTS of each port controls the operation of the ship if the visibility distance is less than 1km, and in this case, there is a limit to the evaluation of objective data collection to the extent that the visibility of sea fog depends on the visibility meter or visual observation. The government is building a marine weather signal sign and sea fog observation networks for sea fog detection and prediction as part of solving these obstacles to marine traffic safety, but the system for observing locally occurring sea fog is in a very insufficient practical situation. Accordingly, this paper examines domestic and foreign policy trends to solve social problems caused by low visibility at sea and provides basic data on the need for government support to ensure maritime traffic safety due to sea fog by factually investigating and analyzing social problems. Also, this aims to establish a more stable maritime traffic operation system by blocking marine safety risks that may ultimately arise from sea fog in advance.

• Progress in Medical Physics
• /
• v.22 no.3
• /
• pp.140-147
• /
• 2011

The purpose of this study was to estimate internal motion using molecular sieve for quantitative improvement of lung tumor and to localize lung tumor in the small animal PET image by evaluated data. Internal motion has been demonstrated in small animal lung region by molecular sieve contained radioactive substance. Molecular sieve for internal lung motion target was contained approximately 37 kBq Cu-64. The small animal PET images were obtained from Siemens Inveon scanner using external trigger system (BioVet). SD-Rat PET images were obtained at 60 min post injection of FDG 37 MBq/0.2 mL via tail vein for 20 min. Each line of response in the list-mode data was converted to sinogram gated frames (2~16 bin) by trigger signal obtained from BioVet. The sinogram data was reconstructed using OSEM 2D with 4 iterations. PET images were evaluated with count, SNR, FWHM from ROI drawn in the target region for quantitative tumor analysis. The size of molecular sieve motion target was $1.59{\times}2.50mm$. The reference motion target FWHM of vertical and horizontal was 2.91 mm and 1.43 mm, respectively. The vertical FWHM of static, 4 bin and 8 bin was 3.90 mm, 3.74 mm, and 3.16 mm, respectively. The horizontal FWHM of static, 4 bin and 8 bin was 2.21 mm, 2.06 mm, and 1.60 mm, respectively. Count of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.10, 4.83, 5.59, 5.38, and 5.31, respectively. The SNR of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.18, 4.05, 4.22, 3.89, and 3.58, respectively. The FWHM were improved in accordance with gate number increase. The count and SNR were not proportionately improve with gate number, but shown the highest value in specific bin number. We measured the optimal gate number what minimize the SNR loss and gain improved count when imaging lung tumor in small animal. The internal motion estimation provide localized tumor image and will be a useful method for organ motion prediction modeling without external motion monitoring system.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.147-168
• /
• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.