• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.569-575
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• 2010

The occupancy based O/D is essential for measuring efficiency of various transportation policies like HOV/HOT lane, ramp metering, and public parking station. There has been many studies on occupancy survey methodology and O/D estimation using TCS (Toll Collection System) data separately. The occupancy O/D estimation methodology using TCS data has not been attempted thus far. An overall process from data collection stage to the occupancy O/D estimation stage has been suggested. Field survey was performed at the northbound Seoul toll station of Gyeongbu Expressway by each 2 hours of AM peak, PM non-peak, PM peak, midnight periods on a day. The process of matching the TCS data and field survey data classified by tollbooth ID, car type/mode, and arrival time was also performed. One typical output of the results showed that the ratio of single occupancy vehicles bounding for Seoul during the AM peak amounted to 60%. With the key output of this study and the specific O/D estimation methodology suggested, the whole centroid-to-centroid occupancy O/D of the country could be available, and then various applications in which the occupancy information is required could be possible.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.129-140
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• 2004

In this paper, we conduct the research about optimal aggregation interval of travel time data on interrupted traffic flow and verify the reliability of AVI collected data by using car plate matching method in RTMS for systematic collection and analysis of link travel time data on interrupted traffic flow rural arterial. We perform Kolmosorov-Smirnov test on AVT collected sample data and on entire population data, and conclude that the sample data does not represent pure random sampling and hence includes sample collection error. We suggest that additional review is necessary to investigate the effectiveness of AVI collected sample data as link representative data. We also develop statistical model by applying two estimation techniques namely point estimation and interval estimation for calculating optimal aggregation interval. We have implemented our model and determine that point estimate is preferable over interval estimate for exactly selecting and deciding optimal aggregation interval. Our final conclusion is that 5-minute aggregation interval is optimal to estimate travel time in RTMS, as is currently being used our investigation is based on AVI data collected from Yang-ji to Yong-in $42^{nd}$ National road.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.284-295
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• 2019

Celebrities form a dominant culture of one era and are cultivating influence to lead new fashion. Domestic women celebrities attending Seoul Fashion Week build their image as a fashion leader by exposing their own fashion aesthetics to the public. This promotes PR and sales of the brand of fashion designers in the collection. This study considers the fashion trends of women celebrities by analyzing the fashion style of women celebrities in Seoul Collection over the recent five years. The results of this study on contents analysis are as follows. First, straight silhouettes, achromatic colors, and an absence of a pattern or decoration comprised a high proportion. Celebrities preferred a modern and minimal style. Second, they preferred a feminine style that shows traditional feminine beauty through slim and princess silhouettes, one-piece dress or skirts, soft materials, and decorations with ruffles. In addition, as a matching jacket on one-piece dresses also appeared, it showed that celebrities attempted to change the chic feminine style with masculine beauty. Third, boxy silhouettes, multi-color mixed with colorful colors, graphic or lettering patterns, glittering materials and lots of details comprised a high proportion. This means celebrities pursue a maximal style that reveals their strong presence as fashion leaders.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Korean Journal of Community Nutrition
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• v.20 no.6
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• pp.460-467
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• 2015

Objectives: Excess sodium intake has been linked to obesity and obesity-related indices. However, the scientific evidence for this association is inadequate. The purpose of this study was to investigate the association between urinary sodium excretion and obesity-related indices among Korean adults. Methods: A convenience sample of 120 subjects (60 obese and 60 non-obese subjects) were recruited applying frequency matching for sex and age between two groups. Sodium intake level was assessed through 24-hour urine collection. Obesity-related metabolic risk factors, including fasting blood lipid indices, subcutaneous and visceral fat through computed tomography (CT), insulin resistance indices, blood pressure and liver enzymes were measured in all subjects. These obesity-related metabolic risk factors were compared between obese and non-obese group according to sodium excretion levels (<110 mEq/day, 110~180 mEq/day, >180 mEq/day). Results: After adjusting for age, gender, health behaviors (smoking, exercise, drinking), and energy intake, several obesity-related metabolic risk factors, including abdominal circumference, body fat percentage, subcutaneous and visceral fat, triglyceride, and systolic blood pressure were found to be significantly deteriorated as the sodium excretion level increases. In addition, multivariate adjusted-odds ratios of abdominal obesity, high blood triglyceride, and high blood pressure were found significantly higher in the highest sodium excretion group compared to the lowest group. The mean number of metabolic syndrome risk factors was also significantly greater in the highest sodium excretion group than in the lowest group. Conclusions: The current study findings suggested that high sodium intake can affect obesity and metabolic syndrome risk negatively, implying the necessity of future research on low-sodium diet intervention in relation to obesity and related health problems.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.161-167
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• 2018

The purpose of this study is to investigate how the advertising campaign is spreading in social networks, and how the advertising model plays an important role in advertisement diffusion. In order to grasp the diffusion patterns of advertising, a text mining and social network analysis were conducted using the beer brand 'Kloud' as a collection keyword. After analyzing the social data for two months since the on-air of 'Good Body' advertisement, which was the first ad that "Sulhyun" appeared in. After the launch of the ad, Kloud has been mainly associated with keywords such as 'yavis & trendy style', 'beer brand', 'beer matching food', 'luxury beer drinking place', 'leisure trend', and 'SNS activity', etc. In addition, "Sul Hyun" also showed that an advertising model contributes to the spread of advertisement on social media in terms of image transition as well as brand's name and unique selling point.

• Journal of the Korean Society of Costume
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• v.56 no.7 s.106
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• pp.79-95
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• 2006

The relationships between costumes and literature are the remarkable characteristics in the history of Japanese costumes. Among them, the literary designs which have literary subject matters seem unique to Japan. In Japan, the history of the literary design traces far back and its examples are abundant in various literatures in the Heian era. It is particularly notable that the literary designs take a relatively large part of Kosode pattern in the pre-modern period, the Edo era, which can be cleary seen in Kosodehinagata-bon, a collection of Kosode pattern of those era, in addition to various sources of extant relics or paintings. These literary designs lie the tradition of the literary lyricism as aesthetic sense in the japanese costume history. The literary lyricism means the lyrical mood evoked by literature. The purpose of this study is to examine how the literary lyricism which has supported those literary designs was formed and developed. The literary designs on costumes related with the relationships between literature and formative art, for example painting. Those typical example, which started in the literature tournament, utaawase, was devised for matching up with the character of the assembly. They continued as a sort of the intellectual amusements. In the pre-modern period, the literary designs developed In relation to not only subject matters but those expression. Moreover, it shows the extremely typical example that a series of Kosodehiinagata-bons, consisted solely of literary designs, was enjoyed as a device of reading materials like poem anthology.

• Journal of Preventive Medicine and Public Health
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• v.33 no.3
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• pp.313-322
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• 2000

Objectives : To estimate mumps incidence during the study period and to evaluate the completeness of case reporting. Methods : Capture-recapture methods, originally developed for counting wildlife animals, were used. The data sources were 1) the National Notifiable Communicable Disease Reporting System (NNCDRS; 848 cases), 2) the School Health Reporting System, temporarily administered by the Division of Education (SHRS; 1,026 cases), and 3) a survey of students (785 cases). We estimated the number of unobserved mumps cases by matching the three data sources and fitting loglinear models to the data. We then determined the estimated total number of mumps cases by adding this to the number of observed cases. Completeness was defined as the proportion of observed cases from each source to the total of estimated cases. Results : The total number of observed cases was 1,844 and the total number of estimated cases was 1,935 (95%, CI: $1,878\sim2,070$). The overall completeness was 43.8% of the NNCDRS, 53.0% of the SHRS, and 40.6% of the survey. However, completeness varied by area and age. Conclusion : Although the completeness of NNCDRS data appeared higher than in the past, it is difficult to generalize this result In Korea, it is possible to estimate the size of health hazards relatively cheaply and quickly, by applying capture-recapture methods to various data using a multiple data collection system.

• Journal of KIISE
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• v.43 no.11
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• pp.1201-1209
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• 2016

As the use of SNS continues to increase, various related studies have been conducted. According to the effectiveness of the topic model for existing theme extraction, a huge number of related research studies on topic model based analysis have been introduced. In this research, we suggested an automation system to analyze topics of each country and its distribution in twitter by combining world map visualization and issue matching method. The core system components are the following three modules; 1) collection of tweets and classification by nation, 2) extraction of topics and distribution by country based on topic model algorithm, and 3) visualization of topics and distribution based on Google geochart. In experiments with USA and UK, we could find issues of the two nations and how they changed. Based on these results, we could analyze the differences of each nation's position on ISIS problem.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1396-1405
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• 2020

Cyber threats such as forced personal information collection and distribution of malicious codes using malicious URLs continue to occur. In order to cope with such cyber threats, a security technologies that quickly detects malicious URLs and prevents damage are required. In a web environment, malicious URLs have various forms and are created and deleted from time to time, so there is a limit to the response as a method of detecting or filtering by signature matching. Recently, researches on detecting and predicting malicious URLs using machine learning techniques have been actively conducted. Existing studies have proposed various features and machine learning algorithms for predicting malicious URLs, but most of them are only suggesting specialized algorithms by supplementing features and preprocessing, so it is difficult to sufficiently reflect the strengths of various machine learning algorithms. In this paper, a system for predicting malicious URLs using multiple machine learning algorithms was proposed, and an experiment was performed to combine the prediction results of multiple machine learning models to increase the accuracy of predicting malicious URLs. Through experiments, it was proved that the combination of multiple models is useful in improving the prediction performance compared to a single model.