• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.123-133
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• 2008

Information collection systems and applications in a ubiquitous environment has emerged as a leading issue in transportation and logistics. A productive application example is a traffic information collection system based on probe vehicles and wireless communication technology. Estimation of hourly OD pairs using probe OD data is a possible target. Since probe OD data consists of sample OD pairs, which vary over time and space, computation of sample rates of OD pairs and expansion of sample OD pairs into static OD pairs is required. In this paper, the authors proposed a method to estimate sample OD data with probe data in Jeju City and expand those into static OD data. Mean absolute percentage difference (MAPD) error between observed traffic volume and assigned traffic volume was about 22.9%. After removing abnormal data, MAPD error improved to 17.6%. Development of static OD estimation methods using probe vehicle data in a real environment is considered the main contribution of this paper.

• Journal of Korean Clinical Nursing Research
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• v.25 no.3
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• pp.333-341
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• 2019

Purpose: The purpose of this study was to determine the most appropriate shelf life for sterilized products according to their packaging material. Methods: Samples were prepared to target six nursing units in one general hospital in Seoul. After steam and E.O gas sterilization, sterilized product, samples were supplied to wards. Data collection was conducted for 3 months, after the expiration date of 3 months had passed for samples packaged with crepe paper and nonwoven wraps. For samples packaged with paper-plastic pouches, data collection conducted for 3 months when the expiration date of 9 months had passed. The sterilized products were collected and tested for microbial contamination. Identification of the storage environment was done as samples were collected. Results: This study confirmed that the storage environment met international standards such as CDC, except for temperature. For steam sterilized crepe paper packaging samples and steam and E.O gas sterilized for nonwoven packaging samples no contamination in all products was found for 3 months past the expiration date. However, in the E.O gas sterilized paper-plastic pouch packaging sterile samples, Gram-positive bacilli were detected in one sample from a surgical intensive care unit at 45 weeks and another sample from an operating room at 47 weeks. Furthermore, the results did not show any microorganisms for up to 52 weeks in all products. Conclusion: According to the results of this study, sterilized product packaging made with crepe paper and nonwoven wraps is better able an extended shelf life from 3 months to 6 months, reducing unnecessary costs.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.87-87
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• 2019

The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.786-792
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• 2019

Currently, various kinds of contents using smart phone's location information are developed and provided to users. The market size of the location-based service industry utilizing location information is also increasing every year and the majority of smart phone users occupy university students and most of the university students are using their owns smart phones, and they are the biggest users of location-based services and the main target of location information collection. In this paper, we conduct to a survey how university students understand about location information. Based on the results of the survey, we will deeply examine which one is needed to improve understanding of university students' location information collection and usage and what should be considered for the development of the location-based service industry and education of location information and then we propose some helpful suggestion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.277-277
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• 2022

Lignin modification has been a breeding target for the improvements of forage digestibility and fermentation in whole crop silage(WCS) rice. In rice, gold hull and internode 2 (gh2) was identified as a lignin-deficient mutant. gh2 exhibits a reddish-brown pigmentation in the hull and the internode is located on the short arm of chromosome 2 and codes for cinnamyl-alcohol dehydrogenase (CAD). To develop WCS rice variety improved digestibility and fermentation, we measured acid detergent fiber (ADF), lignin and total digestible nutrient (TDN) calculated from ADF (TDN=88.9-(0.79% × ADF) and performed marker-assisted selection using CAD(Os2g0187800) gene first intron region specific marker with 55 Jungmo1038/J.collection lines. Those lines had lignin content range from 0.82 to 6.61%, ADF from 15.8 to 45.8%, TDN from 52.7 to 78.8 compared to 'Jungmo1038'(1.53,20.7,72.6), 'J.collection'(0.98,12.8,78.8%) and gh2 were introgressed into 44 lines. Considering on these genotype and low-lignin phenotype, we finally selected 2 elite lines(Suweon668, Suweon669). Suweon668 and Suweon669 line are high biomass-low lignin lines that the ADF content is relatively low, even though the dry matter weight is high. Also they have lodging and shattering resistance and glabrous leaf and hull important to improve cattle palatability. Our results will provide that rice can be improved for forage digestibility and fermentation with low lignin concentration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.1-9
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• 2014

Recently, a study is conducting to image collection and auto detection of attribute information using mobile mapping system. The road sign attribute information detection is difficult because of various size and placement, interference of other facilities like trees. In this study, a text detection method that does not rely on a Korean character template is required to successfully detect the target text when a variety of differently sized texts are present near the target texts. To overcome this, the method of incremental right-to-left blob projection (IRBP) was suggested as a solution; the potential and improvement of the method was also assessed. To assess the performance improvement of the IRBP that was developed, the IRBP method was compared to the existing method that uses Korean templates through the 60 videos of street signs that were used. It was verified that text detection can be improved with the IRBP method.

• Journal of Korean Home Economics Education Association
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• v.13 no.2
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• pp.73-83
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• 2001

This study attempts to enhance the research quality and the desirable direction of Home Economics Education research in Korea. based upon the analyses of the articles appeared in The Journal of Korea Home Economics Education published by The Korea Home Economics Education Association since 1989. Total number of 142 articles were collected for analysis from the number 1 of volume 1 in 1989 to the number 2 of volume 10 in 1998 of the journal. The major findings by each factors considered in analysis are as follows : 1. Total numbers have been 15 volume for the last 10 years. and published bi-annually. and the size of the article ranges from minimum 7 pages to maximum 46 pages. 2. Among 9 major fields or research. 3 major fields consist of I) 32 articles in the perception of Home Economics(22.54%) : ⅱ) 31 articles in teaching-learning method and teaching materials(21.83%) : and ⅲ)22 articles in curriculum and textbooks(15.49%). 3. Among various types of research. survey research was the most frequently used. 91 articles(64.08%). followed by 16 experimental researches(11.27%) and others of descriptive research. content analysis. and case study. 4. The major data collecting method was the questionnaire survey method of 87 articles(61.27%). followed by the interview. braining storming. and experiment. The major data analysis technique was the statistical analysis of 118 articles. 5. The major target groups for data collection of researches were teacher of junior and high school. followed by the student. The size of the target ranges from 101 to 200 of 12.04% from 201 to 300 of 11.11%. 501 to 600 of 9.26%. and over 1.000 of 6.48%. 6. The numbers of researchers consist of roughly between 1 to 7. Among them. articles by one individual was 35 articles(24.65%). Most studies were not financially supported by ant institutions and universities and the researches with outside financial support were counted only 14 articles(9.86%).

• Journal of Information Technology Services
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• v.13 no.3
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• pp.221-233
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• 2014

Because people's interest of the stock market has been increased with the development of economy, a lot of studies have been going to predict fluctuation of stock prices. Latterly many studies have been made using scientific and technological method among the various forecasting method, and also data using for study are becoming diverse. So, in this paper we propose stock prices prediction models using sentiment analysis and machine learning based on news articles and SNS data to improve the accuracy of prediction of stock prices. Stock prices prediction models that we propose are generated through the four-step process that contain data collection, sentiment dictionary construction, sentiment analysis, and machine learning. The data have been collected to target newspapers related to economy in the case of news article and to target twitter in the case of SNS data. Sentiment dictionary was built using news articles among the collected data, and we utilize it to process sentiment analysis. In machine learning phase, we generate prediction models using various techniques of classification and the data that was made through sentiment analysis. After generating prediction models, we conducted 10-fold cross-validation to measure the performance of they. The experimental result showed that accuracy is over 80% in a number of ways and F1 score is closer to 0.8. The result can be seen as significantly enhanced result compared with conventional researches utilizing opinion mining or data mining techniques.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.393-403
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• 2021

The purpose of this study is to propose a method of designing a systematic panel survey at the institutional level to lay the foundation for data-based decision-making using vocational training teachers and instructors as the population. In this study, the target population and sampling frame, which are the main elements necessary for planning a panel survey, are proposed. Also based on expert advice and empirical data analysis, the sampling unit and sampling method taking into account the outer and inner variables are presented, comprehensively considering the representativeness of data, the efficiency and sustainability of data collection. As a result of the study, with the unit of the panel as a vocational training institution, a two-stage stratified proportional sampling plan is proposed so that the institution selected as the panel and the vocational training teachers and instructors belonging to the institution can participate in the survey. Based on this, implications for the panel survey sample design are presented.