• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.387-392
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• 2012

This paper discusses the concept of merging multiple sources of data on the same 2D CAD drawing(s) for power plant operation. It also presents the concepts and tools used in this project.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.325-333
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• 2020

In the past, eating outside was usually the purpose of eating. However, it has recently expanded into a restaurant culture market. In particular, a dessert culture is being established where people can talk and enjoy. Each consumer has a different tendency to buy chocolate such as health, taste, and atmosphere. Therefore, it is time to recommend chocolate according to consumers' tendency to eat out. In this paper, we propose a chocolate recommendation application based on the tendency to eat out using data on social networks. To collect keyword-based chocolate information, Textom is used as a text mining big data analysis solution.Text mining analysis and related topics are extracted and modeled. Because to shorten the time to recommend chocolate to users. In addition, research on the propensity of eating out is based on prior research. Finally, it implements hybrid app base.

• The Korean Journal of Food And Nutrition
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• v.21 no.4
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• pp.536-544
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• 2008

The principal objectives of this study were to identify diet problems associated with dining out, and to suggest dining out strategies for groups with diet problems. The data collected from adults(all over 20 years old) from the third Korea National Health and Nutrition Examination Survey III(KNHANES III), conducted in 2005, were used in this study. A total of 6,497 data were included in our statistical analyses, using SPSS 14.0. The results of this study demonstrated that there were significant differences in dining out frequency between different genders(p<0.001), ages(p<0.001), and economic status (p<0.001). With the crosstabulation analysis using the Chi-square statistics, the middle class males aged $20{\sim}29$(p<0.05), and lower class females aged 65 and over evidenced different degrees of compliance with the following guidelines. 'Eat a variety of foods' varied by frequency of dining out. In addition, the degree of compliance with the guidelines 'Increase activity and eat an adequate amount of foods for weight control', 'Enjoy the Korean traditional diet', and 'Control consumption of alcohol' also differed by dining out frequency in certain populations. With these results, dining out strategies were suggested for the groups with diet problems associated with dining out.

• Korean Journal of Child Studies
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• v.28 no.5
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• pp.221-232
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• 2007

The purpose of this study was to investigate the relationship among personal attributions of daycare center teachers in fields, social support, and teachers' burn-out. Data were collected by 228 teachers in day care center. To examine the relationship among personal attributions of daycare center teachers in fields, social support, and teachers' burn-out, it was used the scale of 'the tendency of attributions', 'social supports', and 'burn-out'. To analyze data, Pearsons' correlation and multiple regression were used. The results of this study were as followed. First, the score of daycare center teachers' personal attributions, social support, and teachers' burn-out were higher than the mean score. Second, internal and external variables were related to burn-out factors. Third, attribute disposition were related to teachers' burn-out. As a whole, teachers were tend to be in internal attributions, which led to a tendency to show positive reactions against burn-out. Forth, social supports were related to teachers' burn-out.

• Journal of the Ergonomics Society of Korea
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• v.28 no.4
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• pp.117-124
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• 2009

To inspect the quality of data collected from a large-scale body measurement and investigation project, it is necessary to establish a proper data editing process. The three-dimensional body measurement may have measuring errors caused from measurer's proficiency or changes in the subject's posture. And it may also have errors caused in the process of algorithm expressing the information obtained from the three-dimensional scanner into numerical values, and in the course of data-processing dealing with numerous data for individuals. When those errors are found, the quality of the measured data is deteriorated, and they consequently reduce the quality of statistics which was conducted on the basis of it. Therefore this study intends to suggest a new way to improve the quality of the data collected from the three-dimensional body measurement by proposing a working procedure identifying data errors and correcting them from the whole data processing procedure-collecting, processing, and analyzing- of the 2004 Size Korea Three-dimensional Body Measurement Project. This study was carried out into three stages: Firstly, we detected erroneous data by examining of logical relations among variables under each edit rule. Secondly, we detected suspicious data through independent examination of individual variable value by sex and age. Finally, we examined scatter-plot matrix of many variables to consider the relationships among them. This simple graphical tool helps us to find out whether some suspicious data exist in the data set or not. As a result of this study, we detected some erroneous data included in the raw data. We figured out that the main errors are not because of the system errors that the three-dimensional body measurement system has but because of the subject's original three-dimensional shape data. Therefore by correcting some erroneous data, we have enhanced data quality.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.85-90
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• 2022

In this study, keywords from representative online portal sites such as NAVER, Google, and Youtube were collected based on text mining analysis technique using TEXTOM to check the changes in the restaurant industry before and after COVID-19. The collection keywords were selected as dining out, food service industry, and dining out culture. For the collected data, the top 30 words were derived, respectively, through the refinement process. In addition, comparative analysis was conducted by defining data from 2018 to 2019 before COVID-19, and from 2020 to 2021 after COVID-19. As a result, 8272 keywords before COVID-19 and 9654 keywords after COVID-19, a total of 17926 keywords, were derived. In order for the food service industry to develop after the COVID-19 pandemic, it is necessary to commercialize the recipes of restaurants to revitalize the distribution of home-use food products that replace home-cooked meals such as meal kits. Due to the social distancing caused by COVID-19, the dining out culture has changed and the trend has changed, and it has been confirmed that the consumption culture has changed to eating and delivering at home more safely than visiting restaurants. In addition, it has been confirmed that the consumption culture of existing consumers is changing to a trend of cooking at home rather than visiting restaurants.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.579-582
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• 2002

For train service, safety and reliability is an inevitable performance. Specially, turn-out system of the railway for safety because of actual part. Hence the management is strictly executed over turn-out systems of the railway. Also number of turn-out system need to monitoring systems. In this paper, the data multi-acquisition system for monitoring it is necessary to reduce the cost from the expensive characteristics of multi-monitoring system according to the importance of each data because this system is based on communication of one to several units. We designed the data multi-acquisition system using numbers of micro-controller and the experiment was executed to the actual turn-out system.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.1-8
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• 2021

Detecting Out-of-Distribution (OOD) data is fundamentally required when Deep Neural Network (DNN) is applied to real-world AI such as autonomous driving. However, modern DNNs are quite vulnerable to the over-confidence problem even if the test data are far away from the trained data distribution. To solve the problem, this paper proposes a novel Adversarial-Mixup training method to let the DNN model be more robust by detecting OOD data effectively. Experimental results show that the proposed Adversarial-Mixup method improves the overall performance of OOD detection by 78% comparing with the State-of-the-Art methods. Furthermore, we show that the proposed method can alleviate the over-confidence problem by reducing the confidence score of OOD data than the previous methods, resulting in more reliable and robust DNNs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.231-240
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• 2017

This paper aims to study a method to estimate precise carbon absorption by quantification of forest information that uses accurate LiDAR data, hyperspectral image. To estimate precise carbon absorption value by using spatial data, a problem was found out of carbon absorption value estimation method with statistical method, which is already existed method, and then offered optimized carbon absorption estimation method with spatial information by analyzing with methods of compare digital aerial photogrammetry and LiDAR data. It turned out possible Precise classification and quantification in case of using LiDAR and hyperspectral image. Various classification of tree species was possible with use of LiDAR and hyperspectral image. Classification of hyperspectral image was matched in general with field survey and Mahalanobis distance classification method. Precise forest resources could be extracted using high density LiDAR data. Compared with existing method, 19.7% in forest area, 19.2% in total carbon absorption, 0.9% in absorption per unit area of difference created, and improvement was found out to be estimated precisely in international code.

• Smart Media Journal
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• v.6 no.3
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• pp.75-82
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• 2017

Recently, the marine monitoring technology is actively being studied since the sea is a rich repository of natural resources that is taken notice in the world. In particular, the marine environment data should be collected continuously in order to understand and analyze the marine environment, however the study of automatic monitoring of marine environment in Korea is not enough. In this paper, we proposed the marine environment monitoring system based on open source. The proposed system can be designed as a scale out system using Hadoop based time series database which it can easily process the increasing collection data by a scale out computer resources. It can also be used to analyze marine data by visualizing collected data.